From 5678cc8e690f401538afdbc82958fe57d3710661 Mon Sep 17 00:00:00 2001 From: YikaiFu-cart Date: Wed, 1 Jul 2026 11:26:58 +0800 Subject: [PATCH] Implement dual-arm teleoperation with RM75 QP controller and MuJoCo backend --- AGENTS.md | 4 + README.md | 12 +- ik_qp/CMakeLists.txt | 23 + ik_qp/README.md | 144 +- ik_qp/STAGE1_VALIDATION.md | 76 +- ik_qp/STAGE2_VALIDATION.md | 75 + ik_qp/STAGE3_VALIDATION.md | 79 + ik_qp/environment.yml | 6 +- ik_qp/kine_ctrl/rm75_mjc.py | 314 +- .../dual_arm_base_link_left_vis_1.obj | 16886 + .../dual_arm_base_link_right_vis_1.obj | 16886 + .../dual_arm_obj/dual_arm_gripper1_vis_1.obj | 65916 +++ .../dual_arm_obj/dual_arm_gripper2_vis_1.obj | 65916 +++ .../dual_arm_obj/dual_arm_link10_vis_1.obj | 8151 + .../dual_arm_obj/dual_arm_link11_vis_1.obj | 9346 + .../dual_arm_obj/dual_arm_link12_vis_1.obj | 8648 + .../dual_arm_obj/dual_arm_link13_vis_1.obj | 10687 + .../dual_arm_obj/dual_arm_link14_vis_1.obj | 8728 + .../dual_arm_obj/dual_arm_link1_vis_1.obj | 8926 + .../dual_arm_obj/dual_arm_link2_vis_1.obj | 9943 + .../dual_arm_obj/dual_arm_link3_vis_1.obj | 8151 + .../dual_arm_obj/dual_arm_link4_vis_1.obj | 9346 + .../dual_arm_obj/dual_arm_link5_vis_1.obj | 8648 + .../dual_arm_obj/dual_arm_link6_vis_1.obj | 10687 + .../dual_arm_obj/dual_arm_link7_vis_1.obj | 8728 + .../dual_arm_obj/dual_arm_link8_vis_1.obj | 8926 + .../dual_arm_obj/dual_arm_link9_vis_1.obj | 9943 + .../dual_arm_robot_base_vis_1.obj | 313574 +++++++++++++++ ik_qp/package.xml | 20 + ik_qp/pyproject.toml | 11 +- ik_qp/src/rm75_ik/__init__.py | 38 + ik_qp/src/rm75_ik/dual_arm.py | 16 +- ik_qp/src/rm75_ik/kinematics.py | 15 +- ik_qp/src/rm75_ik/mujoco_backend.py | 247 + ik_qp/src/rm75_ik/mujoco_model.py | 413 + ik_qp/src/rm75_ik/mujoco_robot.py | 185 + ik_qp/src/rm75_ik/mujoco_trajectories.py | 109 + ik_qp/src/rm75_ik/robot_backend.py | 43 + ik_qp/src/rm75_ik/stage2_cli.py | 80 + ik_qp/src/rm75_ik/stage2_demo.py | 232 + ik_qp/src/rm75_ik/stage2_validation.py | 595 + ik_qp/src/rm75_ik/stage3_cli.py | 78 + ik_qp/src/rm75_ik/stage3_validation.py | 311 + ik_qp/src/rm75_ik/teleop_config.py | 197 + ik_qp/src/rm75_ik/teleop_control.py | 429 + ik_qp/src/rm75_ik/types.py | 2 +- ik_qp/tests/test_mujoco_stage2.py | 157 + ik_qp/tests/test_stage3_control.py | 195 + .../launch/dual_arm_qp_sim.launch.py | 85 + xr_rm_teleop/package.xml | 3 + xr_rm_teleop/setup.py | 1 + .../xr_rm_teleop/dual_arm_qp_teleop.py | 212 + 52 files changed, 612116 insertions(+), 327 deletions(-) create mode 100644 ik_qp/CMakeLists.txt create mode 100644 ik_qp/STAGE2_VALIDATION.md create mode 100644 ik_qp/STAGE3_VALIDATION.md create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_base_link_left_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_base_link_right_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_gripper1_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_gripper2_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link10_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link11_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link12_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link13_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link14_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link1_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link2_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link3_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link4_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link5_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link6_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link7_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link8_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_link9_vis_1.obj create mode 100644 ik_qp/models/dual_arm_obj/dual_arm_robot_base_vis_1.obj create mode 100644 ik_qp/package.xml create mode 100644 ik_qp/src/rm75_ik/mujoco_backend.py create mode 100644 ik_qp/src/rm75_ik/mujoco_model.py create mode 100644 ik_qp/src/rm75_ik/mujoco_robot.py create mode 100644 ik_qp/src/rm75_ik/mujoco_trajectories.py create mode 100644 ik_qp/src/rm75_ik/robot_backend.py create mode 100644 ik_qp/src/rm75_ik/stage2_cli.py create mode 100644 ik_qp/src/rm75_ik/stage2_demo.py create mode 100644 ik_qp/src/rm75_ik/stage2_validation.py create mode 100644 ik_qp/src/rm75_ik/stage3_cli.py create mode 100644 ik_qp/src/rm75_ik/stage3_validation.py create mode 100644 ik_qp/src/rm75_ik/teleop_config.py create mode 100644 ik_qp/src/rm75_ik/teleop_control.py create mode 100644 ik_qp/tests/test_mujoco_stage2.py create mode 100644 ik_qp/tests/test_stage3_control.py create mode 100644 xr_rm_bringup/launch/dual_arm_qp_sim.launch.py create mode 100644 xr_rm_teleop/xr_rm_teleop/dual_arm_qp_teleop.py diff --git a/AGENTS.md b/AGENTS.md index 6da3504..f6092fe 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -89,6 +89,10 @@ ros2 launch xr_rm_bringup arm_debug.launch.py arm:=both use_mock:=true ## 文档与生成文件 - `README.md` 是面向用户的主项目文档；`AGENTS.md` 用于记录智能体工作流程和安全规则。 +- 项目自有的 Markdown 文档应以简体中文为主要叙述语言；新建或更新文档时，标题、正文、表格说明和验证结论默认使用中文。 +- 代码、命令、路径、API、类名、函数名、变量名、配置键、topic、坐标系名称、协议字段、公式、单位、版本号、原始日志、英文论文标题及参考文献可按原文保留，避免翻译破坏可执行性、可检索性或技术含义。 +- 编码智能体生成的 Markdown 报告也应遵循中文为主的要求；若固定字段需供程序解析，应保持字段兼容，并为面向读者的说明提供中文。 +- 不得仅为统一语言而批量翻译第三方代码、SDK、依赖包或其随附文档。 - 与具体实现相关的协议、topic 和配置说明应放入对应 README 或专项文档，不在此处重复维护。 - 不得将尚未实现的功能描述为已完成。 - 将 Unity 的 `Library/`、`Builds/`、`Logs/`、`UserSettings/`、APK、生成日志及构建输出视为生成文件。 diff --git a/README.md b/README.md index cfbe974..2c382f7 100755 --- a/README.md +++ b/README.md @@ -199,7 +199,17 @@ ros2 launch xr_rm_bringup arm_debug.launch.py arm:=both use_mock:=false \ ## Launch 入口说明 -`arm_debug.launch.py` 是当前唯一的遥操作 launch 主入口，`launcher_ui.py` 中的 mock、单臂真机和双臂真机按钮都调用它。 +`arm_debug.launch.py` 是现有笛卡尔透传及真机调试主入口，`launcher_ui.py` 中的 mock、 +单臂真机和双臂真机按钮都调用它。独立 QP IK 的双臂 MuJoCo 验证入口为： + +```bash +conda activate qp +ros2 launch xr_rm_bringup dual_arm_qp_sim.launch.py +``` + +该入口订阅同一组左右 `XrController` 话题，但仅创建 `MujocoRobot`，不会连接 RM75。 +关闭 viewer 或按 `Ctrl+C` 会停止控制器并退出。无桌面环境可添加 +`show_viewer:=false mujoco_gl:=egl`。 常用参数： diff --git a/ik_qp/CMakeLists.txt b/ik_qp/CMakeLists.txt new file mode 100644 index 0000000..b6f0ede --- /dev/null +++ b/ik_qp/CMakeLists.txt @@ -0,0 +1,23 @@ +cmake_minimum_required(VERSION 3.8) +project(rm75_ik) + +find_package(ament_cmake REQUIRED) +find_package(ament_cmake_python REQUIRED) + +ament_python_install_package(rm75_ik PACKAGE_DIR src/rm75_ik) + +install(FILES + kine_ctrl/urdf_rm75/RM75-B.urdf + models/dual_arm_mujoco_fixed.urdf + DESTINATION share/${PROJECT_NAME}/models +) + +install(DIRECTORY kine_ctrl/urdf_rm75/meshes/ + DESTINATION share/${PROJECT_NAME}/models/rm75_meshes +) + +install(DIRECTORY models/dual_arm_obj/ + DESTINATION share/${PROJECT_NAME}/models/dual_arm_obj +) + +ament_package() diff --git a/ik_qp/README.md b/ik_qp/README.md index ea37693..5fc77ea 100644 --- a/ik_qp/README.md +++ b/ik_qp/README.md @@ -1,7 +1,8 @@ -# RM75-B 第一阶段运动学与 QP IK +# RM75-B 运动学、QP IK 与 MuJoCo 验证 -本目录是一个独立的离线 Python 包，用于验证 RM75-B 的运动学与逆运动学。它不接入 -ROS 2 遥操作控制链路，也不会建立机器人连接。 +本目录是独立 Python 算法包，用于验证 RM75-B 的运动学、逆运动学和后端无关遥操作 +控制。核心包不依赖 ROS 2，也不会建立真实机器人连接；第三阶段由 `xr_rm_teleop` 提供 +薄 ROS 消息适配层并使用 MuJoCo 后端。 第一阶段包含： @@ -13,7 +14,23 @@ ROS 2 遥操作控制链路，也不会建立机器人连接。 - 由两份标准单臂模型组成的双臂装配模型。 - 可生成 JSON、CSV 和 Markdown 报告的确定性验证流程。 -MuJoCo、MJCF、碰撞规避和真实机器人控制明确不在本阶段范围内。 +第二阶段在完整双臂场景中使用第一阶段求解器驱动一侧机械臂，包含： + +- 由标准单臂 URDF 复制两条运动链生成的规范化 14 轴 MJCF。 +- 来自上传双臂模型的安装变换、平台、挂架、夹爪和 19 个 OBJ 资源。 +- 默认控制左臂、固定右臂的纯运动学 MuJoCo 播放。 +- headless EGL 自动验证和 GLFW 实时 viewer 演示。 +- MuJoCo、Pinocchio 与 RealMan Algo FK 的三方对照。 + +第三阶段包含： + +- 右臂 FK、IK 和连续轨迹快速验收。 +- 按左右工具 TCP 求解的双臂仿真初始姿态。 +- 与 `XrController.msg` 字段兼容、但不导入 ROS 的 grip 相对位姿控制核心。 +- 双臂 SE(3) 目标、QP IK、关节限位、速度限制和故障联停状态机。 +- 可由未来 `RealmanRobot` 实现复用的 `RobotBackend` 协议。 + +碰撞规避、动力学伺服和真实机器人控制仍不在当前范围内。 ## 环境 @@ -25,8 +42,8 @@ conda env update -f environment.yml conda run -n qp python -m pip install -e . --no-deps ``` -RealMan API2 SDK 是外部二进制依赖，不会复制到本包中。请为验证程序指定包含 -`Robotic_Arm/` 的目录： +环境文件会从 PyPI 安装 `Robotic_Arm 1.1.5`，通常无需额外设置。若需要强制使用 +本地 API2 SDK，可为验证程序指定包含 `Robotic_Arm/` 的目录： ```bash export REALMAN_SDK_ROOT=/path/to/RM_API2/Python @@ -52,6 +69,28 @@ if result.success: solution_q_rad = result.q ``` +双臂 MuJoCo 场景： + +```python +from rm75_ik import DualArmMuJoCo + +scene = DualArmMuJoCo(controlled_arm="left") +scene.set_arm_configuration("left", solution_q_rad) +world_flange_pose = scene.get_flange_pose("left") +image = scene.render() +``` + +后端无关双臂控制： + +```python +from rm75_ik import DualArmQpTeleopController, load_dual_arm_profiles +from rm75_ik.mujoco_robot import MujocoRobot + +profiles = load_dual_arm_profiles(teleop_yaml, peripheral_yaml) +robot = MujocoRobot(profiles) +controller = DualArmQpTeleopController(robot, profiles) +``` + 对于任何失败状态，`IkResult.q` 均为 `None`。不得将失败或未经验证的结果发送给 机器人。 @@ -80,6 +119,95 @@ REALMAN_SDK_ROOT=/path/to/RM_API2/Python \ 验收标准和最近一次完整结果请参见 [STAGE1_VALIDATION.md](STAGE1_VALIDATION.md)。 +运行第二阶段完整 headless 验证： + +```bash +REALMAN_SDK_ROOT=/path/to/RM_API2/Python \ + conda run -n qp rm75-stage2-validate --arm left +``` + +启动双臂实时可视化，只驱动左臂： + +```bash +conda run -n qp rm75-stage2-demo --arm left --trajectory combined +``` + +移动到指定目标点。目标位置位于受控机械臂基座坐标系，单位为米；未提供 RPY 时保持 +起始姿态： + +```bash +conda run -n qp rm75-stage2-demo \ + --arm left \ + --target-position 0.45 0.0 0.3375 \ + --duration 8 \ + --wait-before 2 \ + --hold-after 3 +``` + +也可用弧度指定目标姿态： + +```bash +conda run -n qp rm75-stage2-demo \ + --arm left \ + --target-position 0.45 0.0 0.3375 \ + --target-rpy -3.14159 0.52360 -3.14159 \ + --duration 8 +``` + +手动拖动受控机械臂： + +```bash +conda run -n qp rm75-stage2-demo --arm left --manual-drag +``` + +在 Viewer 中双击选中连杆，然后按住 `Ctrl` 并使用鼠标右键拖动。该模式使用零重力、 +有阻尼的 MuJoCo 动力学，只用于检查关节活动与模型装配，不属于 IK 验收结果。 + +支持的演示轨迹为 `joint`、`line`、`arc`、`orientation` 和 `combined`。无桌面环境时 +可添加 `--headless --output stage2_demo.png`。阶段二报告和截图写入 +`artifacts/stage2/`，验收结果见 [STAGE2_VALIDATION.md](STAGE2_VALIDATION.md)。 + +运行第三阶段完整 headless 验证： + +```bash +conda run -n qp rm75-stage3-validate \ + --sdk-root /path/to/RM_API2/Python \ + --teleop-config ../xr_rm_bringup/config/dual_arm_rm75.yaml \ + --peripheral-config ../xr_rm_bringup/config/peripherals_rm75.yaml +``` + +在 ROS 工作空间中启动 PICO/UDP、双臂 QP 和共享 MuJoCo viewer： + +```bash +conda activate qp +cd /home/robot/WS_xr +source /opt/ros/humble/setup.bash +source install/setup.bash +ros2 launch xr_rm_bringup dual_arm_qp_sim.launch.py +``` + +该 launch 将 `robot_backend` 固定为 `mujoco`，不会连接真实机械臂。headless 运行可使用： + +```bash +ros2 launch xr_rm_bringup dual_arm_qp_sim.launch.py \ + show_viewer:=false mujoco_gl:=egl +``` + +常用 launch 参数： + +| 参数 | 默认值 | 说明 | +|---|---:|---| +| `udp_host` | `0.0.0.0` | XR UDP 监听地址 | +| `udp_port` | `15000` | XR UDP 监听端口 | +| `udp_timer_hz` | `200.0` | UDP receiver 轮询频率 | +| `control_rate_hz` | `90.0` | 双臂 QP 控制周期频率 | +| `show_viewer` | `true` | 是否显示共享 MuJoCo viewer | +| `mujoco_gl` | `glfw` | MuJoCo 渲染后端；无桌面环境建议使用 `egl` | + +启动成功后，日志应先显示 UDP receiver 的监听地址，再显示左右臂从 +`initial_tcp_pose` 初始化的残差，最后出现 `dual-arm QP teleop ready`。第三阶段结果见 +[STAGE3_VALIDATION.md](STAGE3_VALIDATION.md)。 + ## 模型说明 单臂 URDF 是 RM75-B 运动链几何参数的唯一来源。导入的双臂 URDF 仅用于提供左右 @@ -87,3 +215,7 @@ REALMAN_SDK_ROOT=/path/to/RM_API2/Python \ 导入的双臂 URDF 中，右侧基座的视觉原点与运动学原点相差约 1 mm。第一阶段采用 第一关节的运动学原点，并叠加文档规定的 240.5 mm 基座至第一关节偏移。 + +第二阶段不会把原始双臂 URDF 的镜像关节角直接交给 MuJoCo。MJCF 的左右关节均采用 +标准 RealMan 弧度定义；原始双臂模型只作为安装和视觉来源。当前场景没有 actuator， +通过设置 `qpos` 并调用 `mj_forward()` 实现确定性的运动学播放。 diff --git a/ik_qp/STAGE1_VALIDATION.md b/ik_qp/STAGE1_VALIDATION.md index 3f3078d..7f43253 100644 --- a/ik_qp/STAGE1_VALIDATION.md +++ b/ik_qp/STAGE1_VALIDATION.md @@ -1,62 +1,58 @@ -# RM75-B Stage-1 Validation Record +# RM75-B 第一阶段验证记录 -Date: 2026-06-29 -Random seed: `20260629` -RealMan API2 C API: `v1.1.5` +- 日期：2026-06-29 +- 随机种子：`20260629` +- RealMan API2 C API 版本：`v1.1.5` -## Acceptance Result +## 验收结果 -The complete strict benchmark passed every required check with zero recorded -failure samples. +完整的严格基准测试通过了全部必需检查，未记录到失败样本。 -| Check | Samples | Result | +| 检查项 | 样本数 | 结果 | |---|---:|---:| -| Physical-limit FK | 10,000 | PASS | -| Teleop-limit FK | 10,000 | PASS | -| Algo finite-difference Jacobian | 200 | PASS | -| Physical-limit near-seed IK | 1,000 / 1,000 | PASS | -| Teleop-limit near-seed IK | 1,000 / 1,000 | PASS | -| Continuous IK | 10,000 / 10,000 | PASS | -| Eight-seed global recovery | 200 / 200 | PASS | -| Documented singularity families | 12 | PASS | -| Dual-arm assembly FK | 100 per arm | PASS | -| Project tool-frame FK | 100 per tool | PASS | +| 物理限位 FK | 10,000 | 通过 | +| 遥操作限位 FK | 10,000 | 通过 | +| Algo 有限差分雅可比矩阵 | 200 | 通过 | +| 物理限位邻近种子 IK | 1,000 / 1,000 | 通过 | +| 遥操作限位邻近种子 IK | 1,000 / 1,000 | 通过 | +| 连续轨迹 IK | 10,000 / 10,000 | 通过 | +| 八种子全局恢复 | 200 / 200 | 通过 | +| 文档所列奇异位形族 | 12 | 通过 | +| 双臂装配模型 FK | 每条机械臂 100 | 通过 | +| 项目工具坐标系 FK | 每个工具 100 | 通过 | -Key measurements: +关键测量结果： -- Maximum physical-limit FK error: `0.003868 mm`, `0.001027 deg`. -- Maximum teleop-limit FK error: `0.003681 mm`, `0.000957 deg`. -- Maximum Jacobian relative/absolute error: `6.97e-5` / `1.70e-4`. -- Near-seed IK P99/max time: `2.44 ms` / `7.43 ms`. -- Maximum continuous joint step: `0.003216 rad` (`0.184 deg`). -- Random single-seed IK success rate: `74%` (diagnostic only). -- Eight-seed recovery success rate: `100%`. -- Right dual-arm visual/kinematic origin difference: `1.0000004 mm`. +- 物理限位 FK 最大误差：`0.003868 mm`、`0.001027 deg`。 +- 遥操作限位 FK 最大误差：`0.003681 mm`、`0.000957 deg`。 +- 雅可比矩阵最大相对误差/绝对误差：`6.97e-5` / `1.70e-4`。 +- 邻近种子 IK 的 P99/最大耗时：`2.44 ms` / `7.43 ms`。 +- 最大连续关节步长：`0.003216 rad`（`0.184 deg`）。 +- 随机单种子 IK 成功率：`74%`（仅用于诊断）。 +- 八种子恢复成功率：`100%`。 +- 双臂模型右侧视觉原点与运动学原点之差：`1.0000004 mm`。 -## Error Definitions +## 误差定义 -Position error: +位置误差： ```text ||p_result - p_target|| ``` -Orientation error: +姿态误差： ```text ||log(R_result^T R_target)|| ``` -IK success is accepted only after applying RealMan Algo FK to the returned joint -configuration. Pinocchio does not validate its own IK result. +仅当对返回的关节配置应用 RealMan Algo FK 并通过检查后，才接受该 IK 结果为成功。 +Pinocchio 不用于验证其自身产生的 IK 结果。 -The validator asks the numerical solver to converge to `0.9 mm / 0.09 deg`, then -applies the independent acceptance limits `1 mm / 0.1 deg`. This guard band -prevents boundary false positives caused by the small measured model difference. +验证程序要求数值求解器收敛至 `0.9 mm / 0.09 deg`，随后应用独立的验收限值 +`1 mm / 0.1 deg`。该保护带用于避免测得的微小模型差异在边界处造成假阳性。 -## Boundaries - -This result validates geometry, FK, local Jacobians, numerical IK and fixed tool -or mounting transforms. It does not validate dynamics, self-collision, -environment collision, torque limits, communication latency or hardware safety. +## 验证边界 +本结果验证了几何模型、FK、局部坐标雅可比矩阵、数值 IK，以及固定的工具变换或 +安装变换。它不验证动力学、自碰撞、环境碰撞、力矩限制、通信延迟或硬件安全性。 diff --git a/ik_qp/STAGE2_VALIDATION.md b/ik_qp/STAGE2_VALIDATION.md new file mode 100644 index 0000000..7c7d214 --- /dev/null +++ b/ik_qp/STAGE2_VALIDATION.md @@ -0,0 +1,75 @@ +# RM75-B 第二阶段 MuJoCo 验证记录 + +日期：2026-06-30 +随机种子：`20260630` +受控机械臂：`left` +固定机械臂：`right` +MuJoCo：`3.10.0` +RealMan API2 C API：`v1.1.5` + +## 验收结果 + +完整 headless 基准全部通过，记录失败样本为 0。 + +| 检查项 | 样本 | 结果 | +|---|---:|---:| +| 规范化双臂模型结构 | 14 轴、27 个 mesh | PASS | +| MuJoCo/Pinocchio/Algo FK | 10,000 | PASS | +| 单点 IK 至 MuJoCo | 1,000 / 1,000 | PASS | +| 连续 IK | 10,000 / 10,000 | PASS | +| 预定义轨迹类型 | 7 / 7 | PASS | +| RGB 与 segmentation | 3 帧 | PASS | +| 固定右臂关节变化 | 0 rad | PASS | + +关键测量值： + +- MuJoCo/Pinocchio 最大误差：`5.69e-13 m`、`1.84e-12 rad`。 +- MuJoCo/RealMan Algo 最大误差：`0.003921 mm`、`0.001065 deg`。 +- 单点 IK 成功率：`100%`。 +- 单点 IK P99/最大耗时：`2.54 ms` / `4.52 ms`。 +- 连续 IK 成功率：`100%`。 +- 连续 IK 最大位置/姿态误差：`0.9000 mm`、`0.0900 deg`。 +- 连续 IK 最大关节步长：`0.002912 rad`（`0.167 deg`）。 +- 固定右臂最大 qpos 变化：`0 rad`。 + +## 场景定义 + +规范化 MJCF 使用第一阶段 RM75-B URDF 生成左右两条标准 7 轴链。上传双臂压缩包提供： + +- 左右机械臂安装变换； +- 平台、挂架和夹爪视觉； +- 19 个 OBJ 资源，全部由 MuJoCo 编译检查。 + +默认左臂从 `[0,30,0,60,0,60,0] deg` 开始运动。右臂固定在项目配置中的初始姿态： + +```text +[-25.60, 34.09, -19.55, 71.59, 16.97, 80.98, 59.67] deg +``` + +原始双臂 URDF 的镜像限位和零位偏置不进入求解或控制接口。 + +## 视觉验证 + +起点、中点和终点分别生成 RGB 与 segmentation 图像。每一帧均满足： + +- RGB 像素方差大于阈值； +- segmentation 中同时存在左右机械臂 geom； +- 双臂前景未接触图像边界。 + +实时 viewer 使用 GLFW；自动验证使用 EGL。MuJoCo 3.10 的 passive viewer 使用显式 +`close()` 并等待渲染线程退出，避免 context-manager 关闭时的 GLFW 退出竞态。 + +Demo 另外提供两种交互方式： + +- 指定受控臂基座坐标系中的目标位置/姿态，显示最终目标 marker，经过 SE(3) 插值和逐点 + QP IK 后播放完整运动，并输出 MuJoCo 回读误差。 +- `--manual-drag` 将受控臂切换为零重力、有阻尼的动力学步进，可在 Viewer 中选择连杆后 + 使用 `Ctrl + 鼠标右键` 拖动；固定臂仍由程序锁定。 + +手动拖动是模型交互检查，不计入第一阶段 IK 或第二阶段算法成功率。 + +## 边界 + +本结果验证双臂场景中的单臂 IK、关节播放、末端位姿回读和视觉呈现。模型没有 actuator， +visual geom 不参与碰撞，因此本阶段不验证动力学、重力补偿、位置伺服、碰撞检测、通信延迟 +或真实硬件安全。 diff --git a/ik_qp/STAGE3_VALIDATION.md b/ik_qp/STAGE3_VALIDATION.md new file mode 100644 index 0000000..2595070 --- /dev/null +++ b/ik_qp/STAGE3_VALIDATION.md @@ -0,0 +1,79 @@ +# RM75-B 第三阶段双臂 QP 遥操验证记录 + +日期：2026-06-30 +随机种子：`20260630` +快速验证机械臂：`right` +MuJoCo：`3.10.0` +RealMan API2 C API：`v1.1.5` + +## 验收结果 + +完整 headless 基准全部通过，记录失败样本为 0。 + +| 检查项 | 样本 | 结果 | +|---|---:|---:| +| 右臂 MuJoCo/Pinocchio/Algo FK | 2,000 | PASS | +| 右臂近邻 IK | 200 / 200 | PASS | +| 右臂连续 IK | 1,000 / 1,000 | PASS | +| 双臂工具 TCP 初始化 | 左右各 1 | PASS | +| 双 grip 相对位姿控制 | 10 帧 | PASS | +| RGB/segmentation 与双臂最终帧 | 7 张 | PASS | +| ROS2 双臂 QP MuJoCo 启动冒烟测试 | 1 次 | PASS | + +关键测量值： + +- MuJoCo/Pinocchio 最大误差：`5.38e-13 m`、`1.52e-12 rad`。 +- MuJoCo/RealMan Algo 最大误差：`0.003721 mm`、`0.000964 deg`。 +- 右臂近邻 IK 成功率：`100%`，P99/最大耗时：`3.61 ms / 5.18 ms`。 +- 右臂连续 IK 成功率：`100%`，最大关节步长：`0.153 deg`。 +- grip 首帧左右关节变化均小于 `1e-10 rad`。 + +## 初始 TCP + +`dual_arm_rm75.yaml` 的 `initial_tcp_pose` 被视为活动工具 TCP。左臂使用 `minisci` +的 `190 mm` 工具变换，右臂使用 `omnipic` 的 `160 mm` 工具变换，再由 QP IK 求出 +初始关节角。 + +| 机械臂 | 位置残差 | 姿态残差 | +|---|---:|---:| +| left | `0.226 mm` | `0.00714 deg` | +| right | `0.422 mm` | `0.01259 deg` | + +配置中的旧 `initial_joint_pose` 无法在标准 RM75-B 模型中复现这些 TCP：计入工具后， +左、右位置误差约为 `123 mm`、`95 mm`。因此它们只进入诊断报告，不用于 MuJoCo 初始化。 + +## 控制边界 + +独立核心按以下顺序处理每个控制周期： + +```text +XrController-compatible sample +-> grip 起点锁定与左右坐标映射 +-> TCP 工作空间、滤波和速度限制 +-> 工具 TCP 到法兰变换 +-> Pinocchio SE(3) + OSQP IK +-> 关节限位与关节速度限制 +-> RobotBackend.command_joint_positions() +``` + +正常松开 grip 只停止对应侧；任一活动臂输入超时、IK 失败或后端异常都会使双臂进入 +FAULT 并共同停止。恢复前必须收到左右两侧新的 grip 释放消息。 + +## ROS2 启动验证 + +在 `qp` Conda 环境和已构建的 ROS2 Humble 工作空间中执行： + +```bash +cd /home/robot/WS_xr +source /opt/ros/humble/setup.bash +source install/setup.bash +ros2 launch xr_rm_bringup dual_arm_qp_sim.launch.py show_viewer:=false +``` + +验证中使用 `mujoco_gl` 的默认值 `glfw`，无需在命令行显式传入。UDP receiver 成功监听 +`0.0.0.0:15000`，左右臂分别以 `0.226 mm`、`0.422 mm` 的位置残差完成初始化，随后 +双臂控制节点进入 `dual-arm QP teleop ready` 状态。该测试只验证节点启动和 MuJoCo +初始化，不包含 XR 数据输入、持续遥操作或真实机械臂行为。 + +第三阶段只实现 `MujocoRobot`。`RealmanRobot` 仅由 `RobotBackend` 协议约束，尚未实现， +也未进行真实机械臂测试。本阶段不验证碰撞规避、动力学跟踪或硬件安全。 diff --git a/ik_qp/environment.yml b/ik_qp/environment.yml index 7b2c24a..cf85210 100644 --- a/ik_qp/environment.yml +++ b/ik_qp/environment.yml @@ -6,9 +6,13 @@ dependencies: - numpy=1.23.5 - scipy=1.10.1 - pinocchio=2.6.20 + - catkin_pkg + - empy=3.3.4 - pip - pip: - osqp==0.6.2.post8 - PyYAML==6.0.3 - pytest==7.4.4 - + - mujoco==3.10.0 + - Pillow==12.2.0 + - Robotic_Arm==1.1.5 diff --git a/ik_qp/kine_ctrl/rm75_mjc.py b/ik_qp/kine_ctrl/rm75_mjc.py index 70ac134..a1473af 100644 --- a/ik_qp/kine_ctrl/rm75_mjc.py +++ b/ik_qp/kine_ctrl/rm75_mjc.py @@ -1,297 +1,81 @@ #!/usr/bin/env python3 -""" -Pure Position Control for MuJoCo - No velocity commands, no forces -Direct joint position control with smoothing -""" +"""Compatibility adapter for the original MuJoCo controller import path.""" + +from time import sleep -import mujoco import mujoco.viewer import numpy as np -import threading -import time -from pathlib import Path + +from rm75_ik.mujoco_backend import DualArmMuJoCo class MuJoCoPositionController: - """ - Pure position control - directly sets joint positions - No velocity commands, no forces - completely stable - """ + """Legacy facade backed by the threadless normalized dual-arm scene.""" - def __init__(self, urdf_path="./urdf_rm75/RM75-B.urdf", smoothness=0.05, enable_viewer=True): - """ - Args: - urdf_path: Path to URDF file - smoothness: Motion smoothness (0.02=very smooth, 0.1=fast) - enable_viewer: Show MuJoCo viewer - """ - # Load model - self.model = mujoco.MjModel.from_xml_path(urdf_path) - self.data = mujoco.MjData(self.model) - - self.time_interval = 0.02 - - print(f'time interval: {self.model.opt.timestep}') - - # Robot info - self.n_joints = self.model.njnt - - # Get joint limits - self.joint_lower_limits = [] - self.joint_upper_limits = [] - for i in range(self.n_joints): - self.joint_lower_limits.append(self.model.jnt_range[i, 0]) - self.joint_upper_limits.append(self.model.jnt_range[i, 1]) - - print(f"Loaded robot: {self.n_joints} joints") - for i in range(self.n_joints): - print( - f" {self.model.joint(i).name}: limit [{self.joint_lower_limits[i]:.2f}, {self.joint_upper_limits[i]:.2f}]") - - # Target joint angles (in radians) - self.target_joints = self.data.qpos[:self.n_joints].copy() - - # Smoothing factor (0-1, lower = smoother) - self.smoothness = smoothness - - # Thread safety - self.command_lock = threading.Lock() - self.feedback_lock = threading.Lock() - self.current_feedback_joint = self.data.qpos[:self.n_joints].copy() - - self.max_ang_inc = 0.02 - - # Control flags - self.running = False - self.simulation_thread = None - - # Viewer - self.viewer = None - if enable_viewer: - try: - self.viewer = mujoco.viewer.launch_passive(self.model, self.data) - print("Viewer launched") - except Exception as e: - print(f"Viewer warning: {e}") - self.start() + def __init__( + self, + urdf_path=None, + smoothness=0.05, + enable_viewer=True, + controlled_arm="left", + ): + del urdf_path, smoothness + self.backend = DualArmMuJoCo(controlled_arm=controlled_arm) + self.controlled_arm = controlled_arm + self.viewer = ( + mujoco.viewer.launch_passive(self.backend.model, self.backend.data) + if enable_viewer + else None + ) def start(self): - """Start the simulation thread""" - if self.running: - return - - self.running = True - self.simulation_thread = threading.Thread(target=self._simulation_loop, daemon=True) - self.simulation_thread.start() - print("Simulation thread started") + return None def stop(self): - """Stop the simulation thread""" - self.running = False - if self.simulation_thread: - self.simulation_thread.join(timeout=2.0) - if self.viewer: + if self.viewer is not None: self.viewer.close() - print("Simulation stopped") + sleep(0.2) + self.viewer = None def send_command(self, joint_positions): - """ - Send target joint positions - - Args: - joint_positions: Array of target joint angles (radians) - """ - cmd = np.array(joint_positions[:self.n_joints], dtype=np.float64) - - # Apply joint limits - for i in range(self.n_joints): - cmd[i] = np.clip(cmd[i], self.joint_lower_limits[i], self.joint_upper_limits[i]) - - with self.command_lock: - self.target_joints = cmd + self.backend.set_arm_configuration( + self.controlled_arm, np.asarray(joint_positions, dtype=float) + ) + if self.viewer is not None: + self.viewer.sync() def get_feedback(self): - """Get current joint positions""" - with self.feedback_lock: - return self.current_feedback_joint.copy() + return self.backend.get_arm_configuration(self.controlled_arm) def get_target(self): - """Get current target positions""" - with self.command_lock: - return self.target_joints.copy() - - def _simulation_loop(self): - """ - Main simulation loop - PURE POSITION CONTROL - No velocity commands, no forces - just direct position setting - """ - last_time = time.time() - - # For smooth interpolation - current_joints = self.data.qpos[:self.n_joints].copy() - - while self.running: - # Get target command - with self.command_lock: - target = self.target_joints.copy() - - # Get current positions - current_joints = self.data.qpos[:self.n_joints].copy() - - # Smooth interpolation toward target - # This creates natural motion without velocity commands - alpha = self.smoothness - - next_joints = current_joints + np.clip(alpha * (target - current_joints) , -self.max_ang_inc, self.max_ang_inc) - - # DIRECT POSITION CONTROL - Set joint positions - self.data.qpos[:self.n_joints] = next_joints - - # IMPORTANT: Set velocities to zero to prevent physics from moving joints - # This ensures pure kinematic control - self.data.qvel[:self.n_joints] = 0 - - # Step physics (this will apply gravity, collisions, etc. to other bodies) - mujoco.mj_step(self.model, self.data) - - # After step, ensure our joint positions are maintained - # (Physics might have altered them slightly) - self.data.qpos[:self.n_joints] = next_joints - self.data.qvel[:self.n_joints] = 0 - - # Update feedback - with self.feedback_lock: - self.current_feedback_joint = self.data.qpos[:self.n_joints].copy() - - # Sync viewer - if self.viewer: - self.viewer.sync() - - # Maintain real-time speed - elapsed = time.time() - last_time - sleep_time = self.time_interval - elapsed - if sleep_time > 0: - time.sleep(sleep_time) - last_time = time.time() + return self.get_feedback() def move_to_joints(self, target, duration=1.0): - """ - Move to target joints over specified duration - - Args: - target: Target joint joints - duration: Time to complete movement (seconds) - """ - start_js = self.get_feedback() - end_js = np.array(target[:self.n_joints]) - - # Apply limits - for i in range(self.n_joints): - end_js[i] = np.clip(end_js[i], self.joint_lower_limits[i], self.joint_upper_limits[i]) - - n_steps = int(duration / self.time_interval) - - print(f" Moving over {duration}s ({n_steps} steps)") - - for step in range(n_steps): - alpha = (step + 1) / n_steps - # Use easing for smoother motion - ease_alpha = 1 - (1 - alpha) ** 2 # Quadratic ease-out - current_target = start_js + ease_alpha * (end_js - start_js) - self.send_command(current_target) - time.sleep(self.time_interval) - - # Ensure exact target - self.send_command(end_js) - time.sleep(0.1) + start = self.get_feedback() + target_q = np.asarray(target, dtype=float) + points = max(2, int(round(duration * 90.0))) + blend = 0.5 - 0.5 * np.cos(np.linspace(0.0, np.pi, points)) + trajectory = start[None, :] + blend[:, None] * (target_q - start)[None, :] + self.backend.play_trajectory( + trajectory, + dt=duration / points, + realtime=True, + viewer=self.viewer, + ) def wait_until_reached(self, tolerance=0.01, timeout=10.0): - """ - Wait until robot reaches target position - - Args: - tolerance: Position error tolerance (radians) - timeout: Maximum wait time (seconds) - """ - start_time = time.time() - - while time.time() - start_time < timeout: - current = self.get_feedback() - target = self.get_target() - error = np.max(np.abs(target - current)) - - if error < tolerance: - return True - - time.sleep(0.01) - - return False + del tolerance, timeout + return True def print_state(self): - """Print current robot state""" - joints = self.get_feedback() - target = self.get_target() - print("Current joints (rad):", [f"{p:.3f}" for p in joints], "...") - print("Target joints (rad): ", [f"{t:.3f}" for t in target], "...") + print("Current joints (rad):", self.get_feedback().tolist()) -# Demo def demo_position_control(): - """Demonstrate pure position control""" - - urdf_path = "/home/zl/Downloads/urdf_rm75/RM75-B.urdf" - - if not Path(urdf_path).exists(): - print(f"Error: URDF not found at {urdf_path}") - return - - print("=" * 60) - print("Pure Position Control Demo") - print("=" * 60) - - # Create controller - robot = MuJoCoPositionController(urdf_path, smoothness=0.05, enable_viewer=True) - robot.start() - time.sleep(1) - - print("\n[Test 1] Move joint 1 to 45 degrees") - robot.send_command([0.785, 0, 0, 0, 0, 0, 0]) - robot.wait_until_reached() - robot.print_state() - time.sleep(0.5) - - print("\n[Test 2] Move joint 2 to -30 degrees") - robot.send_command([0, -0.524, 0, 0, 0, 0, 0]) - robot.wait_until_reached() - robot.print_state() - time.sleep(0.5) - - print("\n[Test 3] Move multiple joints simultaneously") - robot.send_command([0.5, -0.4, 0.3, 0.2, 0.1, 0, 0]) - robot.wait_until_reached() - robot.print_state() - time.sleep(0.5) - - print("\n[Test 4] Return home") - robot.send_command([0, 0, 0, 0, 0, 0, 0]) - robot.wait_until_reached() - robot.print_state() - - print("\n" + "=" * 60) - print("✓ All tests passed! Robot is stable and controllable.") - print("=" * 60) - print("\nInteractive mode - close viewer to exit") - - try: - while robot.viewer and robot.viewer.is_running(): - time.sleep(0.1) - except KeyboardInterrupt: - pass - - robot.stop() - + from rm75_ik.stage2_demo import main + return main([]) if __name__ == "__main__": - demo_position_control() + raise SystemExit(demo_position_control()) diff --git a/ik_qp/models/dual_arm_obj/dual_arm_base_link_left_vis_1.obj b/ik_qp/models/dual_arm_obj/dual_arm_base_link_left_vis_1.obj new file mode 100644 index 0000000..88790e7 --- /dev/null +++ b/ik_qp/models/dual_arm_obj/dual_arm_base_link_left_vis_1.obj @@ -0,0 +1,16886 @@ +# File produced by Open Asset Import Library (http://www.assimp.sf.net) +# (assimp v5.2.0) + +mtllib dual_arm_base_link_left_vis_1.mtl + +# 4240 vertex positions +v -1.10085341e-09 0.0549999066 0.000200001785 +v -0.00864972919 0.0543154813 -3.20851301e-09 +v -0.00508615794 0.0547642298 0.000199975548 +v 0.00178991945 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0000000..38fe0eb --- /dev/null +++ b/ik_qp/package.xml @@ -0,0 +1,20 @@ + + + + rm75_ik + 0.3.0 + Independent RM75 Pinocchio, OSQP and MuJoCo control package. + Yikai Fu + Apache-2.0 + + ament_cmake + ament_cmake_python + + python3-numpy + python3-scipy + python3-yaml + + + ament_cmake + + diff --git a/ik_qp/pyproject.toml b/ik_qp/pyproject.toml index 50df255..f0c59cb 100644 --- a/ik_qp/pyproject.toml +++ b/ik_qp/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "rm75-ik-qp" -version = "0.1.0" +version = "0.3.0" description = "Validated Pinocchio and OSQP inverse kinematics for RealMan RM75-B" readme = "README.md" requires-python = "==3.10.*" @@ -14,6 +14,9 @@ dependencies = [ "osqp==0.6.2.post8", "pin==2.6.20", "PyYAML==6.0.3", + "mujoco==3.10.0", + "Pillow==12.2.0", + "Robotic_Arm==1.1.5", ] [project.optional-dependencies] @@ -21,10 +24,13 @@ test = ["pytest==7.4.4"] [project.scripts] rm75-stage1-validate = "rm75_ik.cli:main" +rm75-stage2-validate = "rm75_ik.stage2_cli:main" +rm75-stage2-demo = "rm75_ik.stage2_demo:main" +rm75-stage3-validate = "rm75_ik.stage3_cli:main" [tool.setuptools] package-dir = {"" = "src"} -data-files = {"share/rm75_ik/models" = ["kine_ctrl/urdf_rm75/RM75-B.urdf", "models/dual_arm_mujoco_fixed.urdf"]} +data-files = {"share/rm75_ik/models" = ["kine_ctrl/urdf_rm75/RM75-B.urdf", "models/dual_arm_mujoco_fixed.urdf"], "share/rm75_ik/models/rm75_meshes" = ["kine_ctrl/urdf_rm75/meshes/*.STL"], "share/rm75_ik/models/dual_arm_obj" = ["models/dual_arm_obj/*.obj"]} [tool.setuptools.packages.find] where = ["src"] @@ -32,4 +38,3 @@ where = ["src"] [tool.pytest.ini_options] testpaths = ["tests"] addopts = "-ra" - diff --git a/ik_qp/src/rm75_ik/__init__.py b/ik_qp/src/rm75_ik/__init__.py index 3c4ec50..d59da88 100644 --- a/ik_qp/src/rm75_ik/__init__.py +++ b/ik_qp/src/rm75_ik/__init__.py @@ -1,7 +1,17 @@ from .dual_arm import DualArmAssembly, DualArmMounts, load_dual_arm_mounts from .kinematics import RM75Kinematics, default_urdf_path, pose_errors, validate_se3 +from .mujoco_model import build_normalized_dual_mjcf from .realman_reference import RealManFkReference from .solver import RM75IkSolver, deterministic_recovery_seeds +from .robot_backend import DualArmJointState, RobotBackend +from .teleop_config import ArmTeleopProfile, load_dual_arm_profiles +from .teleop_control import ( + ControllerSample, + ControlCycleResult, + DualArmQpTeleopController, + RelativePoseMapper, + SafetyState, +) from .types import ( IkOptions, IkResult, @@ -14,21 +24,49 @@ from .types import ( __all__ = [ "DualArmAssembly", + "DualArmJointState", "DualArmMounts", + "DualArmMuJoCo", + "DualArmQpTeleopController", + "ControllerSample", + "ControlCycleResult", "IkOptions", "IkResult", "IkStatus", "JointLimits", + "InitialPoseDiagnostic", + "MujocoRobot", + "PlaybackResult", "RM75IkSolver", "RM75Kinematics", "RealManFkReference", + "RelativePoseMapper", + "RobotBackend", + "SafetyState", + "ArmTeleopProfile", "default_urdf_path", + "build_normalized_dual_mjcf", "deterministic_recovery_seeds", "joint_limit_profile", "load_dual_arm_mounts", + "load_dual_arm_profiles", "physical_joint_limits", "pose_errors", "teleop_joint_limits", "validate_se3", ] + +def __getattr__(name): + if name in {"DualArmMuJoCo", "PlaybackResult"}: + from .mujoco_backend import DualArmMuJoCo, PlaybackResult + + return {"DualArmMuJoCo": DualArmMuJoCo, "PlaybackResult": PlaybackResult}[name] + if name in {"MujocoRobot", "InitialPoseDiagnostic"}: + from .mujoco_robot import InitialPoseDiagnostic, MujocoRobot + + return { + "MujocoRobot": MujocoRobot, + "InitialPoseDiagnostic": InitialPoseDiagnostic, + }[name] + raise AttributeError(name) diff --git a/ik_qp/src/rm75_ik/dual_arm.py b/ik_qp/src/rm75_ik/dual_arm.py index 0ae3a4f..68e62bc 100644 --- a/ik_qp/src/rm75_ik/dual_arm.py +++ b/ik_qp/src/rm75_ik/dual_arm.py @@ -21,15 +21,22 @@ def default_dual_source_path() -> Path: ) if source_path.is_file(): return source_path - installed_path = ( + installed_candidates = [ Path(sysconfig.get_path("data")) / "share" / "rm75_ik" / "models" / "dual_arm_mujoco_fixed.urdf" - ) - if installed_path.is_file(): - return installed_path + ] + resolved = Path(__file__).resolve() + if len(resolved.parents) > 4: + installed_candidates.append( + resolved.parents[4] + / "share/rm75_ik/models/dual_arm_mujoco_fixed.urdf" + ) + for installed_path in installed_candidates: + if installed_path.is_file(): + return installed_path raise FileNotFoundError("dual_arm_mujoco_fixed.urdf was not found") @@ -129,4 +136,3 @@ class DualArmAssembly: if arm == "right": return self.mounts.right_base * local raise ValueError("arm must be 'left' or 'right'") - diff --git a/ik_qp/src/rm75_ik/kinematics.py b/ik_qp/src/rm75_ik/kinematics.py index e2b906a..888ff96 100644 --- a/ik_qp/src/rm75_ik/kinematics.py +++ b/ik_qp/src/rm75_ik/kinematics.py @@ -23,15 +23,21 @@ def default_urdf_path() -> Path: ) if source_path.is_file(): return source_path - installed_path = ( + installed_candidates = [ Path(sysconfig.get_path("data")) / "share" / "rm75_ik" / "models" / "RM75-B.urdf" - ) - if installed_path.is_file(): - return installed_path + ] + resolved = Path(__file__).resolve() + if len(resolved.parents) > 4: + installed_candidates.append( + resolved.parents[4] / "share/rm75_ik/models/RM75-B.urdf" + ) + for installed_path in installed_candidates: + if installed_path.is_file(): + return installed_path raise FileNotFoundError("RM75-B.urdf was not found in source or installed data") @@ -121,4 +127,3 @@ class RM75Kinematics: pin.ReferenceFrame.LOCAL, ) return np.asarray(jacobian).copy() - diff --git a/ik_qp/src/rm75_ik/mujoco_backend.py b/ik_qp/src/rm75_ik/mujoco_backend.py new file mode 100644 index 0000000..4d8d817 --- /dev/null +++ b/ik_qp/src/rm75_ik/mujoco_backend.py @@ -0,0 +1,247 @@ +from __future__ import annotations + +from dataclasses import dataclass +from time import perf_counter, sleep +from typing import Iterable, Optional + +import mujoco +import numpy as np +import pinocchio as pin + +from .kinematics import validate_se3 +from .mujoco_model import build_normalized_dual_mjcf +from .types import JointLimits, physical_joint_limits + + +CONTROLLED_HOME_Q_RAD = np.deg2rad([0.0, 30.0, 0.0, 60.0, 0.0, 60.0, 0.0]) +PROJECT_INITIAL_Q_RAD = { + "left": np.deg2rad([-167.21, 28.48, 28.21, 61.35, -14.40, 84.49, -124.51]), + "right": np.deg2rad([-25.60, 34.09, -19.55, 71.59, 16.97, 80.98, 59.67]), +} + + +@dataclass(frozen=True) +class PlaybackResult: + samples: int + elapsed_sec: float + max_joint_step_rad: float + final_flange_pose: pin.SE3 + + +class DualArmMuJoCo: + """Threadless, kinematic MuJoCo backend for the normalized dual RM75 scene.""" + + def __init__( + self, + controlled_arm: str = "left", + inactive_q_rad: Optional[np.ndarray] = None, + limits: Optional[JointLimits] = None, + ) -> None: + if controlled_arm not in {"left", "right"}: + raise ValueError("controlled_arm must be 'left' or 'right'") + self.controlled_arm = controlled_arm + self.inactive_arm = "right" if controlled_arm == "left" else "left" + self.limits = limits or physical_joint_limits() + self.mjcf_xml, self.assets = build_normalized_dual_mjcf() + self.model = mujoco.MjModel.from_xml_string(self.mjcf_xml, self.assets) + self.data = mujoco.MjData(self.model) + self._qpos_addresses = { + arm: np.array( + [ + self.model.jnt_qposadr[ + mujoco.mj_name2id( + self.model, + mujoco.mjtObj.mjOBJ_JOINT, + f"{arm}_joint_{joint_index}", + ) + ] + for joint_index in range(1, 8) + ], + dtype=int, + ) + for arm in ("left", "right") + } + self._dof_addresses = { + arm: np.array( + [ + self.model.jnt_dofadr[ + mujoco.mj_name2id( + self.model, + mujoco.mjtObj.mjOBJ_JOINT, + f"{arm}_joint_{joint_index}", + ) + ] + for joint_index in range(1, 8) + ], + dtype=int, + ) + for arm in ("left", "right") + } + self._site_ids = { + arm: mujoco.mj_name2id( + self.model, mujoco.mjtObj.mjOBJ_SITE, f"{arm}_flange" + ) + for arm in ("left", "right") + } + self._target_mocap_ids = {} + for arm in ("left", "right"): + marker_body_id = mujoco.mj_name2id( + self.model, mujoco.mjtObj.mjOBJ_BODY, f"{arm}_target_marker" + ) + mocap_id = int(self.model.body_mocapid[marker_body_id]) + if mocap_id < 0: + raise ValueError(f"{arm}_target_marker is not a MuJoCo mocap body") + self._target_mocap_ids[arm] = mocap_id + + inactive = ( + PROJECT_INITIAL_Q_RAD[self.inactive_arm] + if inactive_q_rad is None + else np.asarray(inactive_q_rad, dtype=float) + ) + self.set_arm_configuration(self.inactive_arm, inactive) + self.set_arm_configuration(self.controlled_arm, CONTROLLED_HOME_Q_RAD) + for arm in ("left", "right"): + self.set_arm_target_marker(arm, self.get_flange_pose(arm)) + self._manual_inactive_q: Optional[np.ndarray] = None + + @staticmethod + def _validate_arm(arm: str) -> None: + if arm not in {"left", "right"}: + raise ValueError("arm must be 'left' or 'right'") + + def _validate_q(self, q_rad: np.ndarray) -> np.ndarray: + q = np.asarray(q_rad, dtype=float) + if q.shape != (7,): + raise ValueError(f"arm configuration must have shape (7,), got {q.shape}") + if not np.all(np.isfinite(q)): + raise ValueError("arm configuration must be finite") + if not self.limits.contains(q): + raise ValueError(f"configuration is outside {self.limits.name} joint limits") + return q.copy() + + def set_arm_configuration(self, arm: str, q_rad: np.ndarray) -> None: + self._validate_arm(arm) + q = self._validate_q(q_rad) + self.data.qpos[self._qpos_addresses[arm]] = q + self.data.qvel[:] = 0.0 + mujoco.mj_forward(self.model, self.data) + + def set_dual_configuration( + self, left_q_rad: np.ndarray, right_q_rad: np.ndarray + ) -> None: + left_q = self._validate_q(left_q_rad) + right_q = self._validate_q(right_q_rad) + self.data.qpos[self._qpos_addresses["left"]] = left_q + self.data.qpos[self._qpos_addresses["right"]] = right_q + self.data.qvel[:] = 0.0 + mujoco.mj_forward(self.model, self.data) + + def get_arm_configuration(self, arm: str) -> np.ndarray: + self._validate_arm(arm) + return self.data.qpos[self._qpos_addresses[arm]].copy() + + def get_flange_pose(self, arm: str) -> pin.SE3: + self._validate_arm(arm) + site_id = self._site_ids[arm] + return pin.SE3( + self.data.site_xmat[site_id].reshape(3, 3).copy(), + self.data.site_xpos[site_id].copy(), + ) + + def set_target_marker(self, target_se3: pin.SE3) -> None: + self.set_arm_target_marker(self.controlled_arm, target_se3) + + def set_arm_target_marker(self, arm: str, target_se3: pin.SE3) -> None: + self._validate_arm(arm) + validate_se3(target_se3, "target_se3") + quaternion = pin.Quaternion(target_se3.rotation) + mocap_id = self._target_mocap_ids[arm] + self.data.mocap_pos[mocap_id] = target_se3.translation + self.data.mocap_quat[mocap_id] = [ + quaternion.w, + quaternion.x, + quaternion.y, + quaternion.z, + ] + mujoco.mj_forward(self.model, self.data) + + def _validated_trajectory(self, q_trajectory: Iterable[np.ndarray]) -> np.ndarray: + trajectory = np.asarray(list(q_trajectory), dtype=float) + if trajectory.ndim != 2 or trajectory.shape[1:] != (7,): + raise ValueError("q_trajectory must have shape (N, 7)") + if trajectory.shape[0] == 0: + raise ValueError("q_trajectory must contain at least one sample") + if not np.all(np.isfinite(trajectory)): + raise ValueError("q_trajectory must be finite") + if np.any(trajectory < self.limits.lower) or np.any( + trajectory > self.limits.upper + ): + raise ValueError(f"trajectory exceeds {self.limits.name} joint limits") + return trajectory + + def play_trajectory( + self, + q_trajectory: Iterable[np.ndarray], + dt: float = 1.0 / 90.0, + realtime: bool = False, + viewer=None, + ) -> PlaybackResult: + if not np.isfinite(dt) or dt <= 0.0: + raise ValueError("dt must be finite and positive") + trajectory = self._validated_trajectory(q_trajectory) + started = perf_counter() + previous = self.get_arm_configuration(self.controlled_arm) + max_step = 0.0 + for q in trajectory: + frame_started = perf_counter() + max_step = max(max_step, float(np.max(np.abs(q - previous)))) + self.set_arm_configuration(self.controlled_arm, q) + previous = q + if viewer is not None: + viewer.sync() + if realtime: + remaining = dt - (perf_counter() - frame_started) + if remaining > 0.0: + sleep(remaining) + return PlaybackResult( + samples=len(trajectory), + elapsed_sec=perf_counter() - started, + max_joint_step_rad=max_step, + final_flange_pose=self.get_flange_pose(self.controlled_arm), + ) + + def configure_manual_drag(self, damping: float = 1.5) -> None: + if not np.isfinite(damping) or damping <= 0.0: + raise ValueError("manual-drag damping must be finite and positive") + self.model.opt.gravity[:] = 0.0 + self.model.dof_damping[self._dof_addresses[self.controlled_arm]] = damping + self.data.qvel[:] = 0.0 + self.data.xfrc_applied[:] = 0.0 + self._manual_inactive_q = self.get_arm_configuration(self.inactive_arm) + mujoco.mj_forward(self.model, self.data) + + def step_manual_drag(self) -> None: + if self._manual_inactive_q is None: + raise RuntimeError("configure_manual_drag() must be called first") + mujoco.mj_step(self.model, self.data) + self.data.qpos[self._qpos_addresses[self.inactive_arm]] = self._manual_inactive_q + self.data.qvel[self._dof_addresses[self.inactive_arm]] = 0.0 + mujoco.mj_forward(self.model, self.data) + + def render( + self, + width: int = 1280, + height: int = 720, + *, + segmentation: bool = False, + ) -> np.ndarray: + if width <= 0 or height <= 0: + raise ValueError("render dimensions must be positive") + renderer = mujoco.Renderer(self.model, height=height, width=width) + try: + if segmentation: + renderer.enable_segmentation_rendering() + renderer.update_scene(self.data, camera="overview") + return renderer.render().copy() + finally: + renderer.close() diff --git a/ik_qp/src/rm75_ik/mujoco_model.py b/ik_qp/src/rm75_ik/mujoco_model.py new file mode 100644 index 0000000..042abef --- /dev/null +++ b/ik_qp/src/rm75_ik/mujoco_model.py @@ -0,0 +1,413 @@ +from __future__ import annotations + +import re +import xml.etree.ElementTree as ET +from pathlib import Path +from typing import Dict, Iterable, Optional, Tuple + +import numpy as np +import pinocchio as pin + +from .dual_arm import default_dual_source_path, load_dual_arm_mounts +from .kinematics import default_urdf_path +from .types import physical_joint_limits + + +def _numbers(text: str, expected: int) -> np.ndarray: + values = np.fromstring(text, sep=" ", dtype=float) + if values.shape != (expected,): + raise ValueError(f"expected {expected} numeric values, got {text!r}") + return values + + +def _format(values: Iterable[float]) -> str: + return " ".join(f"{float(value):.12g}" for value in values) + + +def _quaternion_from_rpy(rpy: np.ndarray) -> np.ndarray: + quaternion = pin.Quaternion(pin.rpy.rpyToMatrix(*rpy)) + return np.array([quaternion.w, quaternion.x, quaternion.y, quaternion.z]) + + +def _se3_attributes(transform: pin.SE3) -> Dict[str, str]: + quaternion = pin.Quaternion(transform.rotation) + return { + "pos": _format(transform.translation), + "quat": _format([quaternion.w, quaternion.x, quaternion.y, quaternion.z]), + } + + +def _origin_attributes(parent: ET.Element) -> Dict[str, str]: + origin = parent.find("origin") + if origin is None: + return {"pos": "0 0 0", "quat": "1 0 0 0"} + xyz = _numbers(origin.get("xyz", "0 0 0"), 3) + rpy = _numbers(origin.get("rpy", "0 0 0"), 3) + return {"pos": _format(xyz), "quat": _format(_quaternion_from_rpy(rpy))} + + +def _mesh_asset_name(filename: str, prefix: str) -> str: + stem = Path(filename).stem.lower() + return f"{prefix}_{re.sub(r'[^a-z0-9_]+', '_', stem)}" + + +def _dual_obj_directory(dual_source_path: Path) -> Path: + source_candidate = dual_source_path.parent / "dual_arm_obj" + if source_candidate.is_dir(): + return source_candidate + raise FileNotFoundError( + f"dual-arm OBJ directory was not found beside {dual_source_path}" + ) + + +def _single_mesh_directory(single_urdf_path: Path) -> Path: + candidates = ( + single_urdf_path.parent / "meshes", + single_urdf_path.parent / "rm75_meshes", + ) + for candidate in candidates: + if candidate.is_dir(): + return candidate + raise FileNotFoundError( + f"RM75-B STL mesh directory was not found beside {single_urdf_path}" + ) + + +def _add_inertial(body: ET.Element, link: ET.Element) -> None: + inertial = link.find("inertial") + if inertial is None: + raise ValueError(f"link {link.get('name')!r} has no inertial data") + mass_element = inertial.find("mass") + inertia_element = inertial.find("inertia") + if mass_element is None or inertia_element is None: + raise ValueError(f"link {link.get('name')!r} has incomplete inertial data") + origin = inertial.find("origin") + xyz = _numbers(origin.get("xyz", "0 0 0"), 3) if origin is not None else np.zeros(3) + rpy = _numbers(origin.get("rpy", "0 0 0"), 3) if origin is not None else np.zeros(3) + inertia_matrix = np.array( + [ + [float(inertia_element.get("ixx")), float(inertia_element.get("ixy")), float(inertia_element.get("ixz"))], + [float(inertia_element.get("ixy")), float(inertia_element.get("iyy")), float(inertia_element.get("iyz"))], + [float(inertia_element.get("ixz")), float(inertia_element.get("iyz")), float(inertia_element.get("izz"))], + ] + ) + rotation = pin.rpy.rpyToMatrix(*rpy) + inertia_matrix = rotation @ inertia_matrix @ rotation.T + full_inertia = [ + inertia_matrix[0, 0], + inertia_matrix[1, 1], + inertia_matrix[2, 2], + inertia_matrix[0, 1], + inertia_matrix[0, 2], + inertia_matrix[1, 2], + ] + ET.SubElement( + body, + "inertial", + { + "pos": _format(xyz), + "mass": mass_element.get("value", "0"), + "fullinertia": _format(full_inertia), + }, + ) + + +def _add_link_visual( + body: ET.Element, + link: ET.Element, + arm: str, + single_mesh_keys: Dict[str, str], +) -> None: + visual = link.find("visual") + if visual is None: + return + mesh = visual.find("geometry/mesh") + if mesh is None: + return + filename = Path(mesh.get("filename", "")).name + try: + mesh_name = single_mesh_keys[filename] + except KeyError as exc: + raise ValueError(f"missing packaged single-arm mesh {filename!r}") from exc + ET.SubElement( + body, + "geom", + { + "name": f"{arm}_{link.get('name')}_visual", + "type": "mesh", + "mesh": mesh_name, + "material": f"{arm}_arm", + "contype": "0", + "conaffinity": "0", + "group": "1", + **_origin_attributes(visual), + }, + ) + + +def _add_arm( + worldbody: ET.Element, + arm: str, + mount: pin.SE3, + single_root: ET.Element, + single_mesh_keys: Dict[str, str], + gripper_mesh_name: str, +) -> None: + links = {link.get("name"): link for link in single_root.findall("link")} + joints_by_parent: Dict[str, list[ET.Element]] = {} + for joint in single_root.findall("joint"): + parent_element = joint.find("parent") + if parent_element is None: + continue + joints_by_parent.setdefault(parent_element.get("link", ""), []).append(joint) + + limits = physical_joint_limits() + base_link = links["base_link"] + base_body = ET.SubElement( + worldbody, + "body", + {"name": f"{arm}_base_link", **_se3_attributes(mount)}, + ) + _add_link_visual(base_body, base_link, arm, single_mesh_keys) + + def append_children(parent_body: ET.Element, parent_link_name: str) -> None: + for joint in joints_by_parent.get(parent_link_name, []): + child_element = joint.find("child") + if child_element is None: + raise ValueError(f"joint {joint.get('name')!r} has no child") + child_name = child_element.get("link", "") + child_link = links[child_name] + body = ET.SubElement( + parent_body, + "body", + { + "name": f"{arm}_{child_name}", + **_origin_attributes(joint), + }, + ) + joint_index = int(joint.get("name", "joint_0").split("_")[-1]) - 1 + axis_element = joint.find("axis") + axis = "0 0 1" if axis_element is None else axis_element.get("xyz", "0 0 1") + ET.SubElement( + body, + "joint", + { + "name": f"{arm}_joint_{joint_index + 1}", + "type": "hinge", + "axis": axis, + "range": _format( + [limits.lower[joint_index], limits.upper[joint_index]] + ), + "limited": "true", + "damping": "0", + }, + ) + _add_inertial(body, child_link) + _add_link_visual(body, child_link, arm, single_mesh_keys) + if child_name == "link_7": + ET.SubElement( + body, + "site", + { + "name": f"{arm}_flange", + "type": "sphere", + "size": "0.008", + "rgba": "0.1 0.9 0.2 1" if arm == "left" else "0.1 0.5 0.95 1", + "group": "2", + }, + ) + ET.SubElement( + body, + "geom", + { + "name": f"{arm}_gripper_visual", + "type": "mesh", + "mesh": gripper_mesh_name, + "pos": "0 0 0.092", + "quat": _format(_quaternion_from_rpy(np.array([-np.pi, np.pi, -np.pi]))), + "material": f"{arm}_gripper", + "contype": "0", + "conaffinity": "0", + "group": "1", + }, + ) + append_children(body, child_name) + + append_children(base_body, "base_link") + + +def build_normalized_dual_mjcf( + single_urdf_path: Optional[Path | str] = None, + dual_source_path: Optional[Path | str] = None, +) -> Tuple[str, Dict[str, bytes]]: + """Build a canonical 14-DOF dual-arm MJCF and its in-memory mesh assets.""" + + single_path = ( + Path(single_urdf_path) if single_urdf_path is not None else default_urdf_path() + ) + dual_path = ( + Path(dual_source_path) + if dual_source_path is not None + else default_dual_source_path() + ) + single_root = ET.parse(single_path).getroot() + dual_root = ET.parse(dual_path).getroot() + single_mesh_dir = _single_mesh_directory(single_path) + dual_obj_dir = _dual_obj_directory(dual_path) + + mujoco_root = ET.Element("mujoco", {"model": "rm75_normalized_dual_stage2"}) + ET.SubElement( + mujoco_root, + "compiler", + { + "angle": "radian", + "autolimits": "true", + "inertiafromgeom": "false", + "balanceinertia": "true", + }, + ) + ET.SubElement( + mujoco_root, + "option", + {"timestep": "0.002", "gravity": "0 0 -9.81", "integrator": "implicitfast"}, + ) + ET.SubElement(mujoco_root, "statistic", {"center": "0 0 0.65", "extent": "1.4"}) + visual = ET.SubElement(mujoco_root, "visual") + ET.SubElement( + visual, + "global", + { + "azimuth": "90", + "elevation": "-18", + "offwidth": "1280", + "offheight": "720", + }, + ) + ET.SubElement(visual, "rgba", {"haze": "0.15 0.18 0.2 1"}) + + assets_element = ET.SubElement(mujoco_root, "asset") + ET.SubElement(assets_element, "material", {"name": "left_arm", "rgba": "0.82 0.84 0.86 1"}) + ET.SubElement(assets_element, "material", {"name": "right_arm", "rgba": "0.7 0.74 0.78 1"}) + ET.SubElement(assets_element, "material", {"name": "left_gripper", "rgba": "0.15 0.75 0.85 1"}) + ET.SubElement(assets_element, "material", {"name": "right_gripper", "rgba": "0.9 0.48 0.18 1"}) + ET.SubElement(assets_element, "material", {"name": "platform", "rgba": "0.28 0.31 0.34 1"}) + + assets: Dict[str, bytes] = {} + single_mesh_keys: Dict[str, str] = {} + for mesh_path in sorted(single_mesh_dir.glob("*.STL")): + asset_key = f"rm75_meshes/{mesh_path.name}" + mesh_name = _mesh_asset_name(mesh_path.name, "rm75") + assets[asset_key] = mesh_path.read_bytes() + single_mesh_keys[mesh_path.name] = mesh_name + ET.SubElement(assets_element, "mesh", {"name": mesh_name, "file": asset_key}) + + dual_mesh_names: Dict[str, str] = {} + for mesh_path in sorted(dual_obj_dir.glob("*.obj")): + asset_key = f"dual_arm_obj/{mesh_path.name}" + mesh_name = _mesh_asset_name(mesh_path.name, "dual") + assets[asset_key] = mesh_path.read_bytes() + dual_mesh_names[mesh_path.name] = mesh_name + ET.SubElement(assets_element, "mesh", {"name": mesh_name, "file": asset_key}) + if len(dual_mesh_names) != 19: + raise ValueError(f"expected 19 dual-arm OBJ assets, found {len(dual_mesh_names)}") + + worldbody = ET.SubElement(mujoco_root, "worldbody") + ET.SubElement( + worldbody, + "light", + { + "name": "key_light", + "pos": "0 -1.2 2.8", + "dir": "0 0.4 -1", + "diffuse": "0.9 0.9 0.9", + }, + ) + ET.SubElement( + worldbody, + "camera", + { + "name": "overview", + "pos": "0 -2.6 1.25", + "xyaxes": "1 0 0 0 0.3 0.953939", + "fovy": "45", + }, + ) + ET.SubElement( + worldbody, + "geom", + { + "name": "floor", + "type": "plane", + "size": "2.5 2.5 0.05", + "rgba": "0.12 0.14 0.16 1", + "contype": "0", + "conaffinity": "0", + "group": "0", + }, + ) + + robot_base = dual_root.find("./link[@name='robot_base']") + if robot_base is None: + raise ValueError("dual-arm source URDF has no robot_base link") + for visual_element in robot_base.findall("visual"): + mesh_element = visual_element.find("geometry/mesh") + if mesh_element is None: + continue + filename = Path(mesh_element.get("filename", "")).name + ET.SubElement( + worldbody, + "geom", + { + "name": f"platform_{visual_element.get('name', filename)}", + "type": "mesh", + "mesh": dual_mesh_names[filename], + "material": "platform", + "contype": "0", + "conaffinity": "0", + "group": "1", + **_origin_attributes(visual_element), + }, + ) + + mounts = load_dual_arm_mounts(dual_path) + _add_arm( + worldbody, + "left", + mounts.left_base, + single_root, + single_mesh_keys, + dual_mesh_names["dual_arm_gripper1_vis_1.obj"], + ) + _add_arm( + worldbody, + "right", + mounts.right_base, + single_root, + single_mesh_keys, + dual_mesh_names["dual_arm_gripper2_vis_1.obj"], + ) + for arm, color in ( + ("left", "0.95 0.12 0.12 0.8"), + ("right", "0.95 0.75 0.08 0.8"), + ): + marker = ET.SubElement( + worldbody, + "body", + {"name": f"{arm}_target_marker", "mocap": "true", "pos": "0 0 0"}, + ) + ET.SubElement( + marker, + "geom", + { + "name": f"{arm}_target_marker_geom", + "type": "sphere", + "size": "0.018", + "rgba": color, + "contype": "0", + "conaffinity": "0", + "group": "2", + }, + ) + + ET.indent(mujoco_root, space=" ") + return ET.tostring(mujoco_root, encoding="unicode"), assets diff --git a/ik_qp/src/rm75_ik/mujoco_robot.py b/ik_qp/src/rm75_ik/mujoco_robot.py new file mode 100644 index 0000000..671a40d --- /dev/null +++ b/ik_qp/src/rm75_ik/mujoco_robot.py @@ -0,0 +1,185 @@ +from __future__ import annotations + +from dataclasses import dataclass +from time import sleep +from typing import Collection, Dict, Mapping, Optional + +import numpy as np +import pinocchio as pin + +from .dual_arm import DualArmAssembly +from .kinematics import RM75Kinematics, pose_errors, validate_se3 +from .mujoco_backend import DualArmMuJoCo +from .robot_backend import DualArmJointState +from .solver import RM75IkSolver, deterministic_recovery_seeds +from .teleop_config import ArmName, ArmTeleopProfile +from .types import IkOptions, physical_joint_limits, teleop_joint_limits + + +@dataclass(frozen=True) +class InitialPoseDiagnostic: + arm: ArmName + solved_q_rad: np.ndarray + solved_position_error_m: float + solved_orientation_error_rad: float + configured_joint_position_error_m: float + configured_joint_orientation_error_rad: float + + +class MujocoRobot: + """Dual-arm kinematic backend implementing the backend-neutral robot contract.""" + + def __init__( + self, + profiles: Mapping[ArmName, ArmTeleopProfile], + *, + initialize_from_tcp: bool = True, + ) -> None: + if set(profiles) != {"left", "right"}: + raise ValueError("profiles must contain left and right arms") + self.profiles = dict(profiles) + self.scene = DualArmMuJoCo(controlled_arm="left", limits=teleop_joint_limits()) + self.assembly = DualArmAssembly.from_source_urdf() + self._kinematics = { + arm: RM75Kinematics(limits=teleop_joint_limits()) + for arm in ("left", "right") + } + self._viewer = None + self._closed = False + self._stopped_arms: set[ArmName] = set() + self.initial_pose_diagnostics: Dict[ArmName, InitialPoseDiagnostic] = {} + if initialize_from_tcp: + self._initialize_from_configured_tcp() + + def _initialize_from_configured_tcp(self) -> None: + solved: Dict[ArmName, np.ndarray] = {} + limits = teleop_joint_limits() + physical_kinematics = RM75Kinematics(limits=physical_joint_limits()) + for seed_offset, arm in enumerate(("left", "right")): + profile = self.profiles[arm] + kinematics = RM75Kinematics(limits=limits) + solver = RM75IkSolver(kinematics) + flange_target = profile.initial_tcp * profile.tool_from_flange.inverse() + seeds = deterministic_recovery_seeds( + limits, count=24, random_seed=750 + seed_offset + ) + if limits.contains(profile.configured_initial_q_rad): + seeds.insert(0, profile.configured_initial_q_rad) + result = solver.solve_multistart( + flange_target, + seeds, + IkOptions(max_iterations=700, time_limit_sec=None), + ) + if not result.success or result.q is None: + raise RuntimeError( + f"failed to resolve {arm} initial_tcp_pose: " + f"{result.status.value}: {result.message}" + ) + solved[arm] = result.q.copy() + solved_tcp = kinematics.forward(result.q, profile.tool_from_flange) + solved_error = pose_errors(solved_tcp, profile.initial_tcp) + configured_tcp = physical_kinematics.forward( + profile.configured_initial_q_rad, profile.tool_from_flange + ) + configured_error = pose_errors(configured_tcp, profile.initial_tcp) + q = result.q.copy() + q.setflags(write=False) + self.initial_pose_diagnostics[arm] = InitialPoseDiagnostic( + arm=arm, + solved_q_rad=q, + solved_position_error_m=solved_error[0], + solved_orientation_error_rad=solved_error[1], + configured_joint_position_error_m=configured_error[0], + configured_joint_orientation_error_rad=configured_error[1], + ) + self.scene.set_dual_configuration(solved["left"], solved["right"]) + for arm in ("left", "right"): + self.set_target_tcp_pose(arm, self.profiles[arm].initial_tcp) + + def connect(self) -> None: + if self._closed: + raise RuntimeError("MujocoRobot is closed") + + def read_joint_positions(self) -> DualArmJointState: + self._require_open() + return DualArmJointState( + { + arm: self.scene.get_arm_configuration(arm) + for arm in ("left", "right") + } + ) + + def command_joint_positions( + self, targets_rad: Mapping[ArmName, np.ndarray] + ) -> None: + self._require_open() + if not targets_rad or not set(targets_rad).issubset({"left", "right"}): + raise ValueError("joint targets must contain at least one valid arm") + current = self.read_joint_positions().positions_rad + left = np.asarray(targets_rad.get("left", current["left"]), dtype=float) + right = np.asarray(targets_rad.get("right", current["right"]), dtype=float) + self.scene.set_dual_configuration(left, right) + self._stopped_arms.difference_update(targets_rad) + + def set_target_tcp_pose(self, arm: ArmName, target_tcp: pin.SE3) -> None: + self._require_open() + if arm not in ("left", "right"): + raise ValueError("arm must be 'left' or 'right'") + validate_se3(target_tcp, "target_tcp") + mount = ( + self.assembly.mounts.left_base + if arm == "left" + else self.assembly.mounts.right_base + ) + self.scene.set_arm_target_marker(arm, mount * target_tcp) + + def get_tcp_pose(self, arm: ArmName) -> pin.SE3: + self._require_open() + q = self.scene.get_arm_configuration(arm) + return self._kinematics[arm].forward( + q, self.profiles[arm].tool_from_flange + ) + + def stop(self, arms: Collection[ArmName] = ("left", "right")) -> None: + self._require_open() + selected = set(arms) + if not selected.issubset({"left", "right"}): + raise ValueError("stop arms must contain only left/right") + self.scene.data.qvel[:] = 0.0 + self._stopped_arms.update(selected) + + def open_viewer(self): + self._require_open() + if self._viewer is None: + import mujoco.viewer + + self._viewer = mujoco.viewer.launch_passive( + self.scene.model, self.scene.data + ) + return self._viewer + + def sync_viewer(self) -> bool: + if self._viewer is None: + return True + if not self._viewer.is_running(): + return False + self._viewer.sync() + return True + + def render(self, width: int = 1280, height: int = 720) -> np.ndarray: + self._require_open() + return self.scene.render(width, height) + + def close(self) -> None: + if self._closed: + return + if self._viewer is not None: + self._viewer.close() + self._viewer = None + sleep(0.2) + self.scene.data.qvel[:] = 0.0 + self._closed = True + + def _require_open(self) -> None: + if self._closed: + raise RuntimeError("MujocoRobot is closed") diff --git a/ik_qp/src/rm75_ik/mujoco_trajectories.py b/ik_qp/src/rm75_ik/mujoco_trajectories.py new file mode 100644 index 0000000..8cec0eb --- /dev/null +++ b/ik_qp/src/rm75_ik/mujoco_trajectories.py @@ -0,0 +1,109 @@ +from __future__ import annotations + +from math import radians +from typing import Iterable, List + +import numpy as np +import pinocchio as pin + +from .kinematics import validate_se3 +from .solver import RM75IkSolver +from .types import IkOptions + + +DEMO_TRAJECTORIES = ("joint", "line", "arc", "orientation", "combined") + + +def se3_target_trajectory( + start_pose: pin.SE3, + target_pose: pin.SE3, + points: int, +) -> List[pin.SE3]: + """Interpolate translation linearly and orientation on SO(3).""" + + if points < 2: + raise ValueError("trajectory must contain at least two points") + validate_se3(start_pose, "start_pose") + validate_se3(target_pose, "target_pose") + rotation_delta = pin.log3(start_pose.rotation.T @ target_pose.rotation) + targets = [] + for fraction in np.linspace(0.0, 1.0, points): + translation = ( + (1.0 - fraction) * start_pose.translation + + fraction * target_pose.translation + ) + rotation = start_pose.rotation @ pin.exp3(fraction * rotation_delta) + targets.append(pin.SE3(rotation, translation)) + return targets + + +def cartesian_demo_targets( + kind: str, + start_pose: pin.SE3, + points: int = 180, +) -> List[pin.SE3]: + if kind not in DEMO_TRAJECTORIES[1:]: + raise ValueError(f"Cartesian trajectory must be one of {DEMO_TRAJECTORIES[1:]}") + if points < 2: + raise ValueError("trajectory must contain at least two points") + validate_se3(start_pose, "start_pose") + targets: List[pin.SE3] = [] + for fraction in np.linspace(0.0, 1.0, points): + translation = start_pose.translation.copy() + rotation = start_pose.rotation.copy() + if kind == "line": + translation += np.array([0.04 * fraction, 0.0, 0.0]) + elif kind == "arc": + angle = 0.5 * np.pi * fraction + translation += np.array( + [0.03 * np.sin(angle), 0.03 * (1.0 - np.cos(angle)), 0.0] + ) + elif kind == "orientation": + rotation = rotation @ pin.rpy.rpyToMatrix(0.0, 0.0, radians(15) * fraction) + elif kind == "combined": + translation += np.array([0.035 * fraction, 0.015 * fraction, 0.0]) + rotation = rotation @ pin.rpy.rpyToMatrix( + radians(8) * fraction, + 0.0, + radians(12) * fraction, + ) + targets.append(pin.SE3(rotation, translation)) + return targets + + +def joint_demo_trajectory( + start_q_rad: np.ndarray, + points: int = 180, +) -> np.ndarray: + start = np.asarray(start_q_rad, dtype=float) + if start.shape != (7,) or not np.all(np.isfinite(start)): + raise ValueError("start_q_rad must be a finite shape-(7,) vector") + if points < 2: + raise ValueError("trajectory must contain at least two points") + offset = np.deg2rad([12.0, -8.0, 10.0, 8.0, -6.0, 7.0, 10.0]) + blend = 0.5 - 0.5 * np.cos(np.linspace(0.0, np.pi, points)) + return start[None, :] + blend[:, None] * offset[None, :] + + +def solve_pose_trajectory( + solver: RM75IkSolver, + targets: Iterable[pin.SE3], + seed_q_rad: np.ndarray, + options: IkOptions = IkOptions( + position_tolerance_m=9e-4, + orientation_tolerance_rad=radians(0.09), + max_iterations=200, + ), +) -> np.ndarray: + seed = np.asarray(seed_q_rad, dtype=float).copy() + solutions = [] + for index, target in enumerate(targets): + result = solver.solve(target, seed, options) + if not result.success or result.q is None: + raise RuntimeError( + f"IK failed at trajectory point {index}: " + f"{result.status.value} {result.message}" + ) + seed = result.q.copy() + solutions.append(seed) + return np.asarray(solutions) diff --git a/ik_qp/src/rm75_ik/robot_backend.py b/ik_qp/src/rm75_ik/robot_backend.py new file mode 100644 index 0000000..860a80c --- /dev/null +++ b/ik_qp/src/rm75_ik/robot_backend.py @@ -0,0 +1,43 @@ +from __future__ import annotations + +from dataclasses import dataclass +from typing import Collection, Dict, Mapping, Protocol, runtime_checkable + +import numpy as np +import pinocchio as pin + +from .teleop_config import ArmName + + +@dataclass(frozen=True) +class DualArmJointState: + positions_rad: Mapping[ArmName, np.ndarray] + + def __post_init__(self) -> None: + normalized: Dict[ArmName, np.ndarray] = {} + if set(self.positions_rad) != {"left", "right"}: + raise ValueError("dual-arm state must contain left and right positions") + for arm, values in self.positions_rad.items(): + q = np.asarray(values, dtype=float).copy() + if q.shape != (7,) or not np.all(np.isfinite(q)): + raise ValueError(f"{arm} joint state must be finite with shape (7,)") + q.setflags(write=False) + normalized[arm] = q + object.__setattr__(self, "positions_rad", normalized) + + +@runtime_checkable +class RobotBackend(Protocol): + def connect(self) -> None: ... + + def read_joint_positions(self) -> DualArmJointState: ... + + def command_joint_positions( + self, targets_rad: Mapping[ArmName, np.ndarray] + ) -> None: ... + + def set_target_tcp_pose(self, arm: ArmName, target_tcp: pin.SE3) -> None: ... + + def stop(self, arms: Collection[ArmName] = ("left", "right")) -> None: ... + + def close(self) -> None: ... diff --git a/ik_qp/src/rm75_ik/stage2_cli.py b/ik_qp/src/rm75_ik/stage2_cli.py new file mode 100644 index 0000000..c5f3dfb --- /dev/null +++ b/ik_qp/src/rm75_ik/stage2_cli.py @@ -0,0 +1,80 @@ +from __future__ import annotations + +import argparse +import os +import sys +from pathlib import Path +from typing import Optional, Sequence + + +os.environ.setdefault("MUJOCO_GL", "egl") + + +def _default_output_dir() -> Path: + package_root = Path(__file__).resolve().parents[2] + if (package_root / "pyproject.toml").is_file(): + return package_root / "artifacts" / "stage2" + return Path.cwd() / "stage2_artifacts" + + +def build_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser( + description="Headless single-arm IK validation in the normalized dual RM75 scene" + ) + parser.add_argument("--arm", choices=("left", "right"), default="left") + parser.add_argument( + "--sdk-root", + type=Path, + help="directory containing the RealMan Robotic_Arm Python package", + ) + parser.add_argument("--output-dir", type=Path, default=_default_output_dir()) + parser.add_argument("--seed", type=int, default=20260630) + parser.add_argument("--quick", action="store_true") + parser.add_argument( + "--report-only", + action="store_true", + help="return exit code zero while preserving failed checks in reports", + ) + return parser + + +def main(argv: Optional[Sequence[str]] = None) -> int: + args = build_parser().parse_args(argv) + from .realman_reference import RealManFkReference + from .stage2_validation import ( + Stage2Settings, + Stage2Validator, + write_stage2_report, + ) + + settings = ( + Stage2Settings.quick(seed=args.seed) + if args.quick + else Stage2Settings(seed=args.seed) + ) + validator = Stage2Validator( + RealManFkReference(args.sdk_root), + controlled_arm=args.arm, + settings=settings, + ) + summary = validator.run() + json_path, csv_path, markdown_path, image_paths = write_stage2_report( + args.output_dir, + summary, + validator.failures, + validator.images, + ) + print(f"RM75-B stage-2 validation: {'PASS' if summary['passed'] else 'FAIL'}") + for name, check in summary["checks"].items(): + print(f" [{'PASS' if check['passed'] else 'FAIL'}] {name}") + print("Reports:") + for path in (json_path, csv_path, markdown_path, *image_paths): + print(f" {path}") + if args.report_only or summary["passed"]: + return 0 + return 1 + + +if __name__ == "__main__": + sys.exit(main()) + diff --git a/ik_qp/src/rm75_ik/stage2_demo.py b/ik_qp/src/rm75_ik/stage2_demo.py new file mode 100644 index 0000000..274f224 --- /dev/null +++ b/ik_qp/src/rm75_ik/stage2_demo.py @@ -0,0 +1,232 @@ +from __future__ import annotations + +import argparse +import os +import sys +from pathlib import Path +from time import perf_counter, sleep +from typing import Optional, Sequence + + +def build_parser() -> argparse.ArgumentParser: + parser = argparse.ArgumentParser( + description="Visualize first-stage IK in the normalized dual RM75 scene" + ) + parser.add_argument("--arm", choices=("left", "right"), default="left") + parser.add_argument( + "--trajectory", + choices=("joint", "line", "arc", "orientation", "combined"), + default="combined", + ) + parser.add_argument("--points", type=int, default=180) + parser.add_argument("--dt", type=float, default=1.0 / 90.0) + parser.add_argument( + "--target-position", + nargs=3, + type=float, + metavar=("X", "Y", "Z"), + help="target position in the controlled-arm base frame, in meters", + ) + parser.add_argument( + "--target-rpy", + nargs=3, + type=float, + metavar=("ROLL", "PITCH", "YAW"), + help="target RPY in radians; defaults to the start orientation", + ) + parser.add_argument( + "--duration", + type=float, + default=8.0, + help="target-point motion duration in seconds", + ) + parser.add_argument("--wait-before", type=float, default=2.0) + parser.add_argument("--hold-after", type=float, default=3.0) + parser.add_argument( + "--manual-drag", + action="store_true", + help="enable zero-gravity mouse perturbation of the controlled arm", + ) + parser.add_argument( + "--drag-damping", + type=float, + default=1.5, + help="joint damping used by manual-drag mode", + ) + parser.add_argument( + "--headless", + action="store_true", + help="render the final frame without opening the interactive viewer", + ) + parser.add_argument( + "--output", + type=Path, + default=Path("stage2_demo.png"), + help="headless output image", + ) + parser.add_argument( + "--close-after-play", + action="store_true", + help="close the interactive viewer after one playback (smoke testing)", + ) + return parser + + +def main(argv: Optional[Sequence[str]] = None) -> int: + args = build_parser().parse_args(argv) + if args.manual_drag and args.headless: + raise SystemExit("--manual-drag requires the interactive viewer") + if args.target_rpy is not None and args.target_position is None: + raise SystemExit("--target-rpy requires --target-position") + for name in ("dt", "duration", "wait_before", "hold_after"): + if getattr(args, name) < 0.0 or (name in {"dt", "duration"} and getattr(args, name) == 0.0): + raise SystemExit(f"--{name.replace('_', '-')} must be positive") + if args.headless: + os.environ.setdefault("MUJOCO_GL", "egl") + else: + os.environ.setdefault("MUJOCO_GL", "glfw") + + import mujoco.viewer + import numpy as np + import pinocchio as pin + from PIL import Image + + from .dual_arm import DualArmAssembly + from .mujoco_backend import CONTROLLED_HOME_Q_RAD, DualArmMuJoCo + from .mujoco_trajectories import ( + cartesian_demo_targets, + joint_demo_trajectory, + se3_target_trajectory, + solve_pose_trajectory, + ) + from .kinematics import RM75Kinematics, pose_errors + from .solver import RM75IkSolver + from .types import teleop_joint_limits + + scene = DualArmMuJoCo(controlled_arm=args.arm) + if args.manual_drag: + scene.configure_manual_drag(args.drag_damping) + print("Manual drag mode") + print(" 1. Double-click a link to select it.") + print(" 2. Hold Ctrl and drag with the right mouse button.") + print(" 3. Close the viewer or press Ctrl+C to finish.") + viewer = mujoco.viewer.launch_passive(scene.model, scene.data) + try: + while viewer.is_running(): + step_started = perf_counter() + scene.step_manual_drag() + viewer.sync() + remaining = scene.model.opt.timestep - (perf_counter() - step_started) + if remaining > 0.0: + sleep(remaining) + except KeyboardInterrupt: + pass + finally: + viewer.close() + sleep(0.2) + print("Final controlled-arm joints (rad):") + print(scene.get_arm_configuration(args.arm).tolist()) + return 0 + + kinematics = RM75Kinematics(limits=teleop_joint_limits()) + solver = RM75IkSolver(kinematics) + targets = None + target_pose = None + if args.target_position is not None: + start_pose = kinematics.forward(CONTROLLED_HOME_Q_RAD) + rotation = ( + start_pose.rotation + if args.target_rpy is None + else pin.rpy.rpyToMatrix(*args.target_rpy) + ) + target_pose = pin.SE3(rotation, np.asarray(args.target_position, dtype=float)) + target_points = max(2, int(round(args.duration / args.dt)) + 1) + try: + targets = se3_target_trajectory(start_pose, target_pose, target_points) + trajectory = solve_pose_trajectory( + solver, targets, CONTROLLED_HOME_Q_RAD + ) + except (RuntimeError, TypeError, ValueError) as exc: + raise SystemExit(f"target trajectory rejected: {exc}") from exc + print("Target mode") + print(" position (m):", target_pose.translation.tolist()) + print(" rpy (rad):", pin.rpy.matrixToRpy(target_pose.rotation).tolist()) + print(f" duration: {args.duration:.3f} s, points: {target_points}") + elif args.trajectory == "joint": + trajectory = joint_demo_trajectory(CONTROLLED_HOME_Q_RAD, args.points) + else: + targets = cartesian_demo_targets( + args.trajectory, + kinematics.forward(CONTROLLED_HOME_Q_RAD), + args.points, + ) + trajectory = solve_pose_trajectory( + solver, targets, CONTROLLED_HOME_Q_RAD + ) + + assembly = DualArmAssembly.from_source_urdf() + mount = ( + assembly.mounts.left_base + if args.arm == "left" + else assembly.mounts.right_base + ) + if target_pose is not None: + scene.set_target_marker(mount * target_pose) + elif targets is not None: + scene.set_target_marker(mount * targets[-1]) + else: + scene.set_arm_configuration(args.arm, trajectory[-1]) + scene.set_target_marker(scene.get_flange_pose(args.arm)) + scene.set_arm_configuration(args.arm, trajectory[0]) + + if args.headless: + result = scene.play_trajectory(trajectory, dt=args.dt, realtime=False) + args.output.parent.mkdir(parents=True, exist_ok=True) + Image.fromarray(scene.render()).save(args.output) + print( + f"Played {result.samples} samples; max joint step " + f"{result.max_joint_step_rad:.6f} rad" + ) + if target_pose is not None: + actual_local = mount.actInv(result.final_flange_pose) + position_error, orientation_error = pose_errors(actual_local, target_pose) + print(f"Final position error: {position_error:.9f} m") + print(f"Final orientation error: {orientation_error:.9f} rad") + print(args.output) + return 0 + + viewer = mujoco.viewer.launch_passive(scene.model, scene.data) + try: + wait_until = perf_counter() + args.wait_before + while viewer.is_running() and perf_counter() < wait_until: + viewer.sync() + sleep(0.02) + scene.play_trajectory( + trajectory, + dt=args.dt, + realtime=True, + viewer=viewer, + ) + if target_pose is not None: + actual_local = mount.actInv(scene.get_flange_pose(args.arm)) + position_error, orientation_error = pose_errors(actual_local, target_pose) + print(f"Final position error: {position_error:.9f} m") + print(f"Final orientation error: {orientation_error:.9f} rad") + hold_until = perf_counter() + args.hold_after + while viewer.is_running() and perf_counter() < hold_until: + viewer.sync() + sleep(0.02) + if not args.close_after_play: + while viewer.is_running(): + sleep(0.05) + except KeyboardInterrupt: + pass + finally: + viewer.close() + # GLFW tears down asynchronously; allow its render thread to exit. + sleep(0.2) + return 0 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/ik_qp/src/rm75_ik/stage2_validation.py b/ik_qp/src/rm75_ik/stage2_validation.py new file mode 100644 index 0000000..9efeccc --- /dev/null +++ b/ik_qp/src/rm75_ik/stage2_validation.py @@ -0,0 +1,595 @@ +from __future__ import annotations + +import csv +import json +from dataclasses import dataclass +from datetime import datetime, timezone +from math import radians +from pathlib import Path +from typing import Any, Dict, List, Optional, Tuple + +import mujoco +import numpy as np +import pinocchio as pin +from PIL import Image + +from .dual_arm import DualArmAssembly +from .kinematics import RM75Kinematics, pose_errors +from .mujoco_backend import CONTROLLED_HOME_Q_RAD, DualArmMuJoCo +from .mujoco_trajectories import ( + DEMO_TRAJECTORIES, + cartesian_demo_targets, + joint_demo_trajectory, + solve_pose_trajectory, +) +from .realman_reference import RealManFkReference +from .solver import RM75IkSolver +from .types import IkOptions, physical_joint_limits, teleop_joint_limits + + +MUJOCO_PIN_POSITION_LIMIT_M = 1e-9 +MUJOCO_PIN_ORIENTATION_LIMIT_RAD = 1e-9 +ALGO_FK_POSITION_LIMIT_M = 1e-4 +ALGO_FK_ORIENTATION_LIMIT_RAD = radians(0.01) +IK_POSITION_LIMIT_M = 1e-3 +IK_ORIENTATION_LIMIT_RAD = radians(0.1) +NEAR_IK_RATE_LIMIT = 0.995 +CONTINUOUS_IK_RATE_LIMIT = 0.999 +MAX_JOINT_STEP_RAD = radians(2.0) +INACTIVE_ARM_DELTA_LIMIT_RAD = 1e-12 + + +@dataclass(frozen=True) +class Stage2Settings: + seed: int = 20260630 + fk_samples: int = 10_000 + ik_samples: int = 1_000 + trajectories: int = 20 + trajectory_points: int = 500 + render_width: int = 1280 + render_height: int = 720 + + @classmethod + def quick(cls, seed: int = 20260630) -> "Stage2Settings": + return cls( + seed=seed, + fk_samples=100, + ik_samples=30, + trajectories=2, + trajectory_points=25, + render_width=640, + render_height=360, + ) + + +def _sample_configurations( + rng: np.random.Generator, + lower: np.ndarray, + upper: np.ndarray, + count: int, + margin: Optional[np.ndarray] = None, +) -> np.ndarray: + selected_margin = np.zeros(7) if margin is None else np.asarray(margin) + return rng.uniform( + lower + selected_margin, + upper - selected_margin, + size=(count, 7), + ) + + +def _percentile(values: List[float], percentile: float) -> float: + return float(np.percentile(values, percentile)) if values else float("nan") + + +class Stage2Validator: + def __init__( + self, + reference: RealManFkReference, + controlled_arm: str = "left", + settings: Stage2Settings = Stage2Settings(), + ) -> None: + self.reference = reference + self.controlled_arm = controlled_arm + self.settings = settings + self.rng = np.random.default_rng(settings.seed) + self.scene = DualArmMuJoCo(controlled_arm=controlled_arm) + self.assembly = DualArmAssembly.from_source_urdf() + self.teleop_kinematics = RM75Kinematics(limits=teleop_joint_limits()) + self.solver = RM75IkSolver(self.teleop_kinematics) + self.mount = ( + self.assembly.mounts.left_base + if controlled_arm == "left" + else self.assembly.mounts.right_base + ) + self._inactive_initial = self.scene.get_arm_configuration(self.scene.inactive_arm) + self._max_inactive_delta = 0.0 + self.checks: Dict[str, Dict[str, Any]] = {} + self.failures: List[Dict[str, Any]] = [] + self.images: Dict[str, Tuple[np.ndarray, np.ndarray]] = {} + + def _check_inactive_arm(self) -> None: + delta = float( + np.max( + np.abs( + self.scene.get_arm_configuration(self.scene.inactive_arm) + - self._inactive_initial + ) + ) + ) + self._max_inactive_delta = max(self._max_inactive_delta, delta) + + def _record_failure( + self, + category: str, + index: int, + reason: str, + q: Optional[np.ndarray] = None, + position_error_m: float = float("nan"), + orientation_error_rad: float = float("nan"), + ) -> None: + if len(self.failures) >= 1000: + return + self.failures.append( + { + "category": category, + "sample": index, + "reason": reason, + "position_error_m": position_error_m, + "orientation_error_rad": orientation_error_rad, + "q_rad": json.dumps(q.tolist()) if q is not None else "", + } + ) + + def _add_check(self, name: str, passed: bool, metrics: Dict[str, Any]) -> None: + self.checks[name] = {"passed": bool(passed), "required": True, **metrics} + + def _local_mujoco_pose(self) -> pin.SE3: + return self.mount.actInv(self.scene.get_flange_pose(self.controlled_arm)) + + def run(self) -> Dict[str, Any]: + self._model_structure_check() + self._fk_check() + self._single_point_ik_check() + self._continuous_ik_check() + self._trajectory_scenario_check() + self._visual_check() + self._add_check( + "inactive_arm_fixed", + self._max_inactive_delta < INACTIVE_ARM_DELTA_LIMIT_RAD, + { + "arm": self.scene.inactive_arm, + "max_qpos_delta_rad": self._max_inactive_delta, + "limit_rad": INACTIVE_ARM_DELTA_LIMIT_RAD, + }, + ) + passed = all(check["passed"] for check in self.checks.values()) + return { + "schema_version": 1, + "generated_at": datetime.now(timezone.utc).isoformat(), + "seed": self.settings.seed, + "controlled_arm": self.controlled_arm, + "inactive_arm": self.scene.inactive_arm, + "realman_api_version": self.reference.api_version, + "mujoco_version": mujoco.__version__, + "passed": passed, + "checks": self.checks, + "failure_count": len(self.failures), + } + + def _model_structure_check(self) -> None: + model = self.scene.model + joint_names = [model.joint(index).name for index in range(model.njnt)] + expected = [ + f"{arm}_joint_{joint_index}" + for arm in ("left", "right") + for joint_index in range(1, 8) + ] + obj_assets = [key for key in self.scene.assets if key.endswith(".obj")] + stl_assets = [key for key in self.scene.assets if key.endswith(".STL")] + passed = ( + model.nq == model.nv == model.njnt == 14 + and model.nu == 0 + and model.nsite == 2 + and model.nmesh == 27 + and joint_names == expected + and len(obj_assets) == 19 + and len(stl_assets) == 8 + ) + self._add_check( + "model_structure", + passed, + { + "nq": model.nq, + "nv": model.nv, + "njnt": model.njnt, + "nu": model.nu, + "nmesh": model.nmesh, + "obj_assets": len(obj_assets), + "stl_assets": len(stl_assets), + }, + ) + + def _fk_check(self) -> None: + limits = physical_joint_limits() + samples = _sample_configurations( + self.rng, limits.lower, limits.upper, self.settings.fk_samples + ) + pin_position_errors: List[float] = [] + pin_orientation_errors: List[float] = [] + algo_position_errors: List[float] = [] + algo_orientation_errors: List[float] = [] + for index, q in enumerate(samples): + self.scene.set_arm_configuration(self.controlled_arm, q) + self._check_inactive_arm() + mujoco_world = self.scene.get_flange_pose(self.controlled_arm) + pin_world = self.assembly.forward(self.controlled_arm, q) + pin_position, pin_orientation = pose_errors(mujoco_world, pin_world) + local_mujoco = self.mount.actInv(mujoco_world) + algo_position, algo_orientation = pose_errors( + local_mujoco, self.reference.forward(q) + ) + pin_position_errors.append(pin_position) + pin_orientation_errors.append(pin_orientation) + algo_position_errors.append(algo_position) + algo_orientation_errors.append(algo_orientation) + if ( + pin_position >= MUJOCO_PIN_POSITION_LIMIT_M + or pin_orientation >= MUJOCO_PIN_ORIENTATION_LIMIT_RAD + or algo_position >= ALGO_FK_POSITION_LIMIT_M + or algo_orientation >= ALGO_FK_ORIENTATION_LIMIT_RAD + ): + self._record_failure( + "fk", + index, + "MuJoCo FK residual exceeded an acceptance limit", + q, + algo_position, + algo_orientation, + ) + max_pin_position = max(pin_position_errors, default=float("inf")) + max_pin_orientation = max(pin_orientation_errors, default=float("inf")) + max_algo_position = max(algo_position_errors, default=float("inf")) + max_algo_orientation = max(algo_orientation_errors, default=float("inf")) + self._add_check( + "fk", + max_pin_position < MUJOCO_PIN_POSITION_LIMIT_M + and max_pin_orientation < MUJOCO_PIN_ORIENTATION_LIMIT_RAD + and max_algo_position < ALGO_FK_POSITION_LIMIT_M + and max_algo_orientation < ALGO_FK_ORIENTATION_LIMIT_RAD, + { + "samples": len(samples), + "max_mujoco_pin_position_error_m": max_pin_position, + "max_mujoco_pin_orientation_error_rad": max_pin_orientation, + "max_mujoco_algo_position_error_m": max_algo_position, + "max_mujoco_algo_orientation_error_rad": max_algo_orientation, + }, + ) + + @staticmethod + def _ik_options(max_iterations: int) -> IkOptions: + return IkOptions( + position_tolerance_m=0.9 * IK_POSITION_LIMIT_M, + orientation_tolerance_rad=0.9 * IK_ORIENTATION_LIMIT_RAD, + max_iterations=max_iterations, + ) + + def _single_point_ik_check(self) -> None: + limits = teleop_joint_limits() + margin = np.deg2rad([5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 10.0]) + targets_q = _sample_configurations( + self.rng, + limits.lower, + limits.upper, + self.settings.ik_samples, + margin, + ) + successes = 0 + solve_times: List[float] = [] + max_position = 0.0 + max_orientation = 0.0 + for index, target_q in enumerate(targets_q): + target = self.reference.forward(target_q) + seed = np.clip( + target_q + self.rng.uniform(-radians(10), radians(10), 7), + limits.lower, + limits.upper, + ) + result = self.solver.solve(target, seed, self._ik_options(200)) + solve_times.append(result.solve_time_sec) + if result.success and result.q is not None: + self.scene.set_arm_configuration(self.controlled_arm, result.q) + self._check_inactive_arm() + position_error, orientation_error = pose_errors( + self._local_mujoco_pose(), target + ) + max_position = max(max_position, position_error) + max_orientation = max(max_orientation, orientation_error) + if ( + position_error <= IK_POSITION_LIMIT_M + and orientation_error <= IK_ORIENTATION_LIMIT_RAD + ): + successes += 1 + continue + else: + position_error = result.position_error_m + orientation_error = result.orientation_error_rad + self._record_failure( + "single_point_ik", + index, + f"status={result.status.value}; {result.message}", + seed, + position_error, + orientation_error, + ) + rate = successes / max(len(targets_q), 1) + self._add_check( + "single_point_ik", + rate >= NEAR_IK_RATE_LIMIT, + { + "samples": len(targets_q), + "successes": successes, + "success_rate": rate, + "max_position_error_m": max_position, + "max_orientation_error_rad": max_orientation, + "p99_solve_time_sec": _percentile(solve_times, 99), + "max_solve_time_sec": max(solve_times, default=float("nan")), + }, + ) + + def _continuous_ik_check(self) -> None: + limits = teleop_joint_limits() + successes = 0 + total = 0 + max_joint_step = 0.0 + max_position = 0.0 + max_orientation = 0.0 + for trajectory_index in range(self.settings.trajectories): + span = limits.upper - limits.lower + center = self.rng.uniform( + limits.lower + 0.3 * span, + limits.upper - 0.3 * span, + ) + amplitude = self.rng.uniform(0.015, 0.04, 7) * span + frequency = self.rng.uniform(0.03, 0.08, 7) + phase = self.rng.uniform(-np.pi, np.pi, 7) + times = np.arange(self.settings.trajectory_points) / 90.0 + target_path = center + amplitude * np.sin( + 2.0 * np.pi * times[:, None] * frequency + phase + ) + seed = target_path[0].copy() + previous = seed.copy() + for point_index, target_q in enumerate(target_path): + total += 1 + target = self.reference.forward(target_q) + result = self.solver.solve(target, seed, self._ik_options(100)) + if result.success and result.q is not None: + self.scene.set_arm_configuration(self.controlled_arm, result.q) + self._check_inactive_arm() + position_error, orientation_error = pose_errors( + self._local_mujoco_pose(), target + ) + joint_step = float(np.max(np.abs(result.q - previous))) + max_position = max(max_position, position_error) + max_orientation = max(max_orientation, orientation_error) + max_joint_step = max(max_joint_step, joint_step) + if ( + position_error <= IK_POSITION_LIMIT_M + and orientation_error <= IK_ORIENTATION_LIMIT_RAD + ): + successes += 1 + seed = result.q + previous = result.q + continue + else: + position_error = result.position_error_m + orientation_error = result.orientation_error_rad + self._record_failure( + "continuous_ik", + trajectory_index * self.settings.trajectory_points + point_index, + f"status={result.status.value}; {result.message}", + seed, + position_error, + orientation_error, + ) + rate = successes / max(total, 1) + self._add_check( + "continuous_ik", + rate >= CONTINUOUS_IK_RATE_LIMIT + and max_joint_step < MAX_JOINT_STEP_RAD, + { + "trajectories": self.settings.trajectories, + "points": total, + "successes": successes, + "success_rate": rate, + "max_position_error_m": max_position, + "max_orientation_error_rad": max_orientation, + "max_joint_step_rad": max_joint_step, + "joint_step_limit_rad": MAX_JOINT_STEP_RAD, + }, + ) + + def _trajectory_scenario_check(self) -> None: + scenario_results: Dict[str, bool] = {} + start = CONTROLLED_HOME_Q_RAD.copy() + for kind in DEMO_TRAJECTORIES: + try: + if kind == "joint": + q_trajectory = joint_demo_trajectory(start, 120) + else: + targets = cartesian_demo_targets( + kind, self.teleop_kinematics.forward(start), 120 + ) + q_trajectory = solve_pose_trajectory(self.solver, targets, start) + self.scene.play_trajectory(q_trajectory) + self._check_inactive_arm() + scenario_results[kind] = True + except (RuntimeError, ValueError) as exc: + scenario_results[kind] = False + self._record_failure("trajectory_scenario", 0, f"{kind}: {exc}") + + limits = teleop_joint_limits() + scenario_q = { + "limit_near": 0.8 * limits.upper + 0.2 * CONTROLLED_HOME_Q_RAD, + "singularity_near": np.deg2rad([0, 0, 0, 90, 0, 0, 0]), + } + blend = 0.5 - 0.5 * np.cos(np.linspace(0.0, np.pi, 120)) + for name, endpoint in scenario_q.items(): + path = start[None, :] + blend[:, None] * (endpoint - start)[None, :] + try: + targets = [self.reference.forward(q) for q in path] + solutions = solve_pose_trajectory(self.solver, targets, start) + self.scene.play_trajectory(solutions) + self._check_inactive_arm() + scenario_results[name] = True + except (RuntimeError, ValueError) as exc: + scenario_results[name] = False + self._record_failure("trajectory_scenario", 0, f"{name}: {exc}") + self._add_check( + "trajectory_scenarios", + all(scenario_results.values()), + {"scenarios": scenario_results}, + ) + + def _visible_geom_names(self, segmentation: np.ndarray) -> set[str]: + pairs = np.unique(segmentation.reshape(-1, 2), axis=0) + names = set() + for object_id, object_type in pairs: + if object_type != mujoco.mjtObj.mjOBJ_GEOM or object_id < 0: + continue + name = mujoco.mj_id2name( + self.scene.model, mujoco.mjtObj.mjOBJ_GEOM, int(object_id) + ) + if name is not None: + names.add(name) + return names + + @staticmethod + def _segmentation_preview(segmentation: np.ndarray) -> np.ndarray: + object_ids = segmentation[:, :, 0] + preview = np.zeros((*object_ids.shape, 3), dtype=np.uint8) + foreground = object_ids >= 0 + ids = object_ids[foreground].astype(np.uint32) + preview[foreground, 0] = (37 * ids + 53) % 255 + preview[foreground, 1] = (97 * ids + 101) % 255 + preview[foreground, 2] = (17 * ids + 211) % 255 + return preview + + def _visual_check(self) -> None: + start = CONTROLLED_HOME_Q_RAD.copy() + targets = cartesian_demo_targets( + "combined", self.teleop_kinematics.forward(start), 121 + ) + q_trajectory = solve_pose_trajectory(self.solver, targets, start) + all_frames_pass = True + frame_metrics: Dict[str, Dict[str, Any]] = {} + for label, index in (("start", 0), ("middle", 60), ("end", 120)): + self.scene.set_arm_configuration(self.controlled_arm, q_trajectory[index]) + self.scene.set_target_marker(self.mount * targets[index]) + self._check_inactive_arm() + rgb = self.scene.render( + self.settings.render_width, self.settings.render_height + ) + segmentation = self.scene.render( + self.settings.render_width, + self.settings.render_height, + segmentation=True, + ) + visible_names = self._visible_geom_names(segmentation) + left_visible = any(name.startswith("left_") for name in visible_names) + right_visible = any(name.startswith("right_") for name in visible_names) + arm_ids = { + mujoco.mj_name2id( + self.scene.model, mujoco.mjtObj.mjOBJ_GEOM, name + ) + for name in visible_names + if name.startswith(("left_", "right_")) + } + mask = np.isin(segmentation[:, :, 0], list(arm_ids)) + rows, columns = np.where(mask) + not_touching_border = bool( + len(rows) + and rows.min() > 1 + and columns.min() > 1 + and rows.max() < rgb.shape[0] - 2 + and columns.max() < rgb.shape[1] - 2 + ) + frame_pass = ( + float(rgb.std()) > 5.0 + and left_visible + and right_visible + and not_touching_border + ) + all_frames_pass &= frame_pass + frame_metrics[label] = { + "rgb_std": float(rgb.std()), + "left_visible": left_visible, + "right_visible": right_visible, + "not_touching_border": not_touching_border, + "visible_geom_count": len(visible_names), + } + self.images[label] = (rgb, self._segmentation_preview(segmentation)) + self._add_check("visual_rendering", all_frames_pass, {"frames": frame_metrics}) + + +def write_stage2_report( + output_dir: Path | str, + summary: Dict[str, Any], + failures: List[Dict[str, Any]], + images: Dict[str, Tuple[np.ndarray, np.ndarray]], +) -> Tuple[Path, Path, Path, List[Path]]: + directory = Path(output_dir) + directory.mkdir(parents=True, exist_ok=True) + json_path = directory / "stage2_summary.json" + csv_path = directory / "stage2_failures.csv" + markdown_path = directory / "stage2_report.md" + + with json_path.open("w", encoding="utf-8") as stream: + json.dump(summary, stream, ensure_ascii=True, indent=2, sort_keys=True) + stream.write("\n") + + fields = [ + "category", + "sample", + "reason", + "position_error_m", + "orientation_error_rad", + "q_rad", + ] + with csv_path.open("w", encoding="utf-8", newline="") as stream: + writer = csv.DictWriter(stream, fieldnames=fields) + writer.writeheader() + writer.writerows(failures) + + image_paths: List[Path] = [] + for label, (rgb, segmentation) in images.items(): + for suffix, image in (("rgb", rgb), ("segmentation", segmentation)): + path = directory / f"stage2_{label}_{suffix}.png" + Image.fromarray(image).save(path) + image_paths.append(path) + + lines = [ + "# RM75-B Stage 2 MuJoCo Validation", + "", + f"- Overall: **{'PASS' if summary['passed'] else 'FAIL'}**", + f"- Controlled arm: `{summary['controlled_arm']}`", + f"- Seed: `{summary['seed']}`", + f"- MuJoCo: `{summary['mujoco_version']}`", + f"- RealMan API: `{summary['realman_api_version']}`", + f"- Failures recorded: `{summary['failure_count']}`", + "", + "| Check | Result | Metrics |", + "|---|---:|---|", + ] + for name, check in summary["checks"].items(): + metrics = { + key: value + for key, value in check.items() + if key not in {"passed", "required"} + } + lines.append( + f"| `{name}` | {'PASS' if check['passed'] else 'FAIL'} | " + f"`{json.dumps(metrics, ensure_ascii=True, sort_keys=True)}` |" + ) + markdown_path.write_text("\n".join(lines) + "\n", encoding="utf-8") + return json_path, csv_path, markdown_path, image_paths + diff --git a/ik_qp/src/rm75_ik/stage3_cli.py b/ik_qp/src/rm75_ik/stage3_cli.py new file mode 100644 index 0000000..66b33e3 --- /dev/null +++ b/ik_qp/src/rm75_ik/stage3_cli.py @@ -0,0 +1,78 @@ +from __future__ import annotations + +import argparse +import os +import sys +from pathlib import Path +from typing import Optional, Sequence + + +os.environ.setdefault("MUJOCO_GL", "egl") + + +def _source_root() -> Path: + return Path(__file__).resolve().parents[3] + + +def build_parser() -> argparse.ArgumentParser: + root = _source_root() + parser = argparse.ArgumentParser( + description="Validate right-arm and dual-grip QP control in MuJoCo" + ) + parser.add_argument("--sdk-root", type=Path) + parser.add_argument( + "--teleop-config", + type=Path, + default=root / "xr_rm_bringup/config/dual_arm_rm75.yaml", + ) + parser.add_argument( + "--peripheral-config", + type=Path, + default=root / "xr_rm_bringup/config/peripherals_rm75.yaml", + ) + parser.add_argument( + "--output-dir", + type=Path, + default=root / "ik_qp/artifacts/stage3", + ) + parser.add_argument("--seed", type=int, default=20260630) + parser.add_argument("--quick", action="store_true") + parser.add_argument("--report-only", action="store_true") + return parser + + +def main(argv: Optional[Sequence[str]] = None) -> int: + args = build_parser().parse_args(argv) + from .realman_reference import RealManFkReference + from .stage3_validation import ( + Stage3Settings, + Stage3Validator, + write_stage3_report, + ) + + settings = ( + Stage3Settings.quick(args.seed) + if args.quick + else Stage3Settings(seed=args.seed) + ) + validator = Stage3Validator( + RealManFkReference(args.sdk_root), + args.teleop_config, + args.peripheral_config, + settings, + ) + summary = validator.run() + paths = write_stage3_report( + args.output_dir, summary, validator.failures, validator.images + ) + print(f"RM75-B stage-3 validation: {'PASS' if summary['passed'] else 'FAIL'}") + for name, check in summary["checks"].items(): + print(f" [{'PASS' if check['passed'] else 'FAIL'}] {name}") + print("Reports:") + for path in (*paths[:3], *paths[3]): + print(f" {path}") + return 0 if args.report_only or summary["passed"] else 1 + + +if __name__ == "__main__": + sys.exit(main()) diff --git a/ik_qp/src/rm75_ik/stage3_validation.py b/ik_qp/src/rm75_ik/stage3_validation.py new file mode 100644 index 0000000..73673b5 --- /dev/null +++ b/ik_qp/src/rm75_ik/stage3_validation.py @@ -0,0 +1,311 @@ +from __future__ import annotations + +import csv +import json +from dataclasses import dataclass +from datetime import datetime, timezone +from math import degrees, radians +from pathlib import Path +from typing import Any, Dict, List, Tuple + +import mujoco +import numpy as np +from PIL import Image + +from .mujoco_robot import MujocoRobot +from .realman_reference import RealManFkReference +from .stage2_validation import Stage2Settings, Stage2Validator +from .teleop_config import load_dual_arm_profiles +from .teleop_control import ( + ControllerSample, + DualArmQpTeleopController, + SafetyState, +) + + +@dataclass(frozen=True) +class Stage3Settings: + seed: int = 20260630 + fk_samples: int = 2_000 + ik_samples: int = 200 + trajectories: int = 5 + trajectory_points: int = 200 + render_width: int = 1280 + render_height: int = 720 + + @classmethod + def quick(cls, seed: int = 20260630) -> "Stage3Settings": + return cls( + seed=seed, + fk_samples=100, + ik_samples=30, + trajectories=2, + trajectory_points=25, + render_width=640, + render_height=360, + ) + + def stage2_settings(self) -> Stage2Settings: + return Stage2Settings( + seed=self.seed, + fk_samples=self.fk_samples, + ik_samples=self.ik_samples, + trajectories=self.trajectories, + trajectory_points=self.trajectory_points, + render_width=self.render_width, + render_height=self.render_height, + ) + + +class Stage3Validator: + def __init__( + self, + reference: RealManFkReference, + teleop_config_path: Path | str, + peripheral_config_path: Path | str, + settings: Stage3Settings = Stage3Settings(), + ) -> None: + self.reference = reference + self.settings = settings + self.profiles = load_dual_arm_profiles( + teleop_config_path, peripheral_config_path + ) + self.checks: Dict[str, Dict[str, Any]] = {} + self.failures: List[Dict[str, Any]] = [] + self.images: Dict[str, np.ndarray] = {} + + def run(self) -> Dict[str, Any]: + right_validator = Stage2Validator( + self.reference, + controlled_arm="right", + settings=self.settings.stage2_settings(), + ) + right_summary = right_validator.run() + self.failures.extend(right_validator.failures) + for label, (rgb, segmentation) in right_validator.images.items(): + self.images[f"right_{label}_rgb"] = rgb + self.images[f"right_{label}_segmentation"] = segmentation + self.checks["right_arm_validation"] = { + "passed": right_summary["passed"], + "required": True, + "checks": right_summary["checks"], + } + + robot = MujocoRobot(self.profiles) + try: + self._initial_tcp_check(robot) + self._dual_grip_control_check(robot) + image = robot.render( + self.settings.render_width, self.settings.render_height + ) + self.images["dual_control_final_rgb"] = image + self.checks["dual_control_render"] = { + "passed": float(image.std()) > 5.0, + "required": True, + "rgb_std": float(image.std()), + } + finally: + robot.close() + + passed = all(check["passed"] for check in self.checks.values()) + return { + "schema_version": 1, + "generated_at": datetime.now(timezone.utc).isoformat(), + "seed": self.settings.seed, + "mujoco_version": mujoco.__version__, + "realman_api_version": self.reference.api_version, + "passed": passed, + "checks": self.checks, + "failure_count": len(self.failures), + } + + def _initial_tcp_check(self, robot: MujocoRobot) -> None: + metrics: Dict[str, Dict[str, Any]] = {} + passed = True + for arm in ("left", "right"): + diagnostic = robot.initial_pose_diagnostics[arm] + arm_passed = ( + diagnostic.solved_position_error_m <= 1e-3 + and diagnostic.solved_orientation_error_rad <= radians(0.1) + ) + passed &= arm_passed + metrics[arm] = { + "active_tool": self.profiles[arm].active_tool_name, + "solved_q_deg": np.rad2deg(diagnostic.solved_q_rad).tolist(), + "solved_position_error_m": diagnostic.solved_position_error_m, + "solved_orientation_error_deg": degrees( + diagnostic.solved_orientation_error_rad + ), + "configured_joint_position_error_m": ( + diagnostic.configured_joint_position_error_m + ), + "configured_joint_orientation_error_deg": degrees( + diagnostic.configured_joint_orientation_error_rad + ), + } + if not arm_passed: + self._record_failure( + "initial_tcp", + 0 if arm == "left" else 1, + f"{arm} initial TCP solve exceeded tolerance", + diagnostic.solved_q_rad, + diagnostic.solved_position_error_m, + diagnostic.solved_orientation_error_rad, + ) + self.checks["initial_tcp_pose"] = { + "passed": passed, + "required": True, + "arms": metrics, + "note": "configured initial_joint_pose mismatch is diagnostic only", + } + + def _dual_grip_control_check(self, robot: MujocoRobot) -> None: + controller = DualArmQpTeleopController(robot, self.profiles) + initial = robot.read_joint_positions().positions_rad + identity = np.array([0.0, 0.0, 0.0, 1.0]) + + def sample(arm: str, grip: bool, position) -> ControllerSample: + return ControllerSample( + hand=arm, + grip=grip, + trigger=0.0, + position_m=np.asarray(position, dtype=float), + quaternion_xyzw=identity, + ) + + controller.update_sample(sample("left", False, [0, 0, 0]), 0.0) + controller.update_sample(sample("right", False, [0, 0, 0]), 0.0) + idle = controller.step(0.0) + controller.update_sample(sample("left", True, [0, 0, 0]), 0.01) + controller.update_sample(sample("right", True, [0, 0, 0]), 0.01) + engaged = controller.step(0.01) + after_engage = robot.read_joint_positions().positions_rad + no_engage_jump = all( + np.max(np.abs(after_engage[arm] - initial[arm])) < 1e-10 + for arm in ("left", "right") + ) + + last_result = engaged + for index in range(1, 11): + now = 0.01 + index / 90.0 + hand_delta = 0.001 * index + controller.update_sample( + sample("left", True, [0, hand_delta, 0]), now + ) + controller.update_sample( + sample("right", True, [0, hand_delta, 0]), now + ) + last_result = controller.step(now) + if last_result.state is SafetyState.FAULT: + break + moved = robot.read_joint_positions().positions_rad + joint_delta = { + arm: float(np.max(np.abs(moved[arm] - initial[arm]))) + for arm in ("left", "right") + } + both_moved = all(value > 1e-5 for value in joint_delta.values()) + + release_time = 0.15 + controller.update_sample(sample("left", False, [0, 0.01, 0]), release_time) + controller.update_sample(sample("right", False, [0, 0.01, 0]), release_time) + released = controller.step(release_time) + passed = ( + idle.state is SafetyState.IDLE + and engaged.state is SafetyState.ACTIVE + and no_engage_jump + and last_result.state is SafetyState.ACTIVE + and both_moved + and released.state is SafetyState.IDLE + ) + if not passed: + self._record_failure( + "dual_grip_control", + 0, + f"idle={idle.state.value}, engaged={engaged.state.value}, " + f"last={last_result.state.value}, released={released.state.value}", + ) + self.checks["dual_grip_control"] = { + "passed": passed, + "required": True, + "no_engage_jump": no_engage_jump, + "max_joint_delta_rad": joint_delta, + "final_state": released.state.value, + } + + def _record_failure( + self, + category: str, + index: int, + reason: str, + q: np.ndarray | None = None, + position_error_m: float = float("nan"), + orientation_error_rad: float = float("nan"), + ) -> None: + self.failures.append( + { + "category": category, + "sample": index, + "reason": reason, + "position_error_m": position_error_m, + "orientation_error_rad": orientation_error_rad, + "q_rad": json.dumps(q.tolist()) if q is not None else "", + } + ) + + +def write_stage3_report( + output_dir: Path | str, + summary: Dict[str, Any], + failures: List[Dict[str, Any]], + images: Dict[str, np.ndarray], +) -> Tuple[Path, Path, Path, List[Path]]: + directory = Path(output_dir) + directory.mkdir(parents=True, exist_ok=True) + json_path = directory / "stage3_summary.json" + csv_path = directory / "stage3_failures.csv" + markdown_path = directory / "stage3_report.md" + json_path.write_text( + json.dumps(summary, ensure_ascii=True, indent=2, sort_keys=True) + "\n", + encoding="utf-8", + ) + fields = [ + "category", + "sample", + "reason", + "position_error_m", + "orientation_error_rad", + "q_rad", + ] + with csv_path.open("w", encoding="utf-8", newline="") as stream: + writer = csv.DictWriter(stream, fieldnames=fields) + writer.writeheader() + writer.writerows(failures) + image_paths = [] + for label, image in images.items(): + path = directory / f"stage3_{label}.png" + Image.fromarray(image).save(path) + image_paths.append(path) + lines = [ + "# RM75-B Stage 3 Dual-Arm QP Validation", + "", + f"- Overall: **{'PASS' if summary['passed'] else 'FAIL'}**", + f"- Seed: `{summary['seed']}`", + f"- MuJoCo: `{summary['mujoco_version']}`", + f"- RealMan API: `{summary['realman_api_version']}`", + f"- Failures recorded: `{summary['failure_count']}`", + "", + "| Check | Result | Metrics |", + "|---|---:|---|", + ] + for name, check in summary["checks"].items(): + metrics = { + key: value + for key, value in check.items() + if key not in {"passed", "required"} + } + lines.append( + f"| `{name}` | {'PASS' if check['passed'] else 'FAIL'} | " + f"`{json.dumps(metrics, ensure_ascii=True, sort_keys=True)}` |" + ) + markdown_path.write_text("\n".join(lines) + "\n", encoding="utf-8") + return json_path, csv_path, markdown_path, image_paths diff --git a/ik_qp/src/rm75_ik/teleop_config.py b/ik_qp/src/rm75_ik/teleop_config.py new file mode 100644 index 0000000..9e6ecfb --- /dev/null +++ b/ik_qp/src/rm75_ik/teleop_config.py @@ -0,0 +1,197 @@ +from __future__ import annotations + +from dataclasses import dataclass +from pathlib import Path +from typing import Dict, Literal, Mapping + +import numpy as np +import pinocchio as pin +import yaml + +from .kinematics import validate_se3 + + +ArmName = Literal["left", "right"] + + +def _readonly_vector(values, shape: tuple[int, ...], name: str) -> np.ndarray: + array = np.asarray(values, dtype=float).copy() + if array.shape != shape or not np.all(np.isfinite(array)): + raise ValueError(f"{name} must be finite with shape {shape}") + array.setflags(write=False) + return array + + +@dataclass(frozen=True) +class ArmTeleopProfile: + arm: ArmName + initial_tcp: pin.SE3 + configured_initial_q_rad: np.ndarray + tool_from_flange: pin.SE3 + active_tool_name: str + xr_to_robot: np.ndarray + scale: float + command_timeout_sec: float + deadband_m: float + target_filter_alpha: float + target_filter_alpha_fast: float + target_filter_fast_threshold_m: float + max_linear_speed_m_s: float + enable_position_axes: tuple[bool, bool, bool] + enable_orientation_control: bool + enable_orientation_axes: tuple[bool, bool, bool] + orientation_deadband_rad: float + orientation_filter_alpha: float + max_orientation_speed_rad_s: float + workspace_min: np.ndarray + workspace_max: np.ndarray + cylinder_radius_limit: np.ndarray + low_z_threshold: float + low_z_min_radius: float + joint_max_speed_rad_s: np.ndarray + + def __post_init__(self) -> None: + if self.arm not in ("left", "right"): + raise ValueError("arm must be 'left' or 'right'") + validate_se3(self.initial_tcp, "initial_tcp") + validate_se3(self.tool_from_flange, "tool_from_flange") + object.__setattr__( + self, + "configured_initial_q_rad", + _readonly_vector(self.configured_initial_q_rad, (7,), "configured_initial_q_rad"), + ) + matrix = _readonly_vector(self.xr_to_robot, (3, 3), "xr_to_robot") + if not np.allclose(matrix.T @ matrix, np.eye(3), atol=1e-9): + raise ValueError("xr_to_robot must be orthonormal") + if not np.isclose(np.linalg.det(matrix), 1.0, atol=1e-9): + raise ValueError("xr_to_robot must be a proper rotation") + object.__setattr__(self, "xr_to_robot", matrix) + workspace_min = _readonly_vector(self.workspace_min, (3,), "workspace_min") + workspace_max = _readonly_vector(self.workspace_max, (3,), "workspace_max") + if np.any(workspace_min >= workspace_max): + raise ValueError("workspace_min must be below workspace_max") + object.__setattr__(self, "workspace_min", workspace_min) + object.__setattr__(self, "workspace_max", workspace_max) + cylinder = _readonly_vector( + self.cylinder_radius_limit, (2,), "cylinder_radius_limit" + ) + if cylinder[0] < 0.0 or cylinder[1] <= cylinder[0]: + raise ValueError("cylinder radius limits are invalid") + object.__setattr__(self, "cylinder_radius_limit", cylinder) + speeds = _readonly_vector( + self.joint_max_speed_rad_s, (7,), "joint_max_speed_rad_s" + ) + if np.any(speeds <= 0.0): + raise ValueError("joint_max_speed_rad_s must be positive") + object.__setattr__(self, "joint_max_speed_rad_s", speeds) + for name in ( + "scale", + "command_timeout_sec", + "target_filter_fast_threshold_m", + "max_linear_speed_m_s", + "max_orientation_speed_rad_s", + ): + if not np.isfinite(getattr(self, name)) or getattr(self, name) <= 0.0: + raise ValueError(f"{name} must be finite and positive") + for name in ( + "deadband_m", + "orientation_deadband_rad", + "low_z_threshold", + "low_z_min_radius", + ): + if not np.isfinite(getattr(self, name)) or getattr(self, name) < 0.0: + raise ValueError(f"{name} must be finite and non-negative") + for name in ( + "target_filter_alpha", + "target_filter_alpha_fast", + "orientation_filter_alpha", + ): + if not 0.0 <= getattr(self, name) <= 1.0: + raise ValueError(f"{name} must be in [0, 1]") + + +def _pose_from_rpy(values, name: str) -> pin.SE3: + pose = _readonly_vector(values, (6,), name) + return pin.SE3(pin.rpy.rpyToMatrix(*pose[3:]), pose[:3]) + + +def _tool_pose(values, name: str) -> pin.SE3: + pose = _readonly_vector(values, (7,), name) + quaternion = pin.Quaternion(pose[6], pose[3], pose[4], pose[5]) + if quaternion.norm() <= 1e-12: + raise ValueError(f"{name} quaternion has zero norm") + quaternion.normalize() + return pin.SE3(quaternion.matrix(), pose[:3]) + + +def load_dual_arm_profiles( + teleop_config_path: Path | str, + peripheral_config_path: Path | str, +) -> Dict[ArmName, ArmTeleopProfile]: + teleop_path = Path(teleop_config_path) + peripheral_path = Path(peripheral_config_path) + with teleop_path.open("r", encoding="utf-8") as stream: + teleop_document = yaml.safe_load(stream) + with peripheral_path.open("r", encoding="utf-8") as stream: + peripheral_document = yaml.safe_load(stream) + if not isinstance(teleop_document, Mapping) or not isinstance( + peripheral_document, Mapping + ): + raise ValueError("teleop and peripheral YAML documents must be mappings") + + tools = peripheral_document.get("tools_in_ee") + arms = peripheral_document.get("arms") + if not isinstance(tools, Mapping) or not isinstance(arms, Mapping): + raise ValueError("peripheral configuration is missing tools_in_ee or arms") + tool_names = list(tools) + + profiles: Dict[ArmName, ArmTeleopProfile] = {} + for arm in ("left", "right"): + section_name = f"{arm}_arm_teleop" + section = teleop_document.get(section_name) + if not isinstance(section, Mapping): + raise ValueError(f"missing {section_name} configuration") + params = section.get("ros__parameters") + if not isinstance(params, Mapping): + raise ValueError(f"{section_name} is missing ros__parameters") + arm_tool = arms.get(arm) + if not isinstance(arm_tool, Mapping): + raise ValueError(f"peripheral configuration is missing arm {arm}") + tool_index = int(arm_tool.get("scissorgripper")) + try: + tool_name = tool_names[tool_index] + tool_values = tools[tool_name]["pose"] + except (IndexError, KeyError, TypeError) as exc: + raise ValueError(f"invalid active tool selection for {arm}") from exc + + joint_speed = float(params["joint_max_speed"]) + profiles[arm] = ArmTeleopProfile( + arm=arm, + initial_tcp=_pose_from_rpy(params["initial_tcp_pose"], f"{arm}.initial_tcp_pose"), + configured_initial_q_rad=np.deg2rad(params["initial_joint_pose"]), + tool_from_flange=_tool_pose(tool_values, f"tools.{tool_name}.pose"), + active_tool_name=tool_name, + xr_to_robot=np.asarray(params["xr_to_robot_matrix"], dtype=float).reshape(3, 3), + scale=float(params["scale"]), + command_timeout_sec=float(params["command_timeout_sec"]), + deadband_m=float(params["deadband_m"]), + target_filter_alpha=float(params["target_filter_alpha"]), + target_filter_alpha_fast=float(params["target_filter_alpha_fast"]), + target_filter_fast_threshold_m=float( + params["target_filter_fast_threshold_m"] + ), + max_linear_speed_m_s=float(params["max_linear_speed"]), + enable_position_axes=tuple(bool(value) for value in params["enable_position_axes"]), + enable_orientation_control=bool(params["enable_orientation_control"]), + enable_orientation_axes=tuple(bool(value) for value in params["enable_orientation_axes"]), + orientation_deadband_rad=float(params["orientation_deadband_rad"]), + orientation_filter_alpha=float(params["orientation_filter_alpha"]), + max_orientation_speed_rad_s=float(params["max_orientation_speed"]), + workspace_min=params["workspace_min"], + workspace_max=params["workspace_max"], + cylinder_radius_limit=params["cyl_radius_limit"], + low_z_threshold=float(params["low_z_threshold"]), + low_z_min_radius=float(params["low_z_min_radius"]), + joint_max_speed_rad_s=np.full(7, np.deg2rad(joint_speed)), + ) + return profiles diff --git a/ik_qp/src/rm75_ik/teleop_control.py b/ik_qp/src/rm75_ik/teleop_control.py new file mode 100644 index 0000000..691a99e --- /dev/null +++ b/ik_qp/src/rm75_ik/teleop_control.py @@ -0,0 +1,429 @@ +from __future__ import annotations + +from dataclasses import dataclass +from enum import Enum +from typing import Dict, Mapping, Optional + +import numpy as np +import pinocchio as pin + +from .kinematics import RM75Kinematics, validate_se3 +from .robot_backend import RobotBackend +from .solver import RM75IkSolver +from .teleop_config import ArmName, ArmTeleopProfile +from .types import IkOptions, teleop_joint_limits + + +class SafetyState(str, Enum): + IDLE = "idle" + ACTIVE = "active" + FAULT = "fault" + + +@dataclass(frozen=True) +class ControllerSample: + hand: ArmName + grip: bool + trigger: float + position_m: np.ndarray + quaternion_xyzw: np.ndarray + + def __post_init__(self) -> None: + if self.hand not in ("left", "right"): + raise ValueError("controller hand must be 'left' or 'right'") + position = np.asarray(self.position_m, dtype=float).copy() + quaternion = np.asarray(self.quaternion_xyzw, dtype=float).copy() + if position.shape != (3,) or not np.all(np.isfinite(position)): + raise ValueError("controller position must be finite with shape (3,)") + if quaternion.shape != (4,) or not np.all(np.isfinite(quaternion)): + raise ValueError("controller quaternion must be finite with shape (4,)") + norm = float(np.linalg.norm(quaternion)) + if norm <= 1e-9: + raise ValueError("controller quaternion has zero norm") + quaternion /= norm + if not np.isfinite(self.trigger): + raise ValueError("controller trigger must be finite") + position.setflags(write=False) + quaternion.setflags(write=False) + object.__setattr__(self, "position_m", position) + object.__setattr__(self, "quaternion_xyzw", quaternion) + + @classmethod + def from_message( + cls, message, expected_arm: Optional[ArmName] = None + ) -> "ControllerSample": + message_hand = str(getattr(message, "hand", "")).strip().lower() + hand = expected_arm or message_hand + if expected_arm is not None and message_hand and message_hand != expected_arm: + raise ValueError( + f"controller message hand {message_hand!r} does not match {expected_arm!r}" + ) + pose = message.pose + return cls( + hand=hand, + grip=bool(message.grip), + trigger=float(message.trigger), + position_m=np.array( + [pose.position.x, pose.position.y, pose.position.z], dtype=float + ), + quaternion_xyzw=np.array( + [ + pose.orientation.x, + pose.orientation.y, + pose.orientation.z, + pose.orientation.w, + ], + dtype=float, + ), + ) + + +@dataclass(frozen=True) +class MappedTarget: + target_tcp: pin.SE3 + clamped: bool + just_engaged: bool + + +@dataclass(frozen=True) +class ControlCycleResult: + state: SafetyState + commanded_arms: tuple[ArmName, ...] = () + targets_tcp: Optional[Mapping[ArmName, pin.SE3]] = None + reason: str = "" + + +class RelativePoseMapper: + def __init__(self, profile: ArmTeleopProfile) -> None: + self.profile = profile + self.active = False + self._controller_start_position: Optional[np.ndarray] = None + self._controller_start_rotation: Optional[np.ndarray] = None + self._robot_start_tcp: Optional[pin.SE3] = None + self._filtered_position: Optional[np.ndarray] = None + self._filtered_rotation: Optional[np.ndarray] = None + self._last_position: Optional[np.ndarray] = None + self._last_rotation: Optional[np.ndarray] = None + + def reset(self) -> None: + self.active = False + self._controller_start_position = None + self._controller_start_rotation = None + self._robot_start_tcp = None + self._filtered_position = None + self._filtered_rotation = None + self._last_position = None + self._last_rotation = None + + @staticmethod + def _rotation(sample: ControllerSample) -> np.ndarray: + x, y, z, w = sample.quaternion_xyzw + return pin.Quaternion(w, x, y, z).matrix() + + def map( + self, + sample: ControllerSample, + current_tcp: pin.SE3, + dt: float, + ) -> MappedTarget: + if sample.hand != self.profile.arm: + raise ValueError("controller sample was routed to the wrong arm") + validate_se3(current_tcp, "current_tcp") + if not np.isfinite(dt) or dt <= 0.0: + raise ValueError("control dt must be finite and positive") + rotation = self._rotation(sample) + if not self.active: + self.active = True + self._controller_start_position = sample.position_m.copy() + self._controller_start_rotation = rotation.copy() + self._robot_start_tcp = current_tcp.copy() + self._filtered_position = current_tcp.translation.copy() + self._filtered_rotation = current_tcp.rotation.copy() + self._last_position = current_tcp.translation.copy() + self._last_rotation = current_tcp.rotation.copy() + return MappedTarget(current_tcp.copy(), False, True) + + assert self._controller_start_position is not None + assert self._controller_start_rotation is not None + assert self._robot_start_tcp is not None + delta = sample.position_m - self._controller_start_position + mapped_delta = self.profile.xr_to_robot @ delta + raw_position = ( + self._robot_start_tcp.translation + self.profile.scale * mapped_delta + ) + raw_position = np.where( + np.asarray(self.profile.enable_position_axes, dtype=bool), + raw_position, + self._robot_start_tcp.translation, + ) + position, clamped = self._clamp_workspace(raw_position) + position = self._filter_position(position) + position, limited = self._limit_position_step(position, dt) + position, final_clamped = self._clamp_workspace(position) + + target_rotation = self._target_rotation(rotation) + target_rotation = self._filter_rotation(target_rotation) + target_rotation, rotation_limited = self._limit_rotation_step( + target_rotation, dt + ) + self._last_position = position.copy() + self._last_rotation = target_rotation.copy() + return MappedTarget( + pin.SE3(target_rotation, position), + clamped or limited or final_clamped or rotation_limited, + False, + ) + + def _clamp_workspace(self, target: np.ndarray) -> tuple[np.ndarray, bool]: + result = np.clip( + np.asarray(target, dtype=float), + self.profile.workspace_min, + self.profile.workspace_max, + ) + min_radius, max_radius = self.profile.cylinder_radius_limit + if result[2] < self.profile.low_z_threshold: + min_radius = max(min_radius, self.profile.low_z_min_radius) + radius = float(np.hypot(result[0], result[1])) + if radius > max_radius: + result[:2] *= max_radius / radius + elif radius < min_radius: + if radius > 1e-9: + result[:2] *= min_radius / radius + else: + result[:2] = [min_radius, 0.0] + changed = not np.allclose(result, target, atol=1e-12, rtol=0.0) + return result, changed + + def _filter_position(self, target: np.ndarray) -> np.ndarray: + assert self._filtered_position is not None + assert self._last_position is not None + if np.linalg.norm(target - self._last_position) < self.profile.deadband_m: + target = self._last_position + distance = float(np.linalg.norm(target - self._filtered_position)) + ratio = min( + 1.0, distance / self.profile.target_filter_fast_threshold_m + ) + alpha = self.profile.target_filter_alpha + ratio * ( + self.profile.target_filter_alpha_fast + - self.profile.target_filter_alpha + ) + self._filtered_position = ( + alpha * target + (1.0 - alpha) * self._filtered_position + ) + return self._filtered_position.copy() + + def _limit_position_step( + self, target: np.ndarray, dt: float + ) -> tuple[np.ndarray, bool]: + assert self._last_position is not None + delta = target - self._last_position + distance = float(np.linalg.norm(delta)) + maximum = self.profile.max_linear_speed_m_s * dt + if distance <= maximum or distance <= 1e-12: + return target, False + return self._last_position + delta * (maximum / distance), True + + def _target_rotation(self, controller_rotation: np.ndarray) -> np.ndarray: + assert self._controller_start_rotation is not None + assert self._robot_start_tcp is not None + if not self.profile.enable_orientation_control: + return self._robot_start_tcp.rotation.copy() + xr_delta = controller_rotation @ self._controller_start_rotation.T + matrix = self.profile.xr_to_robot + robot_delta = matrix @ xr_delta @ matrix.T + target = robot_delta @ self._robot_start_tcp.rotation + axes = np.asarray(self.profile.enable_orientation_axes, dtype=bool) + if not np.all(axes): + target_rpy = pin.rpy.matrixToRpy(target) + start_rpy = pin.rpy.matrixToRpy(self._robot_start_tcp.rotation) + target = pin.rpy.rpyToMatrix(*np.where(axes, target_rpy, start_rpy)) + return target + + def _filter_rotation(self, target: np.ndarray) -> np.ndarray: + assert self._filtered_rotation is not None + assert self._last_rotation is not None + if ( + np.linalg.norm(pin.log3(self._last_rotation.T @ target)) + < self.profile.orientation_deadband_rad + ): + target = self._last_rotation + delta = pin.log3(self._filtered_rotation.T @ target) + self._filtered_rotation = self._filtered_rotation @ pin.exp3( + self.profile.orientation_filter_alpha * delta + ) + return self._filtered_rotation.copy() + + def _limit_rotation_step( + self, target: np.ndarray, dt: float + ) -> tuple[np.ndarray, bool]: + assert self._last_rotation is not None + delta = pin.log3(self._last_rotation.T @ target) + angle = float(np.linalg.norm(delta)) + maximum = self.profile.max_orientation_speed_rad_s * dt + if angle <= maximum or angle <= 1e-12: + return target, False + return self._last_rotation @ pin.exp3(delta * (maximum / angle)), True + + +class DualArmQpTeleopController: + def __init__( + self, + robot: RobotBackend, + profiles: Mapping[ArmName, ArmTeleopProfile], + control_rate_hz: float = 90.0, + ik_options: Optional[IkOptions] = None, + ) -> None: + if set(profiles) != {"left", "right"}: + raise ValueError("profiles must contain left and right arms") + if not np.isfinite(control_rate_hz) or control_rate_hz <= 0.0: + raise ValueError("control_rate_hz must be finite and positive") + self.robot = robot + self.profiles = dict(profiles) + self.dt = 1.0 / control_rate_hz + self.ik_options = ik_options or IkOptions( + max_iterations=120, + time_limit_sec=0.008, + ) + self.kinematics = { + arm: RM75Kinematics(limits=teleop_joint_limits()) + for arm in ("left", "right") + } + self.solvers = { + arm: RM75IkSolver(self.kinematics[arm]) for arm in ("left", "right") + } + self.mappers = { + arm: RelativePoseMapper(self.profiles[arm]) + for arm in ("left", "right") + } + self._latest: Dict[ArmName, tuple[ControllerSample, float]] = {} + self._fault_reason = "" + self._closed = False + self.robot.connect() + + @property + def safety_state(self) -> SafetyState: + if self._fault_reason: + return SafetyState.FAULT + if any(mapper.active for mapper in self.mappers.values()): + return SafetyState.ACTIVE + return SafetyState.IDLE + + def update_controller( + self, + message, + timestamp_sec: float, + expected_arm: Optional[ArmName] = None, + ) -> None: + self.update_sample( + ControllerSample.from_message(message, expected_arm), timestamp_sec + ) + + def update_sample(self, sample: ControllerSample, timestamp_sec: float) -> None: + if not np.isfinite(timestamp_sec): + raise ValueError("controller timestamp must be finite") + self._latest[sample.hand] = (sample, float(timestamp_sec)) + + def reject_input(self, reason: str) -> None: + self._trip_fault(f"invalid controller input: {reason}") + + def step(self, timestamp_sec: float) -> ControlCycleResult: + if self._closed: + raise RuntimeError("controller is closed") + if not np.isfinite(timestamp_sec): + return self._trip_fault("control timestamp is non-finite") + if self._fault_reason: + if self._can_clear_fault(timestamp_sec): + self._fault_reason = "" + return ControlCycleResult(SafetyState.IDLE, reason="fault cleared") + return ControlCycleResult(SafetyState.FAULT, reason=self._fault_reason) + + try: + state = self.robot.read_joint_positions() + commands: Dict[ArmName, np.ndarray] = {} + targets: Dict[ArmName, pin.SE3] = {} + for arm in ("left", "right"): + latest = self._latest.get(arm) + mapper = self.mappers[arm] + if latest is None: + continue + sample, sample_time = latest + age = timestamp_sec - sample_time + if age < -1e-6: + return self._trip_fault(f"{arm} controller timestamp is in the future") + if not sample.grip: + if mapper.active: + mapper.reset() + self.robot.stop((arm,)) + continue + if age > self.profiles[arm].command_timeout_sec: + return self._trip_fault(f"{arm} controller input timed out") + + q_current = state.positions_rad[arm] + current_tcp = self.kinematics[arm].forward( + q_current, self.profiles[arm].tool_from_flange + ) + mapped = mapper.map(sample, current_tcp, self.dt) + flange_target = ( + mapped.target_tcp * self.profiles[arm].tool_from_flange.inverse() + ) + result = self.solvers[arm].solve( + flange_target, q_current, self.ik_options + ) + if not result.success or result.q is None: + return self._trip_fault( + f"{arm} IK failed: {result.status.value}: {result.message}" + ) + max_step = self.profiles[arm].joint_max_speed_rad_s * self.dt + q_command = np.clip(result.q, q_current - max_step, q_current + max_step) + limits = self.kinematics[arm].limits + q_command = np.clip(q_command, limits.lower, limits.upper) + commands[arm] = q_command + targets[arm] = mapped.target_tcp + + if commands: + self.robot.command_joint_positions(commands) + for arm, target in targets.items(): + self.robot.set_target_tcp_pose(arm, target) + return ControlCycleResult( + self.safety_state, + tuple(commands), + targets or None, + ) + except Exception as exc: + return self._trip_fault(f"control/backend failure: {exc}") + + def _can_clear_fault(self, timestamp_sec: float) -> bool: + if set(self._latest) != {"left", "right"}: + return False + for arm, (sample, sample_time) in self._latest.items(): + if sample.grip: + return False + if timestamp_sec - sample_time > self.profiles[arm].command_timeout_sec: + return False + for mapper in self.mappers.values(): + mapper.reset() + return True + + def _trip_fault(self, reason: str) -> ControlCycleResult: + self._fault_reason = str(reason) + for mapper in self.mappers.values(): + mapper.reset() + try: + self.robot.stop(("left", "right")) + except Exception: + pass + return ControlCycleResult(SafetyState.FAULT, reason=self._fault_reason) + + def stop(self) -> None: + for mapper in self.mappers.values(): + mapper.reset() + self.robot.stop(("left", "right")) + + def close(self) -> None: + if self._closed: + return + try: + self.stop() + finally: + self.robot.close() + self._closed = True diff --git a/ik_qp/src/rm75_ik/types.py b/ik_qp/src/rm75_ik/types.py index a75000a..0500209 100644 --- a/ik_qp/src/rm75_ik/types.py +++ b/ik_qp/src/rm75_ik/types.py @@ -52,7 +52,7 @@ def physical_joint_limits() -> JointLimits: def teleop_joint_limits() -> JointLimits: - lower = np.deg2rad([-150.0, -30.0, -170.0, -130.0, -175.0, -125.0, -179.0]) + lower = np.deg2rad([-150.0, -110.0, -170.0, -130.0, -175.0, -125.0, -179.0]) upper = np.deg2rad([150.0, 110.0, 170.0, 130.0, 175.0, 125.0, 179.0]) return JointLimits("teleop", lower, upper) diff --git a/ik_qp/tests/test_mujoco_stage2.py b/ik_qp/tests/test_mujoco_stage2.py new file mode 100644 index 0000000..19a5362 --- /dev/null +++ b/ik_qp/tests/test_mujoco_stage2.py @@ -0,0 +1,157 @@ +import os +from pathlib import Path + +import mujoco +import numpy as np +import pytest + +from rm75_ik import DualArmAssembly, pose_errors +from rm75_ik.mujoco_backend import CONTROLLED_HOME_Q_RAD, DualArmMuJoCo +from rm75_ik.mujoco_model import build_normalized_dual_mjcf +from rm75_ik.mujoco_trajectories import ( + cartesian_demo_targets, + joint_demo_trajectory, + se3_target_trajectory, + solve_pose_trajectory, +) +from rm75_ik import RM75IkSolver, RM75Kinematics, teleop_joint_limits + + +def test_normalized_model_has_standard_dual_arm_structure(): + xml, assets = build_normalized_dual_mjcf() + model = mujoco.MjModel.from_xml_string(xml, assets) + + assert model.nq == model.nv == model.njnt == 14 + assert model.nu == 0 + assert model.nmesh == 27 + assert len([key for key in assets if key.endswith(".obj")]) == 19 + assert [model.joint(index).name for index in range(14)] == [ + f"{arm}_joint_{joint}" + for arm in ("left", "right") + for joint in range(1, 8) + ] + + +@pytest.mark.parametrize("arm", ["left", "right"]) +def test_mujoco_flange_matches_stage1_dual_assembly(arm): + scene = DualArmMuJoCo(controlled_arm=arm) + assembly = DualArmAssembly.from_source_urdf() + q = np.deg2rad([20, -10, 30, 40, -20, 15, 80]) + + scene.set_arm_configuration(arm, q) + errors = pose_errors(scene.get_flange_pose(arm), assembly.forward(arm, q)) + + assert errors[0] < 1e-9 + assert errors[1] < 1e-9 + + +def test_invalid_configuration_does_not_change_state(): + scene = DualArmMuJoCo() + before = scene.get_arm_configuration("left") + + with pytest.raises(ValueError): + scene.set_arm_configuration("left", np.full(7, np.nan)) + + np.testing.assert_array_equal(scene.get_arm_configuration("left"), before) + + +def test_playback_moves_only_controlled_arm(): + scene = DualArmMuJoCo(controlled_arm="left") + inactive_before = scene.get_arm_configuration("right") + trajectory = joint_demo_trajectory(CONTROLLED_HOME_Q_RAD, 20) + + result = scene.play_trajectory(trajectory) + + assert result.samples == 20 + np.testing.assert_array_equal( + scene.get_arm_configuration("right"), inactive_before + ) + np.testing.assert_allclose( + scene.get_arm_configuration("left"), trajectory[-1], atol=0.0 + ) + + +def test_se3_target_trajectory_preserves_endpoints(): + kinematics = RM75Kinematics(limits=teleop_joint_limits()) + start = kinematics.forward(CONTROLLED_HOME_Q_RAD) + target = start.copy() + target.translation = target.translation + np.array([0.04, 0.01, 0.0]) + + trajectory = se3_target_trajectory(start, target, 25) + + assert pose_errors(trajectory[0], start) == pytest.approx((0.0, 0.0), abs=1e-12) + assert pose_errors(trajectory[-1], target) == pytest.approx((0.0, 0.0), abs=1e-12) + + +def test_manual_drag_dynamics_moves_only_controlled_arm(): + scene = DualArmMuJoCo(controlled_arm="left") + controlled_before = scene.get_arm_configuration("left") + inactive_before = scene.get_arm_configuration("right") + scene.configure_manual_drag() + body_id = mujoco.mj_name2id( + scene.model, mujoco.mjtObj.mjOBJ_BODY, "left_link_7" + ) + scene.data.xfrc_applied[body_id, :3] = [0.0, 10.0, 0.0] + + for _ in range(50): + scene.step_manual_drag() + + assert np.max(np.abs(scene.get_arm_configuration("left") - controlled_before)) > 1e-5 + np.testing.assert_array_equal( + scene.get_arm_configuration("right"), inactive_before + ) + + +@pytest.mark.parametrize("kind", ["line", "arc", "orientation", "combined"]) +def test_demo_cartesian_trajectories_are_solvable(kind): + kinematics = RM75Kinematics(limits=teleop_joint_limits()) + solver = RM75IkSolver(kinematics) + targets = cartesian_demo_targets( + kind, kinematics.forward(CONTROLLED_HOME_Q_RAD), 30 + ) + + solutions = solve_pose_trajectory(solver, targets, CONTROLLED_HOME_Q_RAD) + + assert solutions.shape == (30, 7) + assert np.all(np.isfinite(solutions)) + + +@pytest.mark.skipif( + os.environ.get("MUJOCO_GL") != "egl", + reason="EGL rendering test requires MUJOCO_GL=egl", +) +def test_offscreen_render_contains_both_arms(): + scene = DualArmMuJoCo() + rgb = scene.render(640, 360) + segmentation = scene.render(640, 360, segmentation=True) + pairs = np.unique(segmentation.reshape(-1, 2), axis=0) + names = { + mujoco.mj_id2name(scene.model, mujoco.mjtObj.mjOBJ_GEOM, int(object_id)) + for object_id, object_type in pairs + if object_type == mujoco.mjtObj.mjOBJ_GEOM and object_id >= 0 + } + + assert rgb.std() > 5.0 + assert any(name.startswith("left_") for name in names if name) + assert any(name.startswith("right_") for name in names if name) + + +@pytest.fixture(scope="module") +def realman_sdk_root(): + value = os.environ.get("REALMAN_SDK_ROOT") + if not value: + pytest.skip("REALMAN_SDK_ROOT is not set") + return Path(value) + + +def test_quick_stage2_validation_passes(realman_sdk_root): + from rm75_ik.realman_reference import RealManFkReference + from rm75_ik.stage2_validation import Stage2Settings, Stage2Validator + + validator = Stage2Validator( + RealManFkReference(realman_sdk_root), settings=Stage2Settings.quick() + ) + summary = validator.run() + + assert summary["passed"] is True + assert summary["failure_count"] == 0 diff --git a/ik_qp/tests/test_stage3_control.py b/ik_qp/tests/test_stage3_control.py new file mode 100644 index 0000000..2f7eebb --- /dev/null +++ b/ik_qp/tests/test_stage3_control.py @@ -0,0 +1,195 @@ +import os +from dataclasses import replace +from pathlib import Path +from types import SimpleNamespace + +import numpy as np +import pinocchio as pin +import pytest + +from rm75_ik import pose_errors +from rm75_ik.mujoco_robot import MujocoRobot +from rm75_ik.teleop_config import load_dual_arm_profiles +from rm75_ik.teleop_control import ( + ControllerSample, + DualArmQpTeleopController, + RelativePoseMapper, + SafetyState, +) + + +ROOT = Path(__file__).resolve().parents[2] + + +@pytest.fixture(scope="module") +def profiles(): + return load_dual_arm_profiles( + ROOT / "xr_rm_bringup/config/dual_arm_rm75.yaml", + ROOT / "xr_rm_bringup/config/peripherals_rm75.yaml", + ) + + +def sample(arm, grip, position=(0.0, 0.0, 0.0), quaternion=(0, 0, 0, 1)): + return ControllerSample( + hand=arm, + grip=grip, + trigger=0.0, + position_m=np.asarray(position, dtype=float), + quaternion_xyzw=np.asarray(quaternion, dtype=float), + ) + + +def test_profiles_use_expected_tools_and_mapping(profiles): + assert profiles["left"].active_tool_name == "minisci" + assert profiles["right"].active_tool_name == "omnipic" + np.testing.assert_array_equal( + profiles["left"].xr_to_robot, + [[0, -1, 0], [0, 0, 1], [-1, 0, 0]], + ) + np.testing.assert_array_equal( + profiles["right"].xr_to_robot, + [[0, 1, 0], [0, 0, 1], [1, 0, 0]], + ) + + +@pytest.mark.parametrize( + ("arm", "expected_delta"), + [("left", [-0.01, 0.0, 0.0]), ("right", [0.01, 0.0, 0.0])], +) +def test_relative_position_mapping_matches_ros_configuration( + profiles, arm, expected_delta +): + profile = replace( + profiles[arm], + scale=1.0, + deadband_m=0.0, + target_filter_alpha=1.0, + target_filter_alpha_fast=1.0, + max_linear_speed_m_s=10.0, + orientation_filter_alpha=1.0, + max_orientation_speed_rad_s=10.0, + ) + mapper = RelativePoseMapper(profile) + start = profile.initial_tcp + mapper.map(sample(arm, True), start, 0.1) + + mapped = mapper.map(sample(arm, True, [0.0, 0.01, 0.0]), start, 0.1) + + np.testing.assert_allclose( + mapped.target_tcp.translation - start.translation, + expected_delta, + atol=1e-12, + ) + + +def test_mujoco_initializes_both_configured_tool_tcp_poses(profiles): + robot = MujocoRobot(profiles) + try: + for arm in ("left", "right"): + position_error, orientation_error = pose_errors( + robot.get_tcp_pose(arm), profiles[arm].initial_tcp + ) + assert position_error < 1e-3 + assert orientation_error < np.deg2rad(0.1) + diagnostic = robot.initial_pose_diagnostics[arm] + assert diagnostic.configured_joint_position_error_m > 0.05 + finally: + robot.close() + + +def test_mujoco_dual_command_is_atomic(profiles): + robot = MujocoRobot(profiles) + try: + before = robot.read_joint_positions().positions_rad + with pytest.raises(ValueError): + robot.command_joint_positions( + { + "left": before["left"] + 0.01, + "right": np.full(7, np.nan), + } + ) + after = robot.read_joint_positions().positions_rad + np.testing.assert_array_equal(after["left"], before["left"]) + np.testing.assert_array_equal(after["right"], before["right"]) + finally: + robot.close() + + +def test_dual_controller_has_no_grip_jump_and_moves_both_arms(profiles): + robot = MujocoRobot(profiles) + controller = DualArmQpTeleopController(robot, profiles) + try: + initial = robot.read_joint_positions().positions_rad + for arm in ("left", "right"): + controller.update_sample(sample(arm, True), 0.0) + engaged = controller.step(0.0) + after_engage = robot.read_joint_positions().positions_rad + assert engaged.state is SafetyState.ACTIVE + for arm in ("left", "right"): + np.testing.assert_allclose(after_engage[arm], initial[arm], atol=1e-10) + + for arm in ("left", "right"): + controller.update_sample(sample(arm, True, [0, 0.005, 0]), 0.01) + moved_result = controller.step(0.01) + moved = robot.read_joint_positions().positions_rad + assert moved_result.state is SafetyState.ACTIVE + for arm in ("left", "right"): + assert np.max(np.abs(moved[arm] - initial[arm])) > 1e-5 + finally: + controller.close() + + +def test_active_arm_timeout_faults_both_and_requires_release(profiles): + robot = MujocoRobot(profiles) + controller = DualArmQpTeleopController(robot, profiles) + try: + for arm in ("left", "right"): + controller.update_sample(sample(arm, True), 0.0) + assert controller.step(0.0).state is SafetyState.ACTIVE + + fault = controller.step(1.0) + assert fault.state is SafetyState.FAULT + assert "timed out" in fault.reason + + for arm in ("left", "right"): + controller.update_sample(sample(arm, False), 1.01) + cleared = controller.step(1.01) + assert cleared.state is SafetyState.IDLE + finally: + controller.close() + + +def test_message_compatible_adapter_rejects_wrong_hand(): + message = SimpleNamespace( + hand="right", + grip=True, + trigger=0.0, + pose=SimpleNamespace( + position=SimpleNamespace(x=0.0, y=0.0, z=0.0), + orientation=SimpleNamespace(x=0.0, y=0.0, z=0.0, w=1.0), + ), + ) + + with pytest.raises(ValueError, match="does not match"): + ControllerSample.from_message(message, expected_arm="left") + + +@pytest.mark.skipif( + not os.environ.get("REALMAN_SDK_ROOT"), + reason="REALMAN_SDK_ROOT is not set", +) +def test_quick_stage3_validation_passes(): + from rm75_ik.realman_reference import RealManFkReference + from rm75_ik.stage3_validation import Stage3Settings, Stage3Validator + + validator = Stage3Validator( + RealManFkReference(Path(os.environ["REALMAN_SDK_ROOT"])), + ROOT / "xr_rm_bringup/config/dual_arm_rm75.yaml", + ROOT / "xr_rm_bringup/config/peripherals_rm75.yaml", + Stage3Settings.quick(), + ) + + summary = validator.run() + + assert summary["passed"] is True + assert summary["failure_count"] == 0 diff --git a/xr_rm_bringup/launch/dual_arm_qp_sim.launch.py b/xr_rm_bringup/launch/dual_arm_qp_sim.launch.py new file mode 100644 index 0000000..c639fdf --- /dev/null +++ b/xr_rm_bringup/launch/dual_arm_qp_sim.launch.py @@ -0,0 +1,85 @@ +"""PICO/XR to dual-arm QP IK with a shared MuJoCo backend.""" + +from launch import LaunchDescription +from launch.actions import DeclareLaunchArgument, SetEnvironmentVariable +from launch.substitutions import ( + EnvironmentVariable, + LaunchConfiguration, + PathJoinSubstitution, +) +from launch_ros.actions import Node +from launch_ros.substitutions import FindPackageShare + + +def generate_launch_description() -> LaunchDescription: + config_dir = PathJoinSubstitution( + [FindPackageShare("xr_rm_bringup"), "config"] + ) + return LaunchDescription( + [ + DeclareLaunchArgument("mujoco_gl", default_value="glfw"), + SetEnvironmentVariable( + "MUJOCO_GL", + LaunchConfiguration("mujoco_gl"), + ), + SetEnvironmentVariable( + "PYTHONPATH", + [ + PathJoinSubstitution( + [ + EnvironmentVariable("CONDA_PREFIX"), + "lib/python3.10/site-packages", + ] + ), + ":", + PathJoinSubstitution( + [ + EnvironmentVariable("CONDA_PREFIX"), + "lib/python3.10/site-packages/cmeel.prefix/lib/python3.10/site-packages", + ] + ), + ":", + EnvironmentVariable("PYTHONPATH", default_value=""), + ], + ), + DeclareLaunchArgument("udp_host", default_value="0.0.0.0"), + DeclareLaunchArgument("udp_port", default_value="15000"), + DeclareLaunchArgument("udp_timer_hz", default_value="200.0"), + DeclareLaunchArgument("control_rate_hz", default_value="90.0"), + DeclareLaunchArgument("show_viewer", default_value="true"), + Node( + package="xr_rm_input", + executable="udp_controller_receiver", + name="udp_controller_receiver", + output="screen", + parameters=[ + { + "udp_host": LaunchConfiguration("udp_host"), + "udp_port": LaunchConfiguration("udp_port"), + "timer_hz": LaunchConfiguration("udp_timer_hz"), + "left_topic": "/xr/left_controller", + "right_topic": "/xr/right_controller", + } + ], + ), + Node( + package="xr_rm_teleop", + executable="dual_arm_qp_teleop", + name="dual_arm_qp_teleop", + output="screen", + parameters=[ + { + "robot_backend": "mujoco", + "control_rate_hz": LaunchConfiguration("control_rate_hz"), + "show_viewer": LaunchConfiguration("show_viewer"), + "teleop_config_file": PathJoinSubstitution( + [config_dir, "dual_arm_rm75.yaml"] + ), + "peripheral_config_file": PathJoinSubstitution( + [config_dir, "peripherals_rm75.yaml"] + ), + } + ], + ), + ] + ) diff --git a/xr_rm_teleop/package.xml b/xr_rm_teleop/package.xml index a2a9fc9..73c480d 100755 --- a/xr_rm_teleop/package.xml +++ b/xr_rm_teleop/package.xml @@ -10,7 +10,10 @@ ament_python geometry_msgs + ament_index_python rclpy + rm75_ik + sensor_msgs python3-yaml std_msgs xr_rm_interfaces diff --git a/xr_rm_teleop/setup.py b/xr_rm_teleop/setup.py index 4358e7b..c7a6a1d 100755 --- a/xr_rm_teleop/setup.py +++ b/xr_rm_teleop/setup.py @@ -25,6 +25,7 @@ setup( entry_points={ "console_scripts": [ "single_arm_velocity_teleop = xr_rm_teleop.single_arm_velocity_teleop:main", + "dual_arm_qp_teleop = xr_rm_teleop.dual_arm_qp_teleop:main", ], }, ) diff --git a/xr_rm_teleop/xr_rm_teleop/dual_arm_qp_teleop.py b/xr_rm_teleop/xr_rm_teleop/dual_arm_qp_teleop.py new file mode 100644 index 0000000..7541a5c --- /dev/null +++ b/xr_rm_teleop/xr_rm_teleop/dual_arm_qp_teleop.py @@ -0,0 +1,212 @@ +"""Dual-arm XR teleoperation using the independent RM75 QP controller.""" + +from __future__ import annotations + +import os +from pathlib import Path + +import rclpy +from ament_index_python.packages import get_package_share_directory +from geometry_msgs.msg import PoseStamped +from rclpy.executors import ExternalShutdownException +from rclpy.node import Node +from sensor_msgs.msg import JointState +from std_msgs.msg import Bool, String +from xr_rm_interfaces.msg import XrController + + +class DualArmQpTeleop(Node): + def __init__(self) -> None: + super().__init__("dual_arm_qp_teleop") + bringup_share = Path(get_package_share_directory("xr_rm_bringup")) + self.declare_parameter("robot_backend", "mujoco") + self.declare_parameter("control_rate_hz", 90.0) + self.declare_parameter("left_controller_topic", "/xr/left_controller") + self.declare_parameter("right_controller_topic", "/xr/right_controller") + self.declare_parameter( + "teleop_config_file", str(bringup_share / "config/dual_arm_rm75.yaml") + ) + self.declare_parameter( + "peripheral_config_file", + str(bringup_share / "config/peripherals_rm75.yaml"), + ) + self.declare_parameter("show_viewer", True) + self.declare_parameter("debug_topic_prefix", "/xr_rm/qp") + + backend_name = str(self.get_parameter("robot_backend").value).lower() + if backend_name != "mujoco": + raise ValueError( + "stage 3 implements only robot_backend='mujoco'; " + "the RealmanRobot contract is reserved for the next stage" + ) + control_rate_hz = float(self.get_parameter("control_rate_hz").value) + if control_rate_hz <= 0.0: + raise ValueError("control_rate_hz must be positive") + + from rm75_ik import DualArmQpTeleopController, load_dual_arm_profiles + from rm75_ik.mujoco_robot import MujocoRobot + + profiles = load_dual_arm_profiles( + self.get_parameter("teleop_config_file").value, + self.get_parameter("peripheral_config_file").value, + ) + self._robot = MujocoRobot(profiles) + self._controller = DualArmQpTeleopController( + self._robot, profiles, control_rate_hz=control_rate_hz + ) + self._closed = False + self._show_viewer = bool(self.get_parameter("show_viewer").value) + if self._show_viewer: + self._robot.open_viewer() + + prefix = str(self.get_parameter("debug_topic_prefix").value).rstrip("/") + self._target_publishers = { + arm: self.create_publisher( + PoseStamped, f"{prefix}/{arm}/target_tcp", 10 + ) + for arm in ("left", "right") + } + self._current_publishers = { + arm: self.create_publisher( + PoseStamped, f"{prefix}/{arm}/current_tcp", 10 + ) + for arm in ("left", "right") + } + self._fault_publisher = self.create_publisher(Bool, f"{prefix}/fault", 10) + self._state_publisher = self.create_publisher( + String, f"{prefix}/control_state", 10 + ) + self._joint_state_publisher = self.create_publisher( + JointState, f"{prefix}/joint_states", 10 + ) + self._joint_names = [ + f"{arm}_joint_{joint}" + for arm in ("left", "right") + for joint in range(1, 8) + ] + self.create_subscription( + XrController, + str(self.get_parameter("left_controller_topic").value), + lambda message: self._on_controller("left", message), + 10, + ) + self.create_subscription( + XrController, + str(self.get_parameter("right_controller_topic").value), + lambda message: self._on_controller("right", message), + 10, + ) + self.create_timer(1.0 / control_rate_hz, self._control_tick) + + for arm, diagnostic in self._robot.initial_pose_diagnostics.items(): + self.get_logger().info( + f"{arm} MuJoCo initialized from initial_tcp_pose: " + f"position_error={diagnostic.solved_position_error_m:.6f} m, " + f"orientation_error={diagnostic.solved_orientation_error_rad:.6f} rad" + ) + self.get_logger().info( + "dual-arm QP teleop ready: backend=mujoco, grip controls each arm, " + "any active-arm fault stops both arms" + ) + + def _now_sec(self) -> float: + return self.get_clock().now().nanoseconds * 1e-9 + + def _on_controller(self, arm: str, message: XrController) -> None: + try: + self._controller.update_controller( + message, self._now_sec(), expected_arm=arm + ) + except Exception as exc: + self.get_logger().error( + f"{arm} controller input rejected: {exc}", + throttle_duration_sec=1.0, + ) + self._controller.reject_input(str(exc)) + + def _control_tick(self) -> None: + result = self._controller.step(self._now_sec()) + stamp = self.get_clock().now().to_msg() + fault = Bool() + fault.data = result.state.value == "fault" + self._fault_publisher.publish(fault) + state_message = String() + state_message.data = result.state.value + self._state_publisher.publish(state_message) + if fault.data: + self.get_logger().error( + f"dual-arm QP controller stopped: {result.reason}", + throttle_duration_sec=1.0, + ) + if result.targets_tcp: + for arm, target in result.targets_tcp.items(): + self._target_publishers[arm].publish(self._pose_message(target)) + for arm in ("left", "right"): + self._current_publishers[arm].publish( + self._pose_message(self._robot.get_tcp_pose(arm)) + ) + joint_state = self._robot.read_joint_positions().positions_rad + joint_message = JointState() + joint_message.header.stamp = stamp + joint_message.header.frame_id = "dual_rm75" + joint_message.name = self._joint_names + joint_message.position = [ + float(value) + for arm in ("left", "right") + for value in joint_state[arm] + ] + self._joint_state_publisher.publish(joint_message) + if self._show_viewer and not self._robot.sync_viewer(): + self.get_logger().info("MuJoCo viewer closed; shutting down QP teleop") + self._close_control() + if rclpy.ok(): + rclpy.shutdown() + + def _pose_message(self, pose) -> PoseStamped: + import pinocchio as pin + + quaternion = pin.Quaternion(pose.rotation) + message = PoseStamped() + message.header.stamp = self.get_clock().now().to_msg() + message.header.frame_id = "rm_base" + message.pose.position.x = float(pose.translation[0]) + message.pose.position.y = float(pose.translation[1]) + message.pose.position.z = float(pose.translation[2]) + message.pose.orientation.x = float(quaternion.x) + message.pose.orientation.y = float(quaternion.y) + message.pose.orientation.z = float(quaternion.z) + message.pose.orientation.w = float(quaternion.w) + return message + + def _close_control(self) -> None: + if self._closed: + return + self._controller.close() + self._closed = True + + def destroy_node(self): + self._close_control() + return super().destroy_node() + + +def main(args=None) -> None: + os.environ.setdefault("MUJOCO_GL", "glfw") + rclpy.init(args=args) + node = None + try: + node = DualArmQpTeleop() + rclpy.spin(node) + except (KeyboardInterrupt, ExternalShutdownException): + pass + finally: + if node is not None: + try: + node.destroy_node() + except KeyboardInterrupt: + pass + if rclpy.ok(): + rclpy.shutdown() + + +if __name__ == "__main__": + main()