# ACT 双相机预览与采样质量判定修正实施计划 > **供代理执行者使用:** 必须使用 `superpowers:subagent-driven-development`(推荐)或 `superpowers:executing-plans`,逐项执行本计划。所有步骤使用复选框(`- [ ]`)跟踪。 **目标:** 保持 ACT 当前因果时间对齐,同时把真实相机丢帧与软件采样相位漂移分开判定,并在 ACT 数采启动时默认显示全局 D455 和右腕 D405 实时画面。 **架构:** 继续由 `act_episode_recorder` 独占两台 RealSense,并按每三个 `90 Hz` 控制周期选择不晚于控制时刻的最新图像。`CameraBuffer` 负责真实采集质量,HDF5 校验只记录 ACT 样本重复/跨帧率;同一节点内新增一个只读 OpenCV 预览线程,复用现有帧缓冲且不进入机器人控制链路。 **技术栈:** Ubuntu 22.04、ROS2 Humble、Python 3、rclpy、NumPy、h5py、pyrealsense2、OpenCV、pytest、HDF5。 --- ## 文件结构 本次不新建 ROS 包或运行进程,文件职责保持如下: - 修改 `xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py`:真实采集统计、ACT 采样相位指标、质量判定、双路预览及关闭顺序; - 修改 `xr_rm_teleop/test/test_act_episode_recorder.py`:指标口径、误拒绝复现、帧号回退和预览隔离测试; - 修改 `README.md`:说明 ACT 数采默认预览、显示内容和关闭行为。 不修改 `arm_debug.launch.py`、`launcher_ui.py`、ROS 消息、机器人控制节点和相机 YAML。工作区已有的 `xr_rm_teleop/xr_rm_teleop/fun_peripheral.py` 未提交改动属于用户,不加入本任务提交。 所有构建和测试命令从工作空间根目录执行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash ``` 自动化测试不得启动真机 launch、移动机械臂或操作夹爪。 ### 任务 1:区分真实丢帧与 ACT 采样相位漂移 **文件:** - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:408-579` - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:595-657` - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:1472-1511` - 测试:`xr_rm_teleop/test/test_act_episode_recorder.py:273-296` - 测试:`xr_rm_teleop/test/test_act_episode_recorder.py:491-607` - [ ] **步骤 1:写异步采样不拒绝和指标测试** 在测试导入中加入 `sample_frame_metrics`,并增加: ```python def test_sample_frame_metrics_separate_repeats_skips_and_regressions(): repeat, skip, regression = sample_frame_metrics( np.asarray((986, 986, 988), dtype=np.uint64) ) assert repeat == pytest.approx(0.5) assert skip == pytest.approx(0.5) assert regression == 0 @requires_h5py def test_validate_episode_accepts_async_camera_phase_drift(tmp_path): path = _valid_episode(tmp_path) with h5py.File(path, "r+") as root: root["debug/cameras/cam_high_frame_number"][:] = (986, 986, 988) report = validate_episode(path, _quality_limits()) assert report.accepted assert report.metrics["cam_high_sample_repeat_ratio"] == pytest.approx(0.5) assert report.metrics["cam_high_sample_skip_ratio"] == pytest.approx(0.5) ``` 在 `_valid_episode()` 写入新增的真实采集属性: ```python root.attrs["camera_high_frame_number_regression_count"] = 0 root.attrs["camera_right_wrist_frame_number_regression_count"] = 0 ``` - [ ] **步骤 2:写真实帧号回退测试** 扩展现有 `CameraBuffer` 测试: ```python def test_camera_buffer_counts_frame_number_regressions(): buffer = CameraBuffer(maxlen=4) for frame_number in (100, 101, 1, 2): buffer.push( CameraFrame( _image(frame_number), frame_number, float(frame_number), time.monotonic_ns(), ) ) stats = buffer.stats() assert stats.frame_number_regression_count == 1 assert stats.dropped_frames == 0 ``` 测试文件顶部增加标准库导入: ```python import time ``` 并在稳定拒绝原因参数中增加真实采集帧号回退: ```python elif mutation == "camera_frame_regression": root.attrs["camera_high_frame_number_regression_count"] = 1 ``` 对应期望: ```python ("camera_frame_regression", "camera_frame_number_regression"), ``` - [ ] **步骤 3:运行新增测试并确认失败** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py \ -k "sample_frame_metrics or async_camera_phase_drift or frame_number_regressions or camera_frame_regression" -v ``` 预期:测试因 `sample_frame_metrics` 尚不存在、`CameraStats` 没有回退计数,或旧校验仍以 `camera_sample_drop_ratio` 拒绝而失败。 - [ ] **步骤 4:实现最小采样相位指标** 在质量校验辅助函数附近增加纯函数: ```python def sample_frame_metrics( frame_numbers: np.ndarray, ) -> tuple[float, float, int]: diffs = np.diff(np.asarray(frame_numbers, dtype=np.int64)) denominator = max(1, len(diffs)) return ( float(np.count_nonzero(diffs == 0) / denominator), float(np.count_nonzero(diffs > 1) / denominator), int(np.count_nonzero(diffs < 0)), ) ``` 把 `validate_episode()` 中原有“所有 `diff != 1` 都拒绝”的循环替换为: ```python for camera in ("cam_high", "cam_wrist"): frame_numbers = datasets[ f"debug/cameras/{camera}_frame_number" ][:] repeat_ratio, skip_ratio, regression_count = sample_frame_metrics( frame_numbers ) metrics[f"{camera}_sample_repeat_ratio"] = repeat_ratio metrics[f"{camera}_sample_skip_ratio"] = skip_ratio if regression_count: return _quality_failure("camera_frame_number_regression", metrics) ``` 这样 `986 → 986 → 988` 只产生统计,不再触发 `camera_sample_drop_ratio`。 - [ ] **步骤 5:在采集层统计帧号回退** 扩展 `CameraStats`: ```python @dataclass(frozen=True) class CameraStats: frame_count: int dropped_frames: int frame_number_regression_count: int first_host_monotonic_ns: int | None last_host_monotonic_ns: int | None ``` 在 `CameraBuffer.__init__()` 增加: ```python self._frame_number_regression_count = 0 ``` 在 `CameraBuffer.push()` 更新帧号前使用互斥分支: ```python if self._last_frame_number is not None: if frame.frame_number <= self._last_frame_number: self._frame_number_regression_count += 1 elif frame.frame_number > self._last_frame_number + 1: self._dropped_frames += ( frame.frame_number - self._last_frame_number - 1 ) ``` 在 `stats()` 返回: ```python frame_number_regression_count=self._frame_number_regression_count, ``` - [ ] **步骤 6:把真实采集回退纳入 episode 属性和拒绝条件** 把 `_interval_camera_metrics()` 的返回值扩展为 FPS、真实丢帧率和本 episode 新增的回退数: ```python @staticmethod def _interval_camera_metrics( baseline: CameraStats, current: CameraStats, ) -> tuple[float, float, int]: frames = max(0, current.frame_count - baseline.frame_count) dropped = max(0, current.dropped_frames - baseline.dropped_frames) regressions = max( 0, current.frame_number_regression_count - baseline.frame_number_regression_count, ) if ( baseline.last_host_monotonic_ns is None or current.last_host_monotonic_ns is None ): return 0.0, 1.0, regressions elapsed_ns = ( current.last_host_monotonic_ns - baseline.last_host_monotonic_ns ) fps = frames * 1e9 / elapsed_ns if elapsed_ns > 0 else 0.0 expected = frames + dropped drop_ratio = dropped / expected if expected else 1.0 return fps, drop_ratio, regressions ``` `_write_camera_metrics()` 写入: ```python "camera_high_frame_number_regression_count": high[2], "camera_right_wrist_frame_number_regression_count": wrist[2], ``` `validate_episode()` 在读取 FPS 和真实丢帧率后要求两个回退属性存在且为零: ```python for name in ( "camera_high_frame_number_regression_count", "camera_right_wrist_frame_number_regression_count", ): if name not in root.attrs: return _quality_failure("camera_stats_missing", metrics) value = int(root.attrs[name]) metrics[name] = value if value: return _quality_failure("camera_frame_number_regression", metrics) ``` - [ ] **步骤 7:确保采样指标写入保存和拒绝文件** 增加读取 HDF5 根节点的辅助函数: ```python def episode_sample_frame_metrics(root: Any) -> dict[str, int | float]: metrics: dict[str, int | float] = {} for camera in ("cam_high", "cam_wrist"): repeat, skip, regression = sample_frame_metrics( root[f"debug/cameras/{camera}_frame_number"][:] ) metrics[f"{camera}_sample_repeat_ratio"] = repeat metrics[f"{camera}_sample_skip_ratio"] = skip metrics[f"{camera}_sample_frame_number_regression_count"] = regression return metrics ``` `validate_episode()` 复用该函数更新 `report.metrics`。在 `_reject_closed_partial()` 已打开 HDF5 后也执行: ```python for name, value in episode_sample_frame_metrics(root).items(): root.attrs[name] = value ``` 保存路径继续由 `_complete_save()` 把 `report.metrics` 写入属性。保存日志追加紧凑摘要: ```python self.get_logger().info( "ACT相机采样相位:" f"high重复={report.metrics['cam_high_sample_repeat_ratio']:.2%}, " f"high跨帧={report.metrics['cam_high_sample_skip_ratio']:.2%}, " f"wrist重复={report.metrics['cam_wrist_sample_repeat_ratio']:.2%}, " f"wrist跨帧={report.metrics['cam_wrist_sample_skip_ratio']:.2%}" ) ``` - [ ] **步骤 8:运行相关测试并确认通过** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py \ -k "camera or validate_episode" -v ``` 预期:所有选中测试通过;真实丢帧率仍使用 `camera_drop_ratio` 拒绝,异步重复/跨帧不拒绝。 - [ ] **步骤 9:提交任务 1** ```bash git add src/xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py \ src/xr_rm_teleop/test/test_act_episode_recorder.py git commit -m "fix: 修正ACT相机采样质量判定" ``` ### 任务 2:在录制器中增加非阻塞双路预览 **文件:** - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:595-657` - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:1006-1152` - 修改:`xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py:1668-1671` - 测试:`xr_rm_teleop/test/test_act_episode_recorder.py` - [ ] **步骤 1:写两秒滚动 FPS 测试** 扩展 `CameraBuffer` 测试,使用明确的单调时间: ```python def test_camera_buffer_reports_two_second_rolling_fps(): buffer = CameraBuffer(maxlen=4) start_ns = 10_000_000_000 for index in range(61): buffer.push( CameraFrame( _image(index), index, float(index), start_ns + index * 33_333_333, ) ) assert buffer.stats().rolling_fps == pytest.approx(30.0, rel=0.02) ``` - [ ] **步骤 2:写预览显示异常隔离测试** 构造不经过 ROS 初始化的录制器和抛错的 `cv2` 替身: ```python def test_preview_failure_does_not_change_recording_state(): recorder = object.__new__(ActEpisodeRecorder) recorder._session = _recording_session() recorder._preview_stop = threading.Event() recorder._preview_thread = None recorder.get_logger = lambda: _Logger() class FailingCv2: WINDOW_NORMAL = 0 @staticmethod def namedWindow(*_args): raise RuntimeError("no display") recorder._preview_loop(FailingCv2()) assert recorder.state is RecordingState.RECORDING ``` `_Logger` 增加 `warns` 收集和 `warn()`: ```python self.warns = [] def warn(self, message): self.warns.append(message) ``` - [ ] **步骤 3:写预览关闭顺序测试** 验证关闭节点时先停预览,再停相机: ```python def test_close_stops_preview_before_cameras_and_releases_lock(): events = [] recorder = object.__new__(ActEpisodeRecorder) recorder._stop_preview = lambda: events.append("preview") recorder._high_camera = SimpleNamespace( stop=lambda: events.append("high") ) recorder._wrist_camera = SimpleNamespace( stop=lambda: events.append("wrist") ) recorder._directory_lock = SimpleNamespace( release=lambda: events.append("lock") ) recorder.close() assert events == ["preview", "high", "wrist", "lock"] ``` - [ ] **步骤 4:运行新增预览测试并确认失败** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py \ -k "rolling_fps or preview or close_stops_preview" -v ``` 预期:测试因 `rolling_fps`、`_preview_loop()` 和 `_stop_preview()` 尚不存在而失败。 - [ ] **步骤 5:实现两秒滚动 FPS** 在 `CameraBuffer.__init__()` 增加: ```python self._recent_host_monotonic_ns: deque[int] = deque() ``` 每次 `push()` 时裁剪两秒窗口: ```python self._recent_host_monotonic_ns.append(frame.host_monotonic_ns) cutoff_ns = frame.host_monotonic_ns - 2_000_000_000 while ( self._recent_host_monotonic_ns and self._recent_host_monotonic_ns[0] < cutoff_ns ): self._recent_host_monotonic_ns.popleft() ``` `CameraStats` 增加字段和属性: ```python recent_host_monotonic_ns: tuple[int, ...] @property def rolling_fps(self) -> float: if len(self.recent_host_monotonic_ns) < 2: return 0.0 elapsed_ns = ( self.recent_host_monotonic_ns[-1] - self.recent_host_monotonic_ns[0] ) return ( (len(self.recent_host_monotonic_ns) - 1) * 1e9 / elapsed_ns if elapsed_ns > 0 else 0.0 ) ``` `stats()` 使用: ```python recent_host_monotonic_ns=tuple(self._recent_host_monotonic_ns), ``` - [ ] **步骤 6:实现最小预览渲染方法** 在 `ActEpisodeRecorder` 增加固定窗口名: ```python PREVIEW_WINDOW = "ACT - D455 Global / D405 Right Wrist" ``` 增加生成单个画面块的方法。相机帧是 RGB,因此显示前转换成 BGR: ```python @staticmethod def _preview_tile(role: str, frame, stats, cv2): if frame is None: tile = np.zeros((480, 640, 3), dtype=np.uint8) frame_number = "-" else: tile = cv2.cvtColor(frame.image, cv2.COLOR_RGB2BGR) frame_number = str(frame.frame_number) tile = tile.copy() cv2.rectangle(tile, (0, 0), (640, 74), (0, 0, 0), -1) lines = ( f"{role} FPS {stats.rolling_fps:.1f} Frame {frame_number}", f"Received {stats.frame_count} Dropped " f"{stats.dropped_frames} ({stats.drop_ratio:.2%})", ) for index, line in enumerate(lines): cv2.putText( tile, line, (10, 28 + index * 30), cv2.FONT_HERSHEY_SIMPLEX, 0.65, (255, 255, 255), 1, cv2.LINE_AA, ) return tile ``` 增加 `_compose_preview()`:读取两个缓冲最新帧,水平拼接,并在底部显示状态: ```python def _compose_preview(self, cv2): high_frames = self._high_camera.buffer.snapshot() wrist_frames = self._wrist_camera.buffer.snapshot() high = high_frames[-1] if high_frames else None wrist = wrist_frames[-1] if wrist_frames else None high_stats = self._high_camera.buffer.stats() wrist_stats = self._wrist_camera.buffer.stats() image = np.hstack( ( self._preview_tile("GLOBAL D455", high, high_stats, cv2), self._preview_tile("RIGHT WRIST D405", wrist, wrist_stats, cv2), ) ) now_ns = self._now_ns() high_age = ( f"{(now_ns - high.host_monotonic_ns) * 1e-6:.1f} ms" if high is not None else "-" ) wrist_age = ( f"{(now_ns - wrist.host_monotonic_ns) * 1e-6:.1f} ms" if wrist is not None else "-" ) skew = ( f"{abs(high.host_monotonic_ns - wrist.host_monotonic_ns) * 1e-6:.1f} ms" if high is not None and wrist is not None else "-" ) episode = ( f"episode_{self._episode_index}" if self._episode_index is not None else "-" ) samples = self._store.count if self._store is not None else 0 footer = np.zeros((80, image.shape[1], 3), dtype=np.uint8) lines = ( f"Age high={high_age} wrist={wrist_age} Camera skew={skew}", f"ACT {self.state.value} {episode} Samples {samples}", ) for index, line in enumerate(lines): cv2.putText( footer, line, (10, 30 + index * 32), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (255, 255, 255), 1, cv2.LINE_AA, ) return np.vstack((image, footer)) ``` 若尚无帧,对应数值显示 `-`;该方法不修改任何录制器状态。 - [ ] **步骤 7:实现预览线程生命周期和故障隔离** 在相机成员创建前初始化: ```python self._preview_stop = threading.Event() self._preview_thread: threading.Thread | None = None ``` 两台相机成功启动后调用 `_start_preview()`: ```python if self._camera_start_error is None: self._start_preview() ``` 实现: ```python def _start_preview(self) -> None: if not (os.environ.get("DISPLAY") or os.environ.get("WAYLAND_DISPLAY")): self.get_logger().warn("未检测到桌面显示环境,ACT双相机预览已停用。") return try: import cv2 except ImportError as exc: self.get_logger().warn(f"OpenCV不可用,ACT双相机预览已停用:{exc}") return self._preview_stop.clear() self._preview_thread = threading.Thread( target=self._preview_loop, args=(cv2,), name="act_camera_preview", daemon=True, ) self._preview_thread.start() def _preview_loop(self, cv2) -> None: try: cv2.namedWindow(self.PREVIEW_WINDOW, cv2.WINDOW_NORMAL) while not self._preview_stop.is_set(): cv2.imshow(self.PREVIEW_WINDOW, self._compose_preview(cv2)) key = cv2.waitKey(1) & 0xFF if key in (ord("q"), ord("Q"), 27): break if cv2.getWindowProperty( self.PREVIEW_WINDOW, cv2.WND_PROP_VISIBLE, ) < 1: break self._preview_stop.wait(0.1) except Exception as exc: self.get_logger().warn(f"ACT双相机预览已停用:{exc}") finally: try: cv2.destroyWindow(self.PREVIEW_WINDOW) except Exception: pass def _stop_preview(self) -> None: self._preview_stop.set() if self._preview_thread is not None: self._preview_thread.join(timeout=2.0) self._preview_thread = None ``` `close()` 的第一步调用 `self._stop_preview()`,然后保持现有相机停止和目录锁释放顺序。 - [ ] **步骤 8:运行预览相关测试并确认通过** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py \ -k "rolling_fps or preview or close_stops_preview" -v ``` 预期:所有选中测试通过,测试过程不打开真实窗口或相机。 - [ ] **步骤 9:运行 ACT 录制器完整单元测试** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py -v ``` 预期:全部通过。 - [ ] **步骤 10:提交任务 2** ```bash git add src/xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py \ src/xr_rm_teleop/test/test_act_episode_recorder.py git commit -m "feat: 添加ACT双相机实时预览" ``` ### 任务 3:更新使用说明并完成工作空间验证 **文件:** - 修改:`README.md:144-169` - [ ] **步骤 1:更新 ACT 数采说明** 在 ACT episode 启动命令后补充: ```markdown `record_act:=true` 启动后默认显示全局 D455 和右腕 D405 双路画面,并显示实时 FPS、真实丢帧率、帧龄、双相机时间差、录制状态、episode 编号和样本数。按 `Q`、`Esc` 或关闭窗口只会停止预览,ACT 相机采集和录制继续运行;没有桌面环境 或 OpenCV 显示失败时也不会影响录制。 相机采集线程观察到的真实掉帧仍会拒绝 episode。独立 `30 Hz` 控制和相机时钟 造成的 ACT 样本重复/跨帧只写入 HDF5 质量指标,不再误报为相机丢包。 ``` - [ ] **步骤 2:运行文档和 Python 静态检查** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash python -m py_compile \ src/xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py \ src/xr_rm_teleop/test/test_act_episode_recorder.py git diff --check ``` 预期:命令返回码为 `0`,没有语法或空白错误。 - [ ] **步骤 3:运行项目要求的工作空间构建** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash colcon build --symlink-install ``` 预期:所有包构建成功。不得在 `/home/robot/WS_xr/src` 中运行该命令。 - [ ] **步骤 4:构建后再次运行 ACT 录制器测试** 运行: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash source install/setup.bash pytest src/xr_rm_teleop/test/test_act_episode_recorder.py -v ``` 预期:全部通过。 - [ ] **步骤 5:确认提交范围并提交任务 3** 运行: ```bash git status --short git diff -- README.md \ src/xr_rm_teleop/xr_rm_teleop/act_episode_recorder.py \ src/xr_rm_teleop/test/test_act_episode_recorder.py git add README.md git commit -m "docs: 更新ACT相机预览说明" ``` 不得暂存或提交 `xr_rm_teleop/xr_rm_teleop/fun_peripheral.py`。 ## 现场验证 自动化实施结束后,由用户在确认现场安全条件后运行现有 ACT 数采入口: ```bash cd /home/robot/WS_xr source /opt/ros/humble/setup.bash source install/setup.bash ros2 launch xr_rm_bringup arm_debug.launch.py \ arm:=right use_mock:=false record_act:=true ``` 该命令会连接右臂真机,代理不得自行执行。现场确认: 1. 双路画面默认出现且角色正确; 2. FPS、真实丢帧率、帧龄、双相机时间差和 ACT 状态持续更新; 3. 关闭窗口后录制状态和 HDF5 写入继续; 4. 正常异步重复/跨帧的 episode 能保存; 5. HDF5 属性包含真实采集质量与两路采样重复/跨帧指标。