This repo is for inverse kinematics and verification

In this branch, the qp-based inverse kinematics method is modified as a python class. The user can call it as in main.py

Inverse Kinematics (IK) is numerically obtained through quadratic programming (QP).

Verification is done with Mujoco simulation.

Key specifications:

1. Time consumption.
2. Success rate
3. Minial joint variation.

Next:
Comparison with Realman official IK method. Embedded with current demo.

Comparison (05June2026):

• With current dual arm joint limit,

ub = np.array([150.0, 110.0, 170.0,  130, 175.0, 125.0,  179.0])
lb = np.array([-150.0, -30.0, -170.0, -130, -175.0, -125.0,  -179.0])

the success rates for qp-based ik and realman Algo ik are 63% and 46%.
At least one solver works out the ik, rate = 74%.

• With realman-75 physical joint limit,

ub = np.array([179.0, 129.0, 179.0, 134, 179.0, 127.0, 359.0])
lb = -ub

the success rates for qp-based ik and realman Algo ik are 76% and 51%.
At least one solver works out the ik, rate = 84%.

update(1st July 2026)

In each iteration, update optimization formula:

• new cost item for distance from middle of the joint range.
• set up different weight for different joints motion.