PolicyIK replaces numerical inverse kinematics with an RL policy, beating 4 classic IK controllers on a real robot
rsasaki0109 · x · 2026-11-11
PolicyIK ditches numerical IK solvers entirely: a goal-conditioned RL policy maps end-effector pose errors to joint updates in a single forward pass, naturally avoiding singularity lockup while handling dynamic obstacle avoidance. Trained directly on a physical robot, it reportedly achieves better reaching and holding performance than four classical IK controllers, potentially making the precision-control layer for VLA-based manipulation more adaptable.
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