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This paper introduces FWIK, an online inverse kinematics method for redundant robot arms that uses a lookahead graph search to select joint configurations optimizing future waypoints rather than just the immediate next step. By integrating a learned collision avoidance model with standard motion planners like MoveIt 2, the approach significantly reduces trajectory duration and improves sequence completion rates across multiple robot architectures. The results demonstrate that considering a small future window effectively balances computational efficiency with robustness in complex robotic tasks.
FWIK: Multi-Waypoint IK Selection via Lookahead Graph Search
arXiv:2611.05897v1 Announce Type: new Abstract: An ordered sequence of end-effector poses can give a redundant robot arm multiple valid joint configurations at each waypoint. Inverse kinematics (IK) computes these configurations. Choosing a configuration only for the next waypoint can leave the arm poorly placed for later waypoints. This may increase planned motion time or cause a later planning failure. This paper presents Future-Window Inverse Kinematics (FWIK), an online method that selects IK solutions by considering a small window of future waypoints. FWIK generates several IK candidates, connects them in a layered joint-space graph, and ranks candidate paths with a simple motion-time estimate. A learned model removes paths whose transitions are likely to cause self-collision. A standard MoveIt 2 planner then checks the next-waypoint IK goals from the remaining paths in ranked order, and the first goal that yields a valid trajectory is selected for execution. We evaluate FWIK in simulation on two 7-DoF manipulators, the Franka Emika Panda and the KUKA LBR iiwa. Each method-planner setting contains five repetitions of 100 sequences with 50 waypoints. Across Pilz, RRT-Connect, CHOMP, and STOMP, FWIK completes 96.8-100% of sequences and gives the shortest planned trajectory duration in all eight robot-planner settings. Its mean duration is 12.8-13.1% lower than STAMPEDE, 22.5-25.6% lower than IKLink, and 27.5-37.2% lower than retry-based TRAC-IK. The results show that a small future window can improve sequence completion and reduce planned motion time while leaving final trajectory validation to the motion planner.
Abstract:An ordered sequence of end-effector poses can give a redundant robot arm multiple valid joint configurations at each waypoint. Inverse kinematics (IK) computes these configurations. Choosing a configuration only for the next waypoint can leave the arm poorly placed for later waypoints. This may increase planned motion time or cause a later planning failure. This paper presents Future-Window Inverse Kinematics (FWIK), an online method that selects IK solutions by considering a small window of future waypoints. FWIK generates several IK candidates, connects them in a layered joint-space graph, and ranks candidate paths with a simple motion-time estimate. A learned model removes paths whose transitions are likely to cause self-collision. A standard MoveIt 2 planner then checks the next-waypoint IK goals from the remaining paths in ranked order, and the first goal that yields a valid trajectory is selected for execution. We evaluate FWIK in simulation on two 7-DoF manipulators, the Franka Emika Panda and the KUKA LBR iiwa. Each method-planner setting contains five repetitions of 100 sequences with 50 waypoints. Across Pilz, RRT-Connect, CHOMP, and STOMP, FWIK completes 96.8-100% of sequences and gives the shortest planned trajectory duration in all eight robot-planner settings. Its mean duration is 12.8-13.1% lower than STAMPEDE, 22.5-25.6% lower than IKLink, and 27.5-37.2% lower than retry-based TRAC-IK. The results show that a small future window can improve sequence completion and reduce planned motion time while leaving final trajectory validation to the motion planner.
Robotics (cs.RO)
arXiv:2611.05897 [cs.RO]
(or arXiv:2611.05897v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2611.05897 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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