FWIK: Multi-Waypoint IK Selection via Lookahead Graph Search
FWIK: Multi-Waypoint IK Selection via Lookahead Graph Search
This research presents Future-Window Inverse Kinematics (FWIK), an online method that selects inverse kinematics solutions by considering a window of future waypoints to avoid poor arm placement for later steps. The approach generates IK candidates, connects them in a layered joint-space graph, and ranks paths using motion-time estimates while filtering out self-collision risks with a learned model. Evaluated on Franka Emika Panda and KUKA LBR iiwa robots in simulation across Pilz, RRT-Connect, CHOMP, and STOMP planners, FWIK achieved 96.8-100% sequence completion rates and reduced planned trajectory durations by 12.8-13.1% compared to STAMPEDE, 22.5-25.6% versus IKLink, and 27.5-37.2% against retry-based TRAC-IK.
The paper introduces FWIK, an online inverse kinematics method using lookahead graph search to improve sequence completion rates and reduce motion time on 7-DoF manipulators in simulation.
Source: arXiv Robotics — research abstracts · Read original article ↗
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t-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 g
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ives 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.
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Source：arXiv Robotics — research abstracts · arxiv.org