VAMP-MR: Vector-Accelerated Motion Planning and Execution for Multi-Robot-Arms

Philip Huang, Chenrui Gao, Jiaoyang Li

Keywords: Multi-Robot Arm Motion Planning, Parallelization

TL;DR: Accelerated multi-robot-arm motion planner through vectorized collision checking

Abstract: Multi-robot-arm motion planning is a key challenge in deploying multiple manipulators for industrial tasks such as manufacturing. Existing search-based and sampling-based solvers often require significant computation time to produce collision-free, high-quality motions suitable for safe execution. In this work, we introduce a new suite of multi-robot-arm motion planners capable of near real-time motion generation, combining classical planning algorithms with state-of-the-art vectorized collision-checking techniques. Based on CPU SIMD instructions, our new planners remove motion validation as the primary bottleneck and achieve up to two orders of magnitude speedup in both motion planning and execution postprocessing for multi-arm manipulation tasks. We also release the implementation of our vector-accelerated multi-robot planning and execution algorithms, and we believe this will lower the barrier for research and development of multi-robot-arm planning and manipulation problems. Our code is available at https://vamp-mr.github.io/vamp-mr/.

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Submission Number: 18