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

2026-07-15

AI Summary

This work addresses the significant computational burden in multi-arm motion planning, where achieving real-time performance while ensuring collision-free, high-quality trajectories remains challenging. The authors present the first deep integration of CPU SIMD-instruction-based vectorized collision detection into a multi-arm planning framework, substantially accelerating the collision-checking bottleneck inherent in sampling- and search-based planners. By leveraging this approach, the system maintains planning quality while improving both motion planning and post-execution processing speeds by nearly two orders of magnitude, thereby achieving near real-time performance. To foster further research, the authors open-source their implementation.

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 real-world 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 accelerate their primary bottleneck, collision checking, and achieve up to two orders of magnitude speedup in both motion planning and execution postprocessing for multi-arm manipulation tasks. We also release our implementation to lower the barrier for research and development of multi-robot-arm planning and manipulation problems. Code is available at https://vamp-mr.github.io/vamp-mr

Problem

• multi-robot-arm motion planning
• collision-free motion
• real-time motion generation
• industrial manipulation
• computational efficiency

Innovation

• multi-robot-arm motion planning
• vectorized collision checking
• SIMD acceleration
• real-time motion generation
• motion execution postprocessing