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This paper presents VAMP-MR, a suite of motion planners that integrates classical planning algorithms with advanced vectorized collision-checking techniques to address the computational challenges of multi-robot-arm motion planning. By leveraging CPU SIMD instructions, the proposed planners achieve up to a 100x speedup in both motion planning and execution postprocessing, enabling near real-time generation of collision-free motions. The release of the implementation aims to facilitate further research and development in the field of multi-robot-arm manipulation.
Achieving up to 100x faster motion planning for multi-robot arms could revolutionize industrial automation by enabling real-time task execution.
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
