Multi-Robot Motions in Milliseconds: Vector-Accelerated Primitives for Sampling-Based Planning
For roboticists needing fast multi-robot motion planning, this work provides a highly efficient SIMD-accelerated approach that dramatically reduces planning times.
This paper extends the Vector-Accelerated Motion Planning (VAMP) framework to multi-robot motion planning, achieving over 1100X speedup in motion validation and over 850X speedup in planning time for various multi-robot scenarios, enabling solutions in milliseconds.
In this paper, we extend the recent Vector-Accelerated Motion Planning (VAMP) framework to multi-robot motion planning (MRMP). We develop two vector-accelerated primitives, multi-robot MotionValidation (MotVal) and FindFirstConflict (FFC), which exploit SIMD parallelism within the multi-robot domain. On pure multi-robot motion validation tests, this achieves over 1100X speedup in validation time. Additionally, we modify a representative set of MRMP algorithms to use these new primitives. The relative speedup for each algorithm is studied on scenarios with manipulator, rigid body, and heterogeneous teams with some instances producing multi-robot solutions in the order of milliseconds and, in many cases, shows planning time speedups of over 850X.