MT-RRT: a general purpose multithreading library for path planning

摘要

Rapidly Random exploring Trees are popular algorithms in the field of motion planning. A feasible path connecting two different poses is found by incrementally building a tree data structure. They are powerful and flexible, but also computationally intense, requiring thousands of iterations before their termination. The aim of this article is to show the capabilities of MT-RRT, a general purpose library which exploits four different multithreading strategies to speed up the planning process of Rapidly Random exploring Trees. MT-RRT will be proved to significantly reduce the computation time on various benchmarks.