Parallelizing Broad Phase Collision Detection Algorithms for Sampling Based Path Planners

Abstract

Collision checking takes most of the time in sampling based path planning algorithms. When the scene gets crowded, more samples are needed and the probability decreases to find a collision free sample. Broad phase algorithms are designed to eliminate obviously collision free samples, so narrow phase algorithms can concentrate on fewer samples suspected to be in collision. In this study, we compare the performance of two broad phase algorithms implemented on both CPU and GPU. A novel technique is proposed to provide load balancing and efficient cache utilization on Bounding Sphere Collision Detection algorithm. Furthermore, Thrust library is extensively utilized on Sweep and Prune (SAP) algorithm. Our experimental results indicate speedups up to 103 times faster for GPU-based SAP algorithm and 134 times faster for GPU-based Bounding Sphere algorithm, compared to CPU implementations. This may allow using sampling based path planning algorithms for scenes with many robots.