PDRRTs: Integrating Graph-Based and Cell-Based Planning

Abstract

Motion-planning problems can be solved by discretizing the continuous configuration space, for example with graph-based or cell-based techniques. We study rapidly exploring random trees (RRTs) as an example of graph-based techniques and the parti-game method as an example of cell-based techniques. We then propose partigame directed RRTs (PDRRTs) as a novel technique that combines them. PDRRTs are based on the parti-game method but use RRTs as local controllers rather than the simplistic controllers used by the parti-game method. Our experimental results show that PDRRTs plan faster and solve more motion-planning problems than RRTs and plan faster and with less memory than the parti-game method.