New approaches in randomized preprocessing for motion planning

Abstract

A powerful new method, randomized preprocessing for motion planning, has emerged recently with great success in robotics, specially when the configuration space is high-dimensional. Our contributions in this paper are two. We describe and implement: (a) a cell-division based heuristic for the node generation phase of randomized preprocessing based on iterative and controlled splitting of the configuration space, and (b) a new approach to randomized preprocessing, termed ray shooting in which we randomly generate rays, instead of isolated configurations, in the configuration space. Our experiments indicate that for certain robots either approach significantly improves performance over naive randomized preprocessing.