ABSTRACT
Recently, a new class of randomized path planning methods, known as Probabilistic Roadmap Methods (prms) have shown great potential for solving compli cated high-dimensional problems, pr m s use randomiza tion (usually during preprocessing) to construct a graph of representative paths in C-space (a roadmap) whose vertices correspond to collision-free configurations of the robot and in which two vertices are connected by an edge if a path between the two corresponding config urations can be found by a local planning method.