Wich Probabilistic Roadmap method should be used by a robot in an actual environment? An analysis of the main methods through simulations

Path planning for autonomous robots into actual enviroments has been an important challenge. Probabilistic roadmaps (PRM) is one of the most used techniques for solve this challenge and several PRM methods have been proposed. In this paper the main PRM methods are analyzed through a huge set of simulations with a robot into complex statics environments. The main results have show which methods are more intersting according to environment characteristics.