title: Evolving a Behavioral Repertoire for a Walking Robot.
abstract: Numerous algorithms have been proposed to allow legged robots to learn to walk. However, most of these algorithms are devised to learn walking in a straight line, which is not sufficient to accomplish any real-world mission. Here we introduce the Transferability-based Behavioral Repertoire Evolution algorithm (TBR-Evolution), a novel evolutionary algorithm that simultaneously discovers several hundreds of simple walking controllers, one for each possible direction. By taking advantage of solutions that are usually discarded by evolutionary processes, TBR-Evolution is substantially faster than independently evolving each controller. Our technique relies on two methods: (1) novelty search with local competition, which searches for both high-performing and diverse solutions, and (2) the transferability approach, which combines simulations and real tests to evolve controllers for a physical robot. We evaluate this new technique on a hexapod robot. Results show that with only a few dozen short experiments performed on the robot, the algorithm learns a repertoire of controllers that allows the robot to reach every point in its reachable space. Overall, TBR-Evolution introduced a new kind of learning algorithm that simultaneously optimizes all the achievable behaviors of a robot.
authors.affiliation: Sorbonne Universités, UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris, France CNRS, UMR 7222, ISIR, F-75005, Paris, France cully@isir.upmc.fr.
authors.forename: A
authors.initials: A
authors.lastname: Cully
authors.affiliation: Sorbonne Universités, UPMC Univ Paris 06, UMR 7222, ISIR, F-75005, Paris, France CNRS, UMR 7222, ISIR, F-75005, Paris, France mouret@isir.upmc.fr.
authors.forename: J-B
authors.initials: JB
authors.lastname: Mouret
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005075:Biological Evolution; D019295:Computational Biology; D003198:Computer Simulation; D006801:Humans; D012371:Robotics / Q000295:instrumentation* / Q000706:statistics & numerical data; D014584:User-Computer Interface; D016138:Walking
keywords: Evolutionary algorithms; behavioral repertoire; evolutionary robotics; exploration; hexapod robot.; mobile robotics; novelty search