Floreano, D.Mondada, F.2006-01-122006-01-122006-01-12199610.1109/3477.499791https://infoscience.epfl.ch/handle/20.500.14299/221486WOS:A1996UL27600004In this paper we describe the evolution of a discrete-time recurrent neural network to control a real mobile robot. In all our experiments the evolutionary procedure is carried out entirely on the physical robot without human intervention. We show that the autonomous development of a set of behaviors for locating a battery charger and periodically returning to it can be achieved by lifting constraints in the design of the robot/environment interactions that were employed in a preliminary experiment. The emergent homing behavior is based on the autonomous development of an internal neural topographic map (which is not pre-designed) that allows the robot to choose the appropriate trajectory as function of location and remaining energy.Autonomous RobotsGenetic AlgorithmsNeural NetworksEvolutionary Roboticstext::journal::journal article::research article