Evolutionary computing systems for obstacle avoidance

In this paper we present two neuronal network architectures to perform the task of obstacle avoidance for a little mobile robot named Khepera, which has 8 infrared proximity detectors and two independent motors. The first one used Hebbian learning for weight adaptation and the second one use evolutionary weight selection. The experiments are only simulated.