Increasing Behavioural Repertoire in a Mobile Robot

Abstract

This paper presents an investigation of the the suitability of the robot controller presented in [Nehmzow et al. 89] and [Nehmzow et al. 90] for a computationally cheap expansion of the behavioural repertoire of a mobile robot. Experiments with mobile robots are presented that show that this is possible by simply adding further so-called instinct-rules without altering the controller itself: through the robot's interaction with its environment effective associations between sensors and actuators arise in an artificial neural network which serves as an associative memory. 1 Introduction Designing intelligent controllers for autonomous mobile robots is a task often underestimated by the designer. Sensor signals turn out to differ from what is expected in theory, and actuators produce different effects than anticipated. Whilst many of these differences between expected and observed behaviour can be overcome by building actual robots, there remain uncertainties and variations that are due...