15th European Conference on Artificial Intelligence
|July 21-26 2002 Lyon France|
louis Hugues, Alexis Drogoul
In this paper we address the problem of learning behaviors for autonomous mobile robots.We particularly focus on methods which enable a human user to train a robot in its real destination environment without giving an a-priori model. Using complex visual input typical of real situations in office environments we show that very simple visual features can be used to represent the perception/action relation specific to a given behavior. From this point we propose a learning model relying on a statistical collection of two-pixels features for representing a behavior. We then present the experiments made on a real robot and propose extensions of the model for active-perception and behavior selection.
Keywords: Robotics, Machine Learning, Vision, Autonomous Agents
Citation: louis Hugues, Alexis Drogoul: Pixel-based Behavior Learning. In F. van Harmelen (ed.): ECAI2002, Proceedings of the 15th European Conference on Artificial Intelligence, IOS Press, Amsterdam, 2002, pp.731-735.