Perceptual navigation around a sensori-motor trajectory

Abstract

Autonomous navigation of a mobile robot along a predefined trajectory is a widely studied problem in the robotics community. We propose a Bayesian architecture that aims at being able to replay any sensori-motor trajectory trajectory defined as a sequence of perceptions and actions - as long as the robot starts in its neighbourhood. In order to increase robustness, we also use this Bayesian framework to estimate system self-confidence while the robot is moving. This work has been validated both on a simulated robot and on a real robot: the CyCab.