A vision agent for mobile robot navigation in time-variable environments

Abstract

We present an architecture for mobile robot navigation based on Bayesian networks. The architecture allows a robot to plan the correct path inside an environment with dynamic obstacles. Interactions between the robot and the environment are based on a powerful vision agent. The results of simulations, showing the effectiveness of the approach, are described.