Sensor planning with Bayesian decision theory

In this paper ongoing work on an approach for planning sensing actions and controlling intelligent, purposive robotic systems is presented, The method uses Bayesian decision analysis (BDA) for deciding what sensing actions should be performed. This offers a probabilistic framework that provides a more dynamic and modular behaviour than traditional rule based planners. Experiments show that the Bayesian sensor planning strategy is capable of controlling an autonomous mobile robot operating in partly known environments.