A decision-theoretic approach to planning, perception, and control
- 1 August 1992
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Expert
- Vol. 7 (4) , 58-65
- https://doi.org/10.1109/64.153465
Abstract
The application of Bayesian decision theory as a framework for designing high-level robotic control systems is discussed. The approach to building planning and control systems integrates sensor fusion, prediction, and sequential decision making. The system explicitly uses the value of sensor information as well as the value of actions that facilitate further sensing. A stochastic decision model and a model for mobile-target localization used in the control system are described. A control system implemented to drive a small mobile robot equipped with eight sonar transducers with a maximum range of six meters and a visual processing system capable of identifying moving targets in its visual field and reporting their motion relative to the robot is also discussed.Keywords
This publication has 6 references indexed in Scilit:
- Sensor abstractions for control of navigationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Coordinating, Planning and ControlPublished by Defense Technical Information Center (DTIC) ,1991
- Utility-Based Control for Computer VisionPublished by Elsevier ,1990
- Dynamic programming and influence diagramsIEEE Transactions on Systems, Man, and Cybernetics, 1990
- A model for reasoning about persistence and causationComputational Intelligence, 1989
- Multiple sensor expert system for diagnostic reasoning, monitoring and control of mechanical systemsMechanical Systems and Signal Processing, 1988