A BAYESIAN-APPROACH TO OPTIMAL SENSOR PLACEMENT

By ″intelligently″ locating a sensor with respect to its environment, it is possible to minimize the number of sensing operations required to perform many tasks. This is particularly important for sensing media, such as tactile sensors and sonar, that provide only ″sparse data. In this paper, a system is described that uses the principle of statistical decision theory to determine the optimal sensing locations for performing recognition and localization operations. The system uses a Bayesian approach to utilize any prior object information (including object models or previously acquired sensory data) in choosing the sensing locations.