AbstractsBusiness Management & Administration

Probabilistic Framework for Sensor Management

by Marco Huber

Institution: Universität Karlsruhe
Year: 2009
Keywords: sensor management, Bayesian estimation, decision theory, information theory, Gaussian mixtures
Record ID: 1114519
Full text PDF: http://digbib.ubka.uni-karlsruhe.de/volltexte/documents/984753


A probabilistic sensor management framework is introduced, which maximizes the utility of sensor systems with many different sensing modalities by dynamically configuring the sensor system in the most beneficial way. For this purpose, techniques from stochastic control and Bayesian estimation are combined such that long-term effects of possible sensor configurations and stochastic uncertainties resulting from noisy measurements can be incorporated into the sensor management decisions.