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Approximate dynamic programming for sensor management

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1 Author(s)
D. A. Castanon ; Dept. of Electr. & Comput. Eng., Boston Univ., MA

This paper studies the problem of dynamic scheduling of multi-mode sensor resources for the problem of classification of multiple unknown objects. Because of the uncertain nature of the object types, the problem is formulated as a partially observed Markov decision problem with a large state space. The paper describes a hierarchical algorithm approach for efficient solution of sensor scheduling problems with large numbers of objects, based on a combination of stochastic dynamic programming and nondifferentiable optimization techniques. The algorithm is illustrated with an application involving classification of 10,000 unknown objects

Published in:

Decision and Control, 1997., Proceedings of the 36th IEEE Conference on  (Volume:2 )

Date of Conference:

10-12 Dec 1997