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Stochastic reachability for surveillance systems: design, implementation and potential extensions via approximate dynamic programming (ADP)


N. Kariotoglou

Polytechnic University of Bucharest, Romania

In this talk we present a stochastic reachability formulation to the surveillance problems of target tracking and acquisition. Our approach involves solving an optimal control problem for Markov decision processes via dynamic programming which is computationally intractable when posed for a collection of surveillance agents. To alleviate this problem we present a task allocation mechanism that decouples agent objectives making solutions tractable but sub-optimal. We verify our results via experiments on a two-camera, two-evader system. In the last part of the talk we present an optimization based approach to ADP which aims to deal, in a more general sense, with computational tractability of dynamic programs arising in stochastic reachability


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J. Lygeros

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