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Multi-agent autonomous surveillance: a framework based on stochastic reachability and hierarchical task allocation


N. Kariotoglou, D. M. Raimondo, S. Summers, J. Lygeros

ASME J. Dynamic Systems, Measurement & Control, Special Issue on Stochastic Models, Control, and Algorithms in Robotics

We develop and implement a framework to address autonomous surveillance problems with a collection of pantilt (PT) cameras. Using tools from stochastic reachability with random sets we formulate the problems of target acquisition, target tracking and acquisition while tracking as reach-avoid dynamic programs for Markov decision processes (MDPs). It is well known that solution methods for MDP problems based on dynamic programming, implemented by state space gridding, suffer from the curse of dimensionality. This becomes a major limitation when one considers a network of PT cameras. To deal with larger problems we propose a hierarchical task allocation mechanism that allows cameras to calculate reach-avoid objectives independently while achieving tasks collectively. We evaluate the proposed algorithms experimentally on a setup involving industrial PT cameras and mobile robots as targets.


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J. Lygeros

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% Autogenerated BibTeX entry
@Article { KarEtal:2014:IFA_4753,
    author={N. Kariotoglou and D. M. Raimondo and S. Summers and J. Lygeros},
    title={{Multi-agent autonomous surveillance: a framework based on
	  stochastic reachability and hierarchical task allocation}},
    journal={ASME J. Dynamic Systems, Measurement \& Control},
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