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Distributed information-based guidance of multiple mobile sensors for urban target search

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Abstract

We present a framework for distributed mobile sensor guidance to locate and track a target inside an urban environment. Our approach leverages the communications between robots when a link is available, but it also allows them to act independently. Each robot actively seeks the target using information maximization. The robots are assumed to be capable of communicating with their peers within some distance radius, and the sensor payload of each robot is a camera modeled to have target detection errors of types I and II. Our contributions include an optimal information fusion algorithm for discrete distributions which allows each agent to combine its local information with that of its neighbors, and a path planner that uses the fused estimate and a recent coverage result for information maximization to guide the agents. We include simulations and laboratory experiments involving multiple robots searching for a moving target within model cities of different sizes.

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Author information

Authors and Affiliations

  1. Research Engineering & Education Facility, University of Florida, Shalimar, FL, USA

    Juan-Pablo Ramirez-Paredes

  2. Air Force Research Laboratory, Eglin, AFB, USA

    Emily A. Doucette & Jess W. Curtis

  3. The University of Texas at Dallas, Richardson, TX, USA

    Nicholas R. Gans

Authors
  1. Juan-Pablo Ramirez-Paredes
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  2. Emily A. Doucette
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  3. Jess W. Curtis
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  4. Nicholas R. Gans
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Corresponding author

Correspondence to Nicholas R. Gans.

Additional information

This is one of several papers published in Autonomous Robots comprising the Special Issue on Active Perception.

This work was supported by the US Air Force Research Laboratory Award Number FA8651-13-1-0003 and the Mexican government through Conacyt fellowship 253761/310475.

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Ramirez-Paredes, JP., Doucette, E.A., Curtis, J.W. et al. Distributed information-based guidance of multiple mobile sensors for urban target search. Auton Robot 42, 375–389 (2018). https://doi.org/10.1007/s10514-017-9658-5

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  • DOI: https://doi.org/10.1007/s10514-017-9658-5

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