Probabilistic Strategies for Pursuit in Cluttered Environments with Multiple Robots

Geoffrey Hollinger, Athanasios Kehagias, and Sanjiv Singh
IEEE International Conference on Robotics and Automation, April, 2007.


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Abstract
In this paper, we describe a method for coordinating multiple robots in a pursuit-evasion domain. We examine the problem of multiple robotic pursuers attempting to locate a non-adversarial mobile evader in an indoor environment. Unlike many other approaches to this problem, our method seeks to minimize expected time of capture rather than guaranteeing capture. This allows us to examine the performance of our algorithm in complex and cluttered environments where guaranteed capture is difficult or impossible with limited pursuers. We present a probabilistic formulation of the problem, discretize the environment, and define cost heuristics for use in planning. We then propose a scalable algorithm using an entropy cost heuristic that searches possible movement paths to determine coordination strategies for the robotic pursuers. We present simulated results describing the performance of our algorithm against state of the art alternatives in a complex office environment. Our algorithm successfully reduces capture time with limited pursuers in an environment beyond the scope of many other approaches.

Keywords
multi-robot coordination, motion planning

Notes
Associated Center(s) / Consortia: Field Robotics Center
Associated Project(s): EMBER

Text Reference
Geoffrey Hollinger, Athanasios Kehagias, and Sanjiv Singh, "Probabilistic Strategies for Pursuit in Cluttered Environments with Multiple Robots," IEEE International Conference on Robotics and Automation, April, 2007.

BibTeX Reference
@inproceedings{Hollinger_2007_5744,
   author = "Geoffrey Hollinger and Athanasios Kehagias and Sanjiv Singh",
   title = "Probabilistic Strategies for Pursuit in Cluttered Environments with Multiple Robots",
   booktitle = "IEEE International Conference on Robotics and Automation",
   month = "April",
   year = "2007",
}