A Sampling Based Algorithm for Multi-Robot Visibility-Based Pursuit-Evasion

Nicholas M. Stiffler, Jason M. O'Kane
In Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems 2014.

Abstract

We introduce a probabilistically complete algorithm for solving a visibility-based pursuit-evasion problem in two-dimensional polygonal environments with multiple pursuers. The input for our algorithm is an environment and the initial positions of the pursuers. The output is a joint strategy for the pursuers that guarantees that the evader has been captured. We create a Sample-Generated Pursuit-Evasion Graph (SG-PEG) that utilizes an abstract sample generator to search the pursuers' Joint Configuration Space for a pursuer solution strategy that captures the evaders, or reports that no such strategy exists under the current constraints. We ran our algorithm in simulation and provide results.

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BibTeX

@inproceedings{StiOKa14b,
  author       = {Nicholas M. Stiffler and Jason M. O'Kane},
  title        = {A Sampling Based Algorithm for Multi-Robot
		 Visibility-Based Pursuit-Evasion},
  year	       = {2014},
  booktitle    = {Proc. IEEE/RSJ International Conference on Intelligent
		 Robots and Systems}
}

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Wed Sep 20 09:19:46 EDT 2017