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.

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


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