Autonomous Robots

, Volume 32, Issue 1, pp 81–95

Distributed pursuit-evasion without mapping or global localization via local frontiers

  • Joseph W. Durham
  • Antonio Franchi
  • Francesco Bullo
Article

DOI: 10.1007/s10514-011-9260-1

Cite this article as:
Durham, J.W., Franchi, A. & Bullo, F. Auton Robot (2012) 32: 81. doi:10.1007/s10514-011-9260-1

Abstract

This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.

Keywords

Pursuit-evasion Clearing Cooperative robotics Distributed algorithms Multi-robot coverage Surveillance Monitoring 

Supplementary material

Video of a simple illustrative simulation where three robots clear an environment using the proposed distributed clearing algorithm (MPG 3.46 MB)

Video of a hardware experiment in which three robots execute the distributed clearing algorithm. The video includes explanatory captions (MPG 12.3 MB)

Video of a simulation where six robots clear a complex environment modeled off of section of a hospital (MPG 12.5 MB)

10514_2011_9260_MOESM4_ESM.mpg (4.6 mb)
Video of a simulation where 12 robots expand to clear as much space as possible in an infinite empty environment using the proposed distributed clearing algorithm (MPG 4.64 MB)

Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Joseph W. Durham
    • 1
  • Antonio Franchi
    • 2
  • Francesco Bullo
    • 1
  1. 1.Department of Mechanical EngineeringUniversity of CaliforniaSanta BarbaraUSA
  2. 2.Dept. Human Perception Cognition and ActionMax Planck Institute for Biological CyberneticsTübingenGermany

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