On a stochastic robotic surveillance problem

Kunal Srivastava, Dušan M. Stipanović, Mark W. Spong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a Markov Chain Monte Carlo (MCMC) based stochastic strategy for a robotic surveillance problem. We justify the use of stochastic strategies by showing that deterministic strategies have inherent limitations which make them unsuitable for the posed problem. We also consider the problem of surveillance with multiple agents in both centralized and decentralized setting. The centralized setting suffers from the problem of explosion in the number of states. We show that by incorporating permutation symmetry we can effectively reduce the size of the problem. For the decentralized case we show the issue of conflict resolution among the agents can be cast in the framework of finding a maximum weighted matching in a bipartite graph. We then provide a distributed implementation of the auction algorithm based on message passing which solves the conflict resolution problem.

Original languageEnglish (US)
Title of host publicationProceedings of the 48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Pages8567-8574
Number of pages8
DOIs
StatePublished - Dec 1 2009
Event48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009 - Shanghai, China
Duration: Dec 15 2009Dec 18 2009

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216

Other

Other48th IEEE Conference on Decision and Control held jointly with 2009 28th Chinese Control Conference, CDC/CCC 2009
Country/TerritoryChina
CityShanghai
Period12/15/0912/18/09

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization

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