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Principled Communication for Dynamic Multi-Robot Task Allocation

  • Brian P. Gerkey
  • Maja J Matarić
Conference paper
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 271)

Abstract

In the pursuit of an efficient cooperative multi-robot system, the researcher must eventually answer the question “how should robots communicate?”; a natural way to attack this question is to decompose it into three simpler corollaries: “what should robots communicate?”, “when should they communicate?” and “with whom should they communicate?”. In this paper, we propose answers to these questions in the form of a general framework for inter-robot communication and, more specifically, advocate its use in dynamic task allocation for teams of cooperative mobile robots. We base our communication model on publish/subscribe messaging and validate our system by using it in a tightly-coupled multi-robot manipulaion task and a loosely-coupled long-term experiment involving many robots concurrently executing different tasks.

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References

  1. [1]
    David L. Martin, Adam J. Cheyer, and Douglas B. Moran. The open agent architecture: A framework for building distributed software system. Applied Artificial Intelligence, 13(1):91–128, Jan–Mar 1999.CrossRefGoogle Scholar
  2. [2]
    Katia Sycara, Keith Decker, Anandeep Pannu, Mike Williamson, and Dajun Zeng. Distributed intelligent agents. IEEE Expert, 11(6):36–46, December 1996.CrossRefGoogle Scholar
  3. [3]
    Milind Tambe. Agent architectures for flexible, practical teamwork. In Proceedings of the Natl. Conf. on Artificial Intelligence (AAAI), Providence, Rhode Island, July 1997.Google Scholar
  4. [4]
    Lynne E. Parker. Alliance: An architecture for fault-tolerant multi-robot cooperation. IEEE Transactions on Robotics and Automation, 14(2), 1998.Google Scholar
  5. [5]
    Barry Brian Werger and Maja J Matarić. Broadcast of local eligibilty for multi-target observation. In Proceedings of the Intl. Symp. on Distributed Autonomous Robotic Systems (DARS), Knoxville, Tennessee, October 2000.Google Scholar
  6. [6]
    Daniel D. Corkill. Blackboard systems. AI Expert, 6(9):40–47, September 1991.Google Scholar
  7. [7]
    William E. Walsh and Michael P. Wellman. A market protocol for decentralized task allocation. In Proceedings of the Intl. Conf. on Multi Agent Systems (ICMAS), Paris, Prance, July 1998.Google Scholar
  8. [8]
    Steven McCanne. Scalable multimedia communication with internet multicast, light-weight sessions, and the mbone. Technical Report CSD 981002, UC Berkeley, March 1998.Google Scholar
  9. [9]
    Arvola Chan. Transactional publish/subscribe: The proactive multicast of database changes. In Proceedings of ACM SIGMOD Conf. of Management of Data, Seattle, WA, June 1998.Google Scholar
  10. [10]
    Guruduth Banavar et al. An efficient multicast protocol for content-based publish-subscribe systems. In Proceedings of the Intl. Conf. on Distributed Computing Systems, Austin, Texas, June 1999.Google Scholar
  11. [11]
    Marcos K. Aguilera et al. Matching events in a content-based subscription system. In Proceedings of the ACM Symposium on Principles of Distributed Computing, Atlanta, Georgia, May 1999.Google Scholar
  12. [12]
    Kutluhan Erol, James Hendler, and Dana S. Nau. HTN planning: Complexity and expressivity. In Proceedings of the Natl. Conf. on Artificial Intelligence (AAAI), Seattle, WA, July 1994.Google Scholar
  13. [13]
    Kutluhan Erol, James Hendler, and Dana S. Nau. UCMP: A sound and complete procedure for hierarchical task-network planning. In Proceedings of the Intl. Conf. on Artificial Intelligence Planning Systems, Chicago, IL, June 1994.Google Scholar
  14. [14]
    Maja J Matarić. Behavior-based control: Examples from navigation, learning, and group behavior. Journal of Experimental and Theoretical Artifical Intelligence, 9(2–3):323–336, 1997.CrossRefGoogle Scholar
  15. [15]
    Ronald C. Arkin. Behavior-Based Robotics. MIT Press, Cambridge, MA, 1998.Google Scholar
  16. [16]
    Brian P. Gerkey, Kasper Støy, and Richard T. Vaughan. Player robot server. Technical Report IRIS-00-392, Institute for Robotics and Intelligent Systems, School of Engineering, University of Southern California, November 2000.Google Scholar
  17. [17]
    Bruce Donald, Jim Jennings, and Daniela Rus. Information invariants for distributed manipulation. The Intl. Journal of Robotics Research, 16(5):673–702, October 1997.CrossRefGoogle Scholar
  18. [18]
    Bruce Donald, Jim Jennings, and Daniela Rus. Minimalism + distribution = supermodularity. Journal of Experimental and Theoretical Artifical Intelligence, 9(2–3):293–321, 1997.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Brian P. Gerkey
    • 1
  • Maja J Matarić
    • 1
  1. 1.Robotics Research LabsUniversity of Southern CaliforniaLos AngelesUSA

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