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Multi-agent Trail Making for Stigmergic Navigation

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Advances in Artificial Intelligence (Canadian AI 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3060))

Abstract

Robotic agents in dynamic environments must sometimes navigate using only their local perceptions. In complex environments, features such as terrain undulation, geometrically complex barriers, and similar obstacles form local maxima and minima that can trap and hinder agents using reactive navigation. Moreover, agents navigating in a purely reactive fashion forget their past discoveries quickly. Preserving this knowledge usually requires that each agent construct a detailed world model as it explores or be forced to rediscover desired goals each time. Explicit communication can also be required to share discoveries and coordinate actions. The cost of explicit communication can be substantial, however, making it desirable to avoid its use in many domains. Accordingly, in this paper we present a method of cooperative trail making that allows a team of agents using reactive navigation to assist one another in their explorations through implicit (stigmergic) communication.

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References

  1. Balch, T., Arkin, R.C.: Communication in reactive multiagent robotic systems. Autonomous Robots 1, 27–52 (1994)

    Article  Google Scholar 

  2. Pirjanian, P.: Behavior coordination mechanisms: State-of-the-art. Technical Report IRIS-99-375, Institute for Robotics and Intelligent Systems, University of Southern California, Los Angeles (1999)

    Google Scholar 

  3. Sgorbissa, A., Arkin, R.C.: Local navigation strategies for a team of robots. Technical report, Georgia Tech Robotics Laboratory (2001)

    Google Scholar 

  4. Balch, T., Arkin, R.C.: Avoiding the past: A simple but effective strategy for reactive navigation. In: Proceedings of the 1993 IEEE International Conference on Robotics and Automation, Atlanta, Georgia, vol. 1, pp. 678–685 (1993)

    Google Scholar 

  5. Arkin, R.C., Balch, T.: Cooperative multiagent robotic systems. In: Bonasso, R., Murphy, R. (eds.) Artificial Intelligence and Mobile Robots, Cambridge, MA, MIT/AAAI Press (1998)

    Google Scholar 

  6. Moorman, K., Ram, A.: A case-based approach to reactive control for autonomous robots. In: AAAI Fall Symposium on AI for Real-World Autonomous Mobile Robots, Cambridge, MA (1992)

    Google Scholar 

  7. Holland, O., Melhuish, C.: Stigmergy, self-organisation, and sorting in collective robotics. Artificial Life 5 (2000)

    Google Scholar 

  8. Werger, B.B., Mataric, M.: Exploiting embodiment in multi-robot teams. Technical Report IRIS-99-378, University of Southern California, Institute for Robotics and Intelligent Systems (1999)

    Google Scholar 

  9. Parunak, H.V.D., Brueckner, S., Sauter, J., Posdamer, J.: Mechanisms and military applications for synthetic pheromones. In: Workshop on Autonomy Oriented Computation, Montreal, Canada (2001)

    Google Scholar 

  10. Werger, B.B., Mataric, M.: Robotic food chains: Externalization of state and program for minimal-agent foraging. In: Proceedings of the 4th International Conference on Simulation of Adaptive Behavior: From Animals to Animats 4, pp. 625–634. MIT Press, Cambridge (1996)

    Google Scholar 

  11. Vaughan, R., Stoy, K., Sukhatme, G., Mataric, M.: Lost: Localization-space trails for robot teams. IEEE Transactions on Robotics and Automation 18, 796–812 (2002)

    Article  Google Scholar 

  12. Sauter, J.A., Matthews, R., Parunak, H.V.D., Brueckner, S.: Evolving adaptive pheromone path planning mechanisms. In: Proceedings of the First International Joint Conference on Autonomous Agents and Multi-Agent Systems, Bologna, Italy, pp. 434–440. ACM Press, New York (2002)

    Chapter  Google Scholar 

  13. Brooks, R.: Cambrian Intelligence. MIT Press, Cambridge (1999)

    MATH  Google Scholar 

  14. Wurr, A.: Robotic team navigation in complex environments using stigmergic clues. Master’s thesis, Department of Computer Science, University of Manitoba, Winnipeg (2003)

    Google Scholar 

  15. Balch, T., Arkin, R.C.: Behavior-based formation control for multi-robot teams. IEEE Trans. On Robotics and Automation 14 (1998)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Wurr, A., Anderson, J. (2004). Multi-agent Trail Making for Stigmergic Navigation. In: Tawfik, A.Y., Goodwin, S.D. (eds) Advances in Artificial Intelligence. Canadian AI 2004. Lecture Notes in Computer Science(), vol 3060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24840-8_31

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  • DOI: https://doi.org/10.1007/978-3-540-24840-8_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22004-6

  • Online ISBN: 978-3-540-24840-8

  • eBook Packages: Springer Book Archive

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