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Balancing the Information Gain Against the Movement Cost for Multi-robot Frontier Exploration

  • Arnoud Visser
  • Bayu A. Slamet
Part of the Springer Tracts in Advanced Robotics book series (STAR, volume 44)

Summary

This article investigates the scenario where a small team of robots needs to explore a hypothetical disaster site. The challenge faced by the robot-team is to coordinate their actions such that they efficiently explore the environment in their search for victims.

A popular paradigm for the exploration problem is based on the notion of frontiers: the boundaries of the current map from where robots can enter yet unexplored area. Coordinating multiple robots is then about intelligently assigning frontiers to robots. Typically, the assignment of a particular frontier to a particular robot is governed by a cost measure, e.g. the movement costs for the robot to reach the frontier. In more recent approaches these costs are traded off with the potential gain in information if the frontier would be explored by the robot.

In this paper we will further investigate the effect of balancing movement costs with information gains while assigning frontiers to robots. In our experiments we will illustrate how various choices for this balance can have a significant impact on the exploratory behavior exposed by the robot team.

Keywords

Mobile Robot Information Gain Multiple Robot Occupancy Grid Movement Cost 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Balakirsky, S., Scrapper, C., Carpin, S., Lewis, M.: Usarsim: providing a framework for multi-robot performance evaluation. In: Proceedings of PerMIS 2006, August 2006, pp. 98–103 (2006)Google Scholar
  2. 2.
    Balakirsky, S., Carpin, S., Kleiner, A., Lewis, M., Visser, A., Wang, J., Ziparo, V.A.: Towards heterogeneous robot teams for disaster mitigation: Results and performance metrics from robocup rescue. Journal of Field Robotics 24(11-12), 943–967 (2007)CrossRefGoogle Scholar
  3. 3.
    Burgard, W., Moors, M., Stachniss, C., Schneider, F.: Coordinated multi-robot exploration. IEEE Transactions on Robotics 21(3), 376–378 (2005)CrossRefGoogle Scholar
  4. 4.
    Choset, H., Lynch, K.M., Hutchinson, S., Kantor, G.A., Burgard, W., Kavraki, L.E., Thrun, S.: Principles of Robot Motion: Theory, Algorithms, and Implementations, June 2005. MIT Press, Cambridge (2005)zbMATHGoogle Scholar
  5. 5.
    Fox, D., Burgard, W., Thrun, S.: Active markov localization for mobile robots. Robotics and Autonomous Systems 25, 195–207 (1998)CrossRefGoogle Scholar
  6. 6.
    González-Baños, H.H., Latombe, J.-C.: Navigation Strategies for Exploring Indoor Environments. The International Journal of Robotics Research 21(10-11), 829–848 (2002)CrossRefGoogle Scholar
  7. 7.
    Jacoff, A., Messina, E., Weiss, B.A., Tadokoro, S., Nakagawa, Y.: Test arenas and performance metrics for urban search and rescue robots. In: Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (October 2003)Google Scholar
  8. 8.
    Moravec, H.: Sensor fusion in certainty grids for mobile robots. AI Magazine 9, 61–74 (1988)Google Scholar
  9. 9.
    Sim, R., Roy, N.: Global a-optimal robot exploration in slam. In: Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Barcelona, Spain (2005)Google Scholar
  10. 10.
    Simmons, R.G., Apfelbaum, D., Burgard, W., Fox, D., Moors, M., Thrun, S., Younes, H.: Coordination for multi-robot exploration and mapping. AAAI/IAAI, 852–858 (2000)Google Scholar
  11. 11.
    Slamet, B., Pfingsthorn, M.: ManifoldSLAM: a Multi-Agent Simultaneous Localization and Mapping System for the RoboCup Rescue Virtual Robots Competition. Master’s thesis, Universiteit van Amsterdam (December 2006)Google Scholar
  12. 12.
    Thrun, S., Burgard, W., Fox, D.: Probabilistic Robotics (Intelligent Robotics and Autonomous Agents), September 2005. MIT Press, Cambridge (2005)Google Scholar
  13. 13.
    Visser, A., Xingrui-Ji, v.I.M., Jaime, L.A.G.: Beyond frontier exploration. In: Proceedings of the 11th RoboCup International Symposium (July 2007)Google Scholar
  14. 14.
    Yamauchi, B.: Frontier-based exploration using multiple robots. In: AGENTS 1998: Proceedings of the second international conference on Autonomous agents, pp. 47–53. ACM Press, New York (1998)CrossRefGoogle Scholar
  15. 15.
    Zlot, R., Stentz, A., Dias, M., Thayer, S.: Multi-robot exploration controlled by a market economy. In: Proceedings of the IEEE International Conference on Robotics and Automation (2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Arnoud Visser
    • 1
  • Bayu A. Slamet
    • 1
  1. 1.Intelligent Systems Laboratorium AmsterdamUniversiteit van Amsterdam (UvA)AmsterdamThe Netherlands

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