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Stigmergic Navigation for Multi-Agent Teams in Complex Environments

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Stigmergic Optimization

Part of the book series: Studies in Computational Intelligence ((SCI,volume 31))

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References

  1. Nehmzow U, Gelder D, Duckett T (2000) Automatic selection of landmarks for mobile robot navigation. Technical report UMCS-00-7-1, Department of Computer Science, University of Manchester

    Google Scholar 

  2. Baltes J, Anderson J (2003) Flexible binary space partitioning for robotic rescue. In: Proceedings of the IEEE international conference on intelligent robots and systems, Volume 3. Las Vegas, pp. 3144-3149

    Google Scholar 

  3. Reece, D, Kraus M (2000) Tactical movement planning for individual combatants. In: Proceedings of the 9th conference on computer generated forces and behavioral representation. Orlando, FL

    Google Scholar 

  4. Verth J, Brueggeman V, Owen J, McMurry P (2000) Formation-based pathfinding with real-world vehicles. In: Proceedings of the game developers conference. CMP Game Group, San Jose, CA

    Google Scholar 

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

    Google Scholar 

  6. Brooks R (1991): The role of learning in autonomous robots. In: Proceedings of the 4th annual workshop on computational learning theory. Santa Cruz, CA, pp. 5-10

    Google Scholar 

  7. Balch T, Arkin R (1993) Avoiding the past: A simple but effective strategy for reactive navigation. In: Proceedings of the IEEE international conference on robotics and automation, Volume 1. Atlanta, GA, pp. 678-685

    Google Scholar 

  8. Fu D, Hammond K, Swain M (1996) Navigation for everyday life. Technical Report TR-96-03, Department of Computer Science, University of Chicago

    Google Scholar 

  9. Sgorbissa A, Arkin R (2001) Local navigation strategies for a team of robots. Technical report, Georgia Tech Robotics Laboratory, Georgia Institute of Technology

    Google Scholar 

  10. Mataric M (1997) Behavior-based control: Examples from navigation, learning and group behavior. Journal of Exp and Theor AI 9:323-336

    Article  Google Scholar 

  11. Brooks R (1991) Intelligence without reason. In: Mylopoulous J, Reiter R(eds) Proceedings of the 12th international joint conference on artificial intelligence. Sydney, Australia, pp. 569-595

    Google Scholar 

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

    Article  Google Scholar 

  13. Baltes J, Anderson J (2002) A pragmatic approach to robot rescue: The keystone fire brigade. In: Smart W, Balch T, Yanco H (eds) Proceedings of the AAAI mobile robot competition. Edmonton, Canada, pp. 38-43

    Google Scholar 

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

    Google Scholar 

  15. Groner T, Anderson J (2001) Efficient multi-robot localization and navigation through passive cooperation. In: Proceedings of the 2001 international conference on artificial intelligence. Las Vegas, pp. 84-89.

    Google Scholar 

  16. Arkin R (1998) Behavior-based robotics. MIT Press, Cambridge, MA

    Google Scholar 

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

    Google Scholar 

  18. Balch T, Arkin R (1995) Motor schema-based formation control for multiagent robot teams. In: Lesser V, Gasser L (eds) Proceedings of the 1st international conference on multiagent systems. AAAI Press, Menlo Park, CA, pp. 10-16

    Google Scholar 

  19. Moorman K, Ram A (1992) A case-based approach to reactive control for autonomous robots. In: Proceedings of the AAAI fall symposium on ai for real-world autonomous mobile robots. AAAI Press, Menlo Park, CA

    Google Scholar 

  20. Balch T, Arkin R (1997) Clay: Integrating motor schemas and reinforcement learning. Technical report, College of Computing, Georgia Institute of Technology

    Google Scholar 

  21. Arkin R., Balch T (1997) Aura: Principles and practice in review. Journal of Exp and Theor AI 9:175-189

    Article  Google Scholar 

  22. Brooks R (1986) A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation RA2:14-23

    MathSciNet  Google Scholar 

  23. Holland O, Melhuish C (1999) Stigmergy, self-organisation, and sorting in collective robotics. Artificial Life 5:173-202

    Article  Google Scholar 

  24. Perez-Uribe A, Hirsbrunner B (2000) Learning and foraging in robot-bees. In: SAB2000 proceedings supplement. International Society for Adaptive Behavior. Honolulu, HI, pp. 185-194

    Google Scholar 

  25. Parunak H, Brueckner S, Sauter J, Posdamer J(2001) Mechanisms and military applications for synthetic pheromones. In: Proceedings of the workshop on autonomy oriented computation. Montreal, Canada

    Google Scholar 

  26. Werger B, Mataric M (1996) Robotic food chains: Externalization of state and program for minimal-agent foraging. In: Proceedings of the 4th international conference on the simulation of adaptive behavior: From animals to animats 4. MIT Press, Cambridge, MA, pp. 625-634

    Google Scholar 

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

    Article  Google Scholar 

  28. Sauter J, Matthews R, Parunak H, Brueckner S (2002) Evolving adaptive pheromone path planning mechanisms. In: Proceedings of the 1st international joint conference on autonomous agents and multi-agent systems. Bologna, Italy, pp. 434-440

    Google Scholar 

  29. Kube C, Bonabeau E (2000) Cooperative transport by ants and robots. Int Journal of Robotics and Autonomous Systems 30:85-101

    Article  Google Scholar 

  30. Kube C, Zhang H (1994) Stagnation recovery behaviors for collective robotics. In: Proceedings of the IEEE international conference on intelligent robots and systems. Munich, pp. 1883-1890

    Google Scholar 

  31. Rumeliotis S, Pirjanian P, Mataric M(2000) Ant-inspired navigation in unknown environments. In: Sierra C, Gini M, Rosenschein J(eds) Proceedings of the4th international conference on autonomous agents. Barcelona, pp. 25-26

    Google Scholar 

  32. Howard A, Mataric M, Sukhatme G (2002) Localization for mobile robot teams using maximum likelihood estimation. In: Proceedings of the IEEE international conference on intelligent robots and systems. Lausanne, Switzerland, pp. 434-459

    Google Scholar 

  33. Arkin R, Balch T (1998) Cooperative multiagent robotic systems. In: Bonasso R, Murphy R (eds) Artificial intelligence and mobile robots. MIT/AAAI Press, Cambridge, MA

    Google Scholar 

  34. Balch T, Arkin R (1998) Behavior-based formation control for multi-robot teams. IEEE Trans on Robotics and Automation 14:926-939

    Article  Google Scholar 

  35. Kuwana Y, Nagasawa S, Shimoyama I, Kanzaki R (1999) Synthesis of silkworm moth’s pheromone-oriented behavior by a mobile robot with moth’s antennae as pheromone sensors. Biosensors and Bioelectronics 14:195-202

    Article  Google Scholar 

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Authors and Affiliations

  1. Autonomous Agents Laboratory, University of Manitoba, R3T2N2, Winnipeg Manitoba, Canada

    Wurr Alfred & Anderson John

Authors
  1. Wurr Alfred
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  2. Anderson John
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© 2006 Springer

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Alfred, W., John, A. (2006). Stigmergic Navigation for Multi-Agent Teams in Complex Environments. In: Stigmergic Optimization. Studies in Computational Intelligence, vol 31. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34690-6_4

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  • DOI: https://doi.org/10.1007/978-3-540-34690-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34689-0

  • Online ISBN: 978-3-540-34690-6

  • eBook Packages: EngineeringEngineering (R0)

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