Skip to main content

Swarming Behavior Using Probabilistic Roadmap Techniques

  • Conference paper
Swarm Robotics (SR 2004)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3342))

Included in the following conference series:

Abstract

While techniques exist for simulating swarming behaviors, these methods usually provide only simplistic navigation and planning capabilities. In this review, we explore the benefits of integrating roadmap-based path planning methods with flocking techniques to achieve different behaviors. We show how group behaviors such as exploring can be facilitated by using dynamic roadmaps (e.g., modifying edge weights) as an implicit means of communication between flock members. Extending ideas from cognitive modeling, we embed behavior rules in individual flock members and in the roadmap. These behavior rules enable the flock members to modify their actions based on their current location and state. We propose new techniques for several distinct group behaviors: homing, exploring (covering and goal searching), passing through narrow areas and shepherding. We present results that show that our methods provide significant improvement over methods that utilize purely local knowledge and moreover, that we achieve performance approaching that which could be obtained by an ideal method that has complete global knowledge. Animations of these behaviors can be viewed on our webpages.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Reynolds, C.W.: Flocks, herds, and schools: A distributed behavioral model. Computer Graphics, 25–34 (1987)

    Google Scholar 

  2. Reynolds, C.W.: Steering behaviors for autonomous characters. In: Game Developers Conference (1999)

    Google Scholar 

  3. Latombe, J.C.: Robot Motion Planning. Kluwer Academic Publishers, Boston (1991)

    Google Scholar 

  4. Bayazit, O.B., Lien, J.M., Amato, N.M.: Better flocking behaviors using rulebased roadmaps. In: Proc. Int. Workshop on Algorithmic Foundations of Robotics, WAFR (2002)

    Google Scholar 

  5. Bayazit, O.B., Lien, J.M., Amato, N.M.: Better group behaviors in complex environments using global roadmaps. Artif. Life (2002)

    Google Scholar 

  6. Bayazit, O.B., Lien, J.M., Amato, N.M.: Roadmap-based flocking for complex environments. In: Proc. Pacific Graphics, pp. 104–113 (2002)

    Google Scholar 

  7. Lien, J.M., Bayazit, O.B., Sowell, R.T.S., Rodrigues, L., Amato, N.M.: Shepherding behaviors. In: Proc. IEEE Int. Conf. Robot. Autom (ICRA), pp. 4159–4164 (2004)

    Google Scholar 

  8. Kavraki, L., Svestka, P., Latombe, J.C., Overmars, M.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. Automat. 12, 566–580 (1996)

    Article  Google Scholar 

  9. Amato, N.M., Bayazit, O.B., Dale, L.K., Jones, C.V., Vallejo, D.: OBPRM: Anobstacle-based PRM for 3D workspaces. In: Robotics: The Algorithmic Perspective, Natick, MA, A.K. Peters Proceedings of the Third Workshop on the Algorithmic Foundations of Robotics (WAFR), Houston, TX, pp. 155–168 (1998)

    Google Scholar 

  10. Hsu, D., Kindel, R., Latombe, J.C., Rock, S.: Randomized Kinodynamic Motion Planning with Moving Obstacles. In: Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR), pp. SA1–SA18 (2000)

    Google Scholar 

  11. Bohlin, R., Kavraki, L.E.: Path planning using Lazy PRM. In: Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 521–528 (2000)

    Google Scholar 

  12. Nielsen, C.L., Kavraki, L.E.: A two level fuzzy prm for manipulation planning. In: IEEE/RSJ International Conference on Intelligent Robotics and Systems (2000)

    Google Scholar 

  13. Song, G., Miller, S.L., Amato, N.M.: Customizing PRM roadmaps at query time. In: Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 1500–1505 (2001)

    Google Scholar 

  14. Bayazit, O.B., Song, G., Amato, N.M.: Enhancing randomized motion planners: Exploring with haptic hints. Autonomous Robots, Special Issue on Personal Robotics 10, 163–174 Preliminary version appeared in ICRA, pp. 529–536 (2001)

    Google Scholar 

  15. Witkin, A., Baraff, D.: Physically Based Modeling: Principles and Practice. SIGGRAPH 1997 Course Notes #19, SIGGRAPH-ACM publication (1997)

    Google Scholar 

  16. Khatib, O.: Real time obstacle avoidance for manipulators and mobile robots. Int. J. Robot. Res. 5, 90–98 (1986)

    Article  Google Scholar 

  17. Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 1st edn. Prentice Hall, Englewood Cliffs (1994)

    Google Scholar 

  18. Vaughan, R.T., Sumpter, N., Henderson, J., Frost, A., Cameron, S.: Experiments in automatic flock control. J. Robot. and Autonom. Sys. 31, 109–117 (2000)

    Article  Google Scholar 

  19. Tu, X., Terzopoulos, D.: Artificial fishes: Physics, locomotion, perception, behavior. In: Computer Graphics, pp. 24–29 (1994)

    Google Scholar 

  20. Nishimura, S., Ikegami, T.: Emergence of collective strategies in prey-predator game model. Artif. Life 3, 243–260 (1997)

    Article  Google Scholar 

  21. Ward, C., Gobet, F., Kendall, G.: Evolving collective behavior in an artificial ecology. Artif. Life 7, 191–209 (2001)

    Article  Google Scholar 

  22. Brogan, D.C., Hodgins, J.K.: Group behaviors for systems with significant dynamics. Autonomous Robots, 137–153 (1997)

    Google Scholar 

  23. Sun, S.J., Sim, D.W.L.K.B.: Artificial immune-based swarm behaviors of distributed autonomous robotic systems. In: Proc. IEEE Int. Conf. Robot. Autom (ICRA), pp. 3993–3998 (2001)

    Google Scholar 

  24. Balch, T., Hybinette, M.: Social potentials for scalable multirobot formations. In: Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pp. 73–80 (2000)

    Google Scholar 

  25. Fukuda, T., Mizoguchi, H., Sekiyama, K., Arai, F.: Group behavior control for MARS (micro autonomous robotic system). In: Proc. IEEE Int. Conf. Robot. Autom (ICRA), pp. 1550–1555 (1999)

    Google Scholar 

  26. Mataric, M.J.: Interaction and Intelligent Behavior. PhD thesis, MIT EECS (1994)

    Google Scholar 

  27. Saiwaki, N., Komatsu, T., Yoshida, T., Nishida, S.: Automatic generation of moving crowd using chaos model. In: IEEE Int. Conference on System, Man and Cybernetics, pp. 3715–3721 (1997)

    Google Scholar 

  28. Li, T.Y., Jeng, Y.J., Chang, S.I.: Simulating virtual human crowds with a leaderfollower model. In: Proceedings of 2001 Computer Animation Conference (2001)

    Google Scholar 

  29. Dorigo, M., Caro, G.D., Gambardella, L.M.: Ant algorithms for discrete optimization. Artificial Life 5, 137–172 (1999)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Bayazıt, O.B., Lien, JM., Amato, N.M. (2005). Swarming Behavior Using Probabilistic Roadmap Techniques. In: Şahin, E., Spears, W.M. (eds) Swarm Robotics. SR 2004. Lecture Notes in Computer Science, vol 3342. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30552-1_10

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30552-1_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24296-3

  • Online ISBN: 978-3-540-30552-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics