Motion Planning of Self-reconfigurable Modular Robots Using Rapidly Exploring Random Trees

  • Vojtěch Vonásek
  • Karel Košnar
  • Libor Přeučil
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7429)

Abstract

Motion planning of self-reconfigurable robots in an environment is a challenging task. In this paper, we propose a sampling-based motion planning approach to plan locomotion of an organism with many degrees of freedom. The proposed approach is based on the Rapidly Exploring Random tree algorithm, which uses physical simulation to explore the configuration space of the highly articulated robots. Due to large number of actuators in such organisms, a novel randomized strategy for generating input signals is proposed. We demonstrate the performance of the proposed planner on a set of complex robots moving on a plane as well as on a rough surface.

Keywords

self-reconfigurable robots motion planning RRT 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    ODE — Open Dynamics Engine, http://www.ode.org/
  2. 2.
    Butler, Z., Fitch, R., Rus, D.: Experiments in distributed locomotion with a unit-compressible modular robot. In: Intelligent Robots and Systems, vol. 3 (2002)Google Scholar
  3. 3.
    Erkmen, I., Erkmen, A.M., Matsuno, F., Chatterjee, R., Kamegawa, T.: Snake robots to the rescue? IEEE Robotics Automation Magazine 9(3), 17–25 (2002)CrossRefGoogle Scholar
  4. 4.
    Gayle, R., Redon, S., Sud, A., Lin, M.C., Manocha, D.: Efficient motion planning of highly articulated chains using physics-based sampling. In: ICRA 2007 (2007)Google Scholar
  5. 5.
    Guibas, L.J., Holleman, C., Kavraki, L.E.: A probabilistic roadmap planner for flexible objects with a workspace medial-axis-based sampling approach. In: IROS 1999 (1999)Google Scholar
  6. 6.
    Jan Ijspeert, A.: Central pattern generators for locomotion control in animals and robots: A review. Neural Networks 21(4), 642–653 (2008)CrossRefGoogle Scholar
  7. 7.
    Stoy, K., Shen, W.-M., Will, P.M.: A simple approach to the control of locomotion in self-reconfigurable robots. Robotics and Autonomous Systems 44(3) (2003)Google Scholar
  8. 8.
    Kalisiak, M., van de Panne, M.: RRT-blossom: RRT with a local flood-fill behavior. In: IEEE International Conference on Robotics and Automation (2006)Google Scholar
  9. 9.
    Kavraki, L.E., Svestka, P., Latombe, J.-C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation 12(4), 566–580 (1996)CrossRefGoogle Scholar
  10. 10.
    Kavraki, L.E., Svestka, P., Latombe, J.C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation 12, 566–580 (1996)CrossRefGoogle Scholar
  11. 11.
    Kotay, K.D., Rus, D.L.: Motion synthesis for the self-reconfiguring molecule. In: Proceedings, 1998 IEEE/RSJ International Conference on Intelligent Robots and Systems, vol. 2, pp. 843–851 (October 1998)Google Scholar
  12. 12.
    Kuffner, J.J., LaValle, S.M.: RRT-Connect: An efficient approach to single-query path planning. In: IEEE International Conference on Robotics and Automation, pp. 995–1001 (2000)Google Scholar
  13. 13.
    Lau, H.Y.K., Ko, A., Lau, T.L.: A decentralized control framework for modular robots. In: IROS (2004)Google Scholar
  14. 14.
    LaValle, S.M.: Rapidly-exploring random trees: A new tool for path planning. TR 98-11 (1998)Google Scholar
  15. 15.
    LaValle, S.M., Yakey, J.H., Kavraki, L.E.: A probabilistic roadmap approach for systems with closed kinematic chains. In: ICRA 1999 (1999)Google Scholar
  16. 16.
    Levi, P., Kernbach, S. (eds.): Symbiotic Multi-Robot Organisms: Reliability, Adaptability, Evolution. Springer (2010)Google Scholar
  17. 17.
    Lindemann, S.R., LaValle, S.M.: Incrementally reducing dispersion by increasing voronoi bias in RRTs. In: IEEE International Conference on Robotics and Automation, vol. 4, pp. 3251–3257 (April 2004)Google Scholar
  18. 18.
    Lindemann, S.R., LaValle, S.M.: Steps toward derandomizing RRTs. In: IEEE Fourth International Workshop on Robot Motion and Control (2004)Google Scholar
  19. 19.
    Salemi, B., Shen, W.-M., Will, P.: Hormone-controlled metamorphic robots, pp. 4194–4199 (2001)Google Scholar
  20. 20.
    Shen, W.-M., Lu, Y., Will, P.: Hormone-based control for self-reconfigurable robots. In: Proceedings of the Fourth International Conference on Autonomous Agents, AGENTS 2000, pp. 1–8. ACM, New York (2000)CrossRefGoogle Scholar
  21. 21.
    Strandberg, M.: Augmenting RRT-planners with local trees. In: IEEE International Conference on Robotics and Automation, vol. 4 (April 2004)Google Scholar
  22. 22.
    Yershova, A., Jaillet, L., Simeon, T., LaValle, S.M.: Dynamic-domain RRTs: Efficient exploration by controlling the sampling domain. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, pp. 3856–3861 (April 2005)Google Scholar
  23. 23.
    Yershova, A., LaValle, S.M.: Improving motion-planning algorithms by efficient nearest-neighbor searching. IEEE Transactions on Robotics 23(1), 151–157 (2007), http://msl.cs.uiuc.edu/~yershova/MPNN/MPNN.htm CrossRefGoogle Scholar
  24. 24.
    Yim, M., Duff, D.G., Roufas, K.D.: Polybot: a modular reconfigurable robot. In: Proceedings. IEEE International Conference on Robotics and Automation, ICRA 2000, vol. 1, pp. 514–520 (2000)Google Scholar
  25. 25.
    Yim, M.: Locomotion with a unit-modular reconfigurable robot. TR (1994)Google Scholar
  26. 26.
    Yoshida, E., Matura, S., Kamimura, A., Tomita, K., Kurokawa, H., Kokaji, S.: A self-reconfigurable modular robot: Reconfiguration planning and experiments. The International Journal of Robotics Research 21(10-11), 903–915 (2002)CrossRefGoogle Scholar
  27. 27.
    Zhang, L., Manocha, D.: An efficient retraction-based RRT planner. In: IEEE International Conference on Robotics and Automation, pp. 3743–3750, 19-23 (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Vojtěch Vonásek
    • 1
  • Karel Košnar
    • 1
  • Libor Přeučil
    • 1
  1. 1.Faculty of Electrical Engineering, Dept. of cyberneticsCzech Technical University in PragueCzech Republic

Personalised recommendations