Skip to main content
SpringerLink
Log in

New Potential Functions with Random Force Algorithms Using Potential Field Method

  • Published:
Journal of Intelligent & Robotic Systems Aims and scope Submit manuscript

Abstract

Autonomous mobile robot path planning is a common topic for robotics and computational geometry. Many important results have been found, but a lot of issues are still veiled. This paper first describes new problem of symmetrically aligned robot-obstacle-goal (SAROG) when using potential field methods for mobile robot path planning. In addition, we consider constant robot speed for practical use. The SAROG and the constant speed involve two potential risks: robot-obstacle collision and local minima trap. For dealing with the two potential risks, we analyze the conditions of the collision and the local minima trap, and propose new potential functions and random force based algorithms. For the algorithm verification, we use WiRobot X80 with three ultrasonic range sensor modules.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Dudek, G., Jenkin, M.: Computational Principles of Mobile Robotics. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  2. Veelaert, P., Bogaerts, W.: Ultrasonic Potential Field Sensor for Obstacle Avoidance. IEEE Trans. Robot. Autom. 15, 774–779 (1999)

    Article  Google Scholar 

  3. Damas, B., Lima, P., Custodio, L.: a modified potential fields method for robot navigation applied to dribbling in robotic soccer. In: Proceddings of RoboCup 2002 Symposium. Fukuoka, Japan (2002)

  4. Latombe, J.: Robot Motion Planning. Kluwer, Norwell (1991)

    Book  Google Scholar 

  5. Tilove, R.: Local obstacle avoidance for mobile robots based on the method of artificial potentials. In: Proceedings of the IEEE Conference on Robotics and Automation, pp. 566–571. Cincinnati, Ohio (1990)

  6. Chengqing, L., Ang, M.H., Krishnan, H., Yong, L.S.: Virtual obstacle concept for local-minimum-recovery in potential-field based navigation. In: Proceedings of the IEEE Conference on Robotics and Automation, pp. 983–988. San Francisco, CA (2000)

  7. Koren, Y., Borenstein, J.: Potential field methods and their inherent limitations for mobile robot navigation. In: Proceedings of the IEEE Confernce on Robotics and Automation, pp. 1398–1404. Sacramento, California (1991)

  8. Ge, S., Cui, Y.: Dynamic motion planning for mobile robots using potential field method. Auton. Robots 13, 207–222 (2002)

    Article  MATH  Google Scholar 

  9. Ge, S., Cui, Y.: New potential functions for mobile robot path planning. IEEE Trans. Robot. Autom. 16(5), 615–620

  10. Connolly, C., Burns, J., Weiss, R.: Path planning using Lapace’s equation. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2102–2106 (1990)

    Chapter  Google Scholar 

  11. Rimon, E., Koditscheck, D.: Exact robot navigation using artificial potential functions. IEEE Trans. Robot. Autom. 8(5), 501–518 (1992)

    Article  Google Scholar 

  12. Singh, L., Wen, J., Stephanou, H.: Real-time robot motion control with circulatory fields. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 2737–2742 (1996)

  13. Ren, J., McIsaac, K.A., Patel, R.V.: Modified Newton’s method applied to potential field-based navigation for mobile robots. IEEE Trans. Robot. 22(2), 384–390 (2006)

    Article  Google Scholar 

  14. Chang, H.: A new technique to handle local minimum for imperfect potential field based motion planning. In: Proceedings of the IEEE International Conference on Robotics and Automation, pp. 108–112 (1996)

  15. Caselli, S., Reggiani, M., Rocchi, R.: Heuristic methods for randomized path planning in potential fields. In: Proceedings of the IEEE International Symposium on Computational Intelligence in Robotics and Automation, pp. 426–431 (2001)

  16. Barraquand, J., Latombe, J.C.: Robot motion planning: a distributed representation approach. Int. J. Rob. Res. 10(6), 628–649 (1991)

    Article  Google Scholar 

  17. Barraquand, J., Langlois, B., Latombe, J.C.: Numerical potential field techniques for robot path planning. IEEE Trans. Syst. Man Cybern. 22(2), 224–241 (1992)

    Article  MathSciNet  Google Scholar 

  18. Ordonez, C., Collins, E.G., Selekwa, M.F., Dunlap, D.D.: The virtual wall approach to limit cycle avoidance for unmanned ground vehicles. In: Robot. Auton. Syst. (Elsevier) 56, 645–657 (2008)

  19. Olunloyo, V.O.S., Ayomoh, M.K.O. Autonomous mobile robot navigation using hybrid virtual force field concept. Eur. J. Sci. Res. 31(2), 204–228 (2009)

    Google Scholar 

  20. http://www.pages.drexel.edu/~weg22/ER1.html

  21. Borenstein, J., Koren, Y.: Real-time obstacle avoidance for fast mobile robots. IEEE Trans. Syst. Man Cybern. 19, 1179–1187 (1989)

    Article  Google Scholar 

  22. Chuang, J.H., Ahuja, N.: An analytically tractable potential field model of free space and its application in obstacle avoidance. IEEE Trans. Syst. Man Cybern. B 28, 729–736 (1998)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Worcester Polytechnic Institute, Worcester, MA, 01609, USA

    Jinseok Lee

  2. Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, 11794-2350, USA

    Yunyoung Nam & Sangjin Hong

  3. Department of Electrical and Computer Engineering, Ajou University, Suwon, 443-749, Korea

    Weduke Cho

Authors
  1. Jinseok Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yunyoung Nam
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sangjin Hong
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Weduke Cho
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sangjin Hong.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Lee, J., Nam, Y., Hong, S. et al. New Potential Functions with Random Force Algorithms Using Potential Field Method. J Intell Robot Syst 66, 303–319 (2012). https://doi.org/10.1007/s10846-011-9595-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10846-011-9595-z

Keywords

Search

Navigation