Robot Navigation Based on Fuzzy Behavior Controller

  • Hongshan Yu
  • Jiang Zhu
  • Yaonan Wang
  • Miao Hu
  • Yuan Zhang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7368)


This paper presents a robot navigation method based on fuzzy inference and behavior control. Stroll, Avoiding, Goal-reaching, Escape and Correct behavior are defined for robot navigation. The detailed scheme for each behavior is described in detail. Furthermore, fuzzy rules are used to switch those behaviors for best robot performances in real time. Experiments about five navigation tasks in two different environments were conducted on pioneer 2-DXE mobile robot. Experiment results shows that the proposed method is robust and efficiency in different environments.


robot navigation behavior control fuzzy control 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Lee, D.: Quantitative Evaluation of the Exploration Strategies of a Mobile Robot: [PhD thesis]. University College London, UK (1997)Google Scholar
  2. 2.
    Mataric, M.J.: Integration of representation into goal-driven behaviour-based robots. IEEE Transactions on Robotics and Automation 8(3), 304–312 (1992)CrossRefGoogle Scholar
  3. 3.
    Nehmzow, U., Owen, C.: Robot navigation in the real world: Experiments with Manchester’s Forty-Two in unmodified, large environments. Robotics and Autonomous Systems (33), 223–242 (2000)CrossRefGoogle Scholar
  4. 4.
    Song, K.-T., Sheen, L.-H.: Heuristic fuzzy-neuro network and its application to reactive navigation of a mobile robot. Fuzzy Sets and Systems 110, 331–340 (2000)CrossRefGoogle Scholar
  5. 5.
    Ip, Y.L., Rad, A.B., Wong, Y.K.: Autonomous exploration and mapping in an unknown enviroments. In: Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, pp. 4194–4199 (2004)Google Scholar
  6. 6.
    Zurada, J., Wright, A.L., Graham, J.H.: A Neuro-Fuzzy Approach for Robot System Safety. IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews 31(1), 49–64 (2001)CrossRefGoogle Scholar
  7. 7.
    Zalama, E., Gómez, J., Paul, M., Perán, J.R.: Adaptive Behavior Navigation of a Mobile Robot. IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans 32(1), 160–169 (2002)CrossRefGoogle Scholar
  8. 8.
    Lee, T.-L., Wu, C.-J.: Fuzzy motion planning of mobile robots in unknown environments. Journal of Intelligent and Robotic Systems 37, 177–191 (2003)CrossRefGoogle Scholar
  9. 9.
    Xu, W.L., Tso, S.K.: Sensor-Based Fuzzy Reactive Navigation of a Mobile Robot through Local Target Switching. IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews 29(3), 451–459 (1999)CrossRefGoogle Scholar
  10. 10.
    Marichal, G.N., Acosta, L., Moreno, L., Mendez, J.A., Rodrigo, J.J., Sigut, M.: Obstacle avoidance for a mobile robot: A neuro-fuzzy approach. Fuzzy Sets and Systems 124, 171–179 (2001)MathSciNetzbMATHCrossRefGoogle Scholar
  11. 11.
    Hagras, H., Callaghan, V., Colley, M.: Learning and adaptation of an intelligent mobile robot navigator operating in unstructured environment based on a novel online Fuzzy-Genetic system. Fuzzy Sets and Systems 141, 107–160 (2004)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Hoffmann, F.: Soft computing techniques for the design of mobile robot behaviors. Information Sciences 122, 241–258 (2000)zbMATHCrossRefGoogle Scholar
  13. 13.
    Borenstein, J., Koren, Y.: Real-time obstacle avoidance for fast mobile robots. IEEE Transactions on Systems, Man, and Cybernetics 19(5), 1179–1187 (1989)CrossRefGoogle Scholar
  14. 14.
    Borenstein, J., Koren, Y.: The vector field histogram – fast obstacle avoidance for mobile robots. IEEE Journal of Robotics and Automation 7(3), 278–288 (1991)CrossRefGoogle Scholar
  15. 15.
    Ulrich, Borenstein, J.: VFH+: reliable obstacle avoidance for fast mobile robots. In: Proceedings of the IEEE International Conference on Robotics and Automation, Leuven, Belgium, pp. 1572–1577 (1998)Google Scholar
  16. 16.
    Abdessemed, F., Benmahammed, K., Monacelli, E.: A fuzzy-based reactive controller for a non-holonomic mobile robot. Robotics and Autonomous Systems 47, 31–46 (2004)CrossRefGoogle Scholar
  17. 17.
    Xu, F., Van Brussel, H., Nuttin, M., Moreas, R.: Concepts for dynamic obstacle avoidance and their extended application in underground navigation. Robotics and Autonomous Systems 42, 1–15 (2003)zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Hongshan Yu
    • 1
  • Jiang Zhu
    • 2
  • Yaonan Wang
    • 1
  • Miao Hu
    • 1
  • Yuan Zhang
    • 1
  1. 1.College of Electrical and Information EngineeringHunan UniversityChangshaChina
  2. 2.School of Information EngineeringXiangtan UniversityXiangtanChina

Personalised recommendations