Skip to main content

Path Planning Strategy for Mobile Robot Navigation Using MANFIS Controller

  • Conference paper

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 247)

Abstract

Nowadays intelligent techniques such as fuzzy inference system (FIS), artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are mainly considered as effective and suitable methods for modeling an engineering system. The hallmark of this paper presents a new intelligent hybrid technique (Multiple Adaptive Neuro-Fuzzy Inference System) based on the combination of fuzzy inference system and artificial neural network for solving path planning problem of autonomous mobile robot. First we develop an adaptive fuzzy controller with four input parameters, two output parameters and five parameters each. Afterwards each adaptive fuzzy controller acts as a single takagi-sugeno type fuzzy inference system, where inputs are front obstacle distance (FOD), left obstacle distance (LOD), right obstacle distance (ROD) (from robot), Heading angle (HA) (angle to target) and output corresponds to the wheel velocities ( Left wheel and right wheel) of the mobile robot. The effectiveness, feasibility and robustness of the proposed navigational controller have been tested by means of simulation results. It has been observed that the proposed path planning strategy is capable of avoiding obstacles and effectively guiding the mobile robot moving from the start point to the desired target point with shortest path length.

Keywords

  • ANFIS
  • obstacle avoidance
  • mobile robot
  • path planning

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-3-319-02931-3_40
  • Chapter length: 9 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   219.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-02931-3
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   279.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Latombe, J.C.: Robot Motion Planning. Kluwer Academic Publishers, New York (1990)

    Google Scholar 

  2. Canny, J.E.: The Complexity of Robot Motion Planning. MIT Press, MA (1988)

    Google Scholar 

  3. Lozano-Perez, T.: A simple motion planning algorithm for general robot manipulators. IEEE Journal of Robotics and Automation 3, 224–238 (1987)

    CrossRef  Google Scholar 

  4. Leven, D., Sharir, M.: Planning a purely translational motion for a convex object in two dimensional space using generalized voronoi diagrams. Discrete & Computational Geometry 2, 9–31 (1987)

    MathSciNet  CrossRef  MATH  Google Scholar 

  5. Payton, D., Rosenblatt, J., Keirsey, D.: Grid-based mapping for autonomous mobile robot. Robotics and Autonomous Systems 11, 13–21 (1993)

    CrossRef  Google Scholar 

  6. Regli, L.: Robot Path Planning. Lectures Notes of Department of computer Science. Drexel University (2007)

    Google Scholar 

  7. Khatib, O.: Real time Obstacle Avoidance for manipulators and Mobile Robots. In: IEEE Conference on Robotics and Automation, vol. 2, pp. 505–505 (1985)

    Google Scholar 

  8. Jang, J.S.R.: ANFIS: Adaptive network-based fuzzy inference system. IEEE Transaction on System, Man and Cybernetics –Part b 23, 665–685 (1993)

    CrossRef  Google Scholar 

  9. Huq, R., Mann, G.K.I., Gosine, R.G.: Mobile robot navigation using motor schema and fuzzy content behavior modulation. Application of Soft Computing 8, 422–436 (2008)

    CrossRef  Google Scholar 

  10. Selekwa, M.F., Dunlap, D.D., Shi, D., CollinsJr, E.G.: Robot navigation in very cluttered environment by preference based fuzzy behaviors. Autonomous System 56, 231–246 (2007)

    CrossRef  Google Scholar 

  11. Abdessemed, F., Benmahammed, K., Monacelli, E.: A fuzzy based reactive controller for a non-holonomic mobile robot. Robotics Autonomous System 47, 31–46 (2004)

    CrossRef  Google Scholar 

  12. Pradhan, S.K., Parhi, D.R., Panda, A.K.: Fuzzy logic techniques for navigation of several mobile robots. Application of Soft Computing 9, 290–304 (2009)

    CrossRef  Google Scholar 

  13. Motlagh, O., Tang, S.H., Ismail, N.: Development of a new minimum avoidance system for behavior based mobile robot. Fuzzy Sets System 160, 1929–1946 (2009)

    CrossRef  Google Scholar 

  14. Velagic, J., Osmic, N., Lacevic, B.: Neural Network Controller for Mobile Robot Motion Control. World Academy of Science, Engineering and Technology 47, 193–198 (2008)

    Google Scholar 

  15. Singh, M.K., Parhi, D.R.: Intelligent Neuro-Controller for Navigation of Mobile Robot. In: Proceedings of the International Conference on Advances in Computing, Communication and Control, Mumbai, Maharashtra, India, pp. 123–128 (2009)

    Google Scholar 

  16. Castro, V., Neira, J.P., Rueda, C.L., Villamizar, J.C., Angel, L.: Autonomous Navigation Strategies for Mobile Robots using a Probabilistic Neural Network (PNN). In: 33rd Annual Conference of the IEEE Industrial Electronics Society, Taipei, Taiwan, pp. 2795–2800 (2007)

    Google Scholar 

  17. Pradhan, S.K., Parhi, D.R., Panda, A.K.: Neuro-fuzzy technique for navigation of multiple mobile robots. Fuzzy Optimum Decision Making 5, 255–288 (2006)

    CrossRef  MATH  Google Scholar 

  18. Nefti, S., Oussalah, M., Djouani, K., Pontnau, J.: Intelligent Adaptive Mobile Robot Navigation. Journal of Intelligent and Robotic Systems 30, 311–329 (2001)

    CrossRef  MATH  Google Scholar 

  19. Hui, N.B., Mahendar, V., Pratihar, D.K.: Time-optimal, collision-free navigation of a car-like mobile robot using neuro-fuzzy approaches. Fuzzy Sets and Systems 157, 2171–2204 (2008)

    MathSciNet  CrossRef  Google Scholar 

  20. Godjevac, J., Steele, N.: Neuro-fuzzy control of a mobile robot. Neuro Computing 28, 127–142 (1999)

    Google Scholar 

  21. The Math Works Company, Natick, MA, ANFIS Toolbox User’s Guide of MATLAB

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Prases Kumar Mohanty .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Mohanty, P.K., Parhi, D.R. (2014). Path Planning Strategy for Mobile Robot Navigation Using MANFIS Controller. In: Satapathy, S., Udgata, S., Biswal, B. (eds) Proceedings of the International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA) 2013. Advances in Intelligent Systems and Computing, vol 247. Springer, Cham. https://doi.org/10.1007/978-3-319-02931-3_40

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-02931-3_40

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-02930-6

  • Online ISBN: 978-3-319-02931-3

  • eBook Packages: EngineeringEngineering (R0)