Advertisement

Analysis of Mobile Robot Path Planning with Artificial Potential Fields

  • Hamzah AhmadEmail author
  • Ahmad Nuur Fakhrullah Mohamad Pajeri
  • Nur Aqilah Othman
  • Mohd Mawardi Saari
  • Mohd Syakirin Ramli
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 538)

Abstract

This paper presents an analysis of a mobile robot path planning using potential field technique. The mobile robot has four wheels which can be driven and steered independently. For simplicity, this paper assumes Ackermann steering such that the vehicle can be modelled as a two-wheel system for path planning purposes. The potential field method which emphasizes on attractive potential and repulsive potential fields for path planning are proposed for analysis. For simulation settings, the mobile robot priorly does not pose any information on the environment and then moves until it reaches its goal using the calculated attractive and repulsive potential fields. The control gains which represents the attractive and repulsive force are studied to determine the effectiveness of the proposed method. Based on the simulation results, the robot is able to avoid obstacle and at the same time successfully arrived at the goal. Different cases of the potential fields and landmarks positions are also presented to determine the effectiveness of the technique.

Keywords

Mobile robot Path planning Potential field 

Notes

Acknowledgements

The authors would like to thank Ministry of Higher Education and Universiti Malaysia Pahang for supporting this research under RDU160145 and RDU160379.

References

  1. 1.
    Japan Robot Association. Summary report on technology strategy for creating a robot society in the 21st century. Japan. May 2001Google Scholar
  2. 2.
    Borenstein, J., Koren, Y.: Real-time obstacle avoidance for fast mobile robots. IEEE Trans. Syst. Man, Cybern. 19(5), 1179–1187 (1989)CrossRefGoogle Scholar
  3. 3.
    Borenstein, J., Koren, Y.: The vector field histogram-fast obstacle avoidance for mobile robots. IEEE Trans. Robot. Autom. 7(3), 278–288 (1991)CrossRefGoogle Scholar
  4. 4.
    Latombe, J.: Robot Motion Planning. Kluwer, Norwell, MK (1991)CrossRefGoogle Scholar
  5. 5.
    Zahra, E., Mehmet O.E.: Multi-objective grasshopper optimization algorithm for robot path planning in static environments. In: 2018 IEEE International Conference on Industrial Technology, pp. 244–249 (2018)Google Scholar
  6. 6.
    Safdar, Z., Mehreen, S., Ayesha, B., Foqia, H., Kaleem, A.: Planning-based optimized path for automatic robot navigation. In: 2018 IEEE International Conference on Computing, Mathematics and Engineering Technologies, pp. 1–6 (2018)Google Scholar
  7. 7.
    Mehmet, K., Akif, D.: Comparison of optimal path planning algorithm. In: 2018 International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering, pp. 255–258 (2018)Google Scholar
  8. 8.
    Yuhong, L., Fating, H., Winjie, L., Sheng, B., Liqian, F.: Optimization of robot path planning parameters based on genetic algorithm. 2017 IEEE International Conference on Real-time Computing and Robotics, pp. 529–534 (2017)Google Scholar
  9. 9.
    Asma, A., Sadok, B.: A new multi-robot path planning algorithm: dynamic distributed particle swarm optimization, In: 2017 IEEE International Conference on Real-Time Computing and Robotics, pp. 437–442 (2017)Google Scholar
  10. 10.
    Farid, B., Denis, G., Herve, P., Dominique, G.: Modified artificial potential field method for online path planning applications. In: 2017 IEEE Intelligent Vehicle Symposium, pp. 180–185 (2017)Google Scholar
  11. 11.
    H. Asadi, S. Ozgoli.: A novel approach to reduce oscillations in path planning based on potential field approach. In: 2017 Iranian Conference on Electrical Engineering, pp. 603–608 (2017)Google Scholar
  12. 12.
    Hendri, H.T., Oyas, W., Teguh, B.A., Adha, I.C.: Framework transformation for local information on artificial potential field path planning. In: 2016 8th International Conference on Information Technology and Electrical Engineering, pp. 1–6 (2016)Google Scholar
  13. 13.
    Yadollah, R., Amir, K., Shih-Ken, C., Bakhtiar, L.: A potential field based model predictive path planning controller for autonomous road vehicles. IEEE Trans. On Intelligent Transportation System 18(5), 1255–1267 (2017)CrossRefGoogle Scholar
  14. 14.
    Youcef, H., Adel, M., Abdelfetah, H., Ourda, H., Brahim, B.: Mobile manipulator path planning based on artificial potential field: application on RobuTER/ULM, 2015 IEEE International Conference on Electrical Engineering, pp. 1–6 (2015)Google Scholar
  15. 15.
    Hossein, K., Poria, N.P., Mehdi, T.M., Roya, S.N.: Path planning of 3-RRR parallel robot by avoiding mechanical interference via artificial potential field. In: 2015 3rd RSI International Conference on Robotics and Mechatronics, pp. 240–245 (2015)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Hamzah Ahmad
    • 1
    Email author
  • Ahmad Nuur Fakhrullah Mohamad Pajeri
    • 1
  • Nur Aqilah Othman
    • 1
  • Mohd Mawardi Saari
    • 1
  • Mohd Syakirin Ramli
    • 1
  1. 1.Faculty of Electrical and Electronics EngineeringUniversity Malaysia PahangPekanMalaysia

Personalised recommendations