Development of Modified Path Planning Algorithm Using Artificial Potential Field (APF) Based on PSO for Factors Optimization

Authors

  • Firas A. Raheem Assistant Prof. Dr. ,University of Technology , Baghdad , Iraq
  • Mustafa M. Badr Engineer , University of Technology , Baghdad , Iraq

Keywords:

Artificial Potential Field, Particle Swarm Optimization (PSO), Path Planning.

Abstract

Solving the path planning problem considered as one of the most important aspects in the navigation of the robot, which should involve with any optimization method to get the best path. This paper presents a mixing approach of modified robot path planning, by applying first particle swarm optimization (PSO) to find the best values of Artificial Potential Field (APF) factors in order to make an iteratively enhancement till reaching the shortest path. This path will be smoothed by spline equation. The result clearly shows the high performance and strength of this mixed approach between the PSO method and APF.

References

[1] Shahab Sheikh-Bahaei, ''Discrete Event Modeling Simulation and Control with Application to Sensor
Based Intelligent Mobile Robotics'', M.Sc. Thesis, Electrical Engineering, The University of New Mexico,
December, 2003.
[2] Conte G, Longhi S, Zulli R, “Robot motion planning for unicycle and car-like robot”,.
International Journal of Systems Science 27: 791–798 , (1996)
[3] Ge SS, Cui YJ , “New potential function for mobile robot path planning”. IEEE Trans. On Robotics and Automation 16(5):615–620 (2000).
[4] Tsourveloudis NC, Valavanis KP, Hebert T .”Autonomous vehicle navigation utilizing
electrostatic potential fields and fuzzy logic”. IEEE Trans. on Robotics and Automation 17(4):490–497, (2001).
[5] Song P, Kumar V, A potential field based approach to multi-robot manipulation. Proceedings
of the IEEE International Conference on Robotics and Automation 2:1217–1222,(2002).
[6] Ahmed T. Sadiq, Firas A. Raheem, Noor Alhuda F. Abbas, “Optimal Trajectory Planning Of 2-D Robot Arm Using The Integration Of PSO Based On D^* Algorithm And Cubic Polynomial Equation”, The First International Conference For Engineering Research, Middle Technical University, Baghdad, Iraq, March 2017.
[7] Firas A. Raheem, Asmaa A. Hussain, ”Modified C-Space Analysis And Construction For Two-Link Robot Arm”, The First International Conference For Engineering Research, Middle Technical University, Baghdad, Iraq, March 2017..
[8] Hui Miao, “Robot Path Planning in Dynamic Environments Using a Simulated Annealing Based
Approach”, M.Sc. Thesis, Queensland University of Technology, March 2009.
[9] Luciano C. A. Pimenta1, Alexandre R. Fonseca, and Guilherme A. S. Pereira, “On Computing Complex
Navigation Functions”, Proceedings of the 2005 IEEE International Conference on Robotics and Automation
Barcelona, Spain, April 2005
[10] Khatib O.,"Real-Time Obstacle Avoidance for Manipulators and Mobile Robots", International Journal
of Robotic Research, vol. 5, pp. 90-98, 1986.
[11] Liu Chengqing, Marcelo HAng Jr, Hariharan Krishnan and Lim Ser Yong, “Virtual Obstacle Concept for Localminimum-recovery in Potential-field Based Navigation”, Proceedings of the 2000 IEEE International Conference on Robotics & Automation San Francisco, CA • April 2000
[12] P. Vadakkepat, K. C. Tan, and W. Ming?Liang, “Evolutionary Artificial Potential Fields and their
Application in Real Time Robot Path Planning”, Congress on Evolutionary Computation (2000) 1256 – 263.
[13] Jinchao Gue, Yu Gao and Guangzhao Cui, “Path planning of mobile Robot base on Improved Potential
Field”, Information Technology Journal 12(11) 2013
[14] Guanghui Li, Atsushi Yamashita and Hajime Asama Yusuke Tamura, “An Efficient Improved Artificial
Potential Field Based Regression Search Method for Robot Path Planning”, Proceedings of the 2000 IEEE
International Conference on Robotics & Automation San Francisco, CA • April 2000
[15] Riccardo Poli • James Kennedy • Tim Blackwell “Particle swarm optimization
An overview “ Springer Science 1 August 2007
[16] Yifan Cai and Simon X. Yang. “A Potential Field-based PSO Approach for Cooperative Target Searching of Multi-robots” in the 11th World Congress on Intelligent Control and Automation
Shenyang, China, June 29 - July 4 2014.
[17] Rainer Palm and Abdelbaki Bouguerra. “Particle Swarm Optimization of Potential Fields for
Obstacle Avoidance “ in conference of Orebro University SE-70182 Orebro, Sweden, September 2013.
[18] Kennedy J, Eberhart R ,“Particle swarm optimization”. IEEE International Conference on
Neural Network, (1995), pp. 1942–1948.

Downloads

Published

2017-11-08

How to Cite

A. Raheem, F., & M. Badr, M. (2017). Development of Modified Path Planning Algorithm Using Artificial Potential Field (APF) Based on PSO for Factors Optimization. American Scientific Research Journal for Engineering, Technology, and Sciences, 37(1), 316–328. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/3482

Issue

Section

Articles