Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques

  • Ibraheem Kasim Ibraheem Department of Electrical Engineering / College of Engineering / University of Baghdad
  • Fatin Hassan Ajeil Department of Electrical Engineering / College of Engineering / University of Baghdad
Keywords: robotics,, Path planning, ant colony optimization, static environment, and collision-avoidance

Abstract

This paper presents a meta-heuristic swarm based optimization technique for solving robot path planning. The natural activities of actual ants inspire which named Ant Colony Optimization. (ACO) has been proposed in this work to find the shortest and safest path for a mobile robot in different static environments with different complexities. A nonzero size for the mobile robot has been considered in the project by taking a tolerance around the obstacle to account for the actual size of the mobile robot. A new concept was added to standard Ant Colony Optimization (ACO) for further modifications. Simulations results, which carried out using MATLAB 2015(a) environment, prove that the suggested algorithm outperforms the standard version of ACO algorithm for the same problem with the same environmental conditions by providing the shortest path for multiple testing environments.

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Published
2017-12-18
How to Cite
Ibraheem, I., & Ajeil, F. (2017). Path Planning of an autonomous Mobile Robot using Swarm Based Optimization Techniques. Al-Khwarizmi Engineering Journal, 12(4), 12- 25. https://doi.org/10.22153/kej.2016.08.002
Section
Articles