Collision Avoidance Using Cat Swarm Algorithm for Multi Mobile Robot Path Planning in Dynamic Environment

Authors

  • Mohammed A. Kareem
  • Themar Ali Jaleel Computer Science Department, University of Technology, Baghdad, Iraq
  • Alia Karim Abdul Hassan Computer Science Department, University of Technology, Baghdad, Iraq

Keywords:

Decoupled planning, Artificial potential field method (APF), A* algorithm, B-Spline curve (B-S), Cat swarm algorithm (CSA)

Abstract

In this paper, we proposed a hybrid control methodology using improved artificial potential field with modify cat swarm algorithm to path planning of decoupled multi-mobile robot in dynamic environment. The proposed method consists of two phase: in the first phase, Artificial Potential Field method (APF) is used to generate path for each one of robots and avoided static obstacles in environment, and improved this method to solve the local minimum problem by using A* algorithm with B-Spline curve while in the second phase, modify Cat Swarm Algorithm (CSA) is used to control collision that occurs among robots or between robot with movable obstacles by using two behaviour modes: seek mode and track mode. Experimental results show that the proposed method success to find a complete, optimal, and collision free path for all robot.

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Published

2022-02-16

Issue

Section

Computer Science

How to Cite

Collision Avoidance Using Cat Swarm Algorithm for Multi Mobile Robot Path Planning in Dynamic Environment. (2022). Iraqi Journal of Science, 57(3C), 2348-2359. https://ijs.uobaghdad.edu.iq/index.php/eijs/article/view/6487

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