University of Isfahan Computational Intelligence in Electrical Engineering 2821-0689 2 1 2011 04 21 CA Based Path Planning Method for Mobile Robots Enhanced by ant Colony Inspired Mechanis CA Based Path Planning Method for Mobile Robots Enhanced by ant Colony Inspired Mechanis 17 26 15307 FA Adel Akbarimajd 1Department of electrical engineering, Faculty of Engineering, University of Mohaghegh Ardabili, Ardabili, Iran Akbar Hassan Zadeh 2Department of electrical engineering, Faculty of Engineering, University of Shiraz, Shiraz, Iran Journal Article 2016 06 14 In path planning of mobile robots dealing with concave obstacles is a major challenge. More specifically in real-time planning where there is no complete representation of the environment, this challenge would be much more problematic. In such cases local minimums and high computations cost are the most important problems. In this paper, in order to reduce computational cost, cellular automata as a distributed computational method with parallel processing properties is employed as tool for path planning purposes. The environment of the robot is modeled as a two dimensional cellular automata with four states. Evolutionary rules of the automata are proposed to perform the planning task. The proposed method is appropriate for single robot systems as well as multi robot systems. The proposed method is afterwards extended to be employed for concave obstacles using a ant colony inspired technique. The most superior advantage of the proposed method is its capability of real-time path planning of mobile robots with no need to prior representation of the environment. In path planning of mobile robots dealing with concave obstacles is a major challenge. More specifically in real-time planning where there is no complete representation of the environment, this challenge would be much more problematic. In such cases local minimums and high computations cost are the most important problems. In this paper, in order to reduce computational cost, cellular automata as a distributed computational method with parallel processing properties is employed as tool for path planning purposes. The environment of the robot is modeled as a two dimensional cellular automata with four states. Evolutionary rules of the automata are proposed to perform the planning task. The proposed method is appropriate for single robot systems as well as multi robot systems. The proposed method is afterwards extended to be employed for concave obstacles using a ant colony inspired technique. The most superior advantage of the proposed method is its capability of real-time path planning of mobile robots with no need to prior representation of the environment. https://isee.ui.ac.ir/article_15307_5feb9c81b7157ccc8c6a65f59a0672f5.pdf