Title: Fractal, chaos and neural networks in path generation of mobile robot

Authors: Salah Nasr; Kais Bouallegue; Hassen Mekki

Addresses: Networked Objects Control and Communication Systems Laboratory, National Engineering School of Sousse, University of Sousse, Tunisia, Sousse, 4023, Tunisia ' Networked Objects Control and Communication Systems Laboratory, National Engineering School of Sousse, University of Sousse, Tunisia, Sousse, 4023, Tunisia ' Networked Objects Control and Communication Systems Laboratory, National Engineering School of Sousse, University of Sousse, Tunisia, Sousse, 4023, Tunisia

Abstract: This paper is an attempt to solve problems involved in the path planning for the mobile robot with obstacle avoidance. Therefore, we propose three approaches for control using a fractal process system, neural networks and a combination between the chaos and the fractal process. Firstly, we present the fractal process system and its impact on the trajectory of robot. Secondly, a new variable structure model of neurons is utilised to control the robot trajectory in the presence of obstacles with different positions. Thirdly, we design as well a controller by combining the chaotic system and the fractal process inspired from the Julia set. Thus, we give several examples of trajectory control for the mobile robot for such an approach with simulation.

Keywords: mobile robot; neural networks; chaos; fractal; path planning; obstacles avoidance.

DOI: 10.1504/IJMIC.2020.108914

International Journal of Modelling, Identification and Control, 2020 Vol.34 No.1, pp.41 - 50

Received: 06 Sep 2019
Accepted: 15 Jan 2020
Published online: 06 Aug 2020 *

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