Chaos Engineering and Control in Mobile Robotics Applications Salah Nasr 1 , Amine Abadi 1 , Kais Bouallegue 2 and Hassen Mekki 1 1 Networked Objects Control and Communication Systems-Laboratory, National Engineering School of Sousse, University of Sousse, Tunisia 2 Department of Electrical Engineering, Higher Institute of Applied Sciences and Technology of Sousse, Tunisia Keywords: Chaos Theory, Chaos Engineering, Chaotic Mobile Robot, Chaos Control, Robotic Applications. Abstract: This article briefly summarizes the theory of chaos and its applications. Firstly, we begin by describing chaos as an aperiodic bounded deterministic motion, which is sensitive to initial states and therefore unpredictable after a certain time. Then, fundamental tools of the chaos theory, used for identifying and quantifying chaotic dynamics, are shared. The paper covers a main numerical approach to identify chaos such as the Lyapunov exponents. Many important applications of chaos in several areas such as chaos in electrical and electronic engineering and chaos applications in robotics have been presented. An analysis of the reviewed publications is presented and a brief survey is reported as well. 1 INTRODUCTION During the 20th century, three great revolutions occurred: quantum mechanics, relativity and chaos. The theory of chaos, also called dynamical systems theory, is the study of unstable aperiodic behavior in deterministic dynamical systems, which show a sensitive dependence on initial conditions (Vaidyanathan, 2013). The sensitive dependence on initial conditions implies that arbitrary initial conditions follow trajectories that move away from one another after a certain time (Moon, 2008), as shown in figure 1. Due to determinism (Morrison, 2012), chaos is predictable for the short time; but it is unpredictable in the long run due to sensitivity to initial conditions. Chaos is characterized by a large sensitive dependence to the initial state, by its inability to predict future consequences, by the Lyapunov exponent (Kuznetsov, 2016), by its fractal dimension, and so on. The nonlinear dynamics and chaos terms have become known to most scientists and engineers over the past few decades. Nonlinearities occur in feedback processes (Gaponov-Grekhov and Rabinovich, 2011), in systems containing interacting subsystems, and in systems interacting with the environment. This scenario is qualitatively and quantitatively distinct from the situations where the perturbations develop linearly. Thanks to the availability of high- speed computers and new analytical techniques, it has become clear that the chaotic phenomenon is of a universal nature and has transverse consequences in various areas of human endeavour. The devices of the fire fighting and floor cleaning have been developed by exploiting autonomous mobile robots as useful tools in activities that put the integrity of humans in danger, such as monitoring and exploring of terrains for explosives or dangerous materials and such as intrusion patrols at military installations. This has driven to the development of intelligent robotic systems (Martins-Filho and Macau, 2007). Therefore, the unpredictability of a trajectory is also a crucial factor for the mission success for such an autonomous mobile robot. To meet this challenge, Sekiguchi and Nakamura suggested a strategy in 2001 to solve the problem of path planning based on chaotic systems (Nakamura and Sekiguchi, 2001). Figure 1: Two trajectories that start close to each other but diverge within a few tens of seconds (Moon, 2008). 364 Nasr, S., Abadi, A., Bouallegue, K. and Mekki, H. Chaos Engineering and Control in Mobile Robotics Applications. DOI: 10.5220/0006867103640371 In Proceedings of the 15th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2018) - Volume 2, pages 364-371 ISBN: 978-989-758-321-6 Copyright © 2018 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved