The Comparative Application of Fuzzy Logic and Genetic Algorithm for Intelligent Navigation of Mobile Robot in Dynamic Unknown Environment in the Case of Fixed and Moving Obstacles

Abstract

Introduction: In recent years, topics related to robotics have become one of the areas of research and development. In the meantime, smart robots are very popular, but the control and navigation of these devices are very difficult, and the lack of handling and staggering obstacles and avoidance of them, due to safe and secure routing, outweigh the basic needs of these systems. Material and Methods: In this research, for the purpose of solving the intelligent navigation problem, a moving robot in a dynamic unknown environment (conditions at any moment in the range of moving and obstacles in motion) and the choice of optimal path, the methods of genetic algorithm and fuzzy logic are used comparatively. Results: By using genetic algorithm and fuzzy logic methods, the robot can move in the dynamic and unknown environment to the optimal path to the target. Conclusion: Information about the environment is also necessary to avoid obstacles, optimal path design and environment exploration, and to establish a clever relationship between perception and practice that requires the use of appropriate algorithms such as the genetic algorithm and fuzzy logic (fuzzy controller) are also needed to manage the control and navigation.