Enhanced Obstacle Avoidance and Intelligent Navigation for Mobile Robots: An Integrated Approach Using Fuzzy Logic and an Optimized APF Method
Youssef Mhanni, Youssef Lagmich · Mathematical Modelling and Engineering Problems · 2023
This study presents a novel algorithm designed to facilitate intelligent navigation and obstacle avoidance for mobile robots.The proposed algorithm provides a reliable means for robots to navigate complex environments, skillfully negotiating both static and dynamic obstacles while identifying the most efficient path from a start point to a destination.The principal aim is to guide a robot's traversal through various environments, preventing collision with obstacles while ensuring an optimal path is followed.The robot's trajectories are generated using an optimized version of the artificial potential field (APF) technique, renowned for its simplicity and effectiveness in dynamic and intricate environments.The developed algorithm calculates both attraction and repulsion forces between the robot and various elements within its environment, including the goal, obstacles, and other robots.This holistic approach ensures the efficiency and continuity of the plotted trajectory.To further refine the robot's movement towards the goal, a fuzzy logic-based intelligent controller is incorporated.The integration of fuzzy logic control (FLC) with the APF technique allows the system to strategically plan the robot's path.This is achieved by determining the subsequent location point and calculating the required angular and linear velocities using a forward linkage controller (FLC).The efficacy of the approach is validated through a series of real-time experiments and simulations.The refined algorithm, with appropriately tuned parameters, is implemented within the Robotics Operating System (ROS) environment using the Gazebo simulator.The results obtained provide a comprehensive evaluation of the modified potential field technique's applicability, validity, and optimal performance in task completion scenarios.Through the integration of the optimized artificial potential field and fuzzy logic control, the proposed approach presents a robust solution for the safe and efficient navigation of mobile robots in complex environments.