C40. Improved potential field controller for obstacle avoidance in mobile robots

Abstract

In this paper, improved potential field controller suitable for obstacle avoidance is proposed. Genetic algorithms are used to improve the potential field controller by optimizing the forces applied to the robot making the robot path much smoother. A measure of smoothness is used to guide the genetic algorithm optimizer during its search. Of course more smoothing gives less distance and more speed to reach the goal. The optimized controller is simulated on Windows Vista using Matlab Software. Many cases including environments with single obstacle up to three obstacles and multi-knee corridor are simulated. Results are compared to previous work, illustrating the superiority of the proposed work.