Smoothening of Artificial Potential Field (APF) Path Using KNS-Clearance Technique

Abstract

Path planning is one of the major hurdles in developing and deploying mobile robots. To ensure the successful operation of a robot, an effective and efficient Path planning technique that guarantees obstacle avoidance and optimal path must be adopted. This paper proposes a novel path improvement technique- KNS-clearance, that reduces the clearance around an obstacle of an APF path to shorten the path length, Smoothening the resultant path, reducing the number of bends in the waypoint and retaining the obstacle avoidance capability of the path. We simulated the technique in different environmental configurations with different obstacle arrangements. We compared the resultant path with the original APF path and the resultant path of similar path improvement techniques like the Ramer-Douglas-Peucker algorithm (RDP). The results show that KNS-clearance is very effective and efficient.