Modified Artificial Potential Field Algorithms for Mobile Robot Path Planning

Abstract

Path planning for a mobile robot means devising a feasible, collision-free route between any two points while operating in tough, busy environments. The design of intelligent and efficient path-planning algorithms is critical for mobile robots’ autonomous navigation and operation. In this work, we attempt to improve the classical artificial potential field (APF) path planning algorithm, which suffers from local minima, failing to reach the goal. The virtual obstacle method (VOM) and the perturbation approach, both conceptually based on the APF but operationally different, have been proposed as improvements to tackle the local minima problem. These algorithms’ performance and ability to generate the path to reach the desired goal were examined using simulations, considering different obstacle scenarios with comparative analysis. The outcomes of these simulations are discussed in detail, followed by their limitations.