Discrete Artificial Potential Field Approach to Mobile Robot Path Planning

Abstract

The paper introduces a path planning method for an autonomous mobile robot, called the Discrete Artificial Potential Field algorithm (DAPF). The method is different from the currently applied similar path planning approaches, such as the classical APF method, using attractive and repulsive potential field functions or the wave front algorithm. The novelty and originality of the method lies in the construction of the discrete potential field, the method of taking dynamic obstacles into account and achievement of effective solutions in terms of the path length and run time of the algorithm. The DAPF algorithm is capable of finding a collision-free path for a mobile robot in static and dynamic environments. The Path Optimization Algorithm (POA) is also proposed in the paper. Its aim is to modify the collision-free path in order to obtain a smoother and shorter path. The DAPF algorithm runs in near-real time, therefore the method can be used in practical applications. The algorithm is evaluated by simulations in the MATLAB environment and by real experiments with the use of four-wheel differentially driven mobile robots. The results were compared with a heuristic approach based on Ant Colony Optimization and demonstrate the feasibility and effectiveness of the presented approach.