Obstacle Avoidance and Navigation Planning of a Wheeled Mobile Robot using Amended Artificial Potential Field Method

Abstract Trajectory planning is a prime method in the research on mobile robot navigation. Sampling-based algorithms can generate trajectories which help the robot to reach the target avoiding obstacles. In this proposed work, an Enhanced Artificial Potential Field (E-APF) generates the trajectories for mobility of mobile robots and simultaneously guarantees the effectiveness and continuity of the trajectory. Aiming at the problem that the classical APF cannot adapt to the complex trajectory planning and fall a as prey to the local optimal solution, E-APF method is proposed for Wheeled Mobile Robot (WMR) route planning. In this research work, this method does not consider the influence of traditional attraction and repulsive forces. The repulsive potential is built by repulsive function for discretizing outline of an arbitrarily shaped obstacle with their boundary points. This process describes the workspace of the wheeled mobile robot more precisely. The reliability is proved for most of the cases by discussing the convergence of this proposed technique. Finally, an efficient obstacle avoidance based action has been performed in the chosen navigable trajectory. Trajectories that have been generated using the proposed E-APF satisfy constraints approach of the direction on both the starting and goal points. Consequently, the trajectories that are generated by the Wheeled Mobile Robot are geometrically and dynamically feasible. Simulation results performed confirm the viability of the proposed E-APF algorithm that it can be effectively utilized in trajectory planning of wheeled mobile robots and can be applied in real-time scenarios.