A Path Planning Method Based on Artificial Potential Field Improved by Potential Flow Theory

Abstract

The ability of the avoidance to movable obstacle is inefficient in robot path planning using traditional artificial potential field. An improved potential field model based on potential flow theory is proposed to achieve high efficient mobile robot path planning. The Zhukovsky transformation is used to optimize the configuration and function of the potential model to satisfy the reliability of avoiding mobile obstacle, and a further investigation of the vortex is applied to prevent the local minima. The application of the improved potential field model to multi-obstacle potential superposition is discussed to verify the effectiveness of the algorithm. The simulation results indicate that the improved method is able to avoid mobile obstacles and prevent local minima efficiently.