Improved artificial potential field method for local minima
Fuyang Miao · Applied and Computational Engineering · 2023
With the development of autonomous driving technology, its applications permeate many aspects of work and life, providing convenience while reducing labor costs. Path planning has always been important for autonomous driving, where APF is widely used thanks to its simplicity of calculation and effectiveness. However, there’re still problems existing such as local minima, influenced by initial positions and parameters, and so on. In this study, a better approach to solving the local minimum issue is suggested. Firstly, the odometry method is used for the determination of falling into local minima by saving and computing the relationships between adjacent steps. Subsequently, a variable step length method is designed for escaping local minimum points and bypassing obstacles in front. The feasibility and robustness of the method were verified by simulations, and this method proved capable of solving the local minima and planning a reasonable trajectory.