Robot path planning based on electrostatic field
Zihan Zhou, Yunchuan Liu, Haiyan Tu, Mengyao Han, Qiuhua Zen · 2022
The traditional artificial potential field method often falls into the local minimum point, resulting in the inability to reach the target point. In order to solve this problem, an electrostatic field algorithm is proposed, which provides a new framework for the trajectory of mobile robot. The electrostatic field algorithm uses the electrostatic field model to generate a gradient equipotential surface under the action of a uniform electric field to maintain the distance from the obstacle. Trajectory optimization reduces path planning based on sensor information and related motion constraint penalty function. The electrostatic field algorithm parallels the robot kinematics model and optimizes the candidate trajectory subset, and considers the allowable speed of the robot to find the optimal trajectory. The robot is closely combined with the environment and retains the global nature of the planned path. Compared with the traditional artificial potential field method, the advantage of path planning based on electrostatic field algorithm is confirmed.