Obstacle Avoidance and Trajectory Optimization of Quadrotor UAV Based on Improved Potential Field

In this paper, an improved potential field algorithm is proposed, which solves the problems of the traditional artificial potential field method. The improved potential field algorithm addresses these problems through two major improvements. First, an improved gravity function is adopted to ensure that the UAV can reach the target point and that the trajectories do not cross or overlap. Secondly, an optimized repulsive potential field calculation method is adopted. By introducing dynamic factor coefficients, the problem that the traditional repulsive potential field calculation is easy to fall into local minima is solved. Simulation results of 3D multi-UAV path planning show that the improved potential field algorithm effectively overcomes the shortcomings of the traditional potential field method.

I. Introduction

The widespread application of UAVs, particularly in military, civilian, scientific, and commercial fields, has made UAV trajectory planning and obstacle avoidance control a hot research topic. In current research, the improved artificial potential field (APF) method for UAV obstacle avoidance trajectory planning has been widely applied and has made significant research progress. Researchers have conducted in-depth research and application of this technology in different directions, such as multiple UAV formation path planning, UAV trajectory planning algorithm review, robot path planning, UAV formation coordinated obstacle avoidance control, autonomous planning of UAV group routes, dynamic trajectory planning of delivery UAV clusters, and quadcopter UAV trajectory planning. These studies not only provide strong support for the safety and stability of UAV s but also provide broad prospects for the development of UAV technology.