UAV Path Planning Based on Improved Artificial Potential Field Method

Abstract

This paper proposes an improved artificial potential field method (APF) and applies it to UAV path planning, aiming to solve the local optimal solution, unreachable target, non-smooth path and excessive gravity often encountered in traditional artificial potential field methods. In order to solve the limitations of the traditional artificial potential field method, this paper solves the local minimum problem by modifying the repulsion potential field function; the smooth force and inertial force are introduced to balance the force field, and the smooth force is used to reduce the jitter phenomenon of the UAV movement, Inertial force adjusts the movement direction of the UAV to prevent it from falling into a local optimal state; solve the problem of excessive gravity by setting the gravity compensation coefficient and the maximum influence range of gravity; the NSGA-II multi-objective optimization algorithm is used to optimize the initialization parameters of the algorithm, so that a better combination of algorithm initialization parameters can be obtained, thereby obtaining better UAV path planning results. The experimental simulation results show that the improved artificial potential field method in this paper can quickly and effectively plan a shorter and smoother path, avoiding a series of problems existing in the traditional artificial potential field method, and applied to UAV path planning in complex environments It has certain practical value.