Abstract: |
Aiming at the problem that the target point is infeasible and local minimum in the traditional artificial potential field method in the path planning and obstacle avoidance of unmanned vehicles, an improved artificial potential field method is proposed. The gravitational potential field function was modified to make the gravitational force converge to a certain value when the distance is large or small, so as to solve the problems of collision between unmanned vehicle and obstacles and infeasibility of the target point caused by excessive gravity in the early stage. A smoother repulsive force calculation formula was used to optimize the repulsive potential field function to solve the problem of the unmanned vehicle staying near the obstacle due to excessive repulsive force when the unmanned vehicle was too close to the obstacle. The formation stability force is defined so that the formation can maintain a stable formation in the process of advancing, and the unmanned vehicle can successfully break away under the action of the force when it falls into a local minimum. The experimental results show that in the static obstacle environment, the improved artificial potential field method has good performance and robustness in both single unmanned vehicle path planning and multiple unmanned vehicle formation collaborative work scenarios, and the planned path is smoother and the speed changes are smoother, which provides an effective solution for safe and efficient unmanned vehicle navigation.ξ |