Research on Path Planning of Unmanned Combat Vehicle Based on Improved Potential Field Method

Unmanned combat vehicle is one of the important development trends of the future battlefield, and the unmanned combat vehicle that can realize positioning navigation and autonomous obstacle avoidance in the complex and changeable battlefield environment is an important research direction of unmanned combat vehicle. The path planning problem of unmanned combat vehicles is studied. Based on the classical potential field method, the inherent defects of the classical potential field method are emphatically analyzed. An improved model of repulsive potential field function based on the social force model is proposed. Aiming at the problem that unmanned combat vehicles are prone to fall into local minima, this solution of sub-target points is proposed. Through simulation verification, the inherent defects of the classical potential field method in the path process of unmanned combat vehicles are optimized, It shows that the model and simulation can provide an effective decision-making basis for the path planning of unmanned combat vehicles.