Strategies of Pursuit-Evasion Game Based on Improved Potential Field and Differential Game Theory for Mobile Robots

In this paper, in view of the current existing problem of algorithm for pursuit-evasion game, such as computational complexity and lack of universality, we firstly propose a hybrid algorithm based on improved dynamic artificial potential field and differential game. According to the changes of environment around the pursuer and evader the algorithm applies flexibly. Simulation results show that the algorithm not only has the simple structure of the artificial potential field model, which can be effective in the pursuit path planning to avoid obstacles, but also can avoid deadlock problem after the improvement. Moreover, Nash equilibrium solution is optimal for both pursuer and evader in barrier-free zone in pursuit-evasion game.