Path Planning System Of Football Robot Based On Evolutionary Artificial Potential Field

Path planning is a kernel problem of robot technology area, and is also an important aspect of robot study in artificial intelligence. The main task of path planning is figuring out a collide-free path at least cost from the known start position to known goal position in the robot environment. In environment only with static obstacles, it is easy to find an optimized path, while in environment with both static obstacles and dynamic obstacles, it is more difficult to find a feasible optimized path.This thesis is based on soccer robot system. It mainly focuses on the problem of robot path-planning and explores effective methods to solve this problem. Firstly, this paper gives the architecture of the soccer robot system and its key technologies. Especially, it discusses the design of Decision-making subsystem and analyzes the importance of} path-planning in this system. We also investigate the system model of robot soccer and collision characteristics of this platform. On the basis of the above work, the author studies the four representative methods which are artificial potential field, grads modeling method, evolutionary algorithms and artificial neural network; and discusses their feasibility in real-time system. Finally, a soccer robot path-planning system is designed based on evolutionary artificial potential field. The system has the merit of combining with platform and includes the basic path-planning subsystem, boundary path-planning subsystem and forbidden zone path-planning subsystem. The method is effective by the testimony on the Robot Soccer Simulator.