Research On Path Planning Of Soccer Robot Based On Improved Genetic Algorithm

Along with the further development of artificial intelligence technology, robot technology has been rapid development. Soccer robot technology combines artificial intelligence, micro controller technology, mechanical design, path planning and other technology, the path planning is the key. In robot soccer game, path planning is to be able to quickly and correctly, and collision free move from the starting point to the target point, find a optimal path, is the embodiment of the soccer robot match strength and artificial intelligence. only with such a control algorithm, the type of robot team, mobility, antagonism can be improved, and good results can be achieve. Therefore, the path planning algorithm is the core task of improving the intelligence and the antagonism of the soccer robot.The system block diagram of the robot soccer are gived in this thesis, each part of the robot system are analyzed, the hardware circuit of the soccer robot with ARM core are designed, a driving environment based on ARM Linux software is created, a wireless sensor network based on ZigBee technology is established. The analysis of the problem of path planning in robot soccer match is focused on, frequently used in the field of research theory and characteristics are analyzed, the genetic algorithm, the method of operation, initial population produce adapt value calculation, selection algorithm, and termination conditions are presented in this thesis, according to the requirements of robot soccer against environment, for different game environment complexity, improvement theory and the improved method are proposed. First step, current environment complexity is analyzed, according to this, simple environment using fuzzy logic control in general, using genetic algorithm to complex environment, and the key parameters of the algorithm are simulated by MATLAB. Finally, comparison of genetic algorithm and fuzzy control algorithm operation time and data analysis, the real-time performance of robot combat to a certain extent is improved by this method.