基于惩罚函数NPGA的多目标路径规划

The Multi-object Path Planning Based on Penalty Function NPGA

通过分析传统的机器人路径规划方法,将足球机器人路径规划归结为一个多目标优化问题,利用基于惩罚函数的小生境遗传算法建立动态目标路径规划的运动模型。仿真表明,与传统的路径规划方法相比,该方法在保证机器人较高体力值的前提下,规划出合理的路径。

On the base of analyzing the traditional path planning methods of the robots, the paper looks path planning as a multi-object optimize problem, set the athletics model which can planning the path for the dynamic object. The simulation result shows that： compared with the traditional path planning methods, the PNPGA can find a reasonable path with the robot has high stamina.