足球机器人路径规划的PSO方法

研究足球机器人在已知静态环境下路径规划问题，在避障环境下寻求最优路径，提出了一种基于粒子群优化算法的足球机器人路径规划方法。为适应PSO算法的自身特点和提高算法搜索的效率，在传统栅格法的基础上引入实际坐标系法，对环境进行建模；为了更好地评价粒子（即解）的性能，在进行碰撞判定的基础之上，引入罚函数方法，克服了传统适应度函数难以更好地表达粒子性能的缺点。进行仿真的结果表明，该算法在足球机器人路径规划方面具有可行性、有效性和鲁棒性。

Soccer Robot Path Planning Based on PSO

A global soccer robot path planning approach based on particle swarm optimization （PSO） is presented for path planning prob- lem in known static environment. In order to adapt the PSO and improve the search efficiency of the algorithm, a new map between start- ing-point and goal-point is made up of semi-grid and semi-coordinate system. In order to evaluate the particles＂ performance, a penalty function method is used based on collision detection. Simulation results show that the PSO applied in soccer robot path planning is in terms of feasibility, validity and robustness.