摘要
为了解决足球机器人无法躲避动态障碍物和容易陷入局部极值的问题,在深入研究粒子群优化算法的基础上,提出了采用栅格法与粒子群优化算法相结合的路径规划算法。首先采用栅格法对小型足球机器人工作环境构造模型,再利用改进的粒子群优化算法进行最优路径搜索。该算法实现简单,收敛速度快,不易陷入局部极值,不仅能够满足足球机器人实时动态的路径规划要求,而且能满足不同环境下的路径规划要求。仿真实验表明,该方法可以很好地应用于足球机器人的路径规划中。
In order to solve the problems that soccer robot could not avoid dynamic obstacles and easily get into local optimal value in the path planning,an algorithm which combined grid theory with particle swarm optimization（PSO） was proposed on the base of deep research about the PSO.Firstly,the working space model of the small-size soccer robot was established by using the grid theory.Then,the optimal path was found out by improving the PSO.The method has simple realization,a rapid convergence;it can avoid getting into local optimization;it can meet the real-time and dynamic requirements of path planning;it can be applied to different environments.The simulation result shows that the algorithm can be applied well in path planning of soccer robot.
出处
《机电工程》
CAS
2010年第12期116-120,共5页
Journal of Mechanical & Electrical Engineering
关键词
小型足球机器人
路径规划
栅格法
粒子群优化算法
small-size soccer robot
path planning
grid model
particle swarm optimization（PSO）
