摘要
针对足球机器人在比赛中复杂的静态和动态环境,提出了基于极坐标建模和优化粒子群算法的足球机器人路径规划方法.这种方法利用极坐标计算方便和模拟路径逼真的优势,把足球机器人的路径编码放在二维的极坐标中,然后利用机器人的当前路径点、下一步路径点和障碍物点的距离关系判断是否进行路径规划,当碰到障碍物时,通过调用加入非线性惯性权重的改进PSO算法进行路径规划.通过计算机仿真,验证了改进PSO算法的收敛性和路径规划的有效性.
In order to adapt to the game′s complex dynamic and static environment,the path planning of soccer robot is proposed based on polar coordinate modeling and improved partide swarm opimization algorithm.This method makes use of the convenient calculation and clear path of the simulation of polar coordinates.The path coding of soccer robot is put in the polar coordinates to judges whether to operate the path planning or not by the distance relationship between current path point,next path point and barrier point.While the robots run into obstacles,the improved PSO algorithm with added nonlinear inertia weight is triggered for path planning.The simulation results prove the convergence of improved PSO algorithm and the effectiveness of path planning.
出处
《西安工程大学学报》
CAS
2016年第5期609-615,共7页
Journal of Xi’an Polytechnic University
基金
西安市科技局产学研协同创新计划(CXY1517(4))
关键词
极坐标建模
粒子群算法
足球机器人
路径规划
polar coordinate modeling
particle swarm optimization algorithm
soccer robot
path planning
