摘要
在自由空间下粒子群算法(Particle Swarm Optimization,PSO)求解机器人路径规划问题时,存在易早熟、编码维度高和路径不平滑等问题,为此提出了一种基于PSO和三次样条插值的路径规划方法。所设计的粒子编码为环境中若干个路径节点的坐标,路径节点的个数决定了样条曲线的个数同时也决定了路径转向的次数。通过3次样条函数对路径的起点、路径节点和终点进行插值,从而得到一条由插值点构成的路径。仿真结果表明,相比传统方法所提出的算法能快速找到平滑的最优路径,并且能为多个机器人规划出最优的无碰路径。
There are shortcomings such as premature convergence, high encoding dimension and unsmooth path for particle swarm optimization（PSO） algorithm to solve the robot path planning problem under free space. The particle coding is coordinates of several path nodes in the environment. The number of spline curves and the maximum turnings of path were determined by the number of path nodes. The cubic spline function was used to interpolate on the path of the starting point, path nodes and target point, thus a full path which was formed by connecting all interpolation points was obtained. Simulation results show that compared with the traditional methods, the proposed algorithm can quickly find the optimal path, and can plan the optimal collision free path for multi-robots.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2017年第7期1397-1404,共8页
Journal of System Simulation
基金
国家自然科学基金(11404205)
中央高校基本科研业务费专项资金(GK201703015)
关键词
粒子群算法
三次样条
多机器人
路径规划
particle swarm optimization algorithm
cubic spline
multi-robots
path planning
