一种采用两段粒子群优化的路径规划方法  

A path planning method using two-stage particle swarm optimization

作　　者：刘彬[1] 张仁津[1] 

机构地区：[1]贵州师范大学数学与计算机科学学院,贵州贵阳550001

出　　处：《山东大学学报（工学版）》2012年第1期12-18,共7页Journal of Shandong University（Engineering Science）

基　　金：贵州省科学技术基金资助项目(黔科合J字LKS[2009]14号);贵州省优秀科技教育人才省长专项资金资助项目(黔省专合字[2009]115号)

摘　　要：在路径规划中普遍采用多条短曲线拼接成一条长曲线,这种方法通常只实现了C1连续,导致相邻短曲线在连接处的二阶导数不连续。为解决这个问题,采用具有C2连续特点的三次B样条曲线作路径,并提出一种两段粒子群优化实现路径规划。在第一阶段确定B样条曲线的控制顶点数,在第二阶段搜索最优路径。为保证粒子的有效性,依据B样条曲线的特点改进了粒子的初始化方法。在适应度函数中通过弧长因子、碰撞因子分别考察路径的长度及碰撞检测,粒子通过循环逐步逼近全局最优解。实验结果表明粒子初始化采用改进的方法后更接近实际路径,采用两段粒子群优化算法能获得C2连续的路径。Multiple short curves are joined to a long curve in path planning,which usually could only realize C1 continuity and could cause the second order derivative to be discontinuous in the joint of adjacent short curves.To resolve this problem,the cubic B-spline curve with the feature of C2 continuity was used to implement path planning carried out by a two-stage particle swarm optimization.Control vertexes of the B-spline curve were determined at the first stage of two-stage particle swarm optimization,and then the optimal path was searched for at the second stage.To ensure the particles effectiveness,the particles initialization was improved according to the characteristic of the B-spline curve.The length of the path and collision detection reflected on the arc length factor and collision factor respectively in the fitness function.The global optimum was gradually approached with the loop by the particles.Experimental results indicated that the improved initialized particles were closer to the actual path and that the C2 continuous path could be achieved by two-stage particle swarm optimization.

关 键 词：粒子群优化 路径规划 导航 防止碰撞 移动智能体 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]