采用粒子群优化和B样条曲线的改进可视图路径规划算法

Improved Visibility Graph Method Using Particle Swarm Optimization and B-Spline Curve for Path Planning

针对传统局部路径规划中容易陷入局部陷阱和规划路径不平滑的问题,提出一种将改进可视图,基于B样条曲线和粒子群优化算法结合起来规划一条平滑路径的算法.该算法由多边形动态生成、路径规划和路径平滑3个步骤组成,为了逃离局部陷阱,在多边形动态生成的过程中增加环境记忆功能,并通过路径平滑过程,使规划的路径更能满足移动机器人动力约束条件.仿真实验结果验证了算法的有效性,对比其他几种路径规划算法,所提出算法规划的路径质量更高.

Trapping in local minima and discontinuities often exist in local path planning.To overcome these drawbacks,this paper presents a smooth path planning algorithm based on modified visibility graph which involves B-spline curves and particle swarm optimization.This algorithm consists of three steps:dynamically generate polygons,plan a path and smooth the path.To escape from traps,the environment is memorized in the dynamic polygon generation process.By the path smooth process,this planned path is more adapt the kinetics constraint of mobile robots.Simulations verify the effectiveness of the proposed algorithm.Comparing other several path planning algorithms,the planned path by the proposed algorithm posses a higher quality.