基于粒子群三次样条优化的局部路径规划方法

Local Path Planning Algorithm Based on Particle Swarm Optimization of Cubic Splines

为解决机器人在静态未知环境下如何利用局部环境信息规划出连续平滑的路径问题,提出一种基于粒子群三次样条优化与滚动窗口结合的局部路径规划方法。借助三次样条描述路径,根据机器人实时探测到的局部环境信息,在滚动窗口中运用粒子群算法解决样条参数的优化问题,使各部分路径光滑且一阶连续,从而实现最优局部路径规划。仿真结果表明:所提算法可以在静态环境下快速有效地实现机器人的无碰撞局部路径规划,且所规划路径平滑,便于运动控制。

In order to solve the problem of mobile robot local path planning smoothly in globally static unknown environment, an algo rithm based on particle swarm optimization （ PSO} of cubic splines and the rolling windows is proposed. With the cubic splines descrip tion of the path and the locally environmental information obtained by mobile robot in real-time, the particle swarm optimization is used to solve the optimization problem of splines parameters. Then, the locally optimal path is got, which is first-order continuous. The sim- ulation results show that a collision-avoidance path can be found fleetly and effectively by the proposed algorithm in static unknown envi ronment. And the planned path is smooth which is useful for robot motion control.