基于粒子群优化算法的机器人路径规划

Robot path planning based on particle swarm optimization

文章提出一种机器人路径规划的有效算法,为机器人找到一条从起点到终点最短的无碰撞路径,主要是优化了粒子群的惯性权重,然而其在不同的阶段采用不同的权重值。通过实验发现,改进后粒子群能够收敛得更快,数据收敛得更精确。

This paper proposes an effective algorithm for robot path planning, which can find the shortest path for robot from start to end. It mainly optimizes the inertia weight of particle swarm, but it uses different weight values in different stages. The experimental results show that the improved particle swarm optimization can converge faster and the data converges more accurately.