基于改进粒子群优化算法的路径规划

针对二维静态环境下移动机器人路径规划问题,该文提出一种改进的粒子群算法求解最优路径。首先,由于传统的粒子群算法初始化粒子时并未考虑到粒子初始位置是否占障碍物空间,没有对占障碍物空间的粒子进行处理,导致粒子初始有效性低下,全局寻优不准确和全局寻优时间长。然后,为解决此问题,在初始化时采用一种修正粒子算法,解决初始时粒子有效性低下的问题。比较传统粒子群算法和该文算法的仿真结果。仿真结果表明,采用这种方法极大限度地增大了初始粒子的有效性,使算法迭代时可以更加快速准确地得到全局最优路径,所提方法有效可行。

Path Planning Based on Improved Particle Swarm Optimization

For mobile robot path planning problem in two-dimensional static environment,an improved particle swarm optimization algorithm is proposed to solve the optimal path. Firstly,because the traditional particle swarm optimization algorithm initializes the particles without considering whether the initial position of the particles occupies the obstacle space,there is no processing of the particles occupying the obstacle space,resulting in low initial validity of the particles,global optimization inaccuracy and global search. Excellent time. Then,in order to solve this problem,a modified particle algorithm is used in the initialization to solve the problem of low particle validity at the initial stage. Compare the traditional particle swarm optimization algorithm with the simulation results of the proposed algorithm. The simulation results show that the method can greatly increase the effectiveness of the initial particles,and the algorithm can obtain the global optimal path more quickly and accurately. The proposed method is effective and feasible.