基于改进烟花-蚁群混合算法的智能移动体避障路径规划

Obstacle avoidance path planning of intelligent mobile based on improved fireworks-ant colony hybrid algorithm

针对二维静态环境下智能移动体避障路径规划问题,提出改进烟花-蚁群混合算法求解最优路径.首先,鉴于基本烟花算法的不足,提出增加"先锋火花"和采用"镜面映射"规则处理越界先锋火花的改进方法;然后,将改进烟花算法得到的最短路径作为参照路径,使其换算成蚁群算法的初始信息素分布,以解决蚁群算法收敛速度慢和初始信息素不足的缺点;最后,进行3种不同环境下的仿真实验,结果表明所提出的算法能够快速寻得高精度的最优路径,在应对复杂环境时也表现出良好的求解性能.所提出的算法为复杂环境下智能移动体避障路径规划提供了一种新思路.

Aiming at the problem of obstacle avoidance path planning for intelligent mobile in two-dimensional static environment, this paper proposes an improved fire-ant colony hybrid algorithm to obtain the optimal path.First of all, in view of the shortcomings of the basic fireworks algorithm, an improved method of increasing the 'pioneer sparks'and using the'mirror mapping'rule to deal with pioneer sparks beyond the boundary is proposed. Then, the optimal path of the improved fireworks algorithm is used as the reference path, which is converted into the initial pheromone distribution of the ant colony algorithm. It makes up for the shortcomings of the initial pheromone deficiency and the slow convergence rate of the ant colony algorithm. Finally, simulation experiments are carried out in three different environments. The experimental results show that the algorithm proposed in this paper can quickly find the optimal path of high precision,and also has a strong performance in dealing with complex environment. The proposed algorithm provides a new idea to solve the problem of obstacle avoidance path planning for intelligent mobile in complex environment.