摘要： 根据传统蚁群算法在机器人的路线规划中具有收敛速度慢、容易陷入局部最优解的缺陷，提供了一个经过改进的蚁群算法。使用栅格法建立路径矩阵，建立一种转角启发函数，增加选择指定路径的概率，提高算法的搜索速度；将A*算法与改进蚁群算法结合，提出一种改进的距离启发函数，避免了陷入局部最优解；并提出一种可根据迭代次数而改变的信息素挥发因子，增强了全域搜寻能力。根据相关数据分析，与Ant Colony Algorithm with Multiple Inspired Factor（ACAM）算法相比，改进的蚁群算法对于解决算法收敛速度慢、防止进入局部最优解等方面效果更好。

中图分类号：TP301.6
文献标志码：A
DOI: 10.16157/j.issn.0258-7998.222741
中文引用格式： 王星宇，胡燕海，徐坚磊，等. 基于改进蚁群算法的机器人路径规划方法[J]. 电子技术应用，2023，49(1)：75-80.
英文引用格式： Wang Xingyu，Hu Yanhai，Xu Jianlei，et al. Robot path planning method based on improved ant colony algorithm[J]. Application of Electronic Technique，2023，49(1)：75-80.

Robot path planning method based on improved ant colony algorithm

Abstract： An improved ant colony algorithm is provided according to the disadvantage of slow convergence and easy to fall into local optimal solution of traditional ant colony algorithm in robot route planning. The raster method is used to build the path matrix, and a corner heuristic function is established to increase the probability of selecting a specified path and improve the search speed of the algorithm. Combining A* algorithm with improved ant colony algorithm, an improved distance heuristic is proposed to avoid falling into local optimal solution. A pheromone volatile factor which can be changed according to the number of iterations was proposed to enhance the global search ability. Based on the related data analysis, the improved ant colony algorithm is better than Ant Colony Algorithm with Multiple Inspired Factor(ACAM )algorithm in resolving problems such as slow convergence rate and preventing entering local optimal solution.

Key words : improved ant colony algorithm；robot；Grid method；A* algorithm