基于改进蚁群算法的机器人路径规划研究  

Research on Path Planning Based on Improved Ant Colony Algorithm

作　　者：罗继曼 刘丰源 LUO Jiman;LIU Fengyuan(School of Mechanical Engineering,Shenyang Jianzhu University,Shenyang,China,110168)

机构地区：[1]沈阳建筑大学机械工程学院,辽宁沈阳110168

出　　处：《沈阳建筑大学学报（自然科学版）》2024年第6期1126-1136,共11页Journal of Shenyang Jianzhu University：Natural Science

基　　金：国家自然科学基金项目(62003226)。

摘　　要：目的针对传统蚁群算法在全局搜索效率低、易陷入局部最优和局部路径不合理等问题,提出一种融合人工势场的蚁群路径规划算法。方法首先,通过引入人工势场目标方向因子来增强目标方向的引导作用,从而提高搜索效率;然后,考虑路径质量和路径长度,提出新的信息素更新策略,从而得到最优解;最后,该算法利用三角修剪法对规划路径进行平滑处理,提高机器人的运行平稳性和安全性。结果在相同地图中,笔者所提改进算法较传统算法路径长度缩短9.74%;在运行时间上,较传统算法缩短10.71%。结论笔者提出的改进算法在整体路径上减少了拐点,且缩短了行走路径与时间,提高了搜索效率,更符合机器人的实际运行要求。In view of the problems of low global search efficiency,easy to fall into local optima,and unreasonable local paths in traditional ant colony algorithms,this paper proposes a fusion of artificial potential field and ant colony path planning algorithm.This algorithm enhances the guidance effect of the target direction by introducing the artificial potential field target direction factor,thereby improving the search efficiency.At the same time,this algorithm improves the information pheromone update strategy,considering both the quality and length of the path,to obtain better solutions.Finally,this algorithm uses the triangle pruning method to smooth the planned path,improving the stability and safety of the robot′s operation.Simulation and experimental results show that in the same map,the improved algorithm in this paper reduces the path length by 9.74%compared to the traditional algorithm.In terms of running time,it is shortened by 10.71%compared to the traditional algorithm.The conclusion shows that the proposed algorithm in this paper reduces the turning points in the overall path,shortens the walking path and time,improves the search efficiency,and is more in line with the actual operation and requirements of robots.

关 键 词：蚁群算法 路径规划 人工势场 信息素更新策略 三角修剪法 

分 类 号：TP242.2[自动化与计算机技术—检测技术与自动化装置]