|本期目录/Table of Contents|

[1]徐 洁,张 锐,汪志锋.改进蚁群算法在自动导引车路径规划中的应用[J].工业仪表与自动化装置,2023,(03):88-92.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.018]
　XU Jie,ZHANG Rui,WANG Zhifeng.Application of improved ant colony algorithm in AGV path planning[J].Industrial Instrumentation & Automation,2023,(03):88-92.[doi:10.19950/j.cnki.cn61-1121/th.2023.03.018]
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改进蚁群算法在自动导引车路径规划中的应用

《工业仪表与自动化装置》[ISSN:1000-0682/CN:61-1121/TH]

卷:
期数:
2023年03期
页码:
88-92
栏目:
出版日期:
2023-06-15

文章信息/Info

Title:
Application of improved ant colony algorithm in AGV path planning
文章编号:
1000-0682（2023）02-0088-05
作者:
徐 洁; 张 锐; 汪志锋
上海第二工业大学 智能制造与控制工程学院，上海 200120
Author(s):
XU Jie; ZHANG Rui; WANG Zhifeng
School of Intelligent Manufacturing and Control Engineering，Shanghai Polytechnic University,Shanghai 200120, China
关键词:
路径规划; 蚁群算法; 栅格地图; 自动导引车(AGV)
Keywords:
path planning; ant algorithm; grid map; automated guided vehi(AGV)
分类号:
TP242
DOI:
10.19950/j.cnki.cn61-1121/th.2023.03.018
文献标志码:
A
摘要:
传统蚁群算法求解自动导引车(Automated Guided Vehicle，AGV)路径规划时生成的最优路径弯曲次数多，累积弯曲角度大，造成路径轨迹整体不平滑；算法解算的路径规划结果容易陷入局部最优；处理死锁状态时路径规划方案多样性减少，导致出现寻优结果失真。针对上述情况，该文提出了将蚁群算法与A*算法相结合的优化模型，通过引入弯曲抑制算子以平滑路径；通过比对限制路径信息素，避免陷入局部最优；利用缩回机制应对凹陷障碍时容易出现的死锁情况，避免陷入死锁状态的蚂蚁在循环迭代中死亡。仿真实验结果表明，改进后的蚁群算法在收敛速度、最短路径长度以及路径轨迹平滑度上都优于传统蚁群算法。
Abstract:
When solving AGV path planning by traditional ant colony algorithm,the optimal path has many bending times and large cumulative bending angle,which results in the overall unsmoothness of the path trajectory.The path planning results solved by the algorithm tend to fall into local optimality;When dealing with deadlock state,the diversity of path planning sch-eme is reduced,resulting in the distortion of optimization results.In view of the above situation,this paper proposes an optimization model combining ant colony algorithm and A* algorithm. The bending suppression operator is introduced to smooth the path.By limiting the path phero-mone, local optimum is avoided. The retracting mechanism is used to deal with the deadlock situation which is easy to occur in the depression obstacle,so that the ants trapped in the dea-dlock state will not die in the cyclic iteration.The simulation results show that the improved ant colony algorithm is superior to the traditional ant colony algorithm in convergence speed, shortest path length and path smoothness.

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备注/Memo

备注/Memo:
收稿日期：2023-01-06?div>
?一作者：
徐洁（1979—），女，上海人，硕士，讲师，研究方向为工业过程控制、过程监控与故障诊断。
更新日期/Last Update: 1900-01-01