AGV optimal path planning based on improved ant colony algorithm

摘要：

　　Using the traditional Ant Colony Algorithm for AGV path planning is easy to fall into the local optimal solution and lacking the capability of obstacle avoidance in the complex storage environment.In this paper,by constructing the MAKLINK undirected network routes and the heuristic function is optimized in the Ant Colony Algorithm,then the AGV path reaches the global optimal path and has the ability to avoid obstacles.According to research,the improved Ant Colony Algorithm proposed in this paper is superior to the traditional Ant Colony Algorithm in terms of convergence speed and the distance of optimal path planning.

作者: Chengwei He Jian Mao

作者单位: School of Mechanical and Automotive Engineering,Shanghai University of Engineering and Technology,Longteng Road No.333,201620,Shanghai,China

会议类型: 国际会议

会议名称: 2018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)(2018第二届电子信息技术与计算机工程国际会议)(EITCE2018)

会议地点: 上海

会议语种:英文

页码: 1-6

在线出版日期: 2018-10-12（万方平台首次上网日期，不代表论文的发表时间）