AGV optimal path planning based on improved ant colony algorithm
Chengwei HeJian Mao
School of Mechanical and Automotive Engineering,Shanghai University of Engineering and Technology
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.
会议名称：
2018 2nd International Conference on Electronic Information Technology and Computer Engineering （EITCE 2018）
会议时间：
2018-10-12
会议地点：
中国上海
- 专辑：
信息科技
- 专题：
自动化技术
- 分类号：
TP18
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