基于云边协同计算的多AGV导航与避障技术的研究  

Research on Multi AGV Navigation and Obstacle Avoidance Technology Based on Cloud Edge Collaborative Computing

作　　者：于会敏[1] 韩宏飞 韩召[1] 张志军 YU Huimin;HAN Hongfei;HAN Zhao;ZHANG Zhijun(School of Electrical and Automation Engineering,Liaoning Institute of Science and Technology,Benxi Liaoning 117004,China;Zhuzhou CRRC Times Electric Co.,Ltd.,Zhuzhou Hunan 412000,China)

机构地区：[1]辽宁科技学院电气与自动化工程学院,辽宁本溪117004 [2]株洲中车时代电气股份有限公司,湖南株洲412000

出　　处：《辽宁科技学院学报》2024年第4期44-47,共4页Journal of Liaoning Institute of Science and Technology

基　　金：辽宁省教育厅2022基本面上项目“机器人一体化电机设计及研究”(LJKMZ20221700).

摘　　要：AGV(Automated Guided Vehicle)作为数字化工厂中主要的运输载体,其自主导航与避障是重要技术之一。由于其任务指派及导航算法复杂且计算量巨大,导致了加工车间的多AGV物流配送会产生延迟问题。为了提高AGV运输的效率,文章提出了基于云边协同计算技术的解决方案,利用人工智能和工业物联网技术,将AGV运输车辆、加工环境与工艺联系起来,中心云接受来自边缘云节点的信息,并将AGV任务指派及全局规划路径信息送给边缘云,边缘侧的AGV负责现场环境信息的收集与局部路径规划。使用云边协同计算技术后,多AGV导航与避障中遇到的延迟问题得到了缓解,且在物流配送过程中响应速度更快,资源利用更加合理。AGV(Automated Guided Vehicle)is the main transportation carrier in digital factories,and its autonomous navigation and obstacle avoidance are important technologies.Due to the complex task assignment and navigation algorithms,as well as the enormous computational complexity,there is a delay problem in the logistics distribution of multiple AGVs in the processing workshop.In order to improve the efficiency of AGV transportation.The article proposes a solution based on cloud edge collaborative computing technology,which utilizes artificial intelligence and industrial Internet of Things technology to link AGV transport vehicles,processing environments,and processes.The central cloud receives information from edge training cloud nodes and sends AGV task assignments and global planning path information to edge training cloud.The AGV on the edge image side is responsible for collecting on-site environmental information and local path planning.After using cloud edge collaborative computing technology,the delay problem encountered in multi AGV navigation and obstacle avoidance has been alleviated,and the response speed is faster and the resource utilization is more reasonable in the logistics distribution process.

关 键 词：云边协同计算 路径规划 动态避障 

分 类 号：TP242.6[自动化与计算机技术—检测技术与自动化装置]