F. Jia, Xiaolong Liu, Jichao Wu, Yunde Shi, Fengyu Xu, Z. S. Zhang
{"title":"基于改进A*算法的多agv自主避障策略研究","authors":"F. Jia, Xiaolong Liu, Jichao Wu, Yunde Shi, Fengyu Xu, Z. S. Zhang","doi":"10.1109/M2VIP.2018.8600834","DOIUrl":null,"url":null,"abstract":"This paper aims at the shortcomings of the traditional A* algorithm in multi-AGV scheduling. On this basis, a multi-AGV autonomous obstacle avoidance scheduling strategy based on improved A* algorithm and traffic control is proposed. By introducing busy-level parameter and weight value for each path, the rate of occupancy of a path can be assessed to make sure that none of the path sections is too busy. On the basis of the improved A* algorithm and given traffic rules and priority, a compound adjustment strategy is formulated to solve the traffic conflict by introducing the speed regulation parameters and the path replanning parameters. As verified by experiments, the dispatch efficiency and stability of the proposed strategy is much higher than traditional algorithms and could effectively achieve autonomous collision avoidance.","PeriodicalId":365579,"journal":{"name":"2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Research on Multi-AGV Autonomous Obstacle Avoidance Strategy Based on Improved A* Algorithm\",\"authors\":\"F. Jia, Xiaolong Liu, Jichao Wu, Yunde Shi, Fengyu Xu, Z. S. Zhang\",\"doi\":\"10.1109/M2VIP.2018.8600834\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper aims at the shortcomings of the traditional A* algorithm in multi-AGV scheduling. On this basis, a multi-AGV autonomous obstacle avoidance scheduling strategy based on improved A* algorithm and traffic control is proposed. By introducing busy-level parameter and weight value for each path, the rate of occupancy of a path can be assessed to make sure that none of the path sections is too busy. On the basis of the improved A* algorithm and given traffic rules and priority, a compound adjustment strategy is formulated to solve the traffic conflict by introducing the speed regulation parameters and the path replanning parameters. As verified by experiments, the dispatch efficiency and stability of the proposed strategy is much higher than traditional algorithms and could effectively achieve autonomous collision avoidance.\",\"PeriodicalId\":365579,\"journal\":{\"name\":\"2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/M2VIP.2018.8600834\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 25th International Conference on Mechatronics and Machine Vision in Practice (M2VIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/M2VIP.2018.8600834","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Multi-AGV Autonomous Obstacle Avoidance Strategy Based on Improved A* Algorithm
This paper aims at the shortcomings of the traditional A* algorithm in multi-AGV scheduling. On this basis, a multi-AGV autonomous obstacle avoidance scheduling strategy based on improved A* algorithm and traffic control is proposed. By introducing busy-level parameter and weight value for each path, the rate of occupancy of a path can be assessed to make sure that none of the path sections is too busy. On the basis of the improved A* algorithm and given traffic rules and priority, a compound adjustment strategy is formulated to solve the traffic conflict by introducing the speed regulation parameters and the path replanning parameters. As verified by experiments, the dispatch efficiency and stability of the proposed strategy is much higher than traditional algorithms and could effectively achieve autonomous collision avoidance.