通过优化任务分配提高自动仓库吞吐量并在已开发的仿真工具中验证算法

Nikolaos Baras, Antonios Chatzisavvas, Dimitris Ziouzios, M. Dasygenis
{"title":"通过优化任务分配提高自动仓库吞吐量并在已开发的仿真工具中验证算法","authors":"Nikolaos Baras, Antonios Chatzisavvas, Dimitris Ziouzios, M. Dasygenis","doi":"10.3390/AUTOMATION2030007","DOIUrl":null,"url":null,"abstract":"It is evident that over the last years, the usage of robotics in warehouses has been rapidly increasing. The usage of robot vehicles in storage facilities has resulted in increased efficiency and improved productivity levels. The robots, however, are only as efficient as the algorithms that govern them. Many researchers have attempted to improve the efficiency of industrial robots by improving on the internal routing of a warehouse, or by finding the best locations for charging power stations. Because of the popularity of the problem, many research works can be found in the literature regarding warehouse routing. The majority of these algorithms found in the literature, however, are statically designed and cannot handle multi-robot situations, especially when robots have different characteristics. The proposed algorithm of this paper attempts to give the following solution to this issue: utilizing more than one robot simultaneously to allocate tasks and tailor the navigation path of each robot based on its characteristics, such as its speed, type and current location within the warehouse so as to minimize the task delivery timing. Moreover, the algorithm finds the optimal location for the placement of power stations. We evaluated the proposed methodology in a synthetic realistic environment and demonstrated that the algorithm is capable of finding an improved solution within a realistic time frame.","PeriodicalId":90013,"journal":{"name":"Mediterranean Conference on Control & Automation : [proceedings]. IEEE Mediterranean Conference on Control & Automation","volume":"39 4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Improving Automatic Warehouse Throughput by Optimizing Task Allocation and Validating the Algorithm in a Developed Simulation Tool\",\"authors\":\"Nikolaos Baras, Antonios Chatzisavvas, Dimitris Ziouzios, M. Dasygenis\",\"doi\":\"10.3390/AUTOMATION2030007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"It is evident that over the last years, the usage of robotics in warehouses has been rapidly increasing. The usage of robot vehicles in storage facilities has resulted in increased efficiency and improved productivity levels. The robots, however, are only as efficient as the algorithms that govern them. Many researchers have attempted to improve the efficiency of industrial robots by improving on the internal routing of a warehouse, or by finding the best locations for charging power stations. Because of the popularity of the problem, many research works can be found in the literature regarding warehouse routing. The majority of these algorithms found in the literature, however, are statically designed and cannot handle multi-robot situations, especially when robots have different characteristics. The proposed algorithm of this paper attempts to give the following solution to this issue: utilizing more than one robot simultaneously to allocate tasks and tailor the navigation path of each robot based on its characteristics, such as its speed, type and current location within the warehouse so as to minimize the task delivery timing. Moreover, the algorithm finds the optimal location for the placement of power stations. We evaluated the proposed methodology in a synthetic realistic environment and demonstrated that the algorithm is capable of finding an improved solution within a realistic time frame.\",\"PeriodicalId\":90013,\"journal\":{\"name\":\"Mediterranean Conference on Control & Automation : [proceedings]. IEEE Mediterranean Conference on Control & Automation\",\"volume\":\"39 4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mediterranean Conference on Control & Automation : [proceedings]. IEEE Mediterranean Conference on Control & Automation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3390/AUTOMATION2030007\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mediterranean Conference on Control & Automation : [proceedings]. IEEE Mediterranean Conference on Control & Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3390/AUTOMATION2030007","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5

摘要

很明显,在过去的几年中,机器人在仓库中的使用一直在迅速增加。在仓储设施中使用机器人车辆提高了效率,提高了生产率水平。然而,机器人的效率取决于控制它们的算法。许多研究人员试图通过改进仓库的内部路线,或找到充电站的最佳位置,来提高工业机器人的效率。由于这个问题的普及,在文献中可以找到许多关于仓库路由的研究工作。然而,在文献中发现的大多数算法都是静态设计的,不能处理多机器人的情况,特别是当机器人具有不同的特征时。本文提出的算法试图给出以下解决方案:同时使用多个机器人来分配任务,并根据每个机器人的速度、类型和当前在仓库中的位置等特征来定制每个机器人的导航路径,以最小化任务交付时间。此外,该算法还为电站的布局找到了最优位置。我们在一个合成的现实环境中评估了所提出的方法,并证明该算法能够在现实的时间框架内找到改进的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving Automatic Warehouse Throughput by Optimizing Task Allocation and Validating the Algorithm in a Developed Simulation Tool
It is evident that over the last years, the usage of robotics in warehouses has been rapidly increasing. The usage of robot vehicles in storage facilities has resulted in increased efficiency and improved productivity levels. The robots, however, are only as efficient as the algorithms that govern them. Many researchers have attempted to improve the efficiency of industrial robots by improving on the internal routing of a warehouse, or by finding the best locations for charging power stations. Because of the popularity of the problem, many research works can be found in the literature regarding warehouse routing. The majority of these algorithms found in the literature, however, are statically designed and cannot handle multi-robot situations, especially when robots have different characteristics. The proposed algorithm of this paper attempts to give the following solution to this issue: utilizing more than one robot simultaneously to allocate tasks and tailor the navigation path of each robot based on its characteristics, such as its speed, type and current location within the warehouse so as to minimize the task delivery timing. Moreover, the algorithm finds the optimal location for the placement of power stations. We evaluated the proposed methodology in a synthetic realistic environment and demonstrated that the algorithm is capable of finding an improved solution within a realistic time frame.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信