Unmanned Vehicle Control System Using Microwave Sensors

D. Khablov
{"title":"Unmanned Vehicle Control System Using Microwave Sensors","authors":"D. Khablov","doi":"10.1109/MLSD49919.2020.9247759","DOIUrl":null,"url":null,"abstract":"To effectively manage the flow of unmanned vehicles in large manufacturing plants and warehouses, both in open spaces and indoors, an accurate dynamic positioning system is required. This is necessary to optimize routes in order to increase the speed of movement and prevent collisions. The article considers the application of an autonomous navigation system that uses radar motion sensors together with odometric data. The developed algorithm of adaptive data filtering based on the Kalman filter is described, which allows continuously receiving information about the current position of unmanned vehicles with the required accuracy. As a result, it is possible to optimize the trajectory of all unmanned vehicles in dynamics in order to increase the productivity and reliability of cargo transportation.","PeriodicalId":103344,"journal":{"name":"2020 13th International Conference \"Management of large-scale system development\" (MLSD)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 13th International Conference \"Management of large-scale system development\" (MLSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MLSD49919.2020.9247759","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

To effectively manage the flow of unmanned vehicles in large manufacturing plants and warehouses, both in open spaces and indoors, an accurate dynamic positioning system is required. This is necessary to optimize routes in order to increase the speed of movement and prevent collisions. The article considers the application of an autonomous navigation system that uses radar motion sensors together with odometric data. The developed algorithm of adaptive data filtering based on the Kalman filter is described, which allows continuously receiving information about the current position of unmanned vehicles with the required accuracy. As a result, it is possible to optimize the trajectory of all unmanned vehicles in dynamics in order to increase the productivity and reliability of cargo transportation.
利用微波传感器的无人驾驶车辆控制系统
为了有效地管理大型制造工厂和仓库中无人驾驶车辆的流动,无论是在开放空间还是在室内,都需要精确的动态定位系统。这对于优化路线以提高移动速度和防止碰撞是必要的。本文考虑了雷达运动传感器与里程数据相结合的自主导航系统的应用。提出了一种基于卡尔曼滤波的自适应数据滤波算法,该算法能够以要求的精度连续接收无人车辆当前位置信息。因此,可以对所有无人驾驶车辆的动态轨迹进行优化,以提高货物运输的生产率和可靠性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信