改进的室内环境移动机器人纯视觉定位方法

Gang Huang, Liangzhu Lu, Yifan Zhang, Gangfu Cao, Zhe Zhou
{"title":"改进的室内环境移动机器人纯视觉定位方法","authors":"Gang Huang,&nbsp;Liangzhu Lu,&nbsp;Yifan Zhang,&nbsp;Gangfu Cao,&nbsp;Zhe Zhou","doi":"10.1007/s43684-024-00075-9","DOIUrl":null,"url":null,"abstract":"<div><p>To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment, a localization method based on scene modeling and recognition has been designed. Firstly, the offline scene model is created by both handcrafted feature and semantic feature. Then, the scene recognition and location calculation are performed online based on the offline scene model. To improve the accuracy of recognition and location calculation, this paper proposes a method that integrates both semantic features matching and handcrafted features matching. Based on the results of scene recognition, the accurate location is obtained through metric calculation with 3D information. The experimental results show that the accuracy of scene recognition is over 90%, and the average localization error is less than 1 meter. Experimental results demonstrate that the localization has a better performance after using the proposed improved method.</p></div>","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s43684-024-00075-9.pdf","citationCount":"0","resultStr":"{\"title\":\"Improved vision-only localization method for mobile robots in indoor environments\",\"authors\":\"Gang Huang,&nbsp;Liangzhu Lu,&nbsp;Yifan Zhang,&nbsp;Gangfu Cao,&nbsp;Zhe Zhou\",\"doi\":\"10.1007/s43684-024-00075-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment, a localization method based on scene modeling and recognition has been designed. Firstly, the offline scene model is created by both handcrafted feature and semantic feature. Then, the scene recognition and location calculation are performed online based on the offline scene model. To improve the accuracy of recognition and location calculation, this paper proposes a method that integrates both semantic features matching and handcrafted features matching. Based on the results of scene recognition, the accurate location is obtained through metric calculation with 3D information. The experimental results show that the accuracy of scene recognition is over 90%, and the average localization error is less than 1 meter. Experimental results demonstrate that the localization has a better performance after using the proposed improved method.</p></div>\",\"PeriodicalId\":71187,\"journal\":{\"name\":\"自主智能系统(英文)\",\"volume\":\"4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s43684-024-00075-9.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"自主智能系统(英文)\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s43684-024-00075-9\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"自主智能系统(英文)","FirstCategoryId":"1093","ListUrlMain":"https://link.springer.com/article/10.1007/s43684-024-00075-9","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

为了解决移动机器人在室内环境中到达目标点后需要调整姿态以便准确操作的问题,我们设计了一种基于场景建模和识别的定位方法。首先,通过手工特征和语义特征创建离线场景模型。然后,根据离线场景模型进行在线场景识别和定位计算。为了提高识别和位置计算的准确性,本文提出了一种集成语义特征匹配和手工特征匹配的方法。在场景识别结果的基础上,通过三维信息的度量计算获得准确的位置。实验结果表明,场景识别的准确率超过 90%,平均定位误差小于 1 米。实验结果表明,使用改进方法后,定位效果更好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved vision-only localization method for mobile robots in indoor environments

To solve the problem of mobile robots needing to adjust their pose for accurate operation after reaching the target point in the indoor environment, a localization method based on scene modeling and recognition has been designed. Firstly, the offline scene model is created by both handcrafted feature and semantic feature. Then, the scene recognition and location calculation are performed online based on the offline scene model. To improve the accuracy of recognition and location calculation, this paper proposes a method that integrates both semantic features matching and handcrafted features matching. Based on the results of scene recognition, the accurate location is obtained through metric calculation with 3D information. The experimental results show that the accuracy of scene recognition is over 90%, and the average localization error is less than 1 meter. Experimental results demonstrate that the localization has a better performance after using the proposed improved method.

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
CiteScore
3.90
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