天空之眼:一种面向室内环境的单目教学与重复系统

N. Zhang, M. Warren, T. Barfoot
{"title":"天空之眼:一种面向室内环境的单目教学与重复系统","authors":"N. Zhang, M. Warren, T. Barfoot","doi":"10.1109/CRV.2018.00056","DOIUrl":null,"url":null,"abstract":"Visual Teach and Repeat (VT&R) allows a robotic vehicle to navigate autonomously along a network of paths in the presence of illumination and scene changes. Traditionally, the system uses a stereo camera as the primary sensor for triangulating visual landmarks and often operates in highly textured outdoor environments. In this paper, we modify the VT&R system to use a monocular pipeline under the same framework, but also target indoor operation as a demonstration of a low-cost VT&R solution for warehouse logistics in a visually difficult environment. Unlike previous monocular VT&R solutions, we make no assumptions about the nature of the scene (e.g., local ground planarity). This allows the system to be readily deployable on more vehicles in a wider range of environments. To test the system, and motivated by a warehouse navigation application, an upward pointing camera is mounted on a Clearpath Husky ground vehicle. We demonstrate the vehicle is able to navigate with a 99.6% autonomy rate using such a system during 1.1 kilometers of driving, with an average scene depth that varies from 8-16 meters. The cross-track deviation from the taught path is less than 0.5 meters over 90% of the path, reaching a maximum of 0.85 meters and an average of 0.26 meters.","PeriodicalId":281779,"journal":{"name":"2018 15th Conference on Computer and Robot Vision (CRV)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Eye on the Sky: An Upward-Looking Monocular Teach-and-Repeat System for Indoor Environments\",\"authors\":\"N. Zhang, M. Warren, T. Barfoot\",\"doi\":\"10.1109/CRV.2018.00056\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visual Teach and Repeat (VT&R) allows a robotic vehicle to navigate autonomously along a network of paths in the presence of illumination and scene changes. Traditionally, the system uses a stereo camera as the primary sensor for triangulating visual landmarks and often operates in highly textured outdoor environments. In this paper, we modify the VT&R system to use a monocular pipeline under the same framework, but also target indoor operation as a demonstration of a low-cost VT&R solution for warehouse logistics in a visually difficult environment. Unlike previous monocular VT&R solutions, we make no assumptions about the nature of the scene (e.g., local ground planarity). This allows the system to be readily deployable on more vehicles in a wider range of environments. To test the system, and motivated by a warehouse navigation application, an upward pointing camera is mounted on a Clearpath Husky ground vehicle. We demonstrate the vehicle is able to navigate with a 99.6% autonomy rate using such a system during 1.1 kilometers of driving, with an average scene depth that varies from 8-16 meters. The cross-track deviation from the taught path is less than 0.5 meters over 90% of the path, reaching a maximum of 0.85 meters and an average of 0.26 meters.\",\"PeriodicalId\":281779,\"journal\":{\"name\":\"2018 15th Conference on Computer and Robot Vision (CRV)\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 15th Conference on Computer and Robot Vision (CRV)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2018.00056\",\"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 15th Conference on Computer and Robot Vision (CRV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2018.00056","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

视觉教学和重复(VT&R)允许机器人车辆在照明和场景变化的情况下沿着路径网络自主导航。传统上,该系统使用立体摄像机作为主要传感器来三角化视觉地标,通常在高度纹理的户外环境中运行。在本文中,我们修改了VT&R系统,在相同的框架下使用单目管道,但也针对室内操作,作为在视觉困难环境下仓库物流的低成本VT&R解决方案的演示。与以前的单目VT&R解决方案不同,我们没有对场景的性质(例如,局部地面平面度)进行假设。这使得该系统可以在更广泛的环境中部署在更多的车辆上。为了测试该系统,在仓库导航应用程序的激励下,在Clearpath Husky地面车辆上安装了一个向上指向的摄像头。我们证明,在1.1公里的行驶中,车辆能够使用该系统以99.6%的自主率导航,平均场景深度从8米到16米不等。90%以上的路径与教学路径的交叉偏差小于0.5米,最大偏差为0.85米,平均偏差为0.26米。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Eye on the Sky: An Upward-Looking Monocular Teach-and-Repeat System for Indoor Environments
Visual Teach and Repeat (VT&R) allows a robotic vehicle to navigate autonomously along a network of paths in the presence of illumination and scene changes. Traditionally, the system uses a stereo camera as the primary sensor for triangulating visual landmarks and often operates in highly textured outdoor environments. In this paper, we modify the VT&R system to use a monocular pipeline under the same framework, but also target indoor operation as a demonstration of a low-cost VT&R solution for warehouse logistics in a visually difficult environment. Unlike previous monocular VT&R solutions, we make no assumptions about the nature of the scene (e.g., local ground planarity). This allows the system to be readily deployable on more vehicles in a wider range of environments. To test the system, and motivated by a warehouse navigation application, an upward pointing camera is mounted on a Clearpath Husky ground vehicle. We demonstrate the vehicle is able to navigate with a 99.6% autonomy rate using such a system during 1.1 kilometers of driving, with an average scene depth that varies from 8-16 meters. The cross-track deviation from the taught path is less than 0.5 meters over 90% of the path, reaching a maximum of 0.85 meters and an average of 0.26 meters.
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:481959085
Book学术官方微信