Road boundary detection in range imagery for an autonomous robot

{"title":"Road boundary detection in range imagery for an autonomous robot","authors":"U. Sharma, L. Davis","doi":"10.1109/56.20436","DOIUrl":null,"url":null,"abstract":"The authors describe a road-following system for an autonomous land vehicle, based on range image analysis. The system is divided into two parts: low-level data-driven analysis, followed by high-level model-directed search. The sequence of steps performed in order to detect three-dimensional (3-D) road boundaries is as follows. Range data are first converted from spherical into Cartesian coordinates. A quadric (or planar) surface is then fitted to the neighborhood of each range pixel, using a least squires fit method. Based on this fit, minimum and maximum principal surface curvatures are computed at each point to detect edges. Next, using Hough transform techniques, 3-D local line segments are extracted. Finally, model-directed reasoning is applied to detect the road boundaries. >","PeriodicalId":370047,"journal":{"name":"IEEE J. Robotics Autom.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1988-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE J. Robotics Autom.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/56.20436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 18

Abstract

The authors describe a road-following system for an autonomous land vehicle, based on range image analysis. The system is divided into two parts: low-level data-driven analysis, followed by high-level model-directed search. The sequence of steps performed in order to detect three-dimensional (3-D) road boundaries is as follows. Range data are first converted from spherical into Cartesian coordinates. A quadric (or planar) surface is then fitted to the neighborhood of each range pixel, using a least squires fit method. Based on this fit, minimum and maximum principal surface curvatures are computed at each point to detect edges. Next, using Hough transform techniques, 3-D local line segments are extracted. Finally, model-directed reasoning is applied to detect the road boundaries. >
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
自主机器人距离图像中的道路边界检测
作者描述了一种基于距离图像分析的自动陆地车辆道路跟踪系统。该系统分为两部分:底层数据驱动分析和高层模型导向搜索。检测三维(3d)道路边界的步骤顺序如下。距离数据首先从球面坐标转换为笛卡尔坐标。然后使用最小二乘拟合方法将二次曲面(或平面)拟合到每个距离像素的邻域。基于这种拟合,计算每个点的最小和最大主曲面曲率以检测边缘。然后,利用霍夫变换技术提取三维局部线段;最后,应用模型导向推理进行道路边界检测。>
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 去求助
相关文献
Edge, Shade and Mixed Range Detection by Fuzzy Gaussian Filter for an Autonomous Robot
IF 3.3 4区 计算机科学Journal of Intelligent & Robotic SystemsPub Date : 2003-07-01 DOI: 10.1023/A:1025445105604
S. Patnaik, K. Karibasappa
Tillage boundary detection based on RGB imagery classification for an autonomous tractor
IF 0 Korean Journal of Agricultural SciencePub Date : 2020-01-01 DOI: 10.7744/KJOAS.20200006
Gook-Hwan Kim, Dasom Seo, Kyoung-Chul Kim, Youngki Hong, Meong-hun Lee, S. Lee, Hyunjong Kim, H. Ryu, Yong-Joo Kim, Sun-Ok Chung, Dae-Hyun Lee
Wrapper for object detection in an autonomous mobile robot
IF 0 Object recognition supported by user interaction for service robotsPub Date : 2002-12-10 DOI: 10.1109/ICPR.2002.1048411
Nicolas Bredèche, Y. Chevaleyre, L. Hugues
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Omnidirectional supervisory control of a multilegged vehicle using periodic gaits Symbolic derivation of dynamic equations of motion for robot manipulators using Piogram symbolic method A group-theoretic approach to the computation of symbolic part relations Robot calibration and compensation Fixed-axis tool positioning with built-in global interference checking for NC path generation
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1