Calibration of a Rotating Laser Range Finder using Intensity Features

Kavindie Katuwandeniya, Ravindra Ranasinghe, Lakshitha Dantanarayana, G. Dissanayake, Dikai Liu
{"title":"Calibration of a Rotating Laser Range Finder using Intensity Features","authors":"Kavindie Katuwandeniya, Ravindra Ranasinghe, Lakshitha Dantanarayana, G. Dissanayake, Dikai Liu","doi":"10.1109/ICARCV.2018.8581350","DOIUrl":null,"url":null,"abstract":"This paper presents an algorithm for calibrating a “3D range sensor” constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process.","PeriodicalId":395380,"journal":{"name":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","volume":"385 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICARCV.2018.8581350","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

This paper presents an algorithm for calibrating a “3D range sensor” constructed using a two-dimensional laser range finder (LRF), that is rotated about an axis using a motor to obtain a three-dimensional point cloud. The sensor assembly is modelled as a two degree of freedom open kinematic chain, with one joint corresponding to the axis of the internal mirror in the LRF and the other joint set along the axis of the motor used to rotate the body of the LRF. In the application described in this paper, the sensor unit is mounted on a robot arm used for infrastructure inspection. The objective of the calibration process is to obtain the coordinate transform required to compute the locations of the 3D points with respect to the robot coordinate frame. Proposed strategy uses observations of a set of markers arbitrarily placed in the environment. Distances between these markers are measured and a metric multidimensional scaling is used to obtain the coordinates of the markers with respect to a local coordinate frame. Intensity associated with each beam point of a laser scan is used to locate the reflective markers in the 3D point cloud and a least squares problem is formulated to compute the relationship between the robot coordinate frame, LRF coordinate frame and the marker coordinate frame. Results from experiments using the robot, LRF combination to map a cavity inside a steel bridge structure are presented to demonstrate the effectiveness of the calibration process.
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
利用强度特征校准旋转激光测距仪
本文提出了一种基于二维激光测距仪(LRF)的“三维距离传感器”的标定算法,该传感器由电机绕轴旋转以获得三维点云。传感器组件被建模为一个两自由度的开放运动链,其中一个关节对应于LRF内镜的轴线,另一个关节沿着用于旋转LRF体的电机的轴线设置。在本文描述的应用中,传感器单元安装在用于基础设施检查的机械臂上。标定过程的目的是获得计算三维点相对于机器人坐标系的位置所需的坐标变换。提出的策略利用对环境中任意放置的一组标记的观察。测量这些标记之间的距离,并使用度量多维缩放来获得标记相对于局部坐标系的坐标。利用激光扫描各光束点的强度来定位三维点云中的反射标记点,并建立最小二乘问题来计算机器人坐标框、LRF坐标框和标记点坐标框之间的关系。利用机器人和LRF组合对钢桥结构内的空腔进行了标定,验证了标定过程的有效性。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Virtual Commissioning of Machine Vision Applications in Aero Engine Manufacturing Barrier Lyapunov Function Based Output-constrained Control of Nonlinear Euler-Lagrange Systems Visuo-Tactile Recognition of Daily-Life Objects Never Seen or Touched Before Synthesis of Point Memory-Based Adaptive Gain Robust Controllers with Guaranteed $\mathcal{L}_{2}$ Gain Performance for a Class of Uncertain Time-Delay Systems Formation Control of Multiple Mobile Robots with Large Obstacle Avoidance
×
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