Optimizing image and camera trajectories in robot vision control using on-line boosting

A. Hafez, E. Cervera, C. V. Jawahar
{"title":"Optimizing image and camera trajectories in robot vision control using on-line boosting","authors":"A. Hafez, E. Cervera, C. V. Jawahar","doi":"10.1109/IROS.2007.4399283","DOIUrl":null,"url":null,"abstract":"In this paper, we present a novel boosted robot vision control algorithm. The method utilizes on-line boosting to produce a strong vision-based robot control starting from two weak algorithms. The notion of weak and strong algorithms has been presented in the context of robot vision control, in presence of uncertainty in the measurement process. Appropriate probabilistic error functions are defined for the weak algorithm to evaluate their suitability in the task. An on-line boosting algorithm is employed to derive a final strong algorithm starting from two weak algorithms. This strong one has superior performance both in image and Cartesian spaces. Experiments justify this claim.","PeriodicalId":227148,"journal":{"name":"2007 IEEE/RSJ International Conference on Intelligent Robots and Systems","volume":"83 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE/RSJ International Conference on Intelligent Robots and Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IROS.2007.4399283","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

In this paper, we present a novel boosted robot vision control algorithm. The method utilizes on-line boosting to produce a strong vision-based robot control starting from two weak algorithms. The notion of weak and strong algorithms has been presented in the context of robot vision control, in presence of uncertainty in the measurement process. Appropriate probabilistic error functions are defined for the weak algorithm to evaluate their suitability in the task. An on-line boosting algorithm is employed to derive a final strong algorithm starting from two weak algorithms. This strong one has superior performance both in image and Cartesian spaces. Experiments justify this claim.
基于在线推进的机器人视觉控制中图像和相机轨迹优化
本文提出了一种新的增强机器人视觉控制算法。该方法利用在线增强技术,从两种弱算法出发,产生一种基于视觉的强机器人控制。在机器人视觉控制的背景下,在测量过程中存在不确定性的情况下,提出了弱和强算法的概念。为弱算法定义了适当的概率误差函数,以评估其在任务中的适用性。采用在线增强算法,由两个弱算法推导出最终的强算法。这个强的在图像和笛卡尔空间上都有优越的表现。实验证明了这种说法。
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:604180095
Book学术官方微信