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Kinematic chain based multi-joint capturing using monocular visual-inertial measurements
Zhang YL(张吟龙); Liang W(梁炜); He, Hongsheng; Tan JD(谈金东)
作者部门工业控制网络与系统研究室
会议名称2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
会议日期September 24-28, 2017
会议地点Vancouver, Canada
会议主办者AIRA; Amazon; Bosch; Clearpath; et al.; Guangdong University of Technology
会议录名称IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
出版者IEEE
出版地New York
2017
页码1818-1823
收录类别EI ; CPCI(ISTP)
EI收录号20180704806907
WOS记录号WOS:000426978202021
产权排序1
ISSN号2153-0858
ISBN号978-1-5386-2682-5
摘要

Combining light-weight visual and inertial modalities for motion capturing has been popular in robotics researches. There exist scale ambiguity, inaccurate pose estimation with little or no baseline, incremental drifts over time in visual-inertial fusion. Thus, in this paper, we propose a robust motion capturing method based on the multi-joint kinematic chain using monocular visual-inertial sensors. Our method is able to recover monocular visual scale through the joint geometry constraint. Additionally, we take inertial pre-integration to assist visual outlier removal using Maximum A Posteriori method. Ultimately, the kinematic chain model is leveraged to constrain the associated multiple visual-inertial estimation drifts during long time tracking. In the experiments, we conduct multi-joint capturing on a robotic arm. The quality of motion reconstruction is evaluated by comparing the estimated results with the measurements from an optical motion tracking system OptiTrack.

语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21539
专题工业控制网络与系统研究室
通讯作者Liang W(梁炜)
作者单位1.Key Laboratory of Networked Control Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Department of Electrical Engineering and Computer Science, Wichita State University, Wichita, KS 67260, United States
3.Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville, TN 37996, United States
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GB/T 7714
Zhang YL,Liang W,He, Hongsheng,et al. Kinematic chain based multi-joint capturing using monocular visual-inertial measurements[C]//AIRA; Amazon; Bosch; Clearpath; et al.; Guangdong University of Technology. New York:IEEE,2017:1818-1823.
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