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题名:
Kinematic chain based multi-joint capturing using monocular visual-inertial measurements
作者: 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
通讯作者: Liang W(梁炜)
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: IROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
会议录出版者: IEEE
会议录出版地: New York
出版日期: 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
Citation statistics:
内容类型: 会议论文
URI标识: http://210.72.131.170/handle/173321/21539
Appears in Collections:工业控制网络与系统研究室_会议论文

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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
3.KS 67260, United States
4.Department of Mechanical, Aerospace and Biomedical Engineering, University of Tennessee, Knoxville
5.TN 37996, United States

Recommended Citation:
Zhang YL,Liang W,He, Hongsheng,et al. Kinematic chain based multi-joint capturing using monocular visual-inertial measurements[C]. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017. Vancouver, Canada. September 24-28, 2017.Kinematic chain based multi-joint capturing using monocular visual-inertial measurements.
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文件名: Kinematic chain based multi-joint capturing using monocular visual-inertial measurements.pdf
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