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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)
Department工业控制网络与系统研究室
Conference Name2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2017
Conference DateSeptember 24-28, 2017
Conference PlaceVancouver, Canada
Author of SourceAIRA; Amazon; Bosch; Clearpath; et al.; Guangdong University of Technology
Source PublicationIROS 2017 - IEEE/RSJ International Conference on Intelligent Robots and Systems
PublisherIEEE
Publication PlaceNew York
2017
Pages1818-1823
Indexed ByEI ; CPCI(ISTP)
EI Accession number20180704806907
WOS IDWOS:000426978202021
Contribution Rank1
ISSN2153-0858
ISBN978-1-5386-2682-5
Abstract

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.

Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21539
Collection工业控制网络与系统研究室
Corresponding AuthorLiang W(梁炜)
Affiliation1.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
Recommended Citation
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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