A Visual-Inertial Servoing Method for Tracking Object with Two Landmarks and an Inertial Measurement Unit

被引:7
|
作者
Nguyen, Ho-Quoc-Phuong [2 ]
Kang, Hee-Jun [1 ]
Suh, Young-Soo [1 ]
机构
[1] Univ Ulsan, Sch Elect Engn, Ulsan 680749, South Korea
[2] Univ Ulsan, Grad Sch Elect Engn, Ulsan 680749, South Korea
关键词
Attitude estimation; inertial sensors; task function approach; visual servoing; visual-inertial jacobian; VISION; MOTION;
D O I
10.1007/s12555-011-0214-3
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper introduces a robot visual-inertial tracking algorithm for a robot manipulator intended to track an object using inertial sensors incorporated into the object. To create this algorithm, the inertial Jacobian is first newly defined in order to show the relationship between an angle set velocity vector of the object and the angular velocity vector of the robot tip. Then, the inertial Jacobian is combined with the conventional image Jacobian. Therefore, the proposed algorithm requires only two landmarks with the help of an inertial measurement unit to track a moving object with six degrees of freedom, while at least three landmarks are required in the conventional stereo visual servoing algorithm. Further, the possession of a multi-rate controller allows the integration system to out-perform conventional systems in the tracking of an object's attitude change. A suggested application of the proposed method is tracking and selection of a container from a shipping vessel that is being affected by large waves. Simulations and experiments were conducted to verify the feasibility of the proposed methodology.
引用
收藏
页码:317 / 327
页数:11
相关论文
共 50 条
  • [31] Accurate Initialization Method for Monocular Visual-Inertial SLAM
    Amrani, Ahderraouf
    Wang, Hesheng
    2019 3RD INTERNATIONAL SYMPOSIUM ON AUTONOMOUS SYSTEMS (ISAS 2019), 2019, : 159 - 164
  • [32] Visual-Inertial Navigation System Based on Virtual Inertial Sensors
    Cai, Yunpiao
    Qian, Weixing
    Zhao, Jiaqi
    Dong, Jiayi
    Shen, Tianxiao
    APPLIED SCIENCES-BASEL, 2023, 13 (12):
  • [33] Deep Gait Tracking With Inertial Measurement Unit
    Sui, Jien De
    Chang, Tian Sheuan
    IEEE SENSORS LETTERS, 2019, 3 (11)
  • [34] Visual-Inertial Adaptive Fusion Algorithm Based on Measurement Uncertainty
    Huang Xinxin
    Ren Yongjie
    Ma Keyao
    Niu Zhiyuan
    ACTA OPTICA SINICA, 2023, 43 (21)
  • [35] Multi-Robot Joint Visual-Inertial Localization and 3-D Moving Object Tracking
    Zhu, Pengxiang
    Ren, Wei
    2020 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2020, : 11573 - 11580
  • [36] An integrated visual-inertial technique for structural displacement and velocity measurement
    Chang, C. C.
    Xiao, X. H.
    SMART STRUCTURES AND SYSTEMS, 2010, 6 (09) : 1025 - 1039
  • [37] A Framework for Visual-Inertial Object-Level Simultaneous Localization and Mapping
    Jung, Jae Hyung
    Park, Chan Gook
    2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS, 2023, : 1335 - 1340
  • [38] VIFTrack!-visual-inertial feature tracking based on affine photometric warping
    Aufderheide, Dominik
    Krybus, Werner
    Edwards, Gerard
    COMPUTATIONAL VISION AND MEDICAL IMAGE PROCESSING IV, 2014, : 155 - 160
  • [39] A Visual-inertial Fusion Based Tracking System for Mobile Augmented Reality
    Lin, Cheng
    Wang, Lianghao
    Li, Dongxiao
    Zhang, Ming
    2015 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING, COMMUNICATIONS AND COMPUTING (ICSPCC), 2015, : 956 - 960
  • [40] Visual-LiDAR-Inertial Odometry: A New Visual-Inertial SLAM Method based on an iPhone 12 Pro
    Jin, Lingqiu
    Ye, Cang
    2023 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, IROS, 2023, : 1511 - 1516