IHUVS: Infinite Homography-Based Uncalibrated Methodology for Robotic Visual Servoing

Xiaoyu Lei; Zhongtao Fu; Emmanouil Spyrakos-Papastavridis; Jiabin Pan; Miao Li; Xubing Chen

doi:10.1109/TIE.2023.3279519

IHUVS: Infinite Homography-Based Uncalibrated Methodology for Robotic Visual Servoing

Xiaoyu Lei, Zhongtao Fu^*, Emmanouil Spyrakos-Papastavridis, Jiabin Pan, Miao Li, Xubing Chen

^*Corresponding author for this work

Engineering

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

The construction of task functions in robotic manipulation is of paramount importance for uncalibrated visual servoing. The existing methods generally use image information as control variables and estimate the image Jacobian matrix online, thus possessing issues relating to convergence, and image Jacobian matrix singularities. Therefore, this article proposes a novel methodology dubbed infinite homography-based uncalibrated visual servoing (IHUVS), in which the visual control of the robot end-effector pose is decomposed into its rotational and translational components. The corresponding rotational controller designs the visual servoing task function using the relationship between the infinite homography matrix and rotation matrix, and employs the Kronecker product to derive linear equations for rotational control, as well as to conduct the associated task error analysis. Meanwhile, the translational controller utilizes Kalman filtering for online estimation of the Jacobian matrix that is required by the proportional control scheme. The robot end-effector motion in the Cartesian space is generated via the IHUVS method, without knowing the camera's intrinsic parameters and the robot hand-eye relationship. A simulation analysis is carried out to assess the algorithm's numerical performance, while robotic visual servoing experiments are also conducted to verify the accuracy and efficacy of the proposed IHUVS method.

Original language	English
Pages (from-to)	3822-3831
Number of pages	10
Journal	IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
Volume	71
Issue number	4
DOIs	https://doi.org/10.1109/TIE.2023.3279519
Publication status	Published - 1 Apr 2024

Keywords

Infinite homography matrix
Kronecker product
rotational and translational controller
uncalibrated visual servoing

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10.1109/TIE.2023.3279519

Cite this

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title = "IHUVS: Infinite Homography-Based Uncalibrated Methodology for Robotic Visual Servoing",

abstract = "The construction of task functions in robotic manipulation is of paramount importance for uncalibrated visual servoing. The existing methods generally use image information as control variables and estimate the image Jacobian matrix online, thus possessing issues relating to convergence, and image Jacobian matrix singularities. Therefore, this article proposes a novel methodology dubbed infinite homography-based uncalibrated visual servoing (IHUVS), in which the visual control of the robot end-effector pose is decomposed into its rotational and translational components. The corresponding rotational controller designs the visual servoing task function using the relationship between the infinite homography matrix and rotation matrix, and employs the Kronecker product to derive linear equations for rotational control, as well as to conduct the associated task error analysis. Meanwhile, the translational controller utilizes Kalman filtering for online estimation of the Jacobian matrix that is required by the proportional control scheme. The robot end-effector motion in the Cartesian space is generated via the IHUVS method, without knowing the camera's intrinsic parameters and the robot hand-eye relationship. A simulation analysis is carried out to assess the algorithm's numerical performance, while robotic visual servoing experiments are also conducted to verify the accuracy and efficacy of the proposed IHUVS method.",

keywords = "Infinite homography matrix, Kronecker product, rotational and translational controller, uncalibrated visual servoing",

author = "Xiaoyu Lei and Zhongtao Fu and Emmanouil Spyrakos-Papastavridis and Jiabin Pan and Miao Li and Xubing Chen",

note = "Funding Information: This work was supported by the Natural Science Foundation of China under Grant 51805380 and Grant 51875415; in part by the Foundation of State Key Laboratory of Digital Manufacturing Equipment and Technology under Grant DMETKF2022019; in part by the Royal Society International Exchanges 2021 Cost Share (RSNSFC) award IEC\NSFC\211345; and in part by the Central Guidance on Local Science and Technology Development Foundation of Hubei Province under Grant 2019ZYYD010. Publisher Copyright: {\textcopyright} 1982-2012 IEEE.",

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AU - Spyrakos-Papastavridis, Emmanouil

AU - Pan, Jiabin

AU - Li, Miao

AU - Chen, Xubing

N1 - Funding Information: This work was supported by the Natural Science Foundation of China under Grant 51805380 and Grant 51875415; in part by the Foundation of State Key Laboratory of Digital Manufacturing Equipment and Technology under Grant DMETKF2022019; in part by the Royal Society International Exchanges 2021 Cost Share (RSNSFC) award IEC\NSFC\211345; and in part by the Central Guidance on Local Science and Technology Development Foundation of Hubei Province under Grant 2019ZYYD010. Publisher Copyright: © 1982-2012 IEEE.

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N2 - The construction of task functions in robotic manipulation is of paramount importance for uncalibrated visual servoing. The existing methods generally use image information as control variables and estimate the image Jacobian matrix online, thus possessing issues relating to convergence, and image Jacobian matrix singularities. Therefore, this article proposes a novel methodology dubbed infinite homography-based uncalibrated visual servoing (IHUVS), in which the visual control of the robot end-effector pose is decomposed into its rotational and translational components. The corresponding rotational controller designs the visual servoing task function using the relationship between the infinite homography matrix and rotation matrix, and employs the Kronecker product to derive linear equations for rotational control, as well as to conduct the associated task error analysis. Meanwhile, the translational controller utilizes Kalman filtering for online estimation of the Jacobian matrix that is required by the proportional control scheme. The robot end-effector motion in the Cartesian space is generated via the IHUVS method, without knowing the camera's intrinsic parameters and the robot hand-eye relationship. A simulation analysis is carried out to assess the algorithm's numerical performance, while robotic visual servoing experiments are also conducted to verify the accuracy and efficacy of the proposed IHUVS method.

AB - The construction of task functions in robotic manipulation is of paramount importance for uncalibrated visual servoing. The existing methods generally use image information as control variables and estimate the image Jacobian matrix online, thus possessing issues relating to convergence, and image Jacobian matrix singularities. Therefore, this article proposes a novel methodology dubbed infinite homography-based uncalibrated visual servoing (IHUVS), in which the visual control of the robot end-effector pose is decomposed into its rotational and translational components. The corresponding rotational controller designs the visual servoing task function using the relationship between the infinite homography matrix and rotation matrix, and employs the Kronecker product to derive linear equations for rotational control, as well as to conduct the associated task error analysis. Meanwhile, the translational controller utilizes Kalman filtering for online estimation of the Jacobian matrix that is required by the proportional control scheme. The robot end-effector motion in the Cartesian space is generated via the IHUVS method, without knowing the camera's intrinsic parameters and the robot hand-eye relationship. A simulation analysis is carried out to assess the algorithm's numerical performance, while robotic visual servoing experiments are also conducted to verify the accuracy and efficacy of the proposed IHUVS method.

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IHUVS: Infinite Homography-Based Uncalibrated Methodology for Robotic Visual Servoing

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