A Framework for IBVS Using Virtual Work

Author:

Yu Qiuda1ORCID,Wei Wu123ORCID,Wang Dongliang4,Li Yanjie5,Gao Yong1ORCID

Affiliation:

1. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510641, China

2. The Key Laboratory of Autonomous Systems and Networked Control, Ministry of Education, Guangzhou 510640, China

3. Unmanned Aerial Vehicle Systems Engineering Technology Research Center of Guangdong, South China University of Technology, Guangzhou 510641, China

4. School of Department of Electronic and Information Engineering, Shantou University, Shantou 515063, China

5. School of Automation, Jiangsu University of Science and Technology, Zhenjiang 212100, China

Abstract

The visual servoing of manipulators is challenged by two main problems: the singularity of the inverse Jacobian and the physical constraints of a manipulator. In order to overcome the singularity issue, this paper presents a novel approach for image-based visual servoing (IBVS), which converts the propagation of errors in the image plane into the conduction of virtual forces using the principle of virtual work. This approach eliminates the need for Jacobian inversion computations and prevents matrix inversion singularity. To tackle physical constraints, reverse thinking is adopted to derive the function of the upper and lower bounds of the joint velocity on the joint angle. This enables the proposed method to configure the physical constraints of the robot in a more intuitive manner. To validate the effectiveness of the proposed method, an eye-in-hand system based on UR5 in VREP, as well as a physical robot, were established.

Funder

Science and Technology Planning Project of Guangdong

Publisher

MDPI AG

Reference28 articles.

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2. Vision-based formation control of mobile robots with FOV constraints and unknown feature depth;Miao;IEEE Trans. Control Syst. Technol.,2020

3. An optimal visual servo trajectory planning method for manipulators based on system nondeterministic model;Qi;Robotica,2022

4. Thomas, J., Loianno, G., Sreenath, K., and Kumar, V. (June, January 31). Toward image based visual servoing for aerial grasping and perching. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Hong Kong, China.

5. Song, J.B. (2010, January 27–30). Object tracking and visual servoing using features computed from local feature descriptor. Proceedings of the IEEE international Conference on Control, Automation and Systems (ICCAS), Gyeonggi-do, Republic of Korea.

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