Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing

Wen Wang; Xiaobin Xu; Ziheng Chen; Zhiqiang Zhang; Haojie Zhang; Zhiying Tan

doi:10.1145/3598151.3598186

Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing

Wen Wang, Xiaobin Xu^*, Ziheng Chen, Zhiqiang Zhang, Haojie Zhang, Zhiying Tan

^*Corresponding author for this work

Hohai University Changzhou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

A visual servoing control method based on depth point cloud is proposed to solve the problem of pose adjustment before obstacle surmounting of a rocker arm tracked robot. By pre-processing the acquired point cloud, a positional error model is created. Combined with the robot kinematics model, the adaptive control law is designed based on Lyapunov method, and the stability of the control algorithm is proved. Simulation results show that, compared with PID control and sliding mode control algorithm, the proposed control algorithm has faster convergence speed and smoother trajectory. The robot can reach the desired pose efficiently in 13. 5s in actual testing.

Original language	English
Title of host publication	Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023
Editors	Aiguo Song, Maki Habib
Publisher	Association for Computing Machinery
Pages	209-214
Number of pages	6
ISBN (Electronic)	9781450398107
DOIs	https://doi.org/10.1145/3598151.3598186
Publication status	Published - 12 May 2023
Externally published	Yes
Event	3rd International Conference on Robotics and Control Engineering, RobCE 2023 - Nanjing, China Duration: 12 May 2023 → 14 May 2023

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	3rd International Conference on Robotics and Control Engineering, RobCE 2023
Country/Territory	China
City	Nanjing
Period	12/05/23 → 14/05/23

Keywords

Depth point cloud
Lyapunov method
Rocker arm tracked robot
Visual servo control

Access to Document

10.1145/3598151.3598186

Cite this

Wang, W., Xu, X., Chen, Z., Zhang, Z., Zhang, H., & Tan, Z. (2023). Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing. In A. Song, & M. Habib (Eds.), Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023 (pp. 209-214). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3598151.3598186

@inproceedings{dbd0ebcfbbe44eaf9f1d4cbc372e059f,

title = "Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing",

abstract = "A visual servoing control method based on depth point cloud is proposed to solve the problem of pose adjustment before obstacle surmounting of a rocker arm tracked robot. By pre-processing the acquired point cloud, a positional error model is created. Combined with the robot kinematics model, the adaptive control law is designed based on Lyapunov method, and the stability of the control algorithm is proved. Simulation results show that, compared with PID control and sliding mode control algorithm, the proposed control algorithm has faster convergence speed and smoother trajectory. The robot can reach the desired pose efficiently in 13. 5s in actual testing.",

keywords = "Depth point cloud, Lyapunov method, Rocker arm tracked robot, Visual servo control",

author = "Wen Wang and Xiaobin Xu and Ziheng Chen and Zhiqiang Zhang and Haojie Zhang and Zhiying Tan",

note = "Publisher Copyright: {\textcopyright} 2023 ACM.; 3rd International Conference on Robotics and Control Engineering, RobCE 2023 ; Conference date: 12-05-2023 Through 14-05-2023",

year = "2023",

month = may,

day = "12",

doi = "10.1145/3598151.3598186",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "209--214",

editor = "Aiguo Song and Maki Habib",

booktitle = "Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023",

}

Wang, W, Xu, X, Chen, Z, Zhang, Z, Zhang, H & Tan, Z 2023, Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing. in A Song & M Habib (eds), Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 209-214, 3rd International Conference on Robotics and Control Engineering, RobCE 2023, Nanjing, China, 12/05/23. https://doi.org/10.1145/3598151.3598186

Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing. / Wang, Wen; Xu, Xiaobin; Chen, Ziheng et al.
Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023. ed. / Aiguo Song; Maki Habib. Association for Computing Machinery, 2023. p. 209-214 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing

AU - Wang, Wen

AU - Xu, Xiaobin

AU - Chen, Ziheng

AU - Zhang, Zhiqiang

AU - Zhang, Haojie

AU - Tan, Zhiying

PY - 2023/5/12

Y1 - 2023/5/12

N2 - A visual servoing control method based on depth point cloud is proposed to solve the problem of pose adjustment before obstacle surmounting of a rocker arm tracked robot. By pre-processing the acquired point cloud, a positional error model is created. Combined with the robot kinematics model, the adaptive control law is designed based on Lyapunov method, and the stability of the control algorithm is proved. Simulation results show that, compared with PID control and sliding mode control algorithm, the proposed control algorithm has faster convergence speed and smoother trajectory. The robot can reach the desired pose efficiently in 13. 5s in actual testing.

AB - A visual servoing control method based on depth point cloud is proposed to solve the problem of pose adjustment before obstacle surmounting of a rocker arm tracked robot. By pre-processing the acquired point cloud, a positional error model is created. Combined with the robot kinematics model, the adaptive control law is designed based on Lyapunov method, and the stability of the control algorithm is proved. Simulation results show that, compared with PID control and sliding mode control algorithm, the proposed control algorithm has faster convergence speed and smoother trajectory. The robot can reach the desired pose efficiently in 13. 5s in actual testing.

KW - Depth point cloud

KW - Lyapunov method

KW - Rocker arm tracked robot

KW - Visual servo control

UR - https://www.scopus.com/pages/publications/85169122381

U2 - 10.1145/3598151.3598186

DO - 10.1145/3598151.3598186

M3 - Conference contribution

AN - SCOPUS:85169122381

T3 - ACM International Conference Proceeding Series

SP - 209

EP - 214

BT - Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023

A2 - Song, Aiguo

A2 - Habib, Maki

PB - Association for Computing Machinery

T2 - 3rd International Conference on Robotics and Control Engineering, RobCE 2023

Y2 - 12 May 2023 through 14 May 2023

ER -

Wang W, Xu X, Chen Z, Zhang Z, Zhang H, Tan Z. Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing. In Song A, Habib M, editors, Proceedings - 2023 3rd International Conference on Robotics and Control Engineering, RobCE 2023. Association for Computing Machinery. 2023. p. 209-214. (ACM International Conference Proceeding Series). doi: 10.1145/3598151.3598186

Visual Servoing Control Method of 3D Robot Based on 3D Point Cloud Processing

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