Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features

Wanyu Ma; Jihong Zhu; David Navarro-Alarcon

doi:10.1007/978-3-030-95892-3_40

Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features

Wanyu Ma, Jihong Zhu, David Navarro-Alarcon

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

1 Citation (Scopus)

Abstract

This paper proposes a general approach to design automatic controls to manipulate elastic objects into desired shapes. The object’s geometric model is defined as the shape feature based on the specific task to globally describe the deformation. Raw visual feedback data is processed using classic regression methods to identify parameters of data-driven geometric models in real-time. Our proposed method is able to analytically compute a pose-shape Jacobian matrix based on implicit functions. This model is then used to derive a shape servoing controller. To validate the proposed method, we report a detailed experimental study with robotic manipulators deforming an elastic rod.

Original language	English
Title of host publication	Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16
Editors	Marcelo H. Ang Jr, Hajime Asama, Wei Lin, Shaohui Foong
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	518-531
Number of pages	14
ISBN (Print)	9783030958916
DOIs	https://doi.org/10.1007/978-3-030-95892-3_40
Publication status	Published - Apr 2022
Event	16th International Conference on Intelligent Autonomous Systems, IAS-16 2020 - Virtual, Online Duration: 22 Jun 2021 → 25 Jun 2021

Publication series

Name	Lecture Notes in Networks and Systems
Volume	412 LNNS
ISSN (Print)	2367-3370
ISSN (Electronic)	2367-3389

Conference

Conference	16th International Conference on Intelligent Autonomous Systems, IAS-16 2020
City	Virtual, Online
Period	22/06/21 → 25/06/21

Keywords

Deformable objects
Robotics
Shape control
Visual servoing

ASJC Scopus subject areas

Control and Systems Engineering
Signal Processing
Computer Networks and Communications

More information

10.1007/978-3-030-95892-3_40

Cite this

Ma, W., Zhu, J., & Navarro-Alarcon, D. (2022). Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features. In M. H. Ang Jr, H. Asama, W. Lin, & S. Foong (Eds.), Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16 (pp. 518-531). (Lecture Notes in Networks and Systems; Vol. 412 LNNS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-95892-3_40

Ma, Wanyu ; Zhu, Jihong ; Navarro-Alarcon, David. / Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features. Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16. editor / Marcelo H. Ang Jr ; Hajime Asama ; Wei Lin ; Shaohui Foong. Springer Science and Business Media Deutschland GmbH, 2022. pp. 518-531 (Lecture Notes in Networks and Systems).

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title = "Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features",

abstract = "This paper proposes a general approach to design automatic controls to manipulate elastic objects into desired shapes. The object{\textquoteright}s geometric model is defined as the shape feature based on the specific task to globally describe the deformation. Raw visual feedback data is processed using classic regression methods to identify parameters of data-driven geometric models in real-time. Our proposed method is able to analytically compute a pose-shape Jacobian matrix based on implicit functions. This model is then used to derive a shape servoing controller. To validate the proposed method, we report a detailed experimental study with robotic manipulators deforming an elastic rod.",

keywords = "Deformable objects, Robotics, Shape control, Visual servoing",

author = "Wanyu Ma and Jihong Zhu and David Navarro-Alarcon",

note = "Funding Information: Acknowledgements. This work is supported in part by the Research Grants Council (grants 14203917, G-PolyU507/18), in part by the Jiangsu Industrial Technology Research Institute Collaborative Research Program Scheme (grant ZG9V), in part by the Key-Area Research and Development Program of Guangdong Province 2020 (project 76), and in part by PolyU (grants YBYT, ZZHJ). Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; 16th International Conference on Intelligent Autonomous Systems, IAS-16 2020 ; Conference date: 22-06-2021 Through 25-06-2021",

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Ma, W, Zhu, J & Navarro-Alarcon, D 2022, Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features. in MH Ang Jr, H Asama, W Lin & S Foong (eds), Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16. Lecture Notes in Networks and Systems, vol. 412 LNNS, Springer Science and Business Media Deutschland GmbH, pp. 518-531, 16th International Conference on Intelligent Autonomous Systems, IAS-16 2020, Virtual, Online, 22/06/21. https://doi.org/10.1007/978-3-030-95892-3_40

Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features. / Ma, Wanyu; Zhu, Jihong; Navarro-Alarcon, David.
Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16. ed. / Marcelo H. Ang Jr; Hajime Asama; Wei Lin; Shaohui Foong. Springer Science and Business Media Deutschland GmbH, 2022. p. 518-531 (Lecture Notes in Networks and Systems; Vol. 412 LNNS).

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

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AU - Navarro-Alarcon, David

N1 - Funding Information: Acknowledgements. This work is supported in part by the Research Grants Council (grants 14203917, G-PolyU507/18), in part by the Jiangsu Industrial Technology Research Institute Collaborative Research Program Scheme (grant ZG9V), in part by the Key-Area Research and Development Program of Guangdong Province 2020 (project 76), and in part by PolyU (grants YBYT, ZZHJ). Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

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N2 - This paper proposes a general approach to design automatic controls to manipulate elastic objects into desired shapes. The object’s geometric model is defined as the shape feature based on the specific task to globally describe the deformation. Raw visual feedback data is processed using classic regression methods to identify parameters of data-driven geometric models in real-time. Our proposed method is able to analytically compute a pose-shape Jacobian matrix based on implicit functions. This model is then used to derive a shape servoing controller. To validate the proposed method, we report a detailed experimental study with robotic manipulators deforming an elastic rod.

AB - This paper proposes a general approach to design automatic controls to manipulate elastic objects into desired shapes. The object’s geometric model is defined as the shape feature based on the specific task to globally describe the deformation. Raw visual feedback data is processed using classic regression methods to identify parameters of data-driven geometric models in real-time. Our proposed method is able to analytically compute a pose-shape Jacobian matrix based on implicit functions. This model is then used to derive a shape servoing controller. To validate the proposed method, we report a detailed experimental study with robotic manipulators deforming an elastic rod.

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Ma W, Zhu J, Navarro-Alarcon D. Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features. In Ang Jr MH, Asama H, Lin W, Foong S, editors, Intelligent Autonomous Systems 16 - Proceedings of the 16th International Conference IAS-16. Springer Science and Business Media Deutschland GmbH. 2022. p. 518-531. (Lecture Notes in Networks and Systems). doi: 10.1007/978-3-030-95892-3_40

Shape Control of Elastic Objects Based on Implicit Sensorimotor Models and Data-Driven Geometric Features

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