ILC-driven control enhancement for integrated MIMO soft robotic system | Intelligent Service Robotics Skip to main content

Advertisement

Springer Nature Link
Log in

ILC-driven control enhancement for integrated MIMO soft robotic system

  • Original Research Paper
  • Published:
Intelligent Service Robotics Aims and scope Submit manuscript

Abstract

This study presents a methodology employing Iterative Learning Control (ILC) to enhance the control performance of soft grippers equipped with multiple curvatures and variable stiffness. ILC is a learning-based control approach that progressively reduces errors in repetitive tasks, known for delivering superior performance in complex systems. In the context of the increasing utilization of robotic technology across various industries, the control technology of soft robots, especially soft grippers with multiple curvatures and variable stiffness, is a crucial issue. While prior research has focused on single-curvature and single-input single-output (SISO) systems, this study addresses the intricate control problem of multi-input multi-output (MIMO) soft gripper systems capable of multiple curvatures. It also proposes an enhanced design for soft grippers with multiple curvatures and variable stiffness while highlighting the potential of ILC for enhancing control performance.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Japan)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13

Similar content being viewed by others

Explore related subjects

Discover the latest articles, news and stories from top researchers in related subjects.

References

  1. Hao Y, Gong Z, Xie Z, Guan S, Yang X, Ren Z, Wang T, Wen L (2016) Universal soft pneumatic robotic gripper with variable effective length. 2016 35th Chinese control conference (CCC), 6109–6114

  2. Hao Yufei, Wang Tianmiao, Ren Ziyu, Gong Zheyuan, Wang Hui, Yang Xingbang, Guan Shaoya, Wen Li (2017) Modeling and experiments of a soft robotic gripper in amphibious environments. Int. J. Adv. Robot. Syst. 14:1729881417707148

    Article  Google Scholar 

  3. Kim Yeunhee, Cha Youngsu (2020) Soft pneumatic gripper with a tendon-driven soft origami pump. Front Bioeng Biotechnol 8:461

    Article  Google Scholar 

  4. Zhong Guoliang, Hou Yangdong, Dou Weiqiang (2019) A soft pneumatic dexterous gripper with convertible grasping modes. Int J Mech Sci 153–154:445–456

    Article  Google Scholar 

  5. Zhong Guoliang, Dou Weiqiang, Zhang Xuechao, Yi Hongdong (2021) Bending analysis and contact force modeling of soft pneumatic actuators with pleated structures. Int J Mech Sci 193:106150

    Article  Google Scholar 

  6. Wang Guoli, Li Meie, Zhou Jinxiong (2019) Modeling soft machines driven by buckling actuators. Int J Mech Sci 157–158:662–667

    Article  Google Scholar 

  7. Yoder Z, Macari D, Kleinwaks G, Schmidt I, Acome E, Keplinger C (2023) A soft, fast and versatile electrohydraulic gripper with capacitive object size detection. Adv Funct Mater 33:2209080

    Article  Google Scholar 

  8. Wang X, Kang H, Zhou H, Au W, Wang M, Chen C (2023) Development and evaluation of a robust soft robotic gripper for apple harvesting. Comput Electron Agric. 204 pp. 107552, https://linkinghub.elsevier.com/retrieve/pii/S0168169922008602

  9. Chu A, Cheng T, Muralt A, Onal C (2023) A passively conforming soft robotic gripper with three-dimensional negative bending stiffness fingers. Soft Robot 10:556–567. https://doi.org/10.1089/soro.2021.0200

    Article  Google Scholar 

  10. Jain S, Dontu S, Teoh J, Alvarado P (2023) A multimodal, reconfigurable workspace soft gripper for advanced grasping tasks. Soft Robot 10:527–544

    Article  Google Scholar 

  11. Yan J, Zhang H, Shi P, Zhang X, Zhao J (2018) Design and fabrication of a variable stiffness soft pneumatic humanoid finger actuator. In: 2018 IEEE international conference on information and automation (ICIA), 1174–1179

  12. Firouzeh Amir, Paik Jamie (2017) An under-actuated origami gripper with adjustable stiffness joints for multiple grasp modes. Smart Mater Struct 26:055035

    Article  Google Scholar 

  13. Wang W, Yu CY, Abrego SPA, Ahn, Sung-Hoon (2020) Shape memory alloy-based soft finger with changeable bending length using targeted variable stiffness. Soft Robot. 7: 283–291

  14. Song E, Lee J, Moon H, Choi H, Koo J (2021) A multi-curvature, variable stiffness soft gripper for enhanced grasping operations. Actuators 10:316

    Article  Google Scholar 

  15. Tang Z, Heung H, Tong K, Li Z (2020) A probabilistic model-based online learning optimal control algorithm for soft pneumatic actuators. IEEE Robot Autom Lett 5:1437–1444

    Article  Google Scholar 

  16. Gerboni G, Diodato A, Ciuti G, Cianchetti M, Menciassi A (2017) Feedback control of soft robot actuators via commercial flex bend sensors. IEEE/ASME Trans Mechatron 22:1881–1888

    Article  Google Scholar 

  17. Tang Z, Heung H, Tong K, Li Z (2019) A novel iterative learning model predictive control method for soft bending actuators. In: International Conference On Robotics And Automation (ICRA). pp. 4004-4010

  18. Phanomchoeng G, Pitchayawetwongsa P, Boonchumanee N, Lin S, Chancharoen R (2023,8) Grasping Profile Control of a Soft Pneumatic Robotic Gripper for Delicate Gripping. Robotics. 12:107, https://www.mdpi.com/2218-6581/12/4/107, Number: 4 Publisher: Multidisciplinary Digital Publishing Institute

  19. Xu Y, Zhu J, Chen H, Yong H, Wu Z. A soft reconfigurable circulator enabled by magnetic liquid metal droplet for multifunctional control of soft robots. Adv Sci

  20. Song E, Yun Y, Lee S, Koo J (2022) Structural optimization of variable stiffness mechanism with particle jamming and core-frame. 2022 31st IEEE International Conference On Robot And Human Interactive Communication (RO-MAN). pp. 83-88

  21. Oh D, Baek S, Nam K, Koo J (2021) Tracking and synchronization with inversion-based ilc for a multi-actuator-driven wafer inspection cartridge transport robot system. Electronics. 10, https://www.mdpi.com/2079-9292/10/23/2904

Download references

Funding

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2023-00209266).

Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Sungkyunkwan University, Suwon, Gyeongii-do, 16419, Republic of Korea

    Eun Jeong Song, Dong Jun Oh, Ji Min Beak & Ja Choon Koo

  2. Department of Ultra-Precision Machines and Systems, Korea Institute of Machinery and Materials, Gajeongbuk-Ro, Daejeon, 34103, Republic of Korea

    Seung Guk Baek

Authors
  1. Eun Jeong Song
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Seung Guk Baek
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dong Jun Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ji Min Beak
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ja Choon Koo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ja Choon Koo.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, E.J., Baek, S.G., Oh, D.J. et al. ILC-driven control enhancement for integrated MIMO soft robotic system. Intel Serv Robotics 17, 357–368 (2024). https://doi.org/10.1007/s11370-024-00511-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11370-024-00511-y

Keywords

Search

Navigation