Log in

Tailoring the in-plane and out-of-plane stiffness of soft fingers by endoskeleton topology optimization for stable gras**

  • Article
  • Published:
Science China Technological Sciences Aims and scope Submit manuscript

Abstract

The intrinsic compliance of soft materials endows soft robots with great advantages to achieve large deformation and adaptive interactions in gras** tasks. However, current soft grippers usually focus on the in-plane large deformation and load capacity but ignore the effect of out-of-plane external loads, which may lead to instability in practical scenarios. This problem calls for stiffness design along multiple directions to withstand not only in-plane interacting forces with objects, but also unexpected out-of-plane loads. In this paper, we design a new type of soft finger by embedding an endoskeleton inside the widely-used Pneu-Nets actuator, and the endoskeleton layout is optimized to achieve a remarkable bending deflection and limited lateral deflection under combined external in-plane and out-of-plane loads. Based on the multi-objective topology optimization approach, the key structural features of the optimized endoskeleton are extracted and parameterized. The multi-material soft fingers are fabricated by the silicone compound mold method. Static and dynamic experiment results validate that the soft gripper with endoskeleton embedded exhibits remarkably improved out-of-plane stiffness, without sacrificing the in-plane bending flexibility, and leads to more stable gras**.

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

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /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 excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Rus D, Tolley M T. Design, fabrication and control of origami robots. Nat Rev Mater, 2018, 3: 101–112

    Article  Google Scholar 

  2. Chen F, Wang M Y. Design optimization of soft robots: A review of the state of the art. IEEE Robot Automat Mag, 2020, 27: 27–43

    Article  Google Scholar 

  3. Ongaro F, Scheggi S, Yoon C K, et al. Autonomous planning and control of soft untethered grippers in unstructured environments. J Micro-Bio Robot, 2017, 12: 45–52

    Article  Google Scholar 

  4. Zhang H, Kumar A S, Chen F, et al. Topology optimized multimaterial soft fingers for applications on grippers, rehabilitation, and artificial hands. IEEE ASME Trans Mechatron, 2018, 24: 120–131

    Article  Google Scholar 

  5. Chen S T, Wang Y S, Li D C, et al. Enhancing interaction performance of soft pneumatic-networks grippers by skeleton topology optimization. Sci China Tech Sci, 2021, 64: 2709–2717

    Article  Google Scholar 

  6. Chen F, Xu W, Zhang H, et al. Topology optimized design, fabrication, and characterization of a soft cable-driven gripper. IEEE Robot Autom Lett, 2018, 3: 2463–2470

    Article  Google Scholar 

  7. Liu C H, Chung F M, Chen Y, et al. Optimal design of a motor-driven three-finger soft robotic gripper. IEEE ASME Trans Mechatron, 2020, 25: 1830–1840

    Article  Google Scholar 

  8. Glick P, Suresh S A, Ruffatto D, et al. A soft robotic gripper with gecko-inspired adhesive. IEEE Robot Autom Lett, 2018, 3: 903–910

    Article  Google Scholar 

  9. Liu C H, Chen L J, Chi J C, et al. Topology optimization design and experiment of a soft pneumatic bending actuator for gras** applications. IEEE Robot Autom Lett, 2022, 7: 2086–2093

    Article  Google Scholar 

  10. Park W, Seo S, Bae J. A hybrid gripper with soft material and rigid structures. IEEE Robot Autom Lett, 2018, 4: 65–72

    Article  Google Scholar 

  11. Lotfiani A, Zhao H, Shao Z, et al. Torsional stiffness improvement of a soft pneumatic finger using embedded skeleton. J Mech Robotics, 2020, 12: 011016

    Article  Google Scholar 

  12. Su R, Tian Y, Du M, et al. Optimizing out-of-plane stiffness for soft grippers. IEEE Robot Autom Lett, 2022, 7: 10430–10437

    Article  Google Scholar 

  13. Brown J, Sukkarieh S. Design and evaluation of a modular robotic plum harvesting system utilizing soft components. J Field Robotics, 2021, 38: 289–306

    Article  Google Scholar 

  14. Fei Y, Wang J, Pang W. A novel fabric-based versatile and stiffness-tunable soft gripper integrating soft pneumatic fingers and wrist. Soft Robotics, 2019, 6: 1–20

    Article  Google Scholar 

  15. Sun Y, Yap H K, Liang X, et al. Stiffness customization and patterning for property modulation of silicone-based soft pneumatic actuators. Soft Robotics, 2017, 4: 251–260

    Article  Google Scholar 

  16. Scharff R B N, Wu J, Geraedts J M P, et al. Reducing out-of-plane deformation of soft robotic actuators for stable gras**. In: 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft). Seoul, 2019. 265–270

  17. Zhu J, Chai Z, Yong H, et al. Bioinspired multimodal multipose hybrid fingers for wide-range force, compliant, and stable gras**. Soft Robotics, 2023, 10: 30–39

    Article  Google Scholar 

  18. Chen S, Chen F, Cao Z, et al. Topology optimization of skeleton-reinforced soft pneumatic actuators for desired motions. IEEE ASME Trans Mechatron, 2021, 26: 1745–1753

    Article  Google Scholar 

  19. Wei H, Shan Y, Zhao Y, et al. A soft robot with variable stiffness multidirectional gras** based on a folded plate mechanism and particle jamming. IEEE Trans Robot, 2022, 38: 3821–3831

    Article  Google Scholar 

  20. Zhou P, Zhang N, Gu G. A biomimetic soft-rigid hybrid finger with autonomous lateral stiffness enhancement. Adv Intelligent Syst, 2022, 4: 2200170

    Article  Google Scholar 

  21. Hu Q, Dong E, Sun D. Soft gripper design based on the integration of flat dry adhesive, soft actuator, and microspine. IEEE Trans Robot, 2021, 37: 1065–1080

    Article  Google Scholar 

  22. Zhang Z, Ni X, Wu H, et al. Pneumatically actuated soft gripper with bistable structures. Soft Robotics, 2022, 9: 57–71

    Article  Google Scholar 

  23. Fang B, Sun F, Wu L, et al. Multimode gras** soft gripper achieved by layer jamming structure and tendon-driven mechanism. Soft Robotics, 2022, 9: 233–249

    Article  Google Scholar 

  24. Li L, **e F, Wang T, et al. Stiffness-tunable soft gripper with soft-rigid hybrid actuation for versatile manipulations. Soft Robotics, 2022, 9: 1108–1119

    Article  Google Scholar 

  25. Chen Y, Chung H, Chen B, et al. A lobster-inspired bending module for compliant robotic applications. Bioinspir Biomim, 2020, 15: 056009

    Article  Google Scholar 

  26. Sun Y L, Liu Y Q, Zhou N D, et al. A matlab-based framework for designing 3D topology optimized soft robotic grippers. In: 2021 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM). Delft, 2021. 1283–1289

  27. Caasenbrood B, Pogromsky A, Nijmeijer H. A computational design framework for pressure-driven soft robots through nonlinear topology optimization. In: 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft). New Haven, 2020. 633–638

  28. Tian J W, Zhao X H, Gu X F D, et al. Designing ferromagnetic soft robots (FerroSoRo) with level-set-based multiphysics topology optimization. In: 2020 IEEE International Conference on Robotics and Automation (ICRA). Paris, 2020. 10067–10074

  29. Yap H K, Ng H Y, Yeow C H. High-force soft printable pneumatics for soft robotic applications. Soft Robotics, 2016, 3: 144–158

    Article  Google Scholar 

  30. Li H, Zhou P, Zhang S, et al. A high-load bioinspired soft gripper with force booster fingers. Mechanism Machine Theor, 2022, 177: 105048

    Article  Google Scholar 

  31. Pan Q, Chen S T, Chen F F, et al. Programmable soft bending actuators with auxetic metamaterials. Sci China Tech Sci, 2020, 63: 2518–2526

    Article  Google Scholar 

  32. Sigmund O. A 99 line topology optimization code written in Matlab. Struct Multidisc Optim, 2001, 21: 120–127

    Article  Google Scholar 

  33. Andreassen E, Clausen A, Schevenels M, et al. Efficient topology optimization in MATLAB using 88 lines of code. Struct Multidisc Optim, 2011, 43: 1–16

    Article  MATH  Google Scholar 

  34. Svanberg K. The method of moving asymptotes—A new method for structural optimization. Int J Numer Meth Engng, 1987, 24: 359–373

    Article  MathSciNet  MATH  Google Scholar 

  35. Ferrari F, Sigmund O. A new generation 99 line Matlab code for compliance topology optimization and its extension to 3D. Struct Multidisc Optim, 2020, 62: 2211–2228

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to FeiFei Chen.

Additional information

This work was supported by the National Natural Science Foundation of China (Grant Nos. 52275026 and 91948302) and the State Key Laboratory of Structural Analysis for Industrial Equipment (Grant No. GZ21117).

Electronic supplementary material

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, D., Chen, S., Song, Z. et al. Tailoring the in-plane and out-of-plane stiffness of soft fingers by endoskeleton topology optimization for stable gras**. Sci. China Technol. Sci. 66, 3080–3089 (2023). https://doi.org/10.1007/s11431-022-2346-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11431-022-2346-6

Navigation