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Enhancing the Performance of Pneu-net Actuators Using a Torsion Resistant Strain Limiting Layer (2311.02454v2)

Published 4 Nov 2023 in cs.RO

Abstract: Pneunets are the primary form of soft robotic grippers. A key limitation to their wider adoption is their inability to grasp larger payloads due to objects slipping out of grasps. We have overcome this limitation by introducing a torsionally rigid strain limiting layer (TRL). This reduces out-of-plane bending while maintaining the gripper's softness and in-plane flexibility. We characterize the design space of the strain limiting layer for a Pneu-net gripper using simulation and experiment and map bending angle and relative grip strength. We found that the use of our TRL reduced out-of-plane bending by up to 97.7% in testing compared to a benchmark Pneu-net gripper from the Soft Robotics Toolkit. We demonstrate a lifting capacity of 5kg when loading using the TRL. We also see a relative improvement in peak grip force of 3N and stiffness of 1200N/m compared to 1N and 150N/m for a Pneu-net gripper without our TRL at equal pressures. Finally, we test the TRL gripper on a suite of six YCB objects above the demonstrated capability of a traditional Pneu-net gripper. We show success on all but one demonstrating significant increased capabilities.

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References (18)
  1. S. Li, D. M. Vogt, D. Rus, and R. J. Wood, “Fluid-driven origami-inspired artificial muscles,” Proceedings of the National academy of Sciences, vol. 114, no. 50, pp. 13 132–13 137, 2017.
  2. S. Li, J. J. Stampfli, H. J. Xu, E. Malkin, E. V. Diaz, D. Rus, and R. J. Wood, “A vacuum-driven origami “magic-ball” soft gripper,” in 2019 International Conference on Robotics and Automation (ICRA).   IEEE, 2019, pp. 7401–7408.
  3. S. Li, S. A. Awale, K. E. Bacher, T. J. Buchner, C. Della Santina, R. J. Wood, and D. Rus, “Scaling up soft robotics: a meter-scale, modular, and reconfigurable soft robotic system,” Soft Robotics, vol. 9, no. 2, pp. 324–336, 2022.
  4. B. Mosadegh, P. Polygerinos, C. Keplinger, S. Wennstedt, R. F. Shepherd, U. Gupta, J. Shim, K. Bertoldi, C. J. Walsh, and G. M. Whitesides, “Pneumatic networks for soft robotics that actuate rapidly,” Advanced functional materials, vol. 24, no. 15, pp. 2163–2170, 2014.
  5. Z. Wang, S. Terryn, J. Legrand, P. Ferrentino, S. K. Tabrizian, J. Brancart, E. Roels, G. Van Assche, and B. Vanderborght, “Topology optimized multi-material self-healing actuator with reduced out of plane deformation,” in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022.
  6. A. Lotfiani, H. Zhao, Z. Shao, and X. Yi, “Torsional stiffness improvement of a soft pneumatic finger using embedded skeleton,” Journal of Mechanisms and Robotics, vol. 12, no. 1, p. 011016, 2020.
  7. J. Rommers, V. van der Wijk, and J. L. Herder, “A new type of spherical flexure joint based on tetrahedron elements,” Precision Engineering, vol. 71, pp. 130–140, 2021.
  8. M. Naves, D. M. Brouwer, and R. G. Aarts, “Building block-based spatial topology synthesis method for large-stroke flexure hinges,” Journal of mechanisms and robotics, vol. 9, no. 4, p. 041006, 2017.
  9. R. B. Scharff, J. Wu, J. M. Geraedts, and C. C. Wang, “Reducing out-of-plane deformation of soft robotic actuators for stable grasping,” in 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft).   IEEE, 2019, pp. 265–270.
  10. R. Su, Y. Tian, M. Du, and C. C. Wang, “Optimizing out-of-plane stiffness for soft grippers,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10 430–10 437, 2022.
  11. Y.-F. Zhang, N. Zhang, H. Hingorani, N. Ding, D. Wang, C. Yuan, B. Zhang, G. Gu, and Q. Ge, “Fast-response, stiffness-tunable soft actuator by hybrid multimaterial 3d printing,” Advanced Functional Materials, vol. 29, no. 15, p. 1806698, 2019.
  12. Y. Jiang, D. Chen, C. Liu, and J. Li, “Chain-like granular jamming: a novel stiffness-programmable mechanism for soft robotics,” Soft robotics, vol. 6, no. 1, pp. 118–132, 2019.
  13. T. L. Buckner, M. C. Yuen, S. Y. Kim, and R. Kramer-Bottiglio, “Enhanced variable stiffness and variable stretchability enabled by phase-changing particulate additives,” Advanced Functional Materials, vol. 29, no. 50, p. 1903368, 2019.
  14. P. Gunawardane, N. Budiardjo, G. Alici, C. de Silva, and M. Chiao, “Thermoelastic strain-limiting layers to actively-control soft actuator trajectories,” in 2022 IEEE 5th International Conference on Soft Robotics (RoboSoft).   IEEE, 2022, pp. 48–53.
  15. F. Visentin, S. P. Murali Babu, F. Meder, and B. Mazzolai, “Selective stiffening in soft actuators by triggered phase transition of hydrogel-filled elastomers,” Advanced Functional Materials, vol. 31, no. 32, p. 2101121, 2021.
  16. G. B. Crowley, X. Zeng, and H.-J. Su, “A 3d printed soft robotic gripper with a variable stiffness enabled by a novel positive pressure layer jamming technology,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 5477–5482, 2022.
  17. D. P. Holland, E. J. Park, P. Polygerinos, G. J. Bennett, and C. J. Walsh, “The soft robotics toolkit: Shared resources for research and design,” Soft Robotics, vol. 1, no. 3, pp. 224–230, 2014.
  18. B. Calli, A. Singh, A. Walsman, S. Srinivasa, P. Abbeel, and A. M. Dollar, “The ycb object and model set: Towards common benchmarks for manipulation research,” in 2015 International Conference on Advanced Robotics (ICAR), 2015, pp. 510–517.
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