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Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization

Author

Listed:
  • Seonggun Joe
  • Massimo Totaro
  • Hongbo Wang
  • Lucia Beccai

Abstract

Pneumatic artificial muscles (PAMs) are one of the key technologies in soft robotics, and they enable actuation in mobile robots, in wearable devices and exoskeletons for assistive and rehabilitative purposes. While they recently showed relevant improvements, they still present quite low payload, limited bandwidth, and lack of repeatability, controllability and robustness. Vacuum-based actuation has been recently demonstrated as a very promising solution, and many challenges are still open, like generating at the same time a large contraction ratio, and a high blocking force with enhanced axial stiffness. In this paper, a novel Ultralight Hybrid PAM (UH-PAM), based on bellow-type elastomeric skin and vacuum actuation, is presented. In particular, open-cell foam is exploited as a structural backbone, together with plastic rings, all embedded in a thin skin. The design and optimization combine numerical, analytical, and experimental data. Both static and dynamic analysis are performed. The weight of the optimized actuator is only 20 g. Nevertheless, a contraction ratio up to 50% and a maximum payload of 3 kg can be achieved. From a dynamic point of view, a rise time of 0.5 s for the contraction phase is observed. Although hysteresis is significant when using the whole contraction span, it can be reduced (down to 11.5%) by tuning both the vacuum range and the operating frequency for cyclic movements. Finally, to demonstrate the potentiality of this soft actuation approach, a 3 DoFs Stewart platform is built. The feasibility of performing smooth movements by exploiting open-loop control is shown through simple and more complex handwriting figures projected on the XY plane.

Suggested Citation

  • Seonggun Joe & Massimo Totaro & Hongbo Wang & Lucia Beccai, 2021. "Development of the Ultralight Hybrid Pneumatic Artificial Muscle: Modelling and optimization," PLOS ONE, Public Library of Science, vol. 16(4), pages 1-21, April.
  • Handle: RePEc:plo:pone00:0250325
    DOI: 10.1371/journal.pone.0250325
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