Monolithically Printed Pneumatic Proprioceptive Actuator with Integrated Optical Waveguide Using a Single Material

In muscle tissues, muscle fibers generate active force, muscle spindles provide passive proprioceptive feedback, and connective tissues tightly bind their movements together, forming a reliable biological system. Inspired by this, we propose a single material fabrication method to monolithically print pneumatic proprioceptive actuators (MPPPAs). By leveraging the multifunctional properties of thermoplastic polyurethane (TPU), including inherent flexibility, fusibility, and translucency, and employing a desktop-level fused deposition modeling printer, airtight chambers and embedded optical waveguides are realized within a continuous printing process. Optimized printing parameters lead to fully densified chambers, resulting in a leakage rate of only 0.85% under 200 kPa and maintaining 462.55 kPa after 10 minutes from an initial 500 kPa. The optical waveguides exhibit robust proprioception, maintaining a stable signal over 5000 bending cycles with less than 0.5% drift. Mechanical tests confirm synchronized deformation and continuous structural integration across the monolithically co-printed actuator-sensor region, enabling MPPPAs to achieve reliable actuation-sensing performance with sensing errors below 1.82%. Demonstrations include precise surface contour measurement with the root mean square error of 0.16 mm and real-time gripping width estimation, validating the method's effectiveness in fabricating compact and stable proprioceptive actuators. This research advances actuation-sensing integration in soft robotics, enabling streamlined fabrication and improved reliability for future intelligent systems.

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Publication Details

Journal
Soft Robotics
Published
2026-02-04
DOI
https://doi.org/10.1177/21695172261420664
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
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article

Monolithically Printed Pneumatic Proprioceptive Actuator with Integrated Optical Waveguide Using a Single Material

Zhonggui Fang, Zheng Wang, Yige Wu, Juan Yi et al.
Soft Robotics
Soft Robotics and Applications
article

Monolithically Printed Pneumatic Proprioceptive Actuator with Integrated Optical Waveguide Using a Single Material

Zhonggui Fang, Zheng Wang, Yige Wu, Juan Yi, Shaowu Tang, Xiaohuang Liu, Sicong Liu, Jian S. Dai
article en

Abstract

In muscle tissues, muscle fibers generate active force, muscle spindles provide passive proprioceptive feedback, and connective tissues tightly bind their movements together, forming a reliable biological system. Inspired by this, we propose a single material fabrication method to monolithically print pneumatic proprioceptive actuators (MPPPAs). By leveraging the multifunctional properties of thermoplastic polyurethane (TPU), including inherent flexibility, fusibility, and translucency, and employing a desktop-level fused deposition modeling printer, airtight chambers and embedded optical waveguides are realized within a continuous printing process. Optimized printing parameters lead to fully densified chambers, resulting in a leakage rate of only 0.85% under 200 kPa and maintaining 462.55 kPa after 10 minutes from an initial 500 kPa. The optical waveguides exhibit robust proprioception, maintaining a stable signal over 5000 bending cycles with less than 0.5% drift. Mechanical tests confirm synchronized deformation and continuous structural integration across the monolithically co-printed actuator-sensor region, enabling MPPPAs to achieve reliable actuation-sensing performance with sensing errors below 1.82%. Demonstrations include precise surface contour measurement with the root mean square error of 0.16 mm and real-time gripping width estimation, validating the method's effectiveness in fabricating compact and stable proprioceptive actuators. This research advances actuation-sensing integration in soft robotics, enabling streamlined fabrication and improved reliability for future intelligent systems.

Soft Robotics
University of Southern California (US), Southern University of Science and Technology (CN), Shenzhen Academy of Robotics (CN), Shenzhen Technology University (CN), Great Bay University
Affordable and clean energy
Openalex Percentile: Top 68%
Soft Robotics and Applications
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