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

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Authors: Shaowu Tang, Xiaohuang Liu, Zhonggui Fang, Yige Wu, Juan Yi, Zheng Wang, Jian S. Dai, Sicong Liu
Cited by: 1
References: 62

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.

Fields of Study & Subjects

Soft Robotics and Applications Advanced Materials and Mechanics Advanced Sensor and Energy Harvesting Materials

Publication details

Journal / source
Soft Robotics
Publisher
SAGE Publications
Volume
13
Issue
5
Pages
711–723
Publication date
4 February 2026
Language
EN