Soft, Multi-DoF, Variable Stiffness Mechanism Using Layer Jamming for Wearable Robots

Won Ho Choi, Sunghwan Kim, Dongun Lee, Dongjun Shin

Research output: Contribution to journalArticlepeer-review

26 Citations (Scopus)

Abstract

Recently, vacuum-based layer jamming mechanisms have been actively researched for safe human-robot interaction. However, most conventional layer jamming mechanisms provide restricted motion in one direction such that their application in wearable robots is significantly limited. To address this problem, we propose a novel, soft, multi-degree of freedom (multi-DoF) layer jamming mechanism that employs a sliding linkage-based layer jamming mechanism (SLLJ). The proposed SLLJ allows movement not only in the linear direction, but also in the pitch and yaw directions. Furthermore, the SLLJ can control its stiffness in multi-directions and generate a large resisting force with small thickness and light weight. Experimental results show that the maximum linear resisting force of SLLJ is 264.8 N, which is comparable to the conventional layer jamming mechanism, and the maximum yaw resisting torque is 1.363 Nm before buckling. In addition, the stiffness of the SLLJ can be increased by 96.6 folds in the linear direction and 60.02 folds in the yaw direction when the SLLJ transforms from soft state to rigid state. Being fabricated in various shapes, the SLLJ can be adapted to a wide range of wearable robots, which require multi-DoF motions with variable stiffness and substantial resisting force.

Original languageEnglish
Article number8678412
Pages (from-to)2539-2546
Number of pages8
JournalIEEE Robotics and Automation Letters
Volume4
Issue number3
DOIs
Publication statusPublished - 2019 Jul

Bibliographical note

Funding Information:
Manuscript received October 15, 2018; accepted March 10, 2019. Date of publication April 1, 2019; date of current version April 12, 2019. This paper was recommended for publication by Associate Editor R. Niiyama and Editor K.-J. Cho upon evaluation of the reviewers’ comments. This work was supported in part by the National Research Foundation of Korea (NRF) of the Korean Government (MSIT) under Grants NRF-2016R1A5A1938472 and NRF-2017M3C1B2085321 and in part by the Chung-Ang University Graduate Research Scholarship 2017. (Corresponding author: Dongjun Shin.) The authors are with the Human-Centered Robotics Lab, Chung-Ang University, Seoul 156-756, South Korea (e-mail:, choig01@cau.ac.kr; tjdghks92030@cau.ac.kr; mistagom@cau.ac.kr; djshin@cau.ac.kr). Digital Object Identifier 10.1109/LRA.2019.2908493

Publisher Copyright:
© 2016 IEEE.

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Biomedical Engineering
  • Human-Computer Interaction
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Control and Optimization
  • Artificial Intelligence

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