Self-Unlocking Active Clutch for Quasi-Passive Wearable Robots
Wearable robots have gained attention as a promising technology for enhancing human functions and capabilities. While early research focused on developing motorized exoskeletons, recent efforts have shifted toward improving wearability for user convenience. However, the size and weight of actuators and battery components in active wearable robots remain significant challenges. As an alternative, passive wearable robots using nonmotorized mechanical components are lightweight and energy-efficient, but they have limitations in adapting to different situations. This article introduces a self-unlocking active clutch (SuAC) for quasi-passive wearable robots, which combines the benefits of both active and passive systems. The SuAC utilizes a shape memory alloy coil spring and an encoder to actively lock and provide assistive force based on the user's movement. Once in a locked state, the clutch can automatically unlock when the assistive force falls below a certain threshold, based on the user's preprogrammed intentions. This self-unlocking feature eliminates the need for additional mechanical triggering components or external sensors. The SuAC weighs approximately 50 grams and can withstand a locking torque of over 500 N, with a fast response time of less than 0.15 s. To demonstrate its application, we applied the SuAC to a neck-assist exosuit, showing that the assistive force can be controlled solely by the user's movements. This research simplifies the design and expands the functionality of quasi-passive wearable robots, providing a more accessible and efficient solution for assistive technology.
Authors
- Kyu‐Jin Cho (ORCID: https://orcid.org/0000-0003-2555-5048)
- Seung-Won Kim (ORCID: https://orcid.org/0000-0003-3190-9172)
- Jin-Sung Choi (ORCID: https://orcid.org/0000-0001-8650-2252)
Institutions
- Seoul National University (KR)
- Korea Institute of Science and Technology (KR)
Publication Details
- Journal
- IEEE/ASME Transactions on Mechatronics
- Published
- 2024-12-13
- DOI
- https://doi.org/10.1109/tmech.2024.3509854
- Citations
- 3
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.64
Funders
- Korea Health Industry Development Institute
- National Research Foundation of Korea