Abstract
This letter presents design and control innovations of wearable robots that tackle two barriers to widespread adoption of powered exoskeletons: restriction of human movement and versatile control of wearable co-robot systems. First, the proposed high torque density actuation comprised of our customized high-torque density motors and low ratio transmission mechanism significantly reduces the mass of the robot and produces high backdrivability. Second, we derive a biomechanics model-based control that generates assistive torque profile for versatile control of both squat and stoop lifting assistance. The control algorithm detects lifting postures using compact inertial measurement unit (IMU) sensors to generate an assistive profile that is proportional to the human joint torque produced from our model. Experimental results demonstrate that the robot exhibits low mechanical impedance (1.5 Nm backdrive torque) when it is unpowered and 0.5 Nm backdrive torque with zero-torque tracking control. Root mean square (RMS) error of torque tracking is less than 0.29 Nm (1.21% error of 24 Nm peak torque). Compared with squatting without the exoskeleton, the controller reduces 87.5%, 80% and 75% of the three knee extensor muscles (average peak EMG of 3 healthy subjects) during squat with 50% of human joint torque assistance.
Original language | English (US) |
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Article number | 8777108 |
Pages (from-to) | 4579-4586 |
Number of pages | 8 |
Journal | IEEE Robotics and Automation Letters |
Volume | 4 |
Issue number | 4 |
DOIs | |
State | Published - Oct 2019 |
Keywords
- human performance augmentation
- physically assistive devices
- Wearable robots
ASJC Scopus subject areas
- Control and Systems Engineering
- Biomedical Engineering
- Human-Computer Interaction
- Mechanical Engineering
- Computer Vision and Pattern Recognition
- Computer Science Applications
- Control and Optimization
- Artificial Intelligence