Abstract
The widespread adoption of powered lower-limb exoskeletons for augmenting mobility requires energy-efficient actuation to provide meaningful assistance over relevant walking durations. We designed, modeled, and validated an ankle exoskeleton design with a parallel elastic element in the form of a carbon fiber leaf spring that stored and returned energy in parallel to a cable-drive ankle joint during stance phase. We assessed the impact of the parallel elastic element on the performance of the untethered robotic ankle exoskeleton at walking speeds of 0.75-1.25 m/s using a previously validated-controller, and a controller designed specifically to maximize the spring's benefit. The spring selected for our adult cohort had a stiffness of 97.2 Nm/rad, engaged best at 0-degrees ankle dorsiflexion, and produced 10-15 Nm peak assistive torque at all walking speeds. When tracking the previously validated exoskeleton controller, peak motor current was reduced by 14-20% and integrated current was reduced by 16-19% for parallel-elastic design vs. without spring engagement; this translated to 15-26% more assisted steps for the same battery capacity. When utilizing the controller designed to take advantage of the parallel spring torque, the number of assisted steps for the same battery capacity increased 46-76% compared to the no spring configuration depending on walking speed. Seeking to facilitate real-world adoption, this powered parallel elastic ankle exoskeleton design holds potential to significantly extend powered walking duration, and improve battery and motor life of operation by reducing peak and mean motor current requirements.
Original language | English (US) |
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Pages (from-to) | 8092-8099 |
Number of pages | 8 |
Journal | IEEE Robotics and Automation Letters |
Volume | 7 |
Issue number | 3 |
DOIs | |
State | Published - Jul 1 2022 |
Externally published | Yes |
Keywords
- Actuator design
- Ankle
- Exoskeleton
- Leaf spring
- Parallel elasticity
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