Comparing the Effectiveness of Control Methodologies of a Hip-Knee-Ankle Exoskeleton During Squatting
Jared M. Li, Owen Winship, Stefan Fasano, Bridget Longo, Nicole M. Esposito, Gregory S. Sawicki, Robert J. Griffin, Gwendolyn M. Bryan
Abstract
Manual materials handling occupations often involve repetitive lifting, lowering, and carrying motions, which can lead to muscular fatigue and/or injury. The risk increases when loads must be worn on the body for the entirety of a job shift. Exoskeletons have been developed to assist these types of motions, but require the user to bear the weight of a load through their body. Load carriage exoskeletons have been developed to offload worn mass from the user to the ground through the device structure, but they have had limited success and have not been well studied in manual materials handling tasks. In this paper, we introduce a hip-knee-ankle exoskeleton and two control methods: virtual model control and gravity compensation. We compared the ability of each controller to reduce lower-limb muscle activity during squatting. Because the virtual model controller is tailored to squatting, we hypothesized that it would outperform gravity compensation. Both controllers were able to reduce the activity of major lower-limb muscle groups during squatting when compared to squatting with the exoskeleton turned off. Contrary to our original hypothesis, the gravity compensation controller generally outperformed the virtual model controller, which may have been caused by the gravity compensation controller having more consistent knee torque application and the virtual model controller requiring better per-user tuning and familiarization. These results indicate the efficacy of both controllers in reducing injury risk in the lower limbs during squatting.
BibTeX
@inproceedings{iros2023_comparingtheeffe,
title = {Comparing the Effectiveness of Control Methodologies of a Hip-Knee-Ankle Exoskeleton During Squatting},
author = {Jared M. Li and Owen Winship and Stefan Fasano and Bridget Longo and Nicole M. Esposito and Gregory S. Sawicki and Robert J. Griffin and Gwendolyn M. Bryan},
booktitle = {IROS 2023},
year = {2023}
}