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2023
Journal Article
Title
Multibody dynamics and optimal control for optimizing spinal exoskeleton design and support
Abstract
In the industrial work environment, spinal exoskeletons can assist workers with heavy lifting tasks by reducing the needed muscle activity. However, the requirements for the design and control of such an exoskeleton to optimally support users with different body builds and movement styles are still open research questions. Thus, extensive testing on the human body is needed, requiring a lot of different sophisticated prototypes that subjects can wear for several hours. To facilitate this development process, we use multibody dynamics combined with optimal control to optimize the support profile of an existing prototype and evaluate a new design concept (DC) that includes motors at the hip joint. A dynamic model of the prototype was developed, including its passive elements with torque generation that accounts for potential misalignment. The human-robot interaction was simulated and optimized in an all-at-once approach. The parameters that describe the characteristics of the passive elements (including beam radius, spring pretension, length of the lever arm, radius of profile) and, in the case of DC, the torque profiles of the motors were optimized. Limits on interaction forces ensured that the exoskeleton remains comfortable to wear. Simulations without the exoskeleton allowed comparing the user’s actuation concerning joint moment and muscle activation. Our results agree well with experimental data using the prototype, making it a useful tool to optimize exoskeleton design and support and evaluate the effect of different actuation systems, mass distributions, and comfort requirements.
Author(s)