University of Illinois at Chicago
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Continuous Exoskeleton Adaptation for Activities of Daily Life

thesis
posted on 2023-08-01, 00:00 authored by Sai Siddarth Vakacherla
Studies have shown that Human-in-the-loop (HIL) optimization with Bayesian optimization(BO) of exoskeleton parameters has succeeded in finding the optimal control strategy, resulting in improved performance of the device and reducing the physical effort of the user. However, a subject’s gait has been shown to change due to various factors such as training or acclimatization, change in environment, time, etc. Such changes in gait would result in a change in the optimal control strategy. Repeated HIL trials using the current state-of-the-art are impractical due to the long trial time and continuous optimization has been known to fail due to the inability of the Gaussian Process to handle large variations within the observed dataset. I employed a new variation of the BO, Rank-Weighted Gaussian Process Ensemble (RGPE)- based BO that can fasten the optimization time and is more noise-resistant thereby allowing continuous optimization. Performance was first evaluated using numerical simulations using test functions that showed that the RGPE-based BO located a better optimal point (p=0.007).

History

Advisor

Kim, Myunghee

Chair

Kim, Myunghee

Department

Mechanical and Industrial Engineeirng

Degree Grantor

University of Illinois at Chicago

Degree Level

  • Masters

Degree name

MS, Master of Science

Committee Member

Patton, James Bradford, Cortney

Submitted date

August 2023

Thesis type

application/pdf

Language

  • en

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