Robotics & Machine Learning Daily News2024,Issue(Apr.18) :158-159.

Simulating human-in-the-loop optimization of exoskeleton assistance to compare o ptimization algorithm performance

Robotics & Machine Learning Daily News2024,Issue(Apr.18) :158-159.

Simulating human-in-the-loop optimization of exoskeleton assistance to compare o ptimization algorithm performance

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – According to news reporting based on a preprint a bstract, our journalists obtained the followingquote sourced from biorxiv.org:“Assistive robotic devices like exoskeletons offer the promise of improving mobi lity for millions ofpeople.“However, developing devices that improve an objective mobility metric is challe nging. Human-inthe-loop optimization is a systematic approach for personalizing robotic assistance to maximize a mobilitymetric that has improved device perfo rmance for different metrics and applications. Successfully performinghuman-in- the-loop optimization requires the experimenter to make many decisions, like sel ecting theappropriate optimization algorithm, hyperparameters, and convergence criteria. Typically, selecting theseexperimental settings involves pilot experi mentation.

Key words

Algorithms/Bioengineering/Biotechnolog y/Emerging Technologies/Machine Learning/Robotics/Robots

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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