Web: http://arxiv.org/abs/2110.00481

Sept. 16, 2022, 1:12 a.m. | Samuel Tesfazgi, Armin Lederer, Johannes F. Kunz, Alejandro J. Ordóñez-Conejo, Sandra Hirche

cs.LG updates on arXiv.org arxiv.org

The use of rehabilitation robotics in clinical applications gains increasing
importance, due to therapeutic benefits and the ability to alleviate
labor-intensive works. However, their practical utility is dependent on the
deployment of appropriate control algorithms, which adapt the level of
task-assistance according to each individual patient's need. Generally, the
required personalization is achieved through manual tuning by clinicians, which
is cumbersome and error-prone. In this work we propose a novel online learning
control architecture, which is able to personalize the …

arxiv online learning personalized robotics

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