Online Reinforcement Learning Control for the Personalization of a Robotic Knee Prosthesis

Robotic prostheses deliver greater function than passive prostheses, but we face the challenge of tuning a large number of control parameters in order to personalize the device for individual amputee users. This problem is not easily solved by traditional control designs or the latest robotic techno...

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Veröffentlicht in:	IEEE transactions on cybernetics Jg. 50; H. 6; S. 2346 - 2356
Hauptverfasser:	Wen, Yue, Si, Jennie, Brandt, Andrea, Gao, Xiang, Huang, He Helen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.06.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adult Algorithms Amputees - rehabilitation Approximate dynamic programming (ADP) Automation Biomechanical Phenomena - physiology direct heuristic dynamic programming (dHDP) Dynamic programming Exoskeleton Device Feasibility Gait Gait - physiology Humans Impedance Kinematics Knee Knee Prosthesis Learning Male Noise measurement Order parameters Prostheses Prosthetics reinforcement learning (RL) Reinforcement, Psychology robotic knee prosthesis Robotics Robots Signal Processing, Computer-Assisted Treadmills Tuning Walking Young Adult
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
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