Sample-Efficient Policy Adaptation for Exoskeletons Under Variations in the Users and the Environment
Author:
Affiliation:
1. Faculty of Applied Sciences, Mechatronic Systems Engineering Department, Simon Fraser University, Surrey, B.C., Canada
2. Max-Planck Institute for Intelligent Systems, Tuebingen, Germany
Funder
Mitacs and Human in Motion Robotics Inc.
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Artificial Intelligence,Control and Optimization,Computer Science Applications,Computer Vision and Pattern Recognition,Mechanical Engineering,Human-Computer Interaction,Biomedical Engineering,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/7083369/9831196/09810345.pdf?arnumber=9810345
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4. Whole-body motion planning with centroidal dynamics and full kinematics
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2. Dual-Loop Control Framework of a Self-Balancing Lower-Limb Exoskeleton for Assisted Walking;IEEE Transactions on Instrumentation and Measurement;2024
3. Learning User-Specific Control Policies for Lower-Limb Exoskeletons Using Gaussian Process Regression;IEEE Access;2024
4. Multi-Terrains Assistive Force Parameter Optimization Method for Soft Exoskeleton;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2023
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