End-to-End High-Level Control of Lower-Limb Exoskeleton for Human Performance Augmentation Based on Deep Reinforcement Learning
Author:
Affiliation:
1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing, China
2. Beijing Institute of Precision Mechatronics and Controls, Beijing, China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10255549.pdf?arnumber=10255549
Reference64 articles.
1. A REVIEW ON HUMAN–EXOSKELETON COORDINATION TOWARDS LOWER LIMB ROBOTIC EXOSKELETON SYSTEMS
2. Learning Natural Locomotion Behaviors for Humanoid Robots Using Human Bias
3. The Body Extender: A Full-Body Exoskeleton for the Transport and Handling of Heavy Loads
4. Emergence of human-comparable balancing behaviours by deep reinforcement learning
5. Biomechanics, actuation, and multi-level control strategies of power-augmentation lower extremity exoskeletons: an overview
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1. Advancements in Sensor Technologies and Control Strategies for Lower-Limb Rehabilitation Exoskeletons: A Comprehensive Review;Micromachines;2024-04-02
2. Research on Human Behavior Intention Perception Method Based on Wearable Sensors;IEEE Access;2024
3. A Novel Locomotion Rule Rmbedding Long Short-Term Memory Network with Attention for Human Locomotor Intent Classification Using Multi-Sensors Signals;Computers, Materials & Continua;2024
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