3 citations · 3 across the 4 of their papers we have counts for
5 papers · 1 filter
UniExo: Unified Multi-Skill Policies for Musculoskeletal Locomotion and Co-Adaptive Exoskeleton Control
Yifei Yuan, Jakob Wolf, Ghaith Androwis +1
Daily locomotion encompasses diverse activities and frequent transitions between them, yet most exoskeleton controllers are designed for a single activity or a narrow set of relate…
Staged Multi-Agent Training for Human-Exoskeleton Co-Adaptation: Simulation-Based Learning and Real-World Metabolic and Biomechanical Validation
Yifei Yuan, Jakob Wolf, Ghaith Androwis +1
Learning-based controllers can enable exoskeleton assistance to be trained entirely in physics-based simulation, but achieving effective assistance on real users remains challengin…
SMAT: Staged Multi-Agent Training for Co-Adaptive Exoskeleton Control
Yifei Yuan, Ghaith Androwis, Xianlian Zhou
Effective exoskeleton assistance requires co-adaptation: as the device alters joint dynamics, the user reorganizes neuromuscular coordination, creating a non-stationary learning pr…
Gait Asymmetry from Unilateral Weakness and Improvement With Ankle Assistance: a Reinforcement Learning based Simulation Study
Yifei Yuan, Ghaith Androwis, Xianlian Zhou
Unilateral muscle weakness often leads to asymmetric gait, disrupting interlimb coordination and stance timing. This study presents a reinforcement learning (RL) based musculoskele…
Reinforcement Learning and Control of a Lower Extremity Exoskeleton for Squat Assistance
S. Luo, G. Androwis, S. Adamovich +2
A significant challenge for the control of a robotic lower extremity rehabilitation exoskeleton is to ensure stability and robustness during programmed tasks or motions, which is c…