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Found 4 papers, 2 papers with code
Bidirectional GaitNet: A Bidirectional Prediction Model of Human Gait and Anatomical Conditions
We present a novel generative model, called Bidirectional GaitNet, that learns the relationship between human anatomy and its gait.
Generative GaitNet
Understanding the relation between anatomy andgait is key to successful predictive gait simulation.
Understanding the Stability of Deep Control Policies for Biped Locomotion
The goal of this study is to answer these questions by evaluating the push-recovery stability of deep policies compared to human subjects and a previous feedback controller.
Muscle-actuated Human Simulation and Control
Many anatomical factors, such as bone geometry and muscle condition, interact to affect human movements.
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