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Found 4 papers, 3 papers with code
Input-to-State Stability in Probability
Input-to-State Stability (ISS) is fundamental in mathematically quantifying how stability degrades in the presence of bounded disturbances.
Preference-Based Learning for User-Guided HZD Gait Generation on Bipedal Walking Robots
This paper presents a framework that leverages both control theory and machine learning to obtain stable and robust bipedal locomotion without the need for manual parameter tuning.
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
ROIAL learns Bayesian posteriors that predict each exoskeleton user's utility landscape across four exoskeleton gait parameters.
Human Preference-Based Learning for High-dimensional Optimization of Exoskeleton Walking Gaits
Optimizing lower-body exoskeleton walking gaits for user comfort requires understanding users' preferences over a high-dimensional gait parameter space.
