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cs.RO2026
Swimming Under Constraints: A Safe Reinforcement Learning Framework for Quadrupedal Bio-Inspired Propulsion
Xinyu Cui, Fei Han, Hang Xu +9
Bio-inspired aquatic propulsion offers high thrust and maneuverability but is prone to destabilizing forces such as lift fluctuations, which are further amplified by six-degree-of-…
cs.RO2025
Learn to Swim: Data-Driven LSTM Hydrodynamic Model for Quadruped Robot Gait Optimization
Fei Han, Pengming Guo, Hao Chen +5
This paper presents a Long Short-Term Memory network-based Fluid Experiment Data-Driven model (FED-LSTM) for predicting unsteady, nonlinear hydrodynamic forces on the underwater qu…
cs.RO2024
Learning Adaptive Hydrodynamic Models Using Neural ODEs in Complex Conditions
Cong Wang, Aoming Liang, Fei Han +4
Reinforcement learning-based quadruped robots excel across various terrains but still lack the ability to swim in water due to the complex underwater environment. This paper presen…