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cs.LG2025
Data-Driven Modeling and Correction of Vehicle Dynamics
Nguyen Ly, Caroline Tatsuoka, Jai Nagaraj +4
We develop a data-driven framework for learning and correcting non-autonomous vehicle dynamics. Physics-based vehicle models are often simplified for tractability and therefore exh…
cs.LG2023
Enabling Efficient, Reliable Real-World Reinforcement Learning with Approximate Physics-Based Models
Tyler Westenbroek, Jacob Levy, David Fridovich-Keil
We focus on developing efficient and reliable policy optimization strategies for robot learning with real-world data. In recent years, policy gradient methods have emerged as a pro…