2025
Achieving Precise and Reliable Locomotion with Differentiable Simulation-Based System Identification
IROS 2025
Accurate system identification is crucial for reducing trajectory drift in bipedal locomotion, particularly in reinforcement learning and model-based control. In this paper, we present a novel control framework that integrates system identification into the reinforcement learning training loop using