6 papers
CARO: Contact-Agnostic Residual Observation for Zero-Shot Robust Quadruped Locomotion
Zihan Yang, Shixuan Han, Kexin Guo +1
We propose CARO, a contact-agnostic residual observation framework for policy adaptation. CARO embeds a fixed-base Euler--Lagrange model into the reinforcement learning control loo…
Physics Filtering Favors the Generalization of Robot Learning
Jindou Jia, Shixuan Han, Meng Wang +8
Living organisms exhibit extraordinary adaptability to unseen environments through their intrinsic physical structures and lifelong feedback-driven learning. Endowing robots with c…
Unified Meta-Representation and Feedback Calibration for General Disturbance Estimation
Zihan Yang, Jindou Jia, Meng Wang +3
Precise control in modern robotic applications is always an open issue due to unknown time-varying disturbances. Existing meta-learning-based approaches require a shared representa…
Optimizing Control-Friendly Trajectories with Self-Supervised Residual Learning
Kexin Guo, Zihan Yang, Yuhang Liu +2
Real-world physics can only be analytically modeled with a certain level of precision for modern intricate robotic systems. As a result, tracking aggressive trajectories accurately…
Accurate Control under Voltage Drop for Rotor Drones
Yuhang Liu, Jindou Jia, Zihan Yang +1
This letter proposes an anti-disturbance control scheme for rotor drones to counteract voltage drop (VD) disturbance caused by voltage drop of the battery, which is a common case f…
Feedback Favors the Generalization of Neural ODEs
Jindou Jia, Zihan Yang, Meng Wang +4
The well-known generalization problem hinders the application of artificial neural networks in continuous-time prediction tasks with varying latent dynamics. In sharp contrast, bio…