5 papers
FADA: Few-Shot Domain Adaptation via Dynamics Alignment for Humanoid Control
Angchen Xie, Nikhil Sobanbabu, Ishayu Shikhare +3
High-precision humanoid control is limited by target-domain dynamics mismatch, where the same control objective can induce different realized motions under changes in terrain, payl…
RIO: Flexible Real-Time Robot I/O for Cross-Embodiment Robot Learning
Pablo Ortega-Kral, Eliot Xing, Arthur Bucker +13
Despite recent efforts to collect multi-task, multi-embodiment datasets, to design recipes for training Vision-Language-Action models (VLAs), and to showcase these models on differ…
Preferenced Oracle Guided Multi-mode Policies for Dynamic Bipedal Loco-Manipulation
Prashanth Ravichandar, Lokesh Krishna, Nikhil Sobanbabu +1
Dynamic loco-manipulation calls for effective whole-body control and contact-rich interactions with the object and the environment. Existing learning-based control synthesis relies…
HDMI: Learning Interactive Humanoid Whole-Body Control from Human Videos
Haoyang Weng, Yitang Li, Nikhil Sobanbabu +5
Enabling robust whole-body humanoid-object interaction (HOI) remains challenging due to motion data scarcity and the contact-rich nature. We present HDMI (HumanoiD iMitation for In…
Sampling-Based System Identification with Active Exploration for Legged Robot Sim2Real Learning
Nikhil Sobanbabu, Guanqi He, Tairan He +2
Sim-to-real discrepancies hinder learning-based policies from achieving high-precision tasks in the real world. While Domain Randomization (DR) is commonly used to bridge this gap,…