6 papers
EgoVerse: An Egocentric Human Dataset for Robot Learning from Around the World
Ryan Punamiya, Simar Kareer, Zeyi Liu +37
Robot learning increasingly depends on large and diverse data, yet robot data collection remains expensive and difficult to scale. Egocentric human data offer a promising alternati…
WARP: Whole-Body Retargeting for Learning from Offline Human Demonstrations
Zhenyang Chen, Chuizheng Kong, Chuye Zhang +4
Direct transfer from human demonstration to learnable robot action is a crucial step towards scalable whole-body mobile manipulation. While human data scales better than mobile tel…
EMMA: Scaling Mobile Manipulation via Egocentric Human Data
Lawrence Y. Zhu, Pranav Kuppili, Ryan Punamiya +5
Scaling mobile manipulation imitation learning is bottlenecked by expensive mobile robot teleoperation. We present Egocentric Mobile MAnipulation (EMMA), an end-to-end framework tr…
STATE-NAV: Stability-Aware Traversability Estimation for Bipedal Navigation on Rough Terrain
Ziwon Yoon, Lawrence Y. Zhu, Jingxi Lu +2
Bipedal robots have advantages in maneuvering human-centered environments, but face greater failure risk compared to other stable mobile platforms such as wheeled or quadrupedal ro…
EgoBridge: Domain Adaptation for Generalizable Imitation from Egocentric Human Data
Ryan Punamiya, Dhruv Patel, Patcharapong Aphiwetsa +5
Egocentric human experience data presents a vast resource for scaling up end-to-end imitation learning for robotic manipulation. However, significant domain gaps in visual appearan…
ThermoHands: A Benchmark for 3D Hand Pose Estimation from Egocentric Thermal Images
Fangqiang Ding, Yunzhou Zhu, Xiangyu Wen +2
Designing egocentric 3D hand pose estimation systems that can perform reliably in complex, real-world scenarios is crucial for downstream applications. Previous approaches using RG…