3 citations · 7 across the 9 of their papers we have counts for
4 papers · 1 filter
Hoi! - A Multimodal Dataset for Force-Grounded, Cross-View Articulated Manipulation
Tim Engelbracht, René Zurbrügg, Matteo Wohlrapp +5
We present a dataset for force-grounded, cross-view articulated manipulation that couples what is seen with what is done and what is felt during real human interaction. The dataset…
Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
NVIDIA, :, Mayank Mittal +104
We present Isaac Lab, the natural successor to Isaac Gym, which extends the paradigm of GPU-native robotics simulation into the era of large-scale multi-modal learning. Isaac Lab c…
Spot-On: A Mixed Reality Interface for Multi-Robot Cooperation
Tim Engelbracht, Petar Lukovic, Tjark Behrens +5
Recent progress in mixed reality (MR) and robotics is enabling increasingly sophisticated forms of human-robot collaboration. Building on these developments, we introduce a novel M…
MAPLE: Encoding Dexterous Robotic Manipulation Priors Learned From Egocentric Videos
Alexey Gavryushin, Xi Wang, Robert J. S. Malate +5
Large-scale egocentric video datasets capture diverse human activities across a wide range of scenarios, offering rich and detailed insights into how humans interact with objects,…