254 citations · 270 across the 5 of their papers we have counts for
5 papers
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…
Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments
Mayank Mittal, Calvin Yu, Qinxi Yu +12
We present Orbit, a unified and modular framework for robot learning powered by NVIDIA Isaac Sim. It offers a modular design to easily and efficiently create robotic environments w…
Assistive Tele-op: Leveraging Transformers to Collect Robotic Task Demonstrations
Henry M. Clever, Ankur Handa, Hammad Mazhar +7
Sharing autonomy between robots and human operators could facilitate data collection of robotic task demonstrations to continuously improve learned models. Yet, the means to commun…
RGB-D Local Implicit Function for Depth Completion of Transparent Objects
Luyang Zhu, Arsalan Mousavian, Yu Xiang +4
Majority of the perception methods in robotics require depth information provided by RGB-D cameras. However, standard 3D sensors fail to capture depth of transparent objects due to…
Transferable Task Execution from Pixels through Deep Planning Domain Learning
Kei Kase, Chris Paxton, Hammad Mazhar +2
While robots can learn models to solve many manipulation tasks from raw visual input, they cannot usually use these models to solve new problems. On the other hand, symbolic planni…