3 citations · 5 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…
SuFIA-BC: Generating High Quality Demonstration Data for Visuomotor Policy Learning in Surgical Subtasks
Masoud Moghani, Nigel Nelson, Mohamed Ghanem +6
Behavior cloning facilitates the learning of dexterous manipulation skills, yet the complexity of surgical environments, the difficulty and expense of obtaining patient data, and r…
Adapt3R: Adaptive 3D Scene Representation for Domain Transfer in Imitation Learning
Albert Wilcox, Mohamed Ghanem, Masoud Moghani +3
Imitation Learning can train robots to perform complex and diverse manipulation tasks, but learned policies are brittle with observations outside of the training distribution. 3D s…
SuFIA: Language-Guided Augmented Dexterity for Robotic Surgical Assistants
Masoud Moghani, Lars Doorenbos, William Chung-Ho Panitch +4
In this work, we present SuFIA, the first framework for natural language-guided augmented dexterity for robotic surgical assistants. SuFIA incorporates the strong reasoning capabil…
ORBIT-Surgical: An Open-Simulation Framework for Learning Surgical Augmented Dexterity
Qinxi Yu, Masoud Moghani, Karthik Dharmarajan +8
Physics-based simulations have accelerated progress in robot learning for driving, manipulation, and locomotion. Yet, a fast, accurate, and robust surgical simulation environment r…