activity
20242026
most citedIsaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

3 citations · 6 across the 6 of their papers we have counts for

collaborators

7 papers

cs.RO2026

ADEPT: Accelerating Dexterity via Pre-Training and Post-Training using Reinforcement Learning

Jayjun Lee, Jessica Yin, Asif Rana +8

We introduce Accelerating Dexterity via Pre-Training (ADEPT), a large-scale reinforcement learning (RL) framework for learning sim-to-real transferable dexterity across high degree…

cs.CV2026

Cosmos 3: Omnimodal World Models for Physical AI

NVIDIA, :, Aditi +293

We introduce Cosmos 3, a family of omnimodal world models designed to jointly process and generate language, image, video, audio, and action sequences within a unified mixture-of-t…

cs.RO2025★ 3 cited

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…

cs.RO2025

End-to-end RL Improves Dexterous Grasping Policies

Ritvik Singh, Karl Van Wyk, Pieter Abbeel +3

This work explores techniques to scale up image-based end-to-end learning for dexterous grasping with an arm + hand system. Unlike state-based RL, vision-based RL is much more memo…

cs.CV2025★ 1 cited

CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models

Qingqing Zhao, Yao Lu, Moo Jin Kim +12

Vision-language-action models (VLAs) have shown potential in leveraging pretrained vision-language models and diverse robot demonstrations for learning generalizable sensorimotor c…

cs.RO2025★ 2 cited

DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands

Ritvik Singh, Arthur Allshire, Ankur Handa +2

One of the most important, yet challenging, skills for a dexterous robot is grasping a diverse range of objects. Much of the prior work has been limited by speed, generality, or re…

cs.CV2024

Synthetica: Large Scale Synthetic Data for Robot Perception

Ritvik Singh, Jingzhou Liu, Karl Van Wyk +5

Vision-based object detectors are a crucial basis for robotics applications as they provide valuable information about object localisation in the environment. These need to ensure…