3 citations · 5 across the 10 of their papers we have counts for
10 papers
Hydra-0: Action Flow for Generalist World Modeling and Control
Hongyu Li, Bowen Wen, Xinghao Zhu +8
We introduce Hydra-0, a generalist world model conditioned on action flow, which represents robot actions as pixel motion. This shared visual interface enables generalist world mod…
Learning Dexterous Manipulation Using Contact Wrench Guidance From Human Demonstration
Xinghao Zhu, Zixi Liu, Shalin Jain +18
Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains challenging. We present Contact…
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…
AGILE: A Comprehensive Workflow for Humanoid Loco-Manipulation Learning
Huihua Zhao, Rafael Cathomen, Lionel Gulich +6
Recent advances in reinforcement learning (RL) have enabled impressive humanoid behaviors in simulation, yet transferring these results to new robots remains challenging. In many r…
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…
mindmap: Spatial Memory in Deep Feature Maps for 3D Action Policies
Remo Steiner, Alexander Millane, David Tingdahl +6
End-to-end learning of robot control policies, structured as neural networks, has emerged as a promising approach to robotic manipulation. To complete many common tasks, relevant o…
cuVSLAM: CUDA accelerated visual odometry and mapping
Alexander Korovko, Dmitry Slepichev, Alexander Efitorov +5
Accurate and robust pose estimation is a key requirement for any autonomous robot. We present cuVSLAM, a state-of-the-art solution for visual simultaneous localization and mapping,…
COMPASS: Cross-embodiment Mobility Policy via Residual RL and Skill Synthesis
Wei Liu, Huihua Zhao, Chenran Li +4
As robots are increasingly deployed in diverse application domains, enabling robust mobility across different embodiments has become a critical challenge. Classical mobility stacks…
X-MOBILITY: End-To-End Generalizable Navigation via World Modeling
Wei Liu, Huihua Zhao, Chenran Li +5
General-purpose navigation in challenging environments remains a significant problem in robotics, with current state-of-the-art approaches facing myriad limitations. Classical appr…
ReMEmbR: Building and Reasoning Over Long-Horizon Spatio-Temporal Memory for Robot Navigation
Abrar Anwar, John Welsh, Joydeep Biswas +2
Navigating and understanding complex environments over extended periods of time is a significant challenge for robots. People interacting with the robot may want to ask questions l…