3 citations · 5 across the 10 of their papers we have counts for
4 papers · 1 filter
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…