10 papers
First Plan Then Evaluate: Multi-Target Planning with Post-Planning Success Evaluation Improves Learning-Based Grasping Pipelines
Martin Matak, Mohanraj Devendran Shanthi, Karl Van Wyk +1
Autonomous multi-finger grasping is a fundamental capability in robotic manipulation. Optimization-based approaches show strong performance, but tend to be sensitive to initializat…
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…
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…
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…
23 DoF Grasping Policies from a Raw Point Cloud
Martin Matak, Karl Van Wyk, Tucker Hermans
Coordinating the motion of robots with high degrees of freedom (DoF) to grasp objects gives rise to many challenges. In this paper, we propose a novel imitation learning approach t…
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…