3 citations · 5 across the 7 of their papers we have counts for
9 papers
RoboSimStudio: An Interactive Toolkit for Human and Agent Rapid Real2Sim of Robot Manipulation Tasks
Kaiyuan Chen, Shuangyu Xie, Uksang Yoo +9
It has been difficult to accurately model the physics of the interaction between a robot and the objects it manipulates, including contact mechanics, coupled contact dynamics, defo…
FlashNeRD: Performance-First Contact-Rich Neural Robot Dynamics
Mohammadmehdi Ataei, Mohammad Amin Nabian, Jie Xu +9
Compared with analytical physics, learned dynamics models promise robot simulation that is faster, inherently differentiable, and easily adaptable to real data. Neural Robot Dynami…
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…
The Reality Gap in Robotics: Challenges, Solutions, and Best Practices
Elie Aljalbout, Jiaxu Xing, Angel Romero +9
Machine learning has facilitated significant advancements across various robotics domains, including navigation, locomotion, and manipulation. Many such achievements have been driv…
TopoCut: Learning Multi-Step Cutting with Spectral Rewards and Discrete Diffusion Policies
Liquan Wang, Jiangjie Bian, Eric Heiden +1
Robotic manipulation tasks involving cutting deformable objects remain challenging due to complex topological behaviors, difficulties in perceiving dense object states, and the lac…
Neural Robot Dynamics
Jie Xu, Eric Heiden, Iretiayo Akinola +3
Accurate and efficient simulation of modern robots remains challenging due to their high degrees of freedom and intricate mechanisms. Neural simulators have emerged as a promising…
Adaptive Horizon Actor-Critic for Policy Learning in Contact-Rich Differentiable Simulation
Ignat Georgiev, Krishnan Srinivasan, Jie Xu +2
Model-Free Reinforcement Learning (MFRL), leveraging the policy gradient theorem, has demonstrated considerable success in continuous control tasks. However, these approaches are p…
HandyPriors: Physically Consistent Perception of Hand-Object Interactions with Differentiable Priors
Shutong Zhang, Yi-Ling Qiao, Guanglei Zhu +6
Various heuristic objectives for modeling hand-object interaction have been proposed in past work. However, due to the lack of a cohesive framework, these objectives often possess…
STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent
Yewon Lee, Andrew Z. Li, Philip Huang +7
Planning for sequential robotics tasks often requires integrated symbolic and geometric reasoning. TAMP algorithms typically solve these problems by performing a tree search over h…