no code implementations • 9 Jul 2024 • Nicolas Moenne-Loccoz, Ashkan Mirzaei, Or Perel, Riccardo de Lutio, Janick Martinez Esturo, Gavriel State, Sanja Fidler, Nicholas Sharp, Zan Gojcic
The benefits of ray tracing are well-known in computer graphics: processing incoherent rays for secondary lighting effects such as shadows and reflections, rendering from highly-distorted cameras common in robotics, stochastically sampling rays, and more.
no code implementations • 20 May 2023 • Aleksei Petrenko, Arthur Allshire, Gavriel State, Ankur Handa, Viktor Makoviychuk
In this work, we propose algorithms and methods that enable learning dexterous object manipulation using simulated one- or two-armed robots equipped with multi-fingered hand end-effectors.
1 code implementation • 10 Jan 2023 • Mayank Mittal, Calvin Yu, Qinxi Yu, Jingzhou Liu, Nikita Rudin, David Hoeller, Jia Lin Yuan, Ritvik Singh, Yunrong Guo, Hammad Mazhar, Ajay Mandlekar, Buck Babich, Gavriel State, Marco Hutter, Animesh Garg
We present Orbit, a unified and modular framework for robot learning powered by NVIDIA Isaac Sim.
2 code implementations • 25 Oct 2022 • Ankur Handa, Arthur Allshire, Viktor Makoviychuk, Aleksei Petrenko, Ritvik Singh, Jingzhou Liu, Denys Makoviichuk, Karl Van Wyk, Alexander Zhurkevich, Balakumar Sundaralingam, Yashraj Narang, Jean-Francois Lafleche, Dieter Fox, Gavriel State
Our policies are trained to adapt to a wide range of conditions in simulation.
1 code implementation • 7 May 2022 • Yashraj Narang, Kier Storey, Iretiayo Akinola, Miles Macklin, Philipp Reist, Lukasz Wawrzyniak, Yunrong Guo, Adam Moravanszky, Gavriel State, Michelle Lu, Ankur Handa, Dieter Fox
We aim for Factory to open the doors to using simulation for robotic assembly, as well as many other contact-rich applications in robotics.
5 code implementations • 24 Aug 2021 • Viktor Makoviychuk, Lukasz Wawrzyniak, Yunrong Guo, Michelle Lu, Kier Storey, Miles Macklin, David Hoeller, Nikita Rudin, Arthur Allshire, Ankur Handa, Gavriel State
Isaac Gym offers a high performance learning platform to train policies for wide variety of robotics tasks directly on GPU.
no code implementations • ICCV 2021 • Aayush Prakash, Shoubhik Debnath, Jean-Francois Lafleche, Eric Cameracci, Gavriel State, Stan Birchfield, Marc T. Law
Synthetic data is emerging as a promising solution to the scalability issue of supervised deep learning, especially when real data are difficult to acquire or hard to annotate.
no code implementations • 28 Sep 2020 • Aayush Prakash, Shoubhik Debnath, Jean Francois Lafleche, Eric Cameracci, Gavriel State, Marc T Law
However, neural network models trained on synthetic data, do not perform well on real data because of the domain gap.
no code implementations • 23 Oct 2018 • Aayush Prakash, Shaad Boochoon, Mark Brophy, David Acuna, Eric Cameracci, Gavriel State, Omer Shapira, Stan Birchfield
Moreover, synthetic SDR data combined with real KITTI data outperforms real KITTI data alone.