Newton Physics Integration#
Newton is a GPU-accelerated, extensible, and differentiable physics simulation engine designed for robotics, research, and advanced simulation workflows. Built on top of NVIDIA Warp and integrating MuJoCo Warp, Newton provides high-performance simulation, modern Python APIs, and a flexible architecture for both users and developers.
Newton is an Open Source community-driven project with contributions from NVIDIA, Google Deep Mind, and Disney Research, managed through the Linux Foundation.
This experimental feature branch of Isaac Lab provides an initial integration with the Newton Physics Engine, and is under active development. Many features are not yet supported, and only a limited set of classic RL and flat terrain locomotion reinforcement learning examples are included at the moment.
Both this Isaac Lab integration branch and Newton itself are under heavy development. We intend to support additional features for other reinforcement learning and imitation learning workflows in the future, but the above tasks should be a good lens through which to understand how Newton integration works in Isaac Lab.
We have validated Newton simulation against PhysX by transferring learned policies from Newton to PhysX and vice versa Furthermore, we have also successfully deployed a Newton-trained locomotion policy to a G1 robot. Please see here for more information.
Newton can support multiple solvers for handling different types of physics simulation, but for the moment, the Isaac Lab integration focuses primarily on the MuJoCo-Warp solver.
Future updates of this branch and Newton should include both ongoing improvements in performance as well as integration with additional solvers.
Note that this branch does not include support for the PhysX physics engine - only Newton is supported. We are considering several possible paths to continue to support PhysX within Lab, and feedback from users about their needs around that would be appreciated.
During the early development phase of both Newton and this Isaac Lab integration, you are likely to encounter breaking changes as well as limited documentation. We do not expect to be able to provide official support or debugging assistance until the framework has reached an official release. We appreciate your understanding and patience as we work to deliver a robust and polished framework!