MuJoCo.org

deepmind.googleGemini Robotics

12 Mar 2025

Our new Gemini Robotics model brings Gemini 2.0 to the physical world. It's our most advanced vision language action model, enabling robots that are interactive, dexterous, and general. Learn more about how we're enabling the next generation of robotic AI agents at deepmind.google/robotics

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

Introducing playground.mujoco.org Combining MuJoCo’s rich and thriving ecosystem, massively parallel GPU-accelerated simulation, and real-world results across a diverse range of robot platforms: quadrupeds, humanoids, dexterous hands, and arms. Get started today: pip install playground

You can get started today 🌐 Project page: playground.mujoco.org 📂 Code: github.com/google-deepm... 📝 Paper: playground.mujoco.org/assets/playg...

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

This work wouldn’t have been possible without the most wonderful cast of collaborators from Berkeley, U. Toronto, Cambridge, Stanford and @deepmind.google.web.brid.gy.

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

With the Franka arm and playground.mujoco.org, we trained torque-controlled policies for contact-rich tasks like block reorientation. We obtain smooth, compliant and reactive behaviors running at 200Hz.

playground.mujoco.org integrates high throughput batch rendering on GPU with Madrona-MJX. Using this, we trained a pixel-based block picking policy within minutes - achieving robust 100% success in real world trials.

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

playground.mujoco.org allows humanoid robots to learn robust walking on different surfaces (below: Berkeley Humanoid, see other humanoid robots on the website).

Locomotion is important, but what about the finer things in robotics? With playground.mujoco.org we took on the challenging task of dexterous in-hand reorientation with the open-source and low-cos LEAP hand. Our policy below was trained in 30 minutes on 2 4090s.

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

playground.mujoco.orgMuJoCo PlaygroundAn open-source framework for GPU-accelerated robot learning and sim-to-real transfer

The key to fast progress in robotics? Rapid iteration loops. playground.mujoco.org streamlines the entire process from simulation to deployment and back. In just 8 weeks, this unlocked: - Zero-shot transfer across 5 robots. - Locomotion, manipulation, and vision-based control.