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Motphys

Motphys builds high-performance infrastructure for physics simulation, robot learning, and embodied AI.

Our open-source projects span the full development loop—from accurate, efficient simulation to scalable training and real-world deployment:

  • MotrixSim — a high-performance physics simulation engine for multibody dynamics and robotics.
  • MotrixLab — an open-source reinforcement learning framework for training and deploying robot policies.
  • UniLab — infrastructure for robot learning across physics backends, compute platforms, and hardware.

We are building the tools that help researchers and engineers develop, evaluate, and deploy intelligent robots—from virtual worlds to the real world.

Explore Motphys

Project Description
MotrixSim Physics simulation for multibody dynamics and robotics
MotrixSim Documentation Guides, API references, and examples
MotrixLab Robot reinforcement learning and sim-to-real deployment
UniLab Cross-backend infrastructure for robot learning

What we care about

  • Reliable and high-performance physics simulation
  • Scalable robot learning and reinforcement learning
  • Reproducible sim-to-real workflows
  • Open tools for embodied AI research and development

Contributions, ideas, and collaboration are welcome.

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High-performance physics simulation, robot learning, and sim-to-real infrastructure for embodied AI.

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