Research & News

Our research on real2sim2real for general-purpose robotics, along with talks and company news.

Real-world data as the foundation for robotics simulations

  • We release 1,000 simulation environments for five bimanual tasks from the ABC dataset, created real-to-sim from real robot trajectories.
  • Our environments show strong sim-to-real performance correlation on ABC's learned policies and reproduce real-world failures in sim.
  • Policies trained in our simulation show strong sim-to-real performance on a new robot cell, achieving 4x higher success rates than policies trained on real data from other cells.

Simulation is only useful if its lessons transfer to the real world. At Versor, we are building real-to-sim-to-real systems that use real-world interactions to bridge the sim-to-real gap, turning real-world experience into realistic environments.

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Versor is the real2sim partner on Sim2World ↗

Sim2World is a coalition of startups, academic labs and industry teams working on taking simulation into the real world.

Closing the real-to-sim-to-real loop for Physical AI ↗

On NVIDIA's OpenUSD Insiders livestream. Our research vision starts at 27:40.