ROBOTICS & PHYSICAL AI

Sim-to-real robotic calibration

Sim-to-real robotic calibration is an OpenEnv-compatible reinforcement learning environment in our Robotics & Physical AI catalog. An agent acts through the tools below, and a deterministic verifier scores every episode, so the reward can be used for GRPO or other RLVR post-training.

Task and verification

Tune physical simulator parameters so replayed robot trajectories match recorded hardware telemetry within strict tolerance, compensating for motor latency and backlash.

Tools and runtime

MuJoCo + Genesis + recorded hardware telemetry verification

OPENENV / SIM-TO-REAL

Related Robotics & Physical AI gyms

• Autonomous driving (CARLA)
• ManiSkill articulation & contact
• LeRobot imitation & policy learning
• PX4 drone aerial navigation
• Dynamic balance & locomotion (Unitree G1 / Go1)
• Real robot arm manipulation (Viam)
• Mobile robot indoor navigation (Gazebo)
• Multi-robot swarm coordination (Robotarium)
• Bimanual stationery manipulation
• MuJoCo batched CPU rollouts (MjBatch)

See how these environments are run privately on the custom RL environments page, and how their rewards are made hard to game in our verifier design guide.

Plan a training run

Check the environment’s availability, compatible models and compute in Studio. A catalog entry does not guarantee that hosted training is enabled for your workspace.