ROBOTICS & PHYSICAL AI

LeRobot imitation & policy learning

LeRobot imitation & policy learning 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

Train dexterous robotic manipulation policies across MetaWorld and LeRobot benchmark tasks. Multi-camera observations, force feedback, and terminal spatial tolerances gate the reward.

Tools and runtime

Hugging Face LeRobot + MetaWorld + Franka/UR5 kinematics

OPENENV / LEROBOT

Related Robotics & Physical AI gyms

• Autonomous driving (CARLA)
• ManiSkill articulation & contact
• PX4 drone aerial navigation
• Dynamic balance & locomotion (Unitree G1 / Go1)
• Sim-to-real robotic calibration
• 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.