ROBOTICS & PHYSICAL AI

Autonomous driving (CARLA)

Autonomous driving (CARLA) 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

Navigate photorealistic multi-lane urban and highway environments in CARLA. Closed-loop sensor streams, trajectory tracking, collision avoidance, and traffic rule conformance gate reward.

Tools and runtime

CARLA 0.9.15 + ROS 2 + sensor fusion + rule verifiers

OPENENV / CARLA

Related Robotics & Physical AI gyms

• ManiSkill articulation & contact
• LeRobot imitation & policy learning
• 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.