# LeRobot LeRobot, Hugging Face Robotics Library **State-of-the-art machine learning for real-world robotics** 🤗 LeRobot provides a hardware-agnostic, Python-native interface for controlling real robots - from affordable arms like the SO-ARM101 to full humanoids. Plus the tools to record, store, and share the datasets they generate. Every dataset uses the standardized **LeRobotDataset** format (synchronized video + action/state data) and can be streamed directly from the [Hugging Face Hub](https://huggingface.co/lerobot). 🤗 On top of that data, LeRobot implements state-of-the-art policies - from lightweight imitation-learning models like ACT to large vision-language-action models like π₀ and SmolVLA - all trainable, shareable, and deployable with the same handful of CLI commands. The goal: lower the barrier to entry for robotics, so that everyone can contribute to, and benefit from, shared datasets and pretrained models. ## How It Works **Teleoperate → Record → Train → Deploy** 1. **Teleoperate** - control the robot yourself (with a leader arm, keyboard, or phone) so it can learn from your movements. 2. **Record** - each demonstration is saved as a dataset: synchronized camera video plus the actions you took. 3. **Train** - a policy (the neural network that will control the robot) learns to imitate your demonstrations. 4. **Deploy** - run the trained policy on the robot and watch it complete the task on its own. ## Get Started New here? [Install LeRobot](./installation), then pick your path: 🔧 I have a robot LeRobot supports a wide range of arms and mobile robots. Popular picks: SO-101 - our flagship, low-cost arm LeKiwi - a mobile base with an arm on top Koch v1.1 - a long-time community favorite or find yours under Robots in the sidebar Once it's assembled and calibrated, record a dataset and train your first policy with the imitation learning tutorial - or skip the CLI entirely with LeLab, a browser GUI for the same workflow. 💻 No hardware yet You can still train and evaluate policies without owning a robot: train on an existing LeRobot dataset from the Hub evaluate in simulation, against benchmarks like LIBERO or Meta-World try the free Colab notebooks - nothing to install 🤝 I want to contribute Start with the Contributing guide, then add a new policy or bring your own hardware. ## Explore the Docs 📋 Cheat Sheet Every LeRobot CLI command, copy-paste ready. 🖥️ Compute & Hardware Guide Which policy fits your GPU, and how long training takes. 🗂️ LeRobotDataset Load, stream, and visualize robot datasets from the Hub. 🖼 LeLab A browser GUI for calibrating, recording, and training - no CLI required. 🧠 Policies Start with ACT, our recommended first policy - or browse SmolVLA, π₀, and more in the sidebar. 🎮 Simulation & Benchmarks Train and evaluate in simulated environments before touching real hardware. ## Common Problems Running into issues? A few of the most frequent ones: - **Blurry or unusable camera footage** - lighting matters more than resolution. See the [Cameras](./cameras) guide. - **Build or install errors** (`cmake`, `ffmpeg`, CUDA) - see the Troubleshooting section of the [Installation guide](./installation#troubleshooting). - **Not sure which policy fits your GPU** - check the [Compute & Hardware Guide](./hardware_guide). - **Still stuck?** Ask on [Discord](https://discord.gg/s3KuuzsPFb) - the community (and the LeRobot team) is there to help.