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add new docs chapters structure
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Nikodem Bartnik
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# LeRobot documentation table of contents
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#
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# Ordering principle: gentle onboarding first, advanced/custom work last.
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# Within each top-level section the same rule applies — concept/overview pages
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# before reference/per-item pages.
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#
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# Pages marked "NEW (to create)" do not yet exist as .mdx files; they are
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# placeholders for the redesign and must be authored before the docs build.
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- sections:
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- local: index
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title: LeRobot
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title: 🤗 LeRobot
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- local: quickstart # NEW (to create) — 15-min zero-to-trained-ACT path
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title: Quickstart
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- local: installation
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title: Installation
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- local: core_concepts # NEW (to create) — datasets, policies, processors, robots, envs in one mental model
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title: Core concepts
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- local: cheat-sheet
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title: Cheat sheet
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title: Command cheat sheet
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title: Get started
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- sections:
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- local: il_robots
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title: Imitation Learning for Robots
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- local: bring_your_own_policies
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title: Adding a Policy
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- local: integrate_hardware
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title: Bring Your Own Hardware
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- local: hilserl
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title: Train a Robot with RL
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- local: hilserl_sim
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title: Train RL in Simulation
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- local: multi_gpu_training
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title: Multi GPU training
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title: Imitation learning end-to-end
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- local: hil_data_collection
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title: Human In the Loop Data Collection
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- local: peft_training
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title: Training with PEFT (e.g., LoRA)
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title: Human-in-the-loop data collection
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- local: inference
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title: Deploying a trained policy
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- local: rename_map
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title: Using Rename Map and Empty Cameras
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title: "Tutorials"
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title: Matching dataset keys to a policy (rename map)
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title: Your first project
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- sections:
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- local: hardware_guide
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title: Compute Hardware Guide
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title: Compute hardware guide
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- local: torch_accelerators
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title: PyTorch accelerators
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title: "Compute & Hardware"
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- local: multi_gpu_training
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title: Multi-GPU training
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- local: peft_training
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title: Parameter-efficient fine-tuning (LoRA)
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title: Training
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- sections:
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- local: lerobot-dataset-v3
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title: Using LeRobotDataset
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- local: porting_datasets_v3
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title: Porting Large Datasets
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- local: using_dataset_tools
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title: Using the Dataset Tools
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title: Dataset tools
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- local: language_and_recipes
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title: Language Columns and Recipes
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title: Language columns & recipes
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- local: tools
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title: Tools
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title: Tool calls in datasets
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- local: video_encoding_parameters
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title: Video encoding parameters
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- local: streaming_video_encoding
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title: Streaming Video Encoding
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title: "Datasets"
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title: Streaming video encoding
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- local: porting_datasets_v3
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title: Porting datasets to v3
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title: Datasets
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- sections:
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- local: act
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title: ACT
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- local: smolvla
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title: SmolVLA
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- local: pi0
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title: π₀ (Pi0)
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- local: pi0fast
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title: π₀-FAST (Pi0Fast)
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- local: pi05
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title: π₀.₅ (Pi05)
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- local: eo1
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title: EO-1
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- local: groot
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title: NVIDIA GR00T N1.5
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- local: xvla
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title: X-VLA
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- local: multi_task_dit
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title: Multitask DiT Policy
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- local: walloss
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title: WALL-OSS
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title: "Policies"
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- local: policies_overview # NEW (to create) — concept hub + "choose a policy" decision guide
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title: Choosing a policy
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- sections:
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- local: act
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title: ACT
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- local: smolvla
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title: SmolVLA
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- local: pi0
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title: π₀ (Pi0)
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- local: pi0fast
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title: π₀-FAST
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- local: pi05
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title: π₀.₅ (Pi05)
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- local: eo1
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title: EO-1
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- local: groot
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title: NVIDIA GR00T N1.5
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- local: xvla
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title: X-VLA
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- local: walloss
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title: WALL-OSS
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- local: multi_task_dit
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title: Multitask DiT
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title: Policy reference
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title: Policies
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- sections:
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- local: sarm
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title: SARM
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title: "Reward Models"
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- sections:
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- local: inference
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title: Policy Deployment (lerobot-rollout)
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- local: async
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title: Use Async Inference
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title: Async inference
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- local: rtc
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title: Real-Time Chunking (RTC)
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title: "Inference"
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title: Real-time chunking (RTC)
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title: Real-time deployment
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- sections:
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- local: hilserl
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title: Train a robot with RL (HIL-SERL)
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- local: hilserl_sim
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title: Train RL in simulation
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- local: sarm
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title: SARM reward model
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title: Reinforcement learning
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- sections:
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- local: envhub
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title: Environments from the Hub
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- local: envhub_leisaac
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title: Control & Train Robots in Sim (LeIsaac)
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title: "Simulation"
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- sections:
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- local: adding_benchmarks
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title: Adding a New Benchmark
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- local: libero
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title: LIBERO
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- local: libero_plus
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title: LIBERO-plus
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- local: metaworld
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title: Meta-World
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- local: robotwin
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title: RoboTwin 2.0
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- local: robocasa
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title: RoboCasa365
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- local: robocerebra
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title: RoboCerebra
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- local: robomme
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title: RoboMME
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title: LeIsaac — control & train in sim
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- local: envhub_isaaclab_arena
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title: NVIDIA IsaacLab Arena Environments
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- local: vlabench
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title: VLABench
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title: "Benchmarks"
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title: NVIDIA IsaacLab Arena environments
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- sections:
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- local: libero
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title: LIBERO
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- local: libero_plus
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title: LIBERO-plus
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- local: metaworld
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title: Meta-World
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- local: robotwin
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title: RoboTwin 2.0
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- local: robocasa
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title: RoboCasa365
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- local: robocerebra
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title: RoboCerebra
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- local: robomme
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title: RoboMME
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- local: vlabench
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title: VLABench
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title: Benchmark suites
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title: Simulation & benchmarks
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- sections:
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- local: introduction_processors
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title: Introduction to Robot Processors
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- local: debug_processor_pipeline
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title: Debug your processor pipeline
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- local: implement_your_own_processor
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title: Implement your own processor
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title: Introduction to processors
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- local: processors_robots_teleop
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title: Processors for Robots and Teleoperators
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title: Processors for robots & teleoperators
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- local: env_processor
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title: Environment Processors
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title: Environment processors
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- local: action_representations
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title: Action Representations
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title: "Robot Processors"
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title: Action representations
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- local: debug_processor_pipeline
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title: Debugging a pipeline
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- local: implement_your_own_processor
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title: Implementing your own processor
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title: Processors
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- sections:
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- local: so101
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title: SO-101
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- local: so100
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title: SO-100
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- local: koch
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title: Koch v1.1
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- local: lekiwi
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title: LeKiwi
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- local: hope_jr
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title: Hope Jr
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- local: reachy2
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title: Reachy 2
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- local: unitree_g1
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title: Unitree G1
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- local: earthrover_mini_plus
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title: Earth Rover Mini
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- local: omx
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title: OMX
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- local: openarm
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title: OpenArm
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- local: rebot_b601
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title: reBot B601-DM
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title: "Robots"
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- sections:
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- local: phone_teleop
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title: Phone
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title: "Teleoperators"
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- sections:
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- local: so101
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title: SO-101
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- local: so100
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title: SO-100
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- local: koch
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title: Koch v1.1
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- local: omx
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title: OMX
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- local: openarm
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title: OpenArm
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title: Low-cost arms
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- sections:
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- local: lekiwi
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title: LeKiwi
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- local: earthrover_mini_plus
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title: Earth Rover Mini
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title: Mobile platforms
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- sections:
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- local: hope_jr
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title: Hope Jr
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- local: reachy2
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title: Reachy 2
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- local: unitree_g1
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title: Unitree G1
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title: Bimanual & humanoid
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- sections:
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- local: rebot_b601
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title: reBot B601-DM
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title: Research & industrial
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title: Supported robots
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- sections:
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- local: cameras
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title: Cameras
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title: "Sensors"
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- sections:
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- local: notebooks
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title: Notebooks
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- local: phone_teleop
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title: Phone teleoperation
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- local: feetech
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title: Updating Feetech Firmware
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title: Feetech firmware update
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- local: damiao
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title: Damiao Motors and CAN Bus
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title: "Resources"
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title: Damiao motors & CAN bus
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title: Sensors, teleop & motors
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- sections:
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- local: contributing
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title: Contribute to LeRobot
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- local: integrate_hardware
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title: Bring your own hardware
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- local: bring_your_own_policies
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title: Add a new policy
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- local: adding_benchmarks
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title: Add a new benchmark
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title: Extend LeRobot
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- sections:
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- local: troubleshooting # NEW (to create) — common errors: USB, calibration drift, CUDA OOM, video decoding…
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title: Troubleshooting & FAQ
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- local: glossary # NEW (to create) — episode, action chunk, leader/follower, teleop, processor…
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title: Glossary
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- local: notebooks
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title: Example notebooks
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- local: backwardcomp
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title: Backward compatibility
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title: "About"
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title: Reference
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- sections:
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- local: contributing
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title: Contributing to LeRobot
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title: About
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