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Pepijn e699e52388 feat(envs): add RoboCasa365 benchmark integration (#3375) 
* feat(envs): add RoboCasa365 benchmark integration

Add RoboCasa365 (arXiv:2603.04356) as a new simulation benchmark with
365 everyday kitchen manipulation tasks across 2,500 diverse environments.

New files:
- src/lerobot/envs/robocasa.py: gym.Env wrapper with deferred env creation,
  flat 12D action / 16D state vectors, 3-camera support
- docs/source/robocasa.mdx: user-facing documentation
- docker/Dockerfile.benchmark.robocasa: CI benchmark image

Modified files:
- src/lerobot/envs/configs.py: RoboCasaEnv config (--env.type=robocasa)
- pyproject.toml: robocasa optional dependency group
- docs/source/_toctree.yml: sidebar entry
- .github/workflows/benchmark_tests.yml: integration test job

Refs: https://arxiv.org/abs/2603.04356, https://robocasa.ai
Related: huggingface/lerobot#321

* fix(docker): use uv pip to install robocasa in benchmark image

The huggingface/lerobot-gpu base image uses `uv` with a venv at
/lerobot/.venv — `pip` is not on PATH, so `pip install` fails with
"pip: not found". Switch to `uv pip install` which installs into the
existing venv.

Also drop the @v1.0.0 tag pin from the robocasa git URL since the
upstream repo may not have that tag; use default branch instead.

* fix(robocasa): editable install + switch to lerobot/smolvla_robocasa

- pip install from git omits data files like box_links_assets.json
  (not declared in package_data). Clone and install editable so the
  source tree is used at runtime.
- Download only tex + fixtures_lw asset types (smoke test doesn't need
  objaverse/aigen objects). Pipe 'y' to auto-accept download prompt.
- Switch CI policy from pepijn223/smolvla_robocasa to lerobot/smolvla_robocasa.

* fix(docker): re-install lerobot editably after COPY

The nightly huggingface/lerobot-gpu image predates the RoboCasaEnv
registration — so `lerobot-eval --env.type=robocasa` fails at argparse
with "invalid choice" even after COPY . . overlays the new source.
Force an editable reinstall so the venv picks up the current configs.py.


* fix(ci): add rename_map for robocasa eval (image* -> camera*)

Policy lerobot/smolvla_robocasa expects observation.images.camera1/2/3,
but RoboCasaEnv produces observation.images.image/image2/image3.

* fix(robocasa): override RoboCasaGymEnv default split (test -> all)

RoboCasaGymEnv defaults split="test", but create_env only accepts
{None, "all", "pretrain", "target"}, so the out-of-the-box default
crashes with ValueError. Always pass "all" when split is None.


* fix(docker): also download objs_lw (lightwheel objects) for robocasa

Kitchen tasks (e.g. CloseFridge) reference lightwheel object meshes
like Stool022/model.xml. fixtures_lw alone isn't enough — we also
need objs_lw. Still skipping objaverse/aigen to keep image size down.

Made-with: Cursor

* feat(robocasa): raw camera names + benchmark-group task shortcuts

Align the LeRobot env with RoboCasa's native conventions so policies
trained on the upstream datasets don't need a --rename_map at eval
time, and expose the standard task groups as first-class --env.task
values.

- Preserve raw RoboCasa camera names (e.g. robot0_agentview_left)
  as observation.images.<name> end-to-end. Drops camera_name_mapping
  and DEFAULT_CAMERA_NAME_MAPPING; features/features_map are now
  built dynamically from the parsed camera list.
- Accept benchmark-group names as --env.task: atomic_seen,
  composite_seen, composite_unseen, pretrain50/100/200/300. Expanded
  lazily via robocasa.utils.dataset_registry and auto-sets the
  split ("target" | "pretrain").
- Update CI smoke-eval rename_map to map raw cam names to the
  camera1/2/3 keys expected by lerobot/smolvla_robocasa.


* docs(robocasa): single-task smolvla train+eval recipe on pepijn223/robocasa_CloseFridge

- Rewrite observation section to use raw RoboCasa camera keys
  (observation.images.robot0_agentview_{left,right},
  observation.images.robot0_eye_in_hand).
- Add a "Training on a single task" section with a full smolvla
  training command on pepijn223/robocasa_CloseFridge, plus matching
  single-task eval command.
- Document benchmark-group task shortcuts (atomic_seen, composite_seen,
  composite_unseen, pretrain50/100/200/300) as valid --env.task values.


* fix(robocasa): restrict obj_registries to lightwheel by default

CloseFridge (and most kitchen tasks) crashed at reset with
`ValueError: Probabilities contain NaN` coming out of
`sample_kitchen_object_helper`. RoboCasa's upstream default
`obj_registries=("objaverse", "lightwheel")` normalizes per-registry
candidate counts as probabilities; when a sampled category has zero
mjcf paths in every configured registry (because the objaverse asset
pack isn't on disk — ~30GB, skipped by our Docker build), the 0/0
divide yields NaNs and `rng.choice` raises.

- Add `obj_registries: list[str] = ["lightwheel"]` to `RoboCasaEnv`
  config; thread it through `create_robocasa_envs`, `_make_env_fns`,
  and the gym.Env wrapper to the underlying `RoboCasaGymEnv` (which
  forwards to `create_env` → `robosuite.make` → kitchen env).
- Default matches what `download_kitchen_assets --type objs_lw`
  actually ships, so the env works out of the box without a 30GB
  objaverse download.
- Document the override (`--env.obj_registries='[objaverse,lightwheel]'`)
  for users who have downloaded the full asset set.


* fix(docker): also download tex_generative for robocasa benchmark

RoboCasa's lightwheel kitchen fixtures embed references to
`generative_textures/wall/tex*.png` directly in their MuJoCo XML, so
`MjModel.from_xml_string` errors out at reset time with
"No such file or directory" even when the env is constructed with
`generative_textures=None`. The generative textures live under a
separate asset registry key (`tex_generative`) in
`download_kitchen_assets`, distinct from the base `tex` pack we were
already fetching.

- Add `tex_generative` to the download list so the fixture XMLs
  resolve.
- Document the remaining omissions (objaverse/aigen, ~30GB) and how
  the runtime side pairs this with obj_registries=["lightwheel"] to
  avoid sampling from categories whose assets aren't on disk.

* ci(robocasa): smoke-eval 10 atomic tasks instead of 1

Broader coverage in the benchmark CI job: evaluate SmolVLA on ten
fixture-centric atomic RoboCasa tasks (one episode each) instead of
just CloseFridge. The tasks are all drawn from TARGET_TASKS.atomic_seen
and selected to avoid object-manipulation categories that would require
the objaverse/aigen asset packs (we only ship objs_lw in the Docker
image, paired with obj_registries=["lightwheel"] on the runtime side).

Tasks: CloseFridge, OpenCabinet, OpenDrawer, TurnOnMicrowave,
TurnOffStove, CloseToasterOvenDoor, SlideDishwasherRack,
TurnOnSinkFaucet, NavigateKitchen, TurnOnElectricKettle.

`scripts/ci/parse_eval_metrics.py` already handles multi-task output
via the `overall` key, so no parser changes needed. Bumped the metrics
artifact's task label to `atomic_smoke_10` to reflect the grouping.

* fix(pyproject): drop unresolvable robocasa extra

robocasa's upstream setup.py hardcodes `lerobot==0.3.3` in
install_requires. Exposing it as the `lerobot[robocasa]` extra made
uv's dep resolver cycle: `lerobot[robocasa]` -> robocasa -> lerobot
(a different version) -> unsolvable. This broke every `uv sync` — even
invocations with an unrelated extra like `--extra test` — because uv
validates the whole lockfile graph.

- Remove the `robocasa` extra from pyproject.toml. Installation
  instructions in docs/source/robocasa.mdx now walk users through the
  manual `git clone` + `pip install --no-deps` flow, which matches
  what the Docker image already does and sidesteps the cyclic dep
  entirely.
- Dockerfile: `uv pip install -e ~/robocasa --no-deps` so the
  shadowed lerobot==0.3.3 never lands in the image; install
  robocasa's actual runtime deps (numpy, numba, scipy, mujoco,
  tianshou, etc.) explicitly.

* docs(robocasa): align page with adding_benchmarks template

Rework docs/source/robocasa.mdx to follow the standard benchmark doc
structure: intro + links + available tasks (with family breakdown and
first-class benchmark-group shortcuts) + installation + eval +
recommended episodes + policy I/O + training + reproducing results.

- Fix the paper link (was pointing at a non-existent arxiv ID).
- Surface lerobot/smolvla_robocasa and pepijn223/robocasa_CloseFridge
  in the top-of-page links so they're findable without reading the
  training section.
- Add an explicit "Object registries" subsection explaining the
  `--env.obj_registries=[objaverse,lightwheel]` override path.
- Add an explicit "Reproducing published results" section pointing
  at the CI smoke eval.

* fix: integrate PR #3375 review feedback

- envs(robocasa): hoist the duplicated `_parse_camera_names` helper
  out of `libero.py` and `robocasa.py` into `envs/utils.py` as the
  public `parse_camera_names`; call sites updated.
- envs(robocasa): give each factory a distinct `episode_index`
  (`0..n_envs-1`) and derive a per-worker seed series in `reset()`
  so n_envs workers don't all roll the same scene under a shared
  outer seed.
- envs(robocasa): drop the unused `**kwargs` on `_make_env`; declare
  `visualization_height` / `visualization_width` on both the wrapper
  and the `RoboCasaEnv` config + propagate via `gym_kwargs`.
- envs(robocasa): emit `info["final_info"]` on termination (matching
  MetaWorld) so downstream vector-env auto-reset keeps the terminal
  task/success flags.
- docs(robocasa): add `--rename_map` (robot0_agentview_left/
  eye_in_hand/agentview_right → camera1/2/3) plus CI-parity flags to
  all three eval snippets.
- docker(robocasa): pin robocasa + robosuite git SHAs and the pip
  dep versions (pygame, Pillow, opencv-python, pyyaml, pynput, tqdm,
  termcolor, imageio, h5py, lxml, hidapi, gymnasium) for
  reproducible benchmark images.
- ci(robocasa): update the workflow comment — there is no
  `lerobot[robocasa]` extra; robocasa/robosuite are installed
  manually because upstream's `lerobot==0.3.3` pin shadows ours.

* docs(robocasa): add benchmark banner image

* fix(envs): preserve AsyncVectorEnv metadata/unwrapped in lazy eval envs

Port of #3416 onto this branch. Also threads the cached metadata
through the RoboCasa factory so async eval on `--env.type=robocasa`
keeps the same improvement.


* fix: integrate PR #3375 review feedback (round 2)

- envs(robocasa): when the caller passes `seed=None` to `reset()`,
  fall back to `self.episode_index` for the inner env seed so each
  worker still samples a distinct trajectory instead of all workers
  inheriting the same global RNG state.
- envs(robocasa): replace the two module-level `print()` calls in
  `create_robocasa_envs` with `logger.info(...)` via a module-level
  `logger = logging.getLogger(__name__)`.
- ci(robocasa): run `scripts/ci/extract_task_descriptions.py` after
  the eval so `metrics.json` carries per-task natural-language
  labels, matching LIBERO / MetaWorld / VLABench jobs. Added a
  `_robocasa_descriptions()` extractor that splits CamelCase task
  names into word-level labels keyed by `<task>_0`.
2026-04-20 17:10:53 +02:00

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- sections:
- local: index
title: LeRobot
- local: installation
title: Installation
title: Get started
- sections:
- local: il_robots
title: Imitation Learning for Robots
- local: bring_your_own_policies
title: Bring Your Own Policies
- local: integrate_hardware
title: Bring Your Own Hardware
- local: hilserl
title: Train a Robot with RL
- local: hilserl_sim
title: Train RL in Simulation
- local: multi_gpu_training
title: Multi GPU training
- local: hil_data_collection
title: Human In the Loop Data Collection
- local: peft_training
title: Training with PEFT (e.g., LoRA)
- local: rename_map
title: Using Rename Map and Empty Cameras
title: "Tutorials"
- sections:
- local: lerobot-dataset-v3
title: Using LeRobotDataset
- local: porting_datasets_v3
title: Porting Large Datasets
- local: using_dataset_tools
title: Using the Dataset Tools
- local: dataset_subtask
title: Using Subtasks in the Dataset
- local: streaming_video_encoding
title: Streaming Video Encoding
title: "Datasets"
- sections:
- local: act
title: ACT
- local: smolvla
title: SmolVLA
- local: pi0
title: π₀ (Pi0)
- local: pi0fast
title: π₀-FAST (Pi0Fast)
- local: pi05
title: π₀.₅ (Pi05)
- local: groot
title: NVIDIA GR00T N1.5
- local: xvla
title: X-VLA
- local: multi_task_dit
title: Multitask DiT Policy
- local: walloss
title: WALL-OSS
title: "Policies"
- sections:
- local: sarm
title: SARM
title: "Reward Models"
- sections:
- local: async
title: Use Async Inference
- local: rtc
title: Real-Time Chunking (RTC)
title: "Inference"
- sections:
- local: envhub
title: Environments from the Hub
- local: envhub_leisaac
title: Control & Train Robots in Sim (LeIsaac)
title: "Simulation"
- sections:
- local: adding_benchmarks
title: Adding a New Benchmark
- local: libero
title: LIBERO
- local: metaworld
title: Meta-World
- local: robocasa
title: RoboCasa365
- local: envhub_isaaclab_arena
title: NVIDIA IsaacLab Arena Environments
title: "Benchmarks"
- sections:
- local: introduction_processors
title: Introduction to Robot Processors
- local: debug_processor_pipeline
title: Debug your processor pipeline
- local: implement_your_own_processor
title: Implement your own processor
- local: processors_robots_teleop
title: Processors for Robots and Teleoperators
- local: env_processor
title: Environment Processors
- local: action_representations
title: Action Representations
title: "Robot Processors"
- sections:
- local: so101
title: SO-101
- local: so100
title: SO-100
- local: koch
title: Koch v1.1
- local: lekiwi
title: LeKiwi
- local: hope_jr
title: Hope Jr
- local: reachy2
title: Reachy 2
- local: unitree_g1
title: Unitree G1
- local: earthrover_mini_plus
title: Earth Rover Mini
- local: omx
title: OMX
- local: openarm
title: OpenArm
title: "Robots"
- sections:
- local: phone_teleop
title: Phone
title: "Teleoperators"
- sections:
- local: cameras
title: Cameras
title: "Sensors"
- sections:
- local: torch_accelerators
title: PyTorch accelerators
title: "Supported Hardware"
- sections:
- local: notebooks
title: Notebooks
- local: feetech
title: Updating Feetech Firmware
- local: damiao
title: Damiao Motors and CAN Bus
title: "Resources"
- sections:
- local: contributing
title: Contribute to LeRobot
- local: backwardcomp
title: Backward compatibility
title: "About"
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