LocoManiLab release

Benchmark data, simulator assets, and fine-tuned policy checkpoints for LocoManiLab, a workflow for humanoid (Unitree G1, SONIC whole-body controller) loco-manipulation policy research. The code, setup guides, and download tools live in the GitHub repository; this repository holds the large files.

Path	Contents	Size
dataset/	LeRobot v2.1 datasets, one directory per task	33 GB
asset/	Asset manifest, task map, and the few asset files hosted here (NOTICE.md)	18 MB
checkpoint/gr00t/	GR00T N1.7, fine-tuned on train50, step 10000	6.9 GB
checkpoint/dm05/	DM0.5, fine-tuned on train50, step 50000	23 GB
checkpoint/xr1/	XR-1 (Lightning run directory), fine-tuned on train50, step 50000	11 GB
checkpoint/controller/	G1 whole-body controller weights (SONIC, HEFT, AMO, ScaleBFM, ALMI) for g1_backend	1.2 GB

Download

Use the helper from a LocoManiLab checkout (pip install -e '.[data,hf]'):

python scripts/hf/download.py list
python scripts/hf/download.py dataset --task IThorKitchenOpenFridge_scene13 --out datasets/hf
python scripts/hf/download.py assets --task IThorKitchenOpenFridge_scene13 --assets-dir external/humanoid_benchmark/robocasa/models/assets
python scripts/hf/download.py checkpoint gr00t --out checkpoints/hf
python scripts/hf/minimal_test.py --work hf-minimal-test

or the Hub CLI directly:

hf download GammaRobotics/LocoManiLab --repo-type dataset \
  --include "dataset/main/atomic/seen/IThorKitchenOpenFridge_scene13/*" --local-dir datasets/hf

See data, assets, and checkpoints for presets, checkpoint requirements, and the minimal download-and-test unit.

Dataset

Every task directory is a LeRobot v2.1 dataset (meta/, data/chunk-*/episode_*.parquet, videos/chunk-*/observation.images.ego_view/episode_*.mp4) recorded at 50 Hz in MuJoCo with the G1 robot and the SONIC v1_1 controller, plus three real-robot tasks.

Group	Contents
main/{atomic,composite}/{seen,unseen_scene,unseen_task}/	the 234 benchmark tasks; names match lab tasks and benchmark/tasks.yaml
data_generation/{human,gpt_aug,kimodo}/	the same tasks from different motion sources
multi_controller/{almi,amo,heft,scalebfm,sonic}/	tasks recorded with other whole-body controllers
real/, real2sim/	three TeleLab tasks on the real robot and their simulated replicas

Each frame has a 320×240 RGB ego view, a 43-D joint state (observation.state), end-effector, root-orientation and projected-gravity observations, the task instruction, and actions including the 64-D SONIC motion token and 7-D left/right hand targets. Directories under data_generation/kimodo/ and two under real/ have no meta/stats.json; LocoManiLab's lab validate and lab prepare do not need it.

Simulator assets

Apart from the files listed in asset/NOTICE.md, this repository does not redistribute simulator assets. asset/manifest.tsv.gz lists every file the benchmark tasks load (path relative to humanoid_benchmark/robocasa/models/assets, sha256, size, source) and asset/tasks.json.gz maps each task to its files. The download helper fetches each file from its original host and verifies its checksum; all 234 benchmark tasks plus the randomization texture pool need 22,745 files (3.4 GB), one iTHOR task about 32 MB.

Source	Content	Terms
MolmoSpaces	iTHOR, ProcTHOR, Holodeck scenes; THOR and Objaverse objects	CC BY 4.0; Objaverse subset ODC-BY 1.0, per-object licenses
RoboCasa asset archives	textures, generative textures, Objaverse and AI-generated object categories	CC BY 4.0
NVIDIA PhysicalAI Kitchen MJCF	Lightwheel fixtures and objects	CC BY 4.0
simulator checkout	TeleLab scenes and objects, layouts, task specs	the simulator's terms
asset/local.tar.gz (this repository)	Gamma Robotics' converted box (objects/usd/box/converted)	MIT
asset/local.tar.gz (this repository)	a folder from ArtVIP folder_25, materials and joints modified, converted to MuJoCo (fixtures/articulated/green_folder001)	Apache-2.0 (asset/LICENSE-Apache-2.0.txt)
asset/local.tar.gz (this repository)	a RoboCasa object file with a corrected texture path	CC BY 4.0 (RoboCasa)

Checkpoints

Inference weights only; optimizer states were not released, so the checkpoints cannot resume training. Serving instructions are in each policy guide of the GitHub repository.

• gr00t/: serve with the Isaac-GR00T environment. It loads the gated backbone nvidia/Cosmos-Reason2-2B at startup (accept its terms and log in on the serving machine).
• dm05/: serve with the OpenDM environment.
• xr1/: serve with the Xiaomi-Robotics-1 environment and a local Qwen3-VL cache; the run directory has no last.ckpt, so pass --ckpt-step 50000.

Whole-body controller weights

checkpoint/controller/ mirrors <g1_backend>/checkpoints/ and holds only the ONNX and TorchScript weights; the matching policy.yaml manifests are tracked in g1_backend. Fetch only the controller you run with the simulator's helper, for example the SONIC v1_1 controller used by the benchmark data:

python external/humanoid_benchmark/robocasa/scripts/download_g1_checkpoints.py \
  --family sonic_v1_1 --dest external/g1_backend/checkpoints

Family	Path	Origin
sonic (low-latency, with the shared planner)	sonic/low_latency/g1/	NVIDIA GEAR-SONIC
sonic_v1_1	sonic/v1_1/g1/	NVIDIA GEAR-SONIC
heft	heft/pmg/	HEFT, converted for g1_backend
amo	amo/	AMO, converted for g1_backend
scalebfm	scalebfm/humanoid_transformer_m/	ScaleBFM, converted for g1_backend
almi	almi/flat_dual/	mjlab Mjlab-Velocity-Flat-Unitree-G1-Dual, exported to ONNX

Sources and terms

The data recorded by this project, the fine-tuned checkpoints, and Gamma Robotics' own assets are released under the MIT License (LICENSE). Third-party material keeps its own terms, which apply in addition:

• Simulator assets are fetched from their original hosts under those hosts' terms (see above); the benchmark data renders them. Two of the 47 Objaverse objects the tasks load are licensed CC BY-NC 4.0: framed wall art 596fd518055a49a28d56c193cd087470 (by 2zqa) and f33af1b399a24448880930fef312ef3f (by jamesgourge) in Holodeck scene 117. They are fetched from MolmoSpaces, not hosted here, and may be visible in the scene-117 videos; their non-commercial terms apply to that content.
• Controller weights in checkpoint/controller/ are converted deploy artifacts of the upstream projects listed above and keep those projects' terms; the SONIC weights are under the NVIDIA Open Model License.
• Checkpoints are fine-tuned from nvidia/GR00T-N1.7-3B (with nvidia/Cosmos-Reason2-2B), DM0.5, and XiaomiRobotics/Xiaomi-Robotics-1-5B (with Qwen/Qwen3-VL-4B-Instruct); their model licenses and acceptance requirements apply.

Check the terms of each source before redistributing or using this material commercially.