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Anchor-Lab

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robotics
sim-to-real
h1
g1
unitree
RL
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metadata 
license: apache-2.0
pretty_name: Anchor-Lab
size_categories:
  - 100K<n<1M
tags:
  - robotics
  - sim-to-real
  - h1
  - g1
  - unitree
  - RL
  - isaaclab
  - newton
  - system-identification
  - robot-calibration
  - physical-ai
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/**/*.parquet

Anchor-Lab Dataset Card

Dataset Description

Anchor-Lab is a tabular robotics dataset captured from Anchor Lab, a sim-to-real transfer laboratory from NVIDIA Robotics. The dataset is designed to support calibration of physics simulation against physical robot measurements for zero-shot sim-to-real deployment.

The public release contains long-form parquet tables of robot experiment telemetry. Each row records a timestamped scalar measurement for an experiment and signal field. The dataset covers H1- and G1-family humanoid robot experiments, including arm, leg, multi-joint, single-joint, and elbow test-stand measurements.

For simplicity, this card refers to the dataset as Anchor-Lab.

Dataset Group Overview

The release is organized into seven top-level data groups under data/.

Group Description Approx. storage
g1_arm_multijoint G1 arm multi-joint excitation trials, including multi-frequency, multisine, chirp, wave-sine, wave-chirp, antiphase, and related patterns. 53.3 MB
g1_arm_single_joint G1 arm single-joint trials across elbow, shoulder pitch, shoulder roll, and related arm joints with pose and excitation variations. 238 MB
g1_leg_multijoint G1 leg multi-joint trials across pose variants, including independent multisine, multi-frequency, slow-wave, wave-sine, and wave-chirp patterns. 85.9 MB
g1_leg_single_joint G1 leg single-joint trials across ankle, hip, knee, and related leg joints with pose and excitation variations. 479 MB
h1_elbow_teststand H1 elbow test-stand system-identification measurements across frequency, amplitude, and position settings. 334 MB
h1_multijoint H1 multi-joint trials with chirp and sine-style excitations across frequency, amplitude, in-phase, antiphase, and wave settings. 318 MB
h1_single_joint H1 single-joint trials for elbow, shoulder pitch, shoulder raise, and related joints using sine and chirp-style excitations. 349 MB

Dataset Category Previews

G1 Dataset H1 Dataset Isolated Motor / Test-Stand Dataset
G1 sim-to-real recording preview H1 sim-to-real recording preview Isolated motor and test-stand recording preview
G1 dataset (G1 arm single-joint and multi-joint). H1 dataset (H1 elbow single-joint and multi-joint). Benchtop isolated H1 motor dataset (test-stand).

These previews are included for qualitative inspection of the experimental setup and motion patterns. They are not required for loading, filtering, or analyzing the parquet data.

Dataset Owner(s)

NVIDIA Corporation / NVIDIA Robotics

Dataset Creation Date

Public release: June 2026

Version

v1.0

Previous version(s): N/A

License/Terms of Use

Apache License 2.0

Intended Usage

This dataset is intended for researchers and AI practitioners working on:

  • Simulation calibration against measured physical robot behavior.
  • System identification for humanoid robot joints, actuators, and coupled multi-joint dynamics.
  • Sim-to-real transfer workflows for zero-shot or few-shot physical deployment.
  • Validation of physics-engine, actuator, controller, and sensor models against laboratory measurements.
  • Robot-control research using timestamped measurements from H1 and G1 humanoid platforms.
  • Analysis pipelines for long-form robot telemetry in parquet format.

This dataset is not intended to be used as the sole validation source for safety-critical robot deployment. Controllers, policies, and calibrated models derived from this dataset should be evaluated in simulation, test stands, and controlled physical environments before any real-world deployment.

Dataset Characterization

Data Collection Method

Physical - The data was captured from Anchor Lab experiments using onboard sensors found in the Unitree platforms and test-stand measurement pipelines. The experiment identifiers and file names encode platform, body region, single-joint or multi-joint scope, joint or joint group, excitation type, pose variant, trial number, and, where available, collection date, frequency, amplitude, or position setting.

The public data is organized around structured excitation and system-identification-style trials. File names indicate patterns such as sine, chirp, multisine, sine sweep, etc.

Labeling Method

Automated / procedural - The released labels are metadata generated by the acquisition and data-processing pipeline. The core metadata fields are:

  • experiment: trial or experiment identifier.
  • field: measured signal name.
  • time_ns and time_utc: timestamp fields.
  • value: scalar measurement value for the given timestamp and field.

The dataset does not provide human-annotated semantic labels. Field names and experiment identifiers should be treated as structured telemetry metadata.

Dataset Category Description

G1 Arm - Multi-Joint

The g1_arm_multijoint group contains multi-joint arm excitation trials for G1. Visible file naming patterns include antiphase, broadband pose, fast wave, multi-chirp, multi-frequency, multisine, slow wave, wave-chirp, and wave-sine trials.

G1 Arm - Single Joint

The g1_arm_single_joint group contains single-joint G1 arm measurements across elbow, shoulder pitch, shoulder roll, and related arm joints. Visible file naming patterns include pose variants such as neutral, forward-raised-extended, and back-bent, and excitation types such as bookend, chirp, multisine, sine sweep, slow ramp, step, and varying amplitude.

G1 Leg - Multi-Joint

The g1_leg_multijoint group contains multi-joint G1 leg excitation trials. Visible file naming patterns include independent multisine, multi-frequency, slow-wave, wave-chirp, and wave-sine experiments across pose variants.

G1 Leg - Single Joint

The g1_leg_single_joint group contains single-joint G1 leg measurements across ankle, hip, knee, and related leg joints. Visible file naming patterns include ankle pitch, ankle roll, hip pitch, and pose variants such as neutral, forward-bent, and back-extended.

H1 Elbow Test Stand

The h1_elbow_teststand group contains H1 elbow test-stand system-identification measurements. File names encode settings such as frequency, amplitude level, and position index.

H1 Multi-Joint

The h1_multijoint group contains H1 multi-joint experiments. Visible file naming patterns include chirp and sine trials with frequency ranges, amplitude values, and phase/coordination variants such as in-phase, wave, and antiphase.

H1 Single Joint

The h1_single_joint group contains H1 single-joint experiments for elbow, shoulder pitch, shoulder raise, and related joints. Visible file naming patterns include chirp and sine trials across pose variants and repeated trial indices.

Dataset Format

Field Type Description
time_ns int64 Nanosecond-resolution timestamp for the measurement row.
time_utc timestamp[ns, tz=UTC] UTC timestamp corresponding to time_ns.
experiment string Experiment or trial identifier.
field string Name of the measured signal.
value float64 Scalar measurement value for the given timestamp, experiment, and field.

The dataset is stored in long format: one row corresponds to one scalar value for one signal field at one timestamp in one experiment. Users who need a wide time-series table can pivot by field after loading a subset.

Dataset Organization 

Anchor-Lab/
├── README.md
├── G1.gif
├── H1.gif
├── isolated_motor.gif
└── data/
    ├── g1_arm_multijoint/
    ├── g1_arm_single_joint/
    ├── g1_leg_multijoint/
    ├── g1_leg_single_joint/
    ├── h1_elbow_teststand/
    ├── h1_multijoint/
    └── h1_single_joint/

Each leaf directory contains parquet files for individual experiments or trials. File names generally follow this pattern, with group-specific variations:

<robot>-<body-region>-<single-or-multijoint>-<joint-or-excitation>-<pose-or-condition>-<trial-or-settings>.parquet

Examples:

data/h1_multijoint/h1-multijoint-v1-chirp-trial-001-freq-0p1-to-0p5hz-amp-0p05.parquet
data/g1_leg_multijoint/g1-leg-multijoint-wave-sine-pose-a-trial-001-20260408-173950.parquet
data/g1_arm_single_joint/g1-arm-single-joint-elbow-step-pose-a-neutral-20260403-091255.parquet

Download And Loading Examples

Install optional dependencies:

pip install -U "huggingface_hub[cli]" datasets pandas pyarrow polars

Download the complete dataset:

hf download nvidia/Anchor-Lab \
  --repo-type dataset \
  --local-dir ./Anchor-Lab

Download one source group, for example H1 multi-joint data:

hf download nvidia/Anchor-Lab \
  --repo-type dataset \
  --include "README.md" "data/h1_multijoint/*" \
  --local-dir ./Anchor-Lab-h1-multijoint

Other useful subset patterns include:

data/g1_arm_multijoint/*
data/g1_arm_single_joint/*
data/g1_leg_multijoint/*
data/g1_leg_single_joint/*
data/h1_elbow_teststand/*
data/h1_multijoint/*
data/h1_single_joint/*

Download a subset from Python:

from huggingface_hub import snapshot_download

snapshot_download(
    repo_id="nvidia/Anchor-Lab",
    repo_type="dataset",
    local_dir="./Anchor-Lab-g1-leg-single-joint",
    allow_patterns=[
        "README.md",
        "data/g1_leg_single_joint/*.parquet",
    ],
)

Load through Hugging Face Datasets:

from datasets import load_dataset

ds = load_dataset("nvidia/Anchor-Lab", split="train")
print(ds)
print(ds.features)
print(ds[0])

Dataset Quantification

Quantity Count / Size
Rows in default train split 992,000
Top-level data groups 7
Public file format Parquet
Total repository file size 1.86 GB
Modalities Tabular telemetry with string metadata fields

Approximate storage by top-level data group:

Group Approx. storage
g1_arm_multijoint 53.3 MB
g1_arm_single_joint 238 MB
g1_leg_multijoint 85.9 MB
g1_leg_single_joint 479 MB
h1_elbow_teststand 334 MB
h1_multijoint 318 MB
h1_single_joint 349 MB
Total 1.86 GB

Curation Notes

  • The dataset uses a compact long-form schema shared across the public parquet files.
  • The default Hugging Face viewer exposes a single train split.
  • Experiment identifiers and file names are important metadata and should be preserved during downstream processing.
  • Users should validate timestamp monotonicity, duplicate rows, missing fields, and field coverage before fitting calibration or system-identification models.
  • Units are field-specific. Do not assume a single unit convention across all field values without a data dictionary or experiment-specific documentation.

Known Limitations and Future Work

  • The current public schema is minimal and does not include a full data dictionary for every field value.
  • The release does not define standardized train/validation/test splits for model benchmarking.
  • Measurements may be specific to the hardware revision, firmware, controller configuration, sensors, test stand, and laboratory setup used during capture.
  • Timing, filtering, actuator latency, sensor latency, and controller-loop details may affect downstream system-identification results.
  • The dataset focuses on H1 and G1 humanoid robot experiments and should not be treated as representative of all robots or all operating conditions.
  • Future releases could add per-file manifests, units, calibration parameters, robot configuration metadata, controller settings, sensor descriptions, and benchmark splits.

Ethical Considerations

This dataset contains robot experiment telemetry and does not intentionally include human-subject data, real-world imagery, or personally identifiable information. However, robotics datasets can still be misused if they are used to calibrate, validate, or deploy unsafe physical controllers without adequate testing.

Users should evaluate derived models in simulation, isolated test stands, and controlled physical settings before deployment. Users are responsible for ensuring that their use of this dataset complies with applicable safety, security, privacy, and robotics deployment requirements.

Contributors

  • Elena Shrestha
  • Vignesh Bhavananthan
  • Vidur Vij
  • Alex Omar
  • Andrew Wrenn
  • Justin Shrake
  • Michael Clive
  • Hong Wang

Citation

Please cite the dataset as:

@dataset{nvidia_anchor_lab_2026,
  title        = {Anchor-Lab},
  author       = {NVIDIA},
  year         = {2026},
  publisher    = {Hugging Face},
  url          = {https://huggingface.co/datasets/nvidia/Anchor-Lab}
}