HIW-500: 500 Hours of Humanoid Teleop Data From 12 Real Homes

On June 23, 2026, BitRobot (@BitRobotNetwork) released HIW-500 — Humanoids-in-the-Wild 500 — calling it the largest open-source humanoid teleoperation dataset collected in real homes.

Built with Unitree and Hugging Face / LeRobot, the drop lands the same day as Nori L2's iPhone-priced robot teaser and a week after Genesis Eno. The through-line in June 2026 robotics: real environments, not lab demos, are where the data wars are being fought.

"Built for learning from real homes, not lab-only scenes." — HIW-500 project page

TL;DR

Why in-the-wild humanoid data matters

Lab datasets teach robots to repeat. Home datasets teach robots to generalize.

HIW-500 explicitly targets variation that controlled benchmarks strip out:

• Layout — different room geometries across 12 homes
• Clutter — object density and placement change episode to episode
• Lighting — natural indoor conditions, not studio rigs
• Operator style — multiple human teleoperators with different habits
• Object state — fridges half-full, pillows moved, trash in different bins

That is the gap between Figure Helix-02 tidying a staged bedroom and a robot that works in your kitchen. Policy researchers have argued for years that pooling diverse teleop data drives generalist policies — Open X-Embodiment showed cross-embodiment pooling improves small-data domains by 50%. HIW-500 is the humanoid-home slice of that bet at scale.

Unitree's response on X:

"We're excited to support BitRobot in open-sourcing the largest humanoid whole-body teleoperation dataset collected in real homes. We hope it accelerates progress toward general-purpose humanoid robots." — @UnitreeRobotics

What is in each episode

Each episode records human whole-body teleoperation of a Unitree G1 in a real home — not joystick-only arm control, but locomotion + bimanual manipulation together.

Camera streams

Videos are encoded AV1 in the LeRobot release (yuv420p, CRF 30).

Robot state and actions

From the LeRobot dataset card:

• observation.state — 29-DoF joint positions (hips, knees, ankles, waist, arms, wrists)
• observation.state.wbc — whole-body control state: pivot velocity, roll/pitch/yaw, height, left/right end-effector poses, gripper triggers
• action — 23-D whole-body teleop commands mirroring human operator inputs
• IMU + odometry — in raw recordings
• language_persistent / language_events — language annotations per episode

This is VLA-ready multimodal data: three video streams + proprioception + language labels in a single LeRobot v3.0 schema (codebase_version: v3.0, robot_type: unitree_g1).

The 11 household tasks

BitRobot's project page lists every task in V1:

161 subtask labels and 148,000+ subtask annotations break episodes into fine-grained action tiles — useful for hierarchical policies, skill discovery, and evaluation rubrics rather than end-to-end black-box imitation only.

Two Hugging Face formats

LeRobot's team re-encoded the full corpus:

"We re-encoded the full dataset into LeRobot format: ~10TB → ~2TB, no loss of fidelity. Same trajectories, a fraction of the footprint, far easier to stream." — @LeRobotHF

For researchers already on LeRobot — the same stack the Columbia Nori Bot paper uses for ACT training — HIW-500-LeRobot is the practical entry point. Parquet chunks at 100 MB, video chunks at 200 MB, 1,000 episodes per chunk.

Quick load check

from lerobot.common.datasets.lerobot_dataset import LeRobotDataset

dataset = LeRobotDataset("BitRobot/HIW-500-LeRobot")
print(dataset.num_episodes)   # 23743
print(dataset.num_frames)     # 40839947
sample = dataset[0]
print(sample.keys())          # observation.images.*, action, language_*, etc.

Verify against your installed LeRobot version — HIW-500 targets LeRobot v3.0.

Who built it and who backs it

BitRobot's roadmap shows V1 in June 2026 (this release) and V2 with more tasks and environments later.

How HIW-500 fits the 2026 robotics stack

Consumer vs research gap: Nori L2 targets sub-$1k manipulators with OpenClaw scheduling. HIW-500 targets Unitree G1-class humanoids learning from hundreds of home hours. Same month, opposite ends of the cost curve — both need data.

Citation

@misc{hiw500_2026,
  title={HIW-500: Humanoids In-the-Wild Dataset for Robot Learning},
  author={BitRobot and Unitree and Hugging Face},
  year={2026},
  howpublished={\url{https://bitrobot-foundation.github.io/humanoids-in-the-wild-500-hours/}}
}

Project page includes a Rerun live preview for browsing episodes before downloading terabytes.

For commercial access beyond the public release, BitRobot offers Request Data Access on their project site.

Related ExplainX guides

Humanoids and datasets:

• Nori L2: iPhone-price robot + LeRobot stack — sub-$1k manipulation vs G1 humanoid scale
• Figure Helix-02 collaborative humanoid tidying — policy demo vs teleop dataset
• Figure AI: robots outnumber humans at BotQ — factory humanoid production context
• Genesis AI Eno agentic robot — foundation-model robotics stack
• Shift-free cleaning: NYC robotics data collection — another real-world data thesis

Physical AI and training:

• NVIDIA Cosmos 3 physical AI world models — simulation for robot training
• What are AI agents? — from teleop demos to autonomous execution
• What is OpenClaw? — proactive scheduling on cheap manipulators (Nori Bot lineage)

Primary sources: HIW-500 project page · LeRobot dataset · Raw dataset · @BitRobotNetwork · @UnitreeRobotics · @LeRobotHF

Summary

HIW-500 is the largest public humanoid teleop dataset from real homes as of June 23, 2026: 500+ hours, 23,743 episodes, 11 household tasks, 12 Southeast Asian homes, Unitree G1 whole-body control, and 148K+ subtask annotations. Download raw at ~10 TB or LeRobot v3.0 at ~2.15 TB on Hugging Face — same trajectories, easier streaming.

For anyone training mobile manipulation, bimanual skills, or home generalization policies, this is the dataset drop to benchmark against. Lab scores still matter; in-the-wild hours are what close the gap between demo videos and deployable humanoids.

Episode counts, file sizes, and task list reflect BitRobot's June 2026 V1 release and the Hugging Face dataset card. Re-check huggingface.co/datasets/BitRobot/HIW-500-LeRobot before large downloads — the corpus is multi-terabyte.