Data Infrastructure for Physical AI

Building the data foundation of physical intelligence.

ropedia / capture / structure / deliver / deploy

We capture, structure, and deliver real-world human experience as machine-usable data — for robotics, world models, and embodied AI.

10M+
Interactions
10K
Hours of Video
~1PB
Total Data
ROPEDIA.DATA — STREAM v2.0 — CONNECTED[ ESC to exit ]
 PHYSICAL AI  ·  IN-THE-WILD DATA  ·  EMBODIED AI  ·  WORLD MODELS  ·  4D CAPTURE  ·  MULTI-MODAL  ·  OPEN DATASET  ·  INTERNET-SCALE  ·  DATA-FIRST  ·  END-TO-END INFRA  ·   PHYSICAL AI  ·  IN-THE-WILD DATA  ·  EMBODIED AI  ·  WORLD MODELS  ·  4D CAPTURE  ·  MULTI-MODAL  ·  OPEN DATASET  ·  INTERNET-SCALE  ·  DATA-FIRST  ·  END-TO-END INFRA  · 
§ 02EXPERIENCE.10M ─── dataset · numbers · access┤ ◈ ├
// open dataset

Xperience 10M

The largest in-the-wild multi-modal 4D human experience dataset for embodied AI — open for the research community.

10 M
Interaction Episodes
7.2 B
IMU Frames
2.88 B
RGB Frames
~1 PB
Total Storage
View on Hugging Face↗LEARN MORE ↗
// modality breakdown — by frame count
RGB FRAMES
2.88B
IMU FRAMES
7.2B
MOCAP FRAMES
576M
CAMERA POSES
576M
DEPTH FRAMES
720M
CAPTION SENTS
16M
OBJECTS
350K
VOCAB
6K
TRAJ.
39K km
dataset.status open · CC BY 4.0 · research use
downloads 2.1M total · growing
modalities RGB · depth · IMU · MoCap · pose
license CC BY 4.0 · open research
// pipeline ──────────────────────────────────────────
  [capture]──→[sync]──→[annotate]──→[4D-pack]──→[index]
      │           │          │           │           │
    in-wild     50µs      spatial      ~1PB       open
    deploy      sync      models      stored      access
§ 02.1DATASET.METRICS ─── scale · fidelity · coverage┤ ◈ ├
§ 03LIVE.PLAYGROUND ─── query · synthesize · cite┤ ◈ ├
In-the-Wild Capture◆4D Multi-Modal Data◆Embodied AI◆World Models◆Open Dataset◆Physical Intelligence◆In-the-Wild Capture◆4D Multi-Modal Data◆Embodied AI◆World Models◆Open Dataset◆Physical Intelligence◆
Ropedia — physical intelligence
§ H1HARDWARE.R-EGO ─── ego-centric · portable · in-the-wild┤ ◈ ├
R-Ego — head-mounted capture device
// R-EGO — EGO-CENTRIC IN-THE-WILD CAPTURE
// render · v1.0 · not finalHARDWARE
// our hardware — r-ego

One device.
Internet-scale capture.

Head-mounted, ego-centric capture for in-the-wild deployment. Multi-modal spatial and interaction sensing with auto-annotation via spatial foundation models. Lightweight, all-day, works anywhere.

FOV360° panoramic
SYNC50µs precision
CONTACT US →LEARN MORE
§ H2HARDWARE.R-DOME ─── dexterous · precision · manipulation┤ ◈ ├
// our hardware — r-dome

Capture context
at the source.

Precision tracking for dexterous manipulation data. High-density multi-view capture with programmable lighting — at a fraction of the cost of comparable lab setups.

DIAMETER1.5m workspace
COST50× reduction
CONTACT US →
R-Dome — hand-object interaction tracking system
// R-DOME — HAND-OBJECT INTERACTION TRACKING
// render · v1.0 · not finalHARDWARE
§ W1WHY.ROPEDIA ─── in the wild · at scale · no one else┤ ◈ ├
§ T2MISSION.VISION ─── purpose · direction · values┤ ◈ ├
╔══════════════════════════════════════════════════════════════════════════╗
║  system.manifest · ROPEDIA INC. · physical-ai data infrastructure       ║
╠══════════════════════════════════════════════════════════════════════════╣
║  entity      : ROPEDIA INC.          class   : data-infrastructure      ║
║  data_type   : 4D [ 3D + time + Δ ]  scale   : internet-grade           ║
║  collection  : in-the-wild           target  : embodied-ai · world-models║
╚══════════════════════════════════════════════════════════════════════════╝
// who we are

Defining the data foundation
of physical intelligence.

/MISSION

We are building the data infrastructure that allows robots, world models, and autonomous agents to truly understand and act in the physical world.

// data-first · deep tech · physical ai
/VISION

A world where physical intelligence is trained on real-world, in-the-wild human experience at internet scale — not bottlenecked by lab data or staged environments.

// from internet intelligence to physical intelligence
PHYSICAL INTELLIGENCE◆IN-THE-WILD DATA◆INTERNET-SCALE COLLECTION◆EMBODIED AI◆WORLD MODELS◆DATA-FIRST◆END-TO-END INFRA◆PHYSICAL INTELLIGENCE◆IN-THE-WILD DATA◆INTERNET-SCALE COLLECTION◆EMBODIED AI◆WORLD MODELS◆DATA-FIRST◆END-TO-END INFRA◆
§ 08GET.STARTED ─── join · deploy · scale┤ ◈ ├
╔══════════════════════════════════════╗ ║ ROPEDIA · PHYSICAL AI DATA
INFRA ║ ╚══════════════════════════════════════╝
// let's build together

Build the future of
physical intelligence.

CONTACT US →VIEW DATASET ↗

✓ Embodied AI  ·  ✓Robotic Systems  ·  ✓ World Models

◈
Open Dataset
Xperience-10M is freely available for research under CC BY 4.0.
◈
2.1M Downloads
Top 3 over all datasets on Hugging Face. Growing daily.
◈
Hardware + Data
End-to-end infrastructure from capture to deployment.
◈
Research Community
Whether you're building agents, robots, or world models — we'd love to hear from you.