MODALITY // 01
EGOCENTRIC · MULTI-VIEW
Visual Layer
What the world looks like from the perspective of an intelligent agent.
New ReleaseWorld's Largest Human Experience Dataset Xperience-10MBuilding the data
Building the data
foundation ofphysical intelligence.
Trusted by the world's best teams & labs
Synchronized multimodal data.
Multi-modal data. Model-ready output. From open datasets to bespoke data-as-a-service for specific Physical AI application.
MODALITY // 02
MANO · MOCAP · OBJECT MESH
Motion Layer
High-fidelity tracking of human-object interaction and dexterity.
MODALITY // 03
SLAM · 3D POSE · OBJECT MESH · 3DGS
Spatial Layer
Precise localization and mapping of environment geometry in real-time.
MODALITY // 04
IMU · NANOSECOND
Inertial Layer
Micro-vibrations and gravitational forces that visual sensors cannot capture.
MODALITY // 05
LLM · VISION-LANGUAGE
Semantic Layer
Language grounding and semantic context layered onto multimodal sensor streams.
// END TO END DATA ENGINE - THE FULL ECOSYSTEM
Ropedia's Data
Ecosystem
Capture, transform, and deliver human experience data for Physical AI.
Data Infrastructure for Physical Intelligence: From real-world capture to model-ready intelligence - one end-to-end stack.
01 · Sense
Homie Toolkit
/01
HARDWARE
Portable, egocentric capture - deployed anywhere, by anyone.
Head-mounted, multi-modal, all-day.
Raw Real World Input
02 · Engine
Data Processing-Experience Engine
/02
DATA PLATFORM
Ingest, structure, and manage physical world data
- from any source.
Data Engine
03 · Deliver
Xperience 10M Dataset / DAAS
/03
MODEL-READY DATA
Deployment grade multimodal datasets and custom data delivery
for Physical AI.
Data Delivery
END-TO-END STACK
The Infrastructure Engine
IN-THE-WILD CAPTUREHUMAN EXPERIENCECAPTURE AT SCALE4D MULTI-MODAL DATADATA INFRASTRUCTUREEMBODIED AIPHYSICAL AI
EGO-CENTRIC · PORTABLE · IN-THE-WILD
//01 - OUR HARDWARE — HOMIE
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.
Coverage360°
coverage
SYNC<50µs
precision
DATA MANAGEMENT
//02 - OUR DATA PROCESSING - ROPEDIA PLATFORM
One platform.
Any source.
Model-ready output.
Multi-source compatible - bring your own capture hardware or use ours. One unified engine for annotation, processing, and delivery.
SUPPORTS
Homie-Collected Data
Native integration with Homie hardware
Third-Party Data
Multi-source, multi-hardware compatible
Data Management
//03 - OUR DATA - DAAS/DATASET
Deployment grade multimodal datasets
and custom data delivery.
Multi-modal data. Model-ready output. From open datasets to bespoke data-as-a-service for specific Physical AI application.
Available Modalities
RGB Video
Depth
Audio
IMU
Hand Tracking
Trajectory
Motion Capture
Language Annotations
[Open Dataset]
// XPERIENCE-10M
Model-ready,
available now.
The largest human experience dataset for Physical AI. Multimodal 4D capture - open for the research community.
10M
Interaction Episodes
2.88B
RGB Frames
7.2B
IMU Frames
~1PB
Total Storage
[Custom / DaaS]
// CUSTOM DATA
Tailored data for
your specific needs.
Custom data collection, annotation, and dataset delivery for specific robotics and AI applications. Tiered service model - from consultation to full engine deployment.
T1Starter - Custom annotation runs
T2Growth - Engine + QC service
T3Enterprise - Full DaaS deployment
APPLICATION LANDSCAPE
Built for the full spectrum of
Physical AI research.
Robotics Foundation Models
Pre-training large-scale robot models on diverse, real-world human behavior data.
Vision-Language-Action
Grounded, multimodal training signal linking visual perception, language, and physical action.
Physical AI
Systems that understand and interact with the physical world through embodied intelligence.
World Models
Learning predictive representations of real-world environments and physics.
Dexterous Manipulation
Fine-grained hand pose and object interaction data for dexterous robot hands.
Mobile Manipulation
Combined locomotion and manipulation across real-world environments at scale.
Long-Horizon Planning
Multi-step task demonstrations for training long-horizon decision-making agents.
Human Demonstration Learning
Imitation and reinforcement learning from large-scale human behavioral demonstrations.
Multimodal Understanding
Cross-modal fusion across RGB, depth, IMU, audio, and language for richer scene understanding.