Build a Decentralized Embodied AI Infrastructure
Build a Decentralized
Embodied AI Infrastructure


Teleoperated mobile robot + arm system for pick-and-place and household tasks.
Authentic, diverse, and messy — just like the real world robots will operate in.
Contributed by real people from around the world, capturing true environmental diversity.
Building the data infrastructure for truly capable embodied AI systems.
Use our app to capture simple photos of floor stains, with labels and descriptions.
No technical background needed. Anyone can help.
A teleoperated mobile robot with a robotic arm will allow contributors to perform real manipulation tasks remotely.
No technical background needed. Anyone can help.
Coming Soon
Earned through participation activities such as daily check-ins, uploads, and streaks.
Redeemable for :
Based on the quality and diversity of your data.
Long-term value :
The ROBOTIN ecosystem is built on a multi-tiered framework.
The Data Collection Layer forms the foundation of ROBOTIN, utilizing household devices to capture high-fidelity, real-world data— ranging from video sequences to motion patterns.
This decentralized approach ensures diverse, high-quality data from everyday environments, vital for the development of embodied AI.
After data is collected, it is processed and refined in the Data Processing and Refinement Layer.
Here, the raw data is enhanced and structured by expert data professionals into valuable, actionable datasets ready for AI training and robotic system development.
The refined data is then made available in the Data Consumption and Application Layer, where it can be utilized by various industries such as physical AI and household robotics.
These applications rely on high-quality datasets to enhance their functionality and efficiency, driving the future of embodied intelligence.
Through the Tokenization and Value Exchange Layer, ROBOTIN tokenizes the real-world data.
This allows data producers to earn tokens for their contributions, while data consumers can access and utilize these datasets to further their work in AI and robotics development.
In parallel, our data collection system gathers video sequences from wrist-mounted cameras on robot arms, capturing end-to-end manipulation actions:
Stains, dust, spills — from everyday homes fuels perception models that help robots navigate and clean real-world environments.
Embodied AI learns by interacting with the real world. Training requires large-scale data, enabling robots to perceive, understand, and act with human-like adaptability. The market is huge.
ROBOTIN is a decentralized, global platform for Physical AI and Embodied Intelligence. Training data collection, processing, and storage.
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