Imagine a robot that can carefully pick up ancient pottery shards and scan them into a computer without a human needing to do it manually. It doesn't just take a picture; it uses special sensors to 'feel' what the object is made of and its hidden properties. This turns dusty museum basements into searchable digital libraries that anyone can access.
Museums and archives have millions of artifacts that are invisible to the public because manual 3D digitisation is too slow, expensive, and labor-intensive.
A robotic system with AI-driven end-effectors and sensors that automatically creates 3D models enriched with material and compositional data.
If you are a digitization service dealing with millions of undocumented artifacts—this project developed AI-augmented robotics that automate 3D scanning and data collection. This reduces the heavy reliance on manual labor and lowers the cost of processing large collections.
If you are a hardware manufacturer dealing with the need for delicate object handling—this project developed novel end-effectors that are released and tested for fragile archaeological finds. This provides a blueprint for high-precision gripping tools for other fragile materials.
If you are a VR studio dealing with a lack of high-quality, verified historical assets—this project developed a workflow to create enriched 3D models with material data. This allows for the creation of hyper-realistic digital twins for educational or commercial reuse.
By replacing manual labor with AI-augmented robotics and sensors, the system enables low-cost and time-efficient 3D model creation. Based on available project data, it streamlines data acquisition to democratize access for smaller institutions.
The project aims to move away from fragmented workflows toward integrated and automated processes capable of managing data at scale. It specifically targets the millions of artifacts currently stored in European repositories.
Based on available project data, the project supports open science and FAIR data principles, aiming for integration into the European Cultural Heritage Cloud (ECCCH). Specific commercial licensing terms are not listed.
The system is designed for seamless integration into the ECCCH Cloud and aligns with the ECHOES initiative to share data and tools among professionals.
The project runs from 2024-09-01 to 2029-02-28, with upgrades to the promotional kit and end-effectors released throughout the project period.
The consortium is well-balanced for a technology transfer project, consisting of 13 partners across 7 countries. With a 23% industry ratio (including 3 industry partners and 2 SMEs), there is a clear bridge between the 6 universities and 4 research organizations and the commercial market, ensuring the robotic tools are developed with practical application in mind.
Contact Universita di Pisa regarding the robotic end-effector testing
Contact us to connect with the AUTOMATA consortium for robotic digitisation licensing.
