top of page


Projects and Initiatives

My Green Lab

My Green Lab introduces sustainability to the community responsible for the world's life-changing medical and technical innovations.

AI for Good

AI for Good is a year-round digital platform where AI innovators and problem owners learn, build and connect to identify practical AI solutions to advance the UN SDGs.

Sustainable Robotics

The first academic-driven robotics community on sustainability.



SOMIRO is a Horizon 2020 funded project that will develop and demonstrate the world’s first energy-autonomous swimming milli-robot with the aim of reducing the environmental impact of farming in terms of carbon footprint, eutrophication and excessive use of pesticides and feed.


Natural Intelligence H2020 project aims to serve the European Green Deal with robots able to accomplish monitoring of natural habitats.


TUBERS sets forth a new paradigm by creating the world’s first combination robotic platforms allowing for 24/7 inspection and targeted in-situ repairs, greatly reducing the costs of regular inspection and maintenance.

Smart Droplets

Smart Droplets’ main objective is to advance both hardware and software capabilities to deliver a holistic system capable of translating large amounts of data into meaningful information and impactful spraying commands on the field.


This project aims to develop a complete solution for robotic based inspection and repair of wind turbine blades (WTBs), both onshore and offshore.


RECLAIM will develop a portable, robotic MRF (prMRF) tailored to small-scale material recovery. The proposal exploits well-tested technology in robotics, AI and data analytics which is improved to facilitate distributed material recovery. RECLAIM adopts a modular multi-robot/multi-gripper approach for material recovery, based on low cost Robotic Recycling Workers (RoReWos).


The Grinner project aims at commercialising an autonomous AI-enabled robotic sorting system capable of detecting and removing waste containing batteries from current waste streams before they enter inhospitable-to-battery machines that crush and consolidate waste.


In DIGIFOREST we propose to create a revolution in spatial data acquisition, organization and analysis and give forestry operators and enterprises up-to-date, tangible information about the status of their forests down to the individual tree by developing a team of heterogeneous robots to collect and update this raw 3D spatial representations, building large scale forest maps and feeding them to machine learning and spatial AI to semantically segment and label the trees and also the terrain.


DARROW will build and demonstrate into an operational environment, an innovative, optimised, modular, and flexible data-driven AI solution to make existing WWTP more autonomous, more energy efficient and better prepared for their transformation into WRRF.


The CLARUS project aims to connect the Sustainable Paradigm in the food industry and AI-based applications, with the goal of developing a platform with high communications and processing capabilities, as well as the use of standardized open protocols and data models that will allow resource consumption assessment and traceability for food industry processes.


ALCHIMIA aims to build a platform based on Federated Learning and Continual Learning to help big European metallurgy industries unlock the full potential of AI to support the needed transformations to create high-quality, competitive, efficient and green manufacturing processes.


FELICE unites multidisciplinary research in collaborative robotics. The key to achieve these goals is to develop technologies that will combine the accuracy and endurance of robots with the cognitive ability and flexibility of humans.

bottom of page