Page in progress. List of projects to be finalised soon.

(priviledged theme with Dr Sören Kerner's and Marco Motta's groups at Fraunhofer Institute for Material Flow and Logistics (IML), with scientific annex)

UGA participates to the TAILOR network of AI research excellence centers through  the MIAI chairs “Explainable and Responsible AI” and “Knowledge communication and evolution” . UGA  contribute in a significant manner to the WP3 (Trustworthy AI) and WP6 (Social AI)  by bringing competences on knowledge representation and reasoning, deep learning, game theory and statistical learning, and their interactions in the context of security, privacy and ethics of online systems and algorithms.

The DesCartes project is highly competitive project awarded and supported by the Singapore National Research Foundation, Prime Minister’s Office, and its Campus for Research Excellence and Technological Enterprise (CREATE) program. It is and international collaborative project conducted under CNRS@CREATE program and involves 12 French universities, 6 Singaporean Universities and 6 industrial partners. The main universities in Singapore (NUS, NTU, SUSS, SUTD, SMU) and A*STAR.

The AI4DG German-French joint research project focuses on AI on the edge for a secure and autonomous distribution grid control with a high share of renewable energies. It is a highly international competitive project awarded under the ANR/BMBF collaboration.

On the basis of a collaboration between the French Ministry of Higher Education, Research and Innovation (MESRI), the German Federal Ministry of Education and Research (BMBF), Fraunhofer ISE, CEA, LPNC, Stiebel-Eltron GmbH & Co. KG, EDF R&D – Dept. Technology and Research for Energy Efficiency.

> More information about AI4HP

Collaboration MIT/LPNC(MIAI)/CEA.

> More information about SUPER

A CREATE Program on AI-based Decision making in Critical Urban Systems.

> More information about DESCARTES

Coordinator: Xavier Alameda-Pineda (Inria)
In the past five years, social robots have been introduced into public spaces, such as museums, airports, commercial malls, banks, company show rooms, hospitals, and retirement homes, to mention a few examples. In addition to classical robotic skills such as navigation, grasping and manipulating objects, i.e. physical interactions, social robots must be able to communicate with people in the most natural way, i.e. cognitive interactions. Nevertheless, today’s Human-Robot Interaction (HRI) technology is not well-suited to fulfil these needs. Indeed, socially assistive robots (SAR) that are currently available suffer from two main bottlenecks: (i) they are limited to a handful of simple scenarios which leads to (ii) SARs not being well accepted by a large percentage of users such as elderly adults. These limitations are largely due to the fact that both their hardware and supporting software have been designed for reactive single-user interaction mostly based on keyword spotting where the robot waits to be instructed what to do based on a limited set of scripted actions. In a nutshell, SPRING’s research question is how to develop robots able to move, see, hear and communicate with several actors, in complex and unstructured populated spaces, so that they can to properly fulfil social roles and successfully execute social tasks. Overcoming these limitations raises difficult scientific and technological challenges with tremendous social impact and economic value.