Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
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Section: Bilateral Contracts and Grants with Industry

Bilateral Contracts with Industry

Safran: Desir/Glose

Participants : Julien Deantoni, Giovanni Liboni, Robert de Simone.

We participate to the bilateral collaborative program Desir, put up by Safran to work with selected academic partners. We share the Glose project started in this program with HyComes, and DiverSE Inria project teams. Technically, the goal of this project is to elaborate on the (under development) Safran's system engineering method to make it simulable at different steps of the development, possibly early in the design process and possibly mixing models at different maturity level. This project is strongly connected to results depicted in Section 7.6.

IRT Saint-Exupery ATIPPIC

Participants : Paul Bouche, Amin Oueslati, Robert de Simone, Julien Deantoni.

In an attempt to build an extension of IRT Saint-Exupery from Occitanie to PACA region, the Thales Alenia Space company promoted the ATIPPIC project, to build the computing digital electronic structure of micro-satellites on ordinary, “COTS” processors. The project was accepted for 30 months, funds two temporary research engineers working under our own supervision, while exchanging extensively with the rest of the ATIPPIC project, which is actually hosted by Inria. The technical content of our contributions is described in Section 7.5 and 7.7.

Renault Software Lab

Participants : Frédéric Mallet, Marie-Agnès Peraldi-Frati, Robert de Simone.

We have just started, at the end of 2018, a collaboration with Renault Software Labs on the definition of rules for ensuring safe maneuvers in autonomous vehicles. The rules express conditions from the environments, safety rules to preserve the integrity of the vehicles, driving legislation rules, local rules from the authorities. The rules must be updated dynamically when the vehicle evolves and are used to monitor at run-time the behavior of the ADAS. While the ADAS contains several algorithms relying on machine learning, the monitoring system must be predictive and rules must guarantee formally that the system does not cause any accident. So it can be seen as a way to build trustworthy monitoring of learning algorithms. A CIFRE PhD will start at the beginning of 2019.

Accenture Labs, Sophia

Participant : Luigi Liquori.

We started in 2018 a collaboration with Accenture Labs, Sophia on the following topics: