M2 Mobile Autonomous Systems

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The objective of this curriculum is to enable students to master the concepts, the models and the techniques required to design and develop mobile autonomous systems (land and aerial vehicles, mobile robots, etc.). The curriculum covers the entire "perception, decision, action" cycle including the "communication" and "interface" aspects between the control centre and the operating part. The curriculum has two main characteristics: the first involves "control" and is for engineers with strong skills in advanced automatic systems. The second involves "perception" and deals with using and combining multi-sensorial information from various embedded sensors. The training is backed by the IBISC laboratory, which is associated with the UFR of the Science and Technologies of the UEVE. The teaching staff does research on aerial or land transportation issues, on aeronautic or spatial robotics, in the following disciplines: modelling and simulation, automatic, signal and image processing, embedded IT.

Course Prerequisites

Students who have completed the first year of a Master's degree, 3rd-year engineering school students, or international students with an engineering degree or an M2, in the following fields: - GEII (Electrical Engineering, Industrial IT) - Informatics - EEA (Electronics, Electrical Engineering, Automation) - E3A (Electronics, Electrical Energy, Automation) - Signal and image processing - Automation and Robotics

  • Acquire in-depth knowledge of embedded signal processing.

  • Be able to use the signals at the output of embedded sensors, combine them, and merge top-level information generated by these signals.

  • Acquire the bases necessary for the processing of discrete two-dimensional signals coming from "camera" type sensors (image signals) and therefore be able to design and integrate top-level perception algorithms.

  • Acquire a transversal vision while having excellent scientific grounding in the automation of embedded systems, in order to be able to design, test, implement and validate control/command methods.

  • Understand the entire functional chain linking sensors, actuators and effectors as well as the hardware and software architectures of the interfaces between the various components of an autonomous system.

  • Become proficient in learning techniques (machine learning) and their application to the field of autonomous systems design.

Post-graduate profile

After completing the programme, students will have acquired dual skills in the command/perception of autonomous systems. Their career prospects include:
- Executives in the R&D departments of large companies operating in the automotive or robotics sectors.
- Doctoral students in research laboratories specialising in subjects related to smart vehicles, autonomous systems and mobile robotics.

Career prospects

At the end of the programme, students can join the study and research departments of companies that incorporate advanced automation into their embedded mobile systems (car, two-wheelers, robots, flying machines, etc.). There are also job opportunities in industry, in the transport, mobile robotics, automotive and aeronautics sectors. Graduates of this programme can also join research laboratories as doctoral students and do these in control/command or perception of autonomous systems. Among the large companies or establishments recruiting in the field, it is worth mentioning: Thalès, PSA, Renault, EADS, Siemens, Veolia, Valeo, Schneider Electric, Safran, Akka, Alten. These types of jobs are also available in subcontracting IT services companies.


Informatique, Biologie Intégrative & Systèmes Complexes
Systèmes et Applications des Technologies de l'Information et de l'Energie.



Le semestre 1 comporte 4 groupes :
- Groupe 1 (obligatoire) : Formation générale (3 ECTS)
- Groupe 2 (obligatoire) : Tronc commun (4 UE, 12 ECTS)

Les étudiants choisissent ensuite l'un des deux sous-parcours au choix : "Perception ou "Automatique dans lesquels sont comptabilisées 5 UE à 3 ECTS qui sont à choisir parmi 6. Le nombre total d'ECTS est de 15 pour chaque sous-parcours.
- Groupe 3 : Sous-parcours "Perception (5 UE parmi 6, 15 ECTS)
- Groupe 4 : Sous-parcours "Automatique (5 UE parmi 6, 15 ECTS)15 ECTS).

Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Surveillance distribuée et systèmes multi-agents 3 10 12 8
Observation, capteurs virtuels 3 10 12 8
Modèles avancés pour l'analyse et la commande 3 10 12 8
Intégration des systèmes de commande 3 10 12 8
Fault Tolerant and Secure Control Systems 3 10 12 8
Commande non linéaire 3 10 12 8
Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Traitement d'images et vision artificielle 3 10 12 8
Perception étendue des systèmes autonomes 3 10 12 8
Localisation, cartographie, planification 3 10 12 8
Fusion multicapteurs 3 10 12 8
Commande référencée capteurs 3 10 12 8
AI for computer vision 3 10 8 12
Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Systèmes mobiles connectés 3 10 12 8
Modélisation et commande 3 10 12 8
Machine Learning 3 10 12 8
Applied optimization 3 10 12 8
Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Conduite de projets 1 10
Anglais 2 30

Le second semestre comporte le stage et deux modules : l'un dédié à des projets recherche ou industriels et l'autre à des séminaires recherche ou industriels.

Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Séminaires recherche ou industriels 3 30
Projet recherche ou industriel 3 30
Matières ECTS Cours TD TP Cours-TD Cours-TP TD-TP A distance Projet Tutorat
Stage 24 6
Modalités de candidatures
Application period
From 01/02/2021 to 09/07/2021
From 15/08/2021 to 31/08/2021
Compulsory supporting documents
  • Copy diplomas.

  • Rank of previous year and size of the promotion.

  • Curriculum EU (description of the units of education followed) of the last two years.

  • Curriculum Vitae.

  • Motivation letter.

  • All transcripts of the years / semesters validated since the high school diploma at the date of application.

Additional supporting documents
Course manager(s)
Samia BOUCHAFA-BRUNEAU - samia.bouchafabruneau@univ-evry.fr
Administrative office
Marie-Laure Marchand - marielaure.marchand@univ-evry.fr