Introduction and Research Topics
The MIAM team develops innovative methodologies for mechatronic and embedded systems. Its strength lies in the integration of two key areas of expertise: expertise in the dynamics of complex systems and advanced environmental perception. Its work, ranging from fundamental research to proof of concept, is primarily applied to the automotive, aerospace, and Industry 4.0 sectors.
Pour concevoir des systèmes autonomes capables de s’adapter en temps réel, l’équipe structure ses recherches autour de deux piliers :
Modeling, Identification, and Control: This research area focuses on developing practical mathematical models and robust control laws for nonlinear and uncertain systems. Researchers are working in particular on vehicle dynamics, trajectory planning, and the management of robot fleets (UGVs, UAVs) in complex environments.
Perception, Data Fusion, and Imaging: The team develops tools for localization and obstacle detection by combining artificial intelligence with the theory of heterogeneous data fusion. Unique expertise focuses on non-conventional imaging (polarimetric and multispectral) to extract physical information invisible to the naked eye and improve decision-making in autonomous systems.
Innovation and Partnership Outreach
L’équipe MIAM se distingue par une recherche fortement ancrée dans le tissu industriel et international :
Collaborations d’envergure : L’équipe collabore avec des leaders des secteurs de la défense, de l’agriculture et des transports (Stellantis, DGA) via des contrats de recherche et des thèses CIFRE.
Transnational Projects : Très active au sein du Campus Européen (EUCOR), elle participe à de nombreux projets d’envergure (ANR, INTERREG) sur la robotique collaborative et la mobilité durable.
Scientific and Civic Engagement : Outre une production scientifique de haut niveau, les membres de l’équipe s’investissent dans la diffusion des savoirs, notamment via la “Cordée des sciences” et la Fête de la Science, pour sensibiliser les jeunes aux enjeux de la recherche.
Team members
Permanent members
Basset Michel
Prof.
Bigue Laurent
Prof.
Binder Gérard
Emeritus Prof. / HDR
Birouche Abderazik
Assoc. Prof.
Changey Sébastien
HDR / Assoc. Res.
Dupuis Raphael
Assoc. Prof. / HDR
Foulonneau Alban
Assoc. Prof.
Hueber Eric
Assoc. Prof.
Josso-Laurain Thomas
Assoc. Prof.
Lapray Pierre-Jean
Assoc. Prof. / HDR
Lauffenburger Jean-Philippe
Prof. / HDR
Ledy Jonathan
Res. Eng.
Mourllion Benjamin
Assoc. Prof.
Orjuela Rodolfo
Prof. / HDR
Prokhorov Aleksandr
Res. Eng.
Sproesser Thomas
Assoc. Prof.
Vieira Gois Fernandes David
Assoc. Prof.
Weisser Thomas
Assoc. Prof.
Non-permanent members
Research Activities
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29th International Conference on Information Fusion
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Reliability-Aware Fusion for Semantic Segmentation under Sensor Degradation and Failures (2026) Conference paper2026 IEEE Intelligent Vehicles Symposium (IV)
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Diffuse and specular component separation using multispectral and polarization images (2026) ArticleSignal, Image and Video Processing
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Journal of Network and Systems Management
No project for now.
Research and Doctoral studies
Fusion d’odométrie multimodale robuste pour robots mobiles autonomes.
Flavie Duthay
Directeur(s) de thèse : Jean-Philippe Lauffenburger and Stéphane Bazeille, Jonathan Ledy
Analyse multimodale de scènes agricoles pour une navigation autonome sensible aux collisions
Florian PHILIPPE
Directeur(s) de thèse : Jean-Philippe LAUFFENBURGER - Pierre-Jean LAPRAY
Design of Hierarchical Control Architectures: From Autonomous Ground Vehicles to Industry 4.0
Rodolfo Orjuela
Contact the team
Team Leader
Pr Michel BASSET
- Send Us a Message
- Téléphone
MIAM Team
- ENSISA, 12 rue des Frères Lumières, 68093 Mulhouse
From the Mulhouse train station:
- Take bus line 31 or 51 to the University stop, or bus line 21 to the Lumière stop at the top of the campus.
From the Mulhouse train station:
- Take Tram Line 1 to the Porte Jeune stop,
- puis prendre le Tram ligne 2 jusqu’à l’arrêt Université,
- then a 5-minute walk.
Depuis l’autoroute A36 :
- take Exit 16a,
- Take the D68 toward “Centre”; the campus is a 5-minute drive away.