Passionate about underwater robotics, I defended a Franco-British PhD thesis about localization methods for underwater robots with set-membership approaches. See more.
Mobile robotics motivates the study of new methods to deal with dynamical systems using a constraint programming approach. I performed a postdoctoral research on this topic at IMT Atlantique/LS2N (Nantes, France).
I am currently an associate professor in Robotics at ENSTA Bretagne (Brest, France) and member of the Robex team in the research laboratory Lab-STICC.
An ellipsoidal predictor-corrector state estimation scheme for linear continuous-time systems with bounded parameters and bounded measurement errors Andreas Rauh, Simon Rohou, Luc Jaulin
To be submitted to Frontiers In Control Engineering, 2021.
Brunovsky decomposition for dynamic interval localization Simon Rohou, Luc Jaulin
Submitted to IEEE Transactions on Automatic Control, 2021.
There are several ways to deal with state estimation in mobile robotics. The constraint programming approach consists of defining a problem as a set of rules and letting a solver perform the estimation. For mobile robotics, rules are constraints coming from state equations or uncertainties from the measurements.
Efforts have been done to propose operators and solvers to apply these constraints. The goal of this tutorial is to learn how to use them and understand the efficiency of the approach on realistic robotic applications. We will see that some problems that are difficult to solve with conventional methods (Kalman filters, particle approaches) can be easily dealt with by constraint programming. This is for instance the case of poor observation measurements, time uncertainties, delays, or when the initial conditions of the system are not known.
The tutorial will stand on the Codac library, that provides tools for computations over sets of trajectories. It has been designed to deal with dynamical systems defined by non-linear differential equations and involving constraints such as trajectory evaluations, time uncertainties or delays. These computations stand on interval analysis, a well suited tool that reliably propagates uncertainties.
Funding: Région Occitanie, Université de Montpellier
Popular science
Underwater exploration techniques : history and innovations. October 2019: A flip-flops conference given during the Festival Baie des Sciences at Saint-Brieuc (France).
24/06/2016
PRASYS Seminar (Brest, France)Collaborative localization over the seabed: a Walking Strategy.
Slides.
09/03/2016GdR Robotique(Montpellier, France)Wide underwater area exploration with autonomous vehicles: a Walking Strategy.
Slides.
16/07/2015
OSM Seminar (Brest, France)Robot localization in an unknown but symmetric environment.
Slides.
10/06/2015SWIM 2015(Praha, Czech Republic)Robot localization in an unknown but symmetric environment.
Abstract. Slides.
Guerlédan project
I am leader of the Guerlédan Project that gathers, twice a year, ENSTA Bretagne's students from Robotics and Hydrography-Oceanography around Guerlédan Lake (Brittany, France).
This offers to the students some unique opportunity to work on realistic challenges involving autonomous robots, hydrographic sensors and nautical resources deployed in such complex environment.
Various issues are dealt with, such as underwater dam inspection, black-box research, hydrographic survey, 3d reconstruction of floodgates, etc.
Software
I am developing the Codac library: a C++ project providing tools to guarantee computations over sets of trajectories. See more on the official webpage.
Consortium
Member of the Contredo project (ANR), that gathers several academic and industrial partners with the aim of designing a software tool based on intervals to handle dynamical systems.
Contact
Office M026
ENSTA Bretagne
2, rue François Verny
29806 Brest Cédex 9
Tél: +33(0)2 98 34 87 66
Since 2020, I am in charge of the Marine working group of the French national Research Group in Robotics (GdR) established by the CNRS. 
There are several ways to deal with state estimation in mobile robotics. The constraint programming approach consists of defining a problem as a set of rules and letting a solver perform the estimation. For mobile robotics, rules are constraints coming from state equations or uncertainties from the measurements.
I am leader of the 
Member of the Contredo project (