Post-doctoral Research Visit F/m Post-doctorant
il y a 3 semaines
Le descriptif de l’offre ci-dessous est en Anglais_
**Niveau de diplôme exigé **:Thèse ou équivalent**Fonction **:Post-Doctorant**Niveau d'expérience souhaité **:Jeune diplôméA propos du centre ou de la direction fonctionnelle
The Inria centre at Université Côte d'Azur includes 37 research teams and 8 support services. The centre's staff (about 500 people) is made up of scientists of different nationalities, engineers, technicians and administrative staff. The teams are mainly located on the university campuses of Sophia Antipolis and Nice as well as Montpellier, in close collaboration with research and higher education laboratories and establishments (Université Côte d'Azur, CNRS, INRAE, INSERM...), but also with the regiona economic players.
With a presence in the fields of computational neuroscience and biology, data science and modeling, software engineering and certification, as well as collaborative robotics, the Inria Centre at Université Côte d'Azur is a major player in terms of scientific excellence through its results and collaborations at both European and international levels.
Contexte et atouts du poste
**Environment**:
Non Destructive Evaluation of Structures and Materials (ENDSUM), directed by Cyrille FAUCHARD, has for main objective to contribute to the development of tools and methods of characterization and diagnosis with great efficiency, less invasive than the current tools and not altering the environments auscultated to meet the challenges of Asset Management of Infrastructures (IPM). The research carried out is aimed first of all at the physical and geometric characterization of environments using a multi-parameter, multi-scale and multi-physical approach linking the quantities measured to indicators useful for the diagnosis and monitoring over time of the environments observed. ENDSUM also aims at the development of analytical and numerical modeling, inversion and data processing and analysis methods (signals, images) allowing access to the desired physical and geometric properties. Finally, ENDSUM aims to develop innovative prototype software and hardware as well as tools for training, research and expertise.
**Context**:
The infrastructures (road network, bridges, buildings,...) are among the most important elements of the public heritage. Operators are responsible for maintaining, operating, developing, replacing and preserving this heritage while ensuring careful management of budgetary and human resources. Today, these infrastructures are put to the test by climate change (increase in the frequency of extreme phenomena which in particular favor floods and land movements). Users are also extremely attentive to questions of safety and comfort related to the use of infrastructure but also to environmental issues relating to their construction and maintenance.
The ROAD-AI Challenge objective is to design a multi-robot system comprising ground vehicles and aerial drones collaborating in the collection of data on structures with on-board sensors. Aerial drones seem to be a very promising solution for data acquisition because they can have points of view not obscured by obstacles and access structures more easily. On the other side, the ground vehicle seems better appropriated to supervise the mission of data acquisition for environment exploration and mapping.
Mission confiée
In this Postdoc, we want to study active strategies of data acquisition involving a master robot (the ground vehicle) and two slave robots (aerial robots) in order to optimize in terms of accuracy and stability the mapping of the environment. Each robot will be equipped with its own large field vision with a time stamping. We assume also that synchronized velocity control inputs can be sent to the ground and aerial robots. The master robot centralizes the information and manages the multi-robots formation. One robot of the formation, so-called the leader (not necessary the master) is manually driven by a human operator who ensures the completness of the exploration of the scene.
The first scientific problem we want to deal with in this Postdoc will be to guarantee a stable structure of the robot formation in the reference frame of the master robot. The choice of an optimal structure of the formation will be directed by the task objectives (i.e., exploration context, optimization of the map acquisition ). Recent works on Cooperative Multi-Robots Systems [1],[2],[3],[4],[5],[6] will be used to organize and to manage the formation taking into account the navigability constraints. Considering that each robot can be observed by at least one of the other, we intend to realize and to control the formation by means of sensor-based control and visual servoing techniques [7], [8].
The second scientific concern will be to investigate how we can use the constraints induced by the formation to stabilize the ill-posed problem of SLAM (Simultaneous Localization and Mapping). SLAM is a key problem in
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