Doctorate degree
I have defended my PhD in Robotics in 2007 within the Robotics, Action, and Perception (RAP) team of Laboratory for Analysis and Architecture of Systems1 (LAAS), CNRS2, under the supervision of Viviane Cadenat, Associate Professor at Paul Sabatier University of Toulouse, France. Specifically, my PhD thesis was entitled “Multi-sensor-based control strategies and visual signal loss management for mobile robots navigation”. The subject was to design multi-sensor-based control strategies allowing a mobile robot to perform vision-based tasks amidst possibly occluding obstacles. Actually, the sensors’ improvement gave rise to the sensor-based control which allows defining the robotic task in the sensor space rather than in the configuration space. As cameras provide high-rate meaningful data, visual servoing has been particularly investigated, and can be used to perform various and accurate navigation tasks [2], [6], [9]. The objectives are then to perform reliable navigation tasks, despite the presence of obstacles. Thereby, it is necessary to preserve not only the robot safety (i.e. ensuring non-collision) but also the visual features’ visibility to ensure the vision-based task feasibility. To achieve these aims we have first proposed techniques able to fulfill simultaneously the mentioned objectives [7], [8]. However, avoiding both collisions and occlusions often over-strained the robotic navigation task, reducing the range of realizable missions. This is the reason why we have developed a second approach which let occurs the loss of the visual features if it is necessary for the success of the task. Using the link between vision and motion, we have proposed different methods (analytical and numerical) to compute the visual signal as soon it becomes unavailable [4]. We have then applied them to perform vision-based tasks in cluttered environments, before highlighting their interest to deal with a camera failure during the mission [1], [5].
In addition, during my doctorate degree, I also had the opportunity to perform teaching activities, first as temporary teacher (3 years), and then as teaching assistant, specifically in French “Attaché Temporaire d’Enseignement et de Recherche” (ATER,1 year, both for the Paul Sabatier University of Toulouse. These global teaching experiences have led to a total volume of 308 hETD3.
Thesis Details
I obtained a PhD thesis in Robots Control from Paul Sabatier University of Toulouse (France), that was entitled: “Multi-sensor-based control strategies and visual signal loss management for mobile robots navigation” [3].
- Manuscript
- D. Folio PhD thesis (view )
- Defended
- the 11th July 2007
- Committee
-
President Michel Devy (DR LAAS) Reviewers François Chaumette (DR IRISA/INRIA)
Seth Hutchinson (Prof. University of Illinois, USA)
Examiners Bernard Bayle (MdC Université de Strasbourg)
Michel Courdesses (Prof. Universités de Toulouse)
Director Viviane Cadenat (MdC Université de Toulouse) Guess Philippe Souères (Prof. Universités de Toulouse)
References
Footnotes
In French Laboratoire d’Analyse et d’Architecture des Systèmes. LAAS is a laboratory depending on the CNRS. http://www.laas.fr↩︎
Form French National Center for Scientific Research, from French Centre National de la Recherche Scientifique (CNRS), is the largest governmental research organization in France. http://www.cnrs.fr↩︎
“Equivalent TD hours” that is in French “heures équivalentes TD” (hETD), are the reference hours to calculate the teaching duties. The rules for a tenured teacher are as follows: 1h of course = 1.5hETD, while the others, e.g. 1h of tutorial (TD) = 1h of practical work (TP) = 1hETD.↩︎
Reuse
Citation
@phdthesis{folio2007,
author = {Folio, David},
publisher = {Université Paul Sabatier, LAAS},
title = {Stratégies de commande référencées multi-capteurs et gestion
de la perte du signal visuel pour la navigation d’un robot mobile},
date = {2007-07-11},
address = {Toulouse, France},
url = {https://dfolio.fr/publications/thesis/folio2007thesis.html},
langid = {fr-FR},
abstract = {The literature provides many techniques to design
efficient control laws to realize robotic navigation tasks. In
recent years, the sensors improvement gave rise to the sensor-based
control which allows to define the robotic task in the sensor space
rather than in the configuration space. In this context, as cameras
provide high-rate meaningful data, visual servoing has been
particularly investigated, and can be used to perform various and
accurate navigation tasks. This method, which relies on the
interaction between the camera and the visual features motions,
consists in regulating an error in the image plane. Nonetheless,
vision-based navigation tasks in cluttered environment cannot be
expressed as a sole regulation of visual data. Indeed, in this case,
it is necessary to preserve not only the robot safety (i.e.
non-collision) but also the visual features visibility. This thesis
addresses this issue and aims at developing sensor-based control
laws allowing a mobile robot to perform vision-based tasks amidst
possibly occluding obstacles. We have first proposed techniques able
to fulfill simultaneously the two previously mentioned objectives.
However, avoiding both collisions and occlusions often over-strained
the robotic navigation task, reducing the range of realizable
missions. This is the reason why we have developed a second approach
which lets the visual features loss occurs if it is necessary for
the task realization. Using the link between vision and motion, we
have proposed different methods (analytical and numerical) to
compute the visual signal as soon it becomes unavailable. We have
then applied them to perform vision-based tasks in cluttered
environments, before highlighting their interest to deal with a
camera failure during the mission.}
}