Hélène ROGGEMAN

En résumé

Entreprises

• Upmc - Chargée de TD

  Paris 2017 - 2017 Encadrement de TDs d'introduction à la robotique (modélisation géométrique et cinématique, analyse de performances)
  
  Tutorials "Introduction to robotics" (geometric and kinematic modeling, performances analysis)

• Onera - Doctorante

  Palaiseau 2014 - 2017 Amélioration de performance de la navigation basée vision pour la robotique autonome : une approche par couplage vision/commande.
  Performance improvement of vision-based navigation for autonomous robotics : a vision and control coupling approach
  
  Mots-clés : Robotique mobile, Navigation autonome, Localisation basée vision, Commande prédictive, Couplage commande/vision
  Keywords : Mobile robotics, Autonomous navigation, Vision-based localization, Model predictive control, Control and perception coupling
  
  The aim of this thesis is to perform various autonomous navigation missions in indoor and cluttered environments with mobile robots. The environment perception is ensured by an embedded stereo-rig and a visual odometry algorithm which computes the localization of the robot. However, when the quality of the scene perceived by the cameras is poor, the visual localization cannot be computed with a high precision.
  Two solutions are proposed to tackle this problem. The first one is the data fusion from multiple sensors to perform a robust computation of the localization. The second solution is the prediction of the future scene quality in order to adapt the robot's trajectory to ensure that the localization remains accurate. In the two cases, the control loop is based on model predictive control, which offers the possibility to consider simultaneously the different objectives of the mission : waypoint navigation, exploration, obstacle avoidance.
  A second issue studied is waypoint navigation with avoidance of mobile obstacles using only the visual information. The mobile obstacles are detected in the images and their position and velocity are estimated in order to predict their future trajectory and consider it in the control strategy.
  Numerous experiments were carried out and demonstrated the effectiveness of the proposed solutions.
  

• Onera - Stage de fin d'études

  Palaiseau 2014 - 2014 Sujet : Ego-localisation visuelle et commande prédictive d’un robot mobile pour l’exploration
  
  Développement et validation d'une boucle de perception-commande sur un robot terrestre lui permettant d’explorer une zone inconnue dans le but d’effectuer des missions d’exploration de bâtiment de type Search-And-Recue ou recueil d’information.
  
  Visual localization and model predictive control of a mobile robot for exploration.
  
  Development and validation of a perception and control loop on a mobile robot to perform autonomous exploration missions of unknown areas (Search-And-Rescue, information gathering)

• Inria - Stage ingénieur

  Le Chesnay 2013 - 2013 Stage au sein de l’équipe FUN (Future Ubiquitous Network) sur le projet de déploiement de nœuds mobiles sur la plateforme FIT. Travail avec des robots Turtlebot et Wifibot sur des problématiques de localisation, de navigation, de communication multi-robots et de rechargement autonome.
  
  Internship in the FUN (Future Ubiquitous Network) team on the deployment project of mobile nodes on FIT platform (https://www.iot-lab.info/). Work with Turtlebot and Wifibot robots on localization, navigation, multi-robots communication and autonomous recharging.

Formations

• INPG ENSE3

  Grenoble 2011 - 2014 Filière Automatique et Systèmes d'Information
  Spécialisation en Mécatronique
  
  Automatique, Traitement du signal, Informatique industrielle,
  Programmation C/C++/Java

Réseau

• Aymeric BERAUD

• Benoît TORTEROTOT