I am professor in the Computer Science and System Engineering Laboratory (U2IS) at ENSTA Paris and a member of the INRIA/ENSTA Paris FLOWERS team on developmental robotics. I am also the scientific director of the IP Paris Interdisciplinary Center for Defense and Security (CIEDS).

My research focuses on robotics and more particularly on perception and learning problems. I am looking to develop methods to simplify and make more robust the use of robots and to increase their autonomy. I am particularly interested in:

  • navigation, mapping, localization, path planning,
  • learning applied to multi-modal perception and reinforcement learning,
  • applications to mobile robots, UAVs and autonomous vehicles.


  • 2021 - …: Scientific director of CIEDS
  • 2018 - 2021: Director of the Computer Science and System Engineering Laboratory
  • 2011 - …: Professor at ENSTA Paris
  • 2009 - …: Member of the INRIA FLOWERS team
  • 2005 - 2011: Associate professor at ENSTA Paris
  • 2001 - 2005: Expert in robotics for Délégation Générale pour l’Armement at Centre d’Expertise Parisien
  • Mobile robotics
  • Artificial Intelligence
  • Computer Vision
  • Machine Learning
  • Habilitation a diriger des recherches, 2011

    University Pierre et Marie Curie

  • PhD in Mobile Robotics, 2001

    University Pierre et Marie Curie

  • Master degree in Artificial Intelligence, 1998

    University Pierre et Marie Curie

  • Engineering degree, 1997 (X94)

    Ecole Polytechnique



ENSTA Paris - Robotics track

I am co-responsible for the robotics and Intelligent Autonomous Systems track in third year at ENSTA Paris: Description of the track


I teach the entire DATAAI963 course and I teach the other courses with colleagues from ENSTA Paris, Ecole Polytechnique and ONERA.

IP Paris - Master DATAAI - TPT-DATAAI963

This course presents the robotic platforms and the most common sensors (vision, Lidar, intertial units, odometry …) and the different components of navigation: control; obstacle avoidance; localization; mapping (SLAM) and trajectory planning as well as filtering techniques (Kalman filter, particle filtering, etc.) and optimization used in these fields.

ENSTA Paris - ROB312

This course presents an overview of sensors, representations and different filtering methods (Kalman filter, particle filtering) and optimization techniques used for localization and mapping (SLAM) in mobile robotics and for autonomous vehicles.

Planning and control

ENSTA Paris - ROB316

This course presents the platforms and an overview of the control, trajectory planning and task planning methods used in robotics and for autonomous vehicles.

Robot Motion Planning, Verification and Control of Hybrid Systems

Ecole Polytechnique - MScT AIAVC - INF641

Drones and robots must create maps of their surroundings to plan their movement and navigate. In addition, enforcing rules and verifying that these mobile entities meet their specifications is essential for security. This course will focus on the safe navigation of robots, introduce map construction techniques, motion planning methods, and give an introduction to the control and verification of the resulting hybrid systems.


Current students

  • Tom Dupuis (PhD 2021-…, funding CEA): Reinforcement learning and representation learning for visuomotor control. Co-supervised with Jaonary Rabarisoa and Quoc Cuong Pham.
  • Kai Zhang (PhD 2021-…, funding CEA): Model of the situation and task planning of a mobile manipulator in an uncertain logistical environment. Co-supervised with Julien Alexandre Dit Sandretto, Eric Lucet, Selma Kchir.
  • Gwendal Priser (PhD 2021-…): Set propagation for Trustworthy Reinforcement Learning, co-supervised with Goran Frehse.
  • David Brellmann (PhD 2020-…): Reinforcement Learning for Autonomous Systems safety. Co-supervised with Goran Frehse.
  • Thomas Rojat (PhD 2020-…, funding Renault): Interpretability of latent representations learned by neural networks for the characterization of abnormal events during vehicle driving. CIFRE with Renault. Co-supervised with Rodolphe Gélin, Raphael Puget & Natalia Diaz Rodriguez.
  • Pavan R Vasishta (Postdoc 2021-…): State representation learning for industrial applications (VeriDREAM project).


  • H2020 VeriDREAM (2020-2022) The VeriDREAM project (VERtical Innovation in the Domain of Robotics Enabled by Artificial intelligence Mandhods) is a European project with the objective of developing industrial applications following the H2020 DREAM and RobDREAM projects.

Former students

Former Projects

  • PIA EVAPS (2016-2020) The objective of the EVAPS project (Eco mobility by Autonomous Vehicles in the Paris-Saclay region) is to develop intelligent mobility services for peri-urban journeys, in autonomous driving, without driver. We have developed trajectory planning and tele-operation algorithms for remote vehicle handover.

  • ITEA3 DANGUN (2016-2019) Project on the development of an autonomous vehicle in which we have developed a remote operation capacity for these vehicles.

  • H2020 DREAM (2015-2018) The DREAM project (Deferred Restructuring of Experience in Autonomous Machines) is a European project focusing on the development of processes inspired by sleep and dreams in a cognitive architecture for robotics. We have developed state representation learning approaches for reinforcement learning.

  • PSPC ROMEO 2 (2012-2017) The ROMEO 2 project carried by Aldebaran Robotics in which we have developed object dandection mandhods by RGB-D camera and semantic mapping mandhods.

  • FUI ROBOT POPULI (2012-2014) Project with the company Awabot in which we have developed a robust visual navigation algorithm for service robotics.

  • ANR MACSi (2010-2014) The MACSi project focuses on the development of social and developmental learning capacities for perception on an iCub robot.

  • ANR PACOM (2009-2012) The PACOM project concerns the development of exploration mandhods and semantic mapping within the framework of the “Carrote” compandition organized by the ANR and the DGA.


All my publications, including preprints are available on my google scholar page

Publications accepted at workshops, conferences or journals (from HAL):