LEASARD CominLabs Project | Florian Pouthier

In unstructured and hostile environments where Search-And-Rescue (SAR) drones operate, network access and GNSS-based positioning may be unavailable. Moreover, the task of each operator dedicated to piloting a unique drone is exhausting and complex in such conditions, which is not optimal when operators have to work continuously in crisis situations.

This requires improving existing navigation and obstacle-avoidance algorithms already employed on drones. Towards this goal, we advocate the enhancement of sensing and processing tasks through low-energy hardware such as event cameras and Field-Programmable Gate Arrays (FPGAs) and to design navigation and obstacle-avoidance algorithms in a way that capitalizes Deep Neural Network (DNNs) architectures that are adapted to this new hardware. This project will prototype such an integrated system that will be made available to the scientific community to allow further investigations on the opportunities brought by this novel concept of drone architecture.

LEASARD

Authors

Florian Pouthier

Doctor in Control and Robotics

My research focuses on the efficient navigation of UAVs in constrained environments. I recently joined the LEASARD CominLabs project at LS2N Nantes, in which I investigate SLAM and navigation algorithms with event-based cameras to improve drone autonomy in cluttered environments. This work is supervised by Isabelle Fantoni. My Ph.D. thesis work, led at ICube Strasbourg and GIPSA-lab Grenoble, has been dedicated to the event-driven navigation of a drone in dark environments, as a part of the dark-NAV ANR project. This thesis has been supervised by Nicolas Marchand and Sylvain Durand. Through my research work, I developed research interests in aerial robotics, robust control and set theory. As a graduate of an engineering school (INSA Strasbourg), I have developed a taste for control theory, which I try to deploy as much as possible on real control systems.

Dark-NAV Aug 18, 2023 →