LEASARD CominLabs Project

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.