We aim at creating a data collection system capable of dealing with multiplatform and multi-sensor (multispectral imaging, humidity, temperature, and others) data to build artificial intelligence models to predict wildfire risk in a coverage area.
Objectives:
Demonstrate aerial autonomous search and rescue systems (manned/unmanned), using image-based Automatic Target Search System. Means of pattern recognition, perception, reasoning, decision-making, and machine learning combining available resources for situation assessment and action on Search and Rescue missions.
Aerial navigation in GNSS contested environments is a challenge for both manned and unmanned aircraft. This research project aims to study and develop technologies and algorithms to address the problem of aerial navigation without relying on GNSS, focusing on a specific image-based navigation with multi-sensor fusion in order to get a precise localization of the aircraft.
A cyber-physical system's roadmap propose applicable for last-mile delivery drones.