Signal Processing theory and applications

Cooperative navigation algorithms for Unmanned Aerial Vehicles
An important problem in flight formation is the possibility of sharing navigation information among the different Unmanned Aerial Vehicles (UAVs) in the platoon. This is essential particularly when a failure has occurred in a sensor and that particular UAV needs to obtain that information from other sources. In this research, an approach will be attempted with local navigation sensors (INS/GPS) and interactive sensors (onboard cameras) in order to integrate all this information and fly as a whole with a distributed sensor arrangement. 
This is a joint ongoing (2013) work with the Control and Systems Center (CeSyC, Centro de Sistemas y Control)ITBA (Instituto Tecnológico de Buenos Aires).

Indoor navigation techniques for unmanned aerial vehicles.
The increasing use of unmanned aerial vehicles (UAV), informally known as drones, has encouraged the research in both the vehicle's system and its software. In order to achieve autonomy, a Navigation, Guidance and Control system is necessary. From these systems, the Navigation part is the one in charge of supplying position and orientation information to the Guidance and Control systems. Therefore, it is essential that the UAV counts with a high quality navigation system in order to achieve a good performance. The development of this system is the core of this project. The main objective is to obtain a system that is responsible for navigating in indoor surroundings in real time, merging information from WiFi antennas and inertial sensors (accelerometers and gyroscopes). The system has to be of the appropriate size and weight so it can be mounted on a UAV platform. Furthermore, it has to be designed so it can deal with those situations and places where there is no available GPS information, or it has been degraded, such as urban canyons, i.e. when the UAV is surrounded by buildings; or in places that have been subject to a catastrophe, i.e. collapsed buildings. It is important to observe that in these extreme situations, the WiFi capability of the system is a key factor for improving the quality of the navigation solution.