AerogridUAV is a TUDelft spinoff with the aim of providing drone services directly to customers through a fully autonomous drone network.

The objective of this research is to design a Vertical Takeoff and Landing (VTOL) Unmanned Aerial Vehicle (UAV) capable of executing precision landings and takeoffs from a designated platform on a moving vessel in high sea states and extreme wind conditions.In the initial year of my PhD, I embarked on an extensive review of existing technologies and innovations within the field of maritime hybrid-lift UAVs, particularly those adept at operating from moving platforms under challenging weather conditions. This comprehensive analysis led to the conceptualization of a novel UAV design, characterized by a six-degree-of-freedom control capability. The UAV's design consists of 4 dual-axis tilting rotors. This feature enhances the UAV's ability to counteract wind disturbances and improve its maneuverability.The subsequent year was dedicated to the development of a controller capable of managing the UAV's nonlinear dynamics. Through rigorous research and experimentation, we developed an advanced real-time nonlinear controller. This controller is adept at maintaining the UAV's stability in a hover state.During the third year, our efforts were directed towards mastering the UAV's transitional control. We achieved this by formulating a unified control strategy, employing a singular loop control system capable of managing the UAV's flight across its entire flight envelope.Currently, in the fourth and final phase of the project, our focus has shifted to perfecting the approach and landing procedures. We are in the process of integrating an LSTM (Long Short-Term Memory) neural network framework with a computer vision algorithm to accurately estimate and predict the ship motion in real time. This predictive capability, combined with a meticulously devised approach strategy, aims to ensure the UAV's successful landing under the adverse conditions of strong winds and high sea states.For more information about this project, please consult the publication section.

Advisor for CIM4.0 in the framework of the Flagship project. With main focus on the aerial node of the project.

Within the MBA program I did my mission at CIM 4.0 (Competence Industry Manufacturing 4.0). I was the responsable of the flagship project "FIXIT". The goal of The FIXIT Project is to develop, in collaboration with the Polytechnic of Turin, a robotic framework able to support the operator in a contest of Industry 4.0. The framework consist of a ground robotic platform, an aerial one and a control station. This framework is physically implemented in their demonstration production plant based in Politecnico di Torino, Turin, IT.

It was an honor for me to be a mentor and project leader for two groups within the Vento (formerly School of Entrepreneurship and Innovation) Pioneer program. Pioneer is an extracurricular experience during which 30 students from the Alta Scuola Politecnica ASP develop a high-tech product guided by companies, and then launch their innovative high tech startup.In our case, the goal of the challenge was to design, develop and test a swarm of cooperative drones able to perform different tasks.

Junior Consultant for the Airbus group on behalf of Altran Technologies.Main tasks: ● Manual and AP(Auto Pilot) flight laws design for SA(Single Aisle) Airbus aircraft● Manual and AP flight laws integration, validation and test for SA(Single Aisle) Airbus aircraft. In particular, my focus was on the certification process of the A320 and A321 NEO for the new PW and CFM motors. Main tools: Simulink , Matlab , Office suite , Osma , Scade, SIMPA

Whitin my master program I worked at Delft University of Technology in the department of Radar signal processing for a project called SWARMSAR. That allow me to gain extensive knowledge on python coding, numerical simulation and radar signal processing.The aim of the SWARMSAR project is to develop a close formation constellation of small Synthetic Aperture Radar (SAR) satellites operating in a multi-static configuration and capable of wide and highly resolute images of the terrain. During my work I developed different signal reconstruction algorithm using constant and random staggered PRF (Pulse Repetition Frequency) techniques. In order to address the performances, I coded a mono and bi-dimensional simulator using python. At the end of the work, I performed several optimization algorithm and strategies in order to define the optimal number of satellites. For more information about this project, please consult the publication section.

Development of a fully autonomous UAV(Unmanned Air Vehicle) in order to attend the AUVSI SUAS AIAA Student Competition in Maryland, USA.● Construction of a real-time antenna tracking platform using a 3D printer, CATIA, custom arduino shield programmed through simulink. ● Development of a real-time obstacle avoidance algorithm based on Dijkstra algorithm using MATLAB ● Design of the RF(Radio Frequency) video system capable of the FPV(first personal view) streaming video● Development of the autonomous flight software for the autopilot system using Simulink. The Autopilot hardware is composed by multiple FPGA, commercial sensors and a customized PCB(Printed Circuit Board). ● Integration of the Sensors drivers in the autopilot embedded platform using Simulink and the S-function building tool

Summer Internship as Flight Operations Manager during which I monitored and scheduled the flight routes of a commercial flight fleet.