Munich, Bavaria, Germany
I hold a B.Sc. in Aerospace Engineering from Politecnico di Milano (2016), an M.Sc. in Robotics from the University of Trento and University of Melbourne (2018), and a Ph.D. in Mechatronics from the University of Trento (2022). My work has focused on developing distributed measurement systems that integrate computer vision and AI for biomedical data acquisition and aerospace applications. I participated in international projects such as Eurobench, contributing to benchmarking frameworks for robotic exoskeletons, and helped design closed-loop control systems for unmanned aerial vehicles (UAVs), implementing real-time control on STM32 microcontrollers and Raspberry Pi boards. Since 2022, I have been with Agile Robots SE as a Senior Robotics Engineer and Software Developer, leading efforts in dynamics and control systems for the next generation of 6-DOF industrial manipulators.
Dynamics and Control Robotics Engineer Agile Methodology Shared memory, mqueue and OpcUa communication protocol implementation Ros2, DDS Middleware C ++ Software Developer for Motion Generation, Robot Control and Dynamics Numerical Optimization and Software Development for Realtime Systems Simulation of Robot Dynamics and Kinematics Robot Calibration and Performance Assessments Robot Performance Certification
Senior software developer for motion planning and control system of 6 dof industrial manipulators. Product owner and developer for : - Trajectory planning system - Simulation of the dynamic system - Development of the control system for torsion, speed, and position - TÜV performance testing certification
Kinematic Calibration of Robotic Manipulators Software Developer C ++ and Python Certification of Industrial robots
Design of simple aircrafts out of waste Materials (recycling of containers and packaging for everyday use) and microcontroller based control system, using Arduino, Stm, Raspberry and compatible sensors
The simulation of human biomechanical movement requires volumetric data to estimate the mass and the inertia of anatomical segments. The project developes a volume and Inertia estimation system. The system proposed operates and calibrates autonomously. The patient lies on a hospital bed while the system acquires RGB images with a Time of Flight (ToF) camera. Then, it processes the acquisition by recalling a joint detection algorithm, Open Pose. Once a new frame is acquired, Open Pose detects the patient’s body and returns the list of joint coordinates. Following this process, Matlab merges the Open Pose joint coordinates with the point cloud generated by the ToF camera. In this way, it is possible to isolate the body segments and compute the related Volumes. This approach is faster and more accurate than the current state of the art. Consequently, it performs better than traditional methods, such as the collection of patient parameters by consulting anatomical tables. This work is part of a larger project – Eurobench - which aims to evaluate loads and joints’ stress of a patient wearing an exoskeleton. For this reason, it requires the knowledge of the weight and the inertia of each body part to run kinematic and dynamic simulations.
Design and development of autonomous systems and computer vision applications
Analysis of environmental parameters for the predictive maintenance of radio stations Data collection and sensor installation ANOVA test on environmental parameters with respect to system failures Shannon Entropy analysis on environmental signals and exchange of mutal information between monitored parameters