Thesis Code: 25003
Research Area: Connected Systems & Cybersecurity (CSC)
Description
In general, for public safety, all types of bridges require regular inspections in order to assess their health status. In this context, the Italian law imposes quarterly inspections where bridges’ stability conditions, their structural elements and conservation need to be assessed. Unfortunately, current UAV-based inspection solutions have significant limitations. Indeed, these solutions can accurately monitor only accessible parts of the bridge structure, while the most critical structural elements remain uninspected due to unreliable GNSS-based localization in the obstructed areas beneath the bridge. In fact, without a robust localisation service, it is challenging to ensure a safe and stable UAV flight beneath the bridge area.
In this challenging scenario, the localization service based only on GNSS is not enough because it provides accurate position estimation only in open sky condition, while beneath the bridge area the satellite signal is obstructed. Consequently, GNSS-only solutions might either heavily degrade or completely fail. A possible monitoring solution would employ a fleet of automated UAVs capable of performing bridge inspection tasks in an efficient way, even in GNSS-denied areas, with reduced time, costs, and risks for human being, and zero impact for the environment.
Objectives
The goal of this thesis is to develop an accurate positioning system for a fleet of UAV-based bridge inspection solutions. More specifically, the activity will be focused on the design and development of a cooperative and hybrid algorithm that combines: positioning data GNSS-RTK (from UAVs with good satellite visibility), measurements from IMU and Ultra-WideBand (UWB)-based ranging measurements performed by the inspection UAV with respect to supportive UAVs moving along the bridge with almost full sky visibility.
Initially, the designed algorithm will be first optimized offline using real data from ROS bag. Subsequently, the optimized algorithm will be implemented in real devices, and its performance will be evaluated first in the Robotic Laboratory made available by LINKS and then in outdoor environments. During the tests in the Robotic Laboratory, the localization performance will be evaluated by using the VICON system as ground truth.
Requirements
– Strong knowledge in software development (C/C++)
– Good knowledge of MATLAB
– Good knowledge in mathematical derivation
– Proactive mindset, problem-solving oriented
– Data processing skills
– Familiarity with embedded platforms (e.g., Raspberry PI) and Linux environment
Duration: 6-8 months.
Contacts: please send a resume with attached the list of exams passed during the Bachelor of Science and Master of Sciences to francesco.sottile@linksfoundation.com specifying the thesis code and title.