Dr. Andrea Motroni, Ph.D.
Dipartimento di Ingegneria dell’Informazione – University of Pisa
56122, Via G. Caruso 16, Pisa (PI), Italy
e-mail: andrea.motroni@unipi.it
phone: +39 0502217624

Assistant Professor
Associate Editor of IEEE Journal of Radio Frequency Identification
Join IEEE RFID-TA 2024 – Daytona Beach, December 18-20

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Teaching (contact me for any question!)

Fondamenti di Elettromagnetismo (Ingegneria delle Telecomunicazioni, LT, II anno)

Tecnologie Elettromagnetiche per Sistemi Wireless (Ingegneria delle Telecomunicazioni, LT, III anno)

Bachelor Thesis (Tesi di Laurea Triennale) and Master Thesis (Tesi di Laurea Magistrale) are available! Some proposals are here. These activities are mainly for Telecommunications Engineers, but are indeed multidisciplinary, so do not hesitate to contact me even if you are graduating in some other field.
Contact me (andrea.motroni@unipi.it) to know more!

Proposte di Tesi (ITA) – tutte le tesi possono essere adattate sia al caso di Laurea Triennale che Magistrale

1. Data Fusion Lidar + RFID per Associazione Oggetti in Ambienti Dinamici
La tesi propone di studiare una tecnica di data fusion tra Lidar e RFID per l’associazione di oggetti in ambienti complessi. Dopo la mappatura con Lidar e clustering tramite DBSCAN, si utilizza la cross-correlazione temporale tra la fase RFID misurata e stimata dai movimenti dei cluster per associare ciascun cluster al suo tag RFID. L’obiettivo è identificare e tracciare oggetti mobili con ID univoci.

2. Integrazione Lidar + UWB per Tracciamento di precisione di oggetti
Il lavoro esplora la data fusion misure di ranging effettuate con sistemi UWB e dati Lidar per ottenere un’associazione robusta tra oggetti e dati di posizione (come nella tesi #1). Dopo il clustering su mappa Lidar, si effettua un matching tra le distanze rilevate dai tag UWB e quelle dei centroidi dei cluster per identificare in modo univoco gli oggetti tracciati.

3. Sistema di Inseguimento RFID con Manipolatore Robotico
L’obiettivo della tesi è progettare un sistema che consenta a un manipolatore robotico di seguire un tag RFID mobile. Utilizzando antenne montate sul braccio robotico, il sistema stima la direzione del tag e lo segue sia in ambienti 2D (scansione planare) che in configurazioni 3D, abilitando funzionalità avanzate di localizzazione e puntamento.

4. Fusione Computer Vision + RFID per Riconoscimento e Navigazione
La tesi analizza un sistema di data-fusion per la navigazione robotica o il riconoscimento oggetti mediante l’uso combinato di marker visivi (QR, ARUCO, marker infrarossi e altro) e tag RFID. I robot possono identificare oggetti “bi-tecnologia” (vision + RFID), anche all’interno di contenitori o in presenza di occlusioni parziali, migliorando l’affidabilità della percezione.

5. Integrazione di Lettori RFID in ROS2 per Robotica Cognitiva
Questo lavoro si focalizza sull’integrazione di un sistema di lettura RFID all’interno dell’ecosistema ROS2. Si svilupperanno nodi ROS per l’acquisizione, la pubblicazione e l’elaborazione dei dati RFID, abilitando il loro utilizzo in scenari robotici complessi come tracciamento oggetti, interazione uomo-robot o logistica.

6. Integrazione di sensori UHF RFID nel tool “Halos For Robotics (https://www.nvidia.com/en-us/ai-trust-center/halos/robotics/)”. Si tratta di un software sviluppato da NVIDIA ed uscito il 22 giugno 2026. Serve per validare con dei simulatori le soluzioni di safety industriale, basate principalmente su telecamere e computer vision.

7. Utilizzo di radar in sistemi di Safety: la tesi consiste nell’effettuare un’analisi dello stato dell’arte (triennale) oppure uno stato dell’arte più una campagna di misure sperimentali (magistrali) per l’utilizzo di radar nei sistemi di safety, in particolare in un contesto dove vegetazione o altri ostacoli possono rendere difficile la rilevazione di target umani.

8. Metodi di decoding dei chipless RFID tag: “La tesi presenta una panoramica delle principali tecniche di decodifica dei chipless RFID tag, una tecnologia emergente che consente l’identificazione di oggetti senza l’impiego di circuiti integrati. Dopo un’introduzione ai principi di funzionamento dei sistemi chipless RFID, vengono analizzati i metodi di interrogazione e decoding proposti in letteratura, confrontandone prestazioni, complessità, robustezza al rumore e principali ambiti applicativi.”
La tecnologia dei tag RFID chipless è molto sperimentale, non è ancora utilizzata a livello industriale. L’idea è sfruttare i parametri S11(f) e S21(f) di questi tag, che in pratica sono delle strutture periodiche con varie risonanze, per codificare stringhe di bit utili per identificare un oggetto direttamente dal dominio elettromagnetico. Il vantaggio è che introduce un argomento di ricerca attuale e permette di familiarizzare con la letteratura scientifica più recente.

9. Approfondimento sull’acustica: come funziona la propagazione acustica, le onde di pressione, i trasmettitori e ricevitori per i segnali acustici, e magari aggiungere qualcosa sulla propagazione nel mondo subacqueo e i trasmettitori e ricevitori per il mondo subacqueo. Si possono anche fare dei piccoli esperimenti usando anche degli smartphone, o dei PC collegati con matlab e delle casse audio, dei microfoni e software free come REW o Audacity.

10. Detection di più tag chipless all’interno della stessa scena: l’obiettivo è trovare algoritmi che possano in qualche modo separare la risposta di più tag RFID chipless che si trovino all’interno del range di lettura del dispositivo reader. Si possono utilizzare varie tecniche: matched filter spaziale per tag in movimento, varianti della trasformata di Fourier, altro.

11. Detection di più tag chipless contemporaneamente abilitata da onde acustiche: l’obiettivo è creare un sistema che consenta la separazione della risposta di più tag chipless affiancando l’eccitazione elettromagnetica con quella acustica.

12. Sistemi di Integrated Sensing And Communication (ISAC): analisi dello stato dell’arte e studio sperimentale di Waveform per la localizzazione.

13. Estensione delle backscattering communications mediante circuiti non-Foster e architetture avanzate:
La tesi riguarda lo studio e lo sviluppo di tecniche avanzate per sistemi di backscattering communication, con particolare attenzione all’impiego di tunnel diodes, circuiti non-Foster e architetture d’antenna in grado di migliorare distanza operativa, banda e capacità di reindirizzamento del segnale retrodiffuso. Saranno analizzate soluzioni basate su Van Atta array e Rotman lens, insieme a tecniche di elettronica attiva o non-Foster per superare alcuni dei limiti tipici dei sistemi passivi. Il lavoro potrà includere analisi dello stato dell’arte, modellazione elettromagnetica e circuitale e, dove possibile, attività sperimentali su prototipi.

Thesis Proposals (ENG) – valid for both Bachelor and Master Degree

1. Lidar + RFID Data Fusion for Object Association in Dynamic Environments
   This thesis proposes to study a data fusion technique between Lidar and RFID for object association in complex environments. After mapping with Lidar and clustering via DBSCAN, temporal cross-correlation between the measured RFID phase and the estimated phase (based on cluster motion) is used to associate each cluster with its corresponding RFID tag. The goal is to identify and track moving objects with unique IDs.
   
2. Lidar + UWB Integration for Accurate Object Tracking
   This work explores the fusion of UWB ranging measurements and Lidar data to achieve robust association between tracked objects and their positional data (as in Thesis #1). After clustering the Lidar map, the distances measured by UWB tags are matched with the distances of cluster centroids to uniquely identify the objects.
   
3. RFID-Based Tracking System with a Robotic Manipulator
   The goal of this thesis is to design a system that allows a robotic manipulator to follow a mobile RFID tag. Using antennas mounted on the robot arm, the system estimates the direction of the tag and follows it, both in 2D (planar scanning) and in 3D configurations, enabling advanced localization and pointing capabilities.
   
4. Computer Vision + RFID Fusion for Object Recognition and Navigation
   This thesis analyzes a data fusion system for robotic navigation or object recognition using a combination of visual markers (e.g., QR, ARUCO, infrared markers) and RFID tags. Robots can identify “dual-technology” objects (vision + RFID), even inside containers or in the presence of partial occlusions, improving the reliability of perception.
   
5. Integration of RFID Readers in ROS2 for Cognitive Robotics
   This work focuses on integrating an RFID reading system within the ROS2 ecosystem. ROS nodes will be developed for acquiring, publishing, and processing RFID data, enabling their use in complex robotic scenarios such as object tracking, human-robot interaction, or logistics.
   
6. Integration of UHF RFID sensors into the “Halos for Robotics” tool (https://www.nvidia.com/en-us/ai-trust-center/halos/robotics/). This software, developed by NVIDIA and released on June 22, 2026, is designed to validate industrial safety solutions through simulation, primarily those based on cameras and computer vision.
   
7. Use of Radar in Safety Systems: The thesis involves carrying out a state-of-the-art analysis for a Bachelor’s thesis, or a state-of-the-art analysis combined with an experimental measurement campaign for a Master’s thesis, focusing on the use of radar in safety systems. Particular attention will be given to scenarios in which vegetation or other obstacles may make the detection of human targets challenging.
   
8. Decoding Methods for Chipless RFID Tags:The thesis provides an overview of the main decoding techniques for chipless RFID tags, an emerging technology that enables object identification without the use of integrated circuits. After an introduction to the operating principles of chipless RFID systems, the interrogation and decoding methods proposed in the scientific literature will be reviewed and compared in terms of performance, complexity, robustness to noise, and main application areas. Chipless RFID technology is still highly experimental and has not yet reached widespread industrial adoption. The basic idea is to exploit the (S_{11}(f)) and (S_{21}(f)) parameters of these tags, which essentially consist of periodic electromagnetic structures exhibiting multiple resonances, to encode bit strings that can be used to identify an object directly in the electromagnetic domain. One of the main advantages of this thesis topic is that it introduces students to an active and emerging research field while providing an opportunity to become familiar with recent scientific literature.
   
9. Introduction to Acoustics and Acoustic Propagation:The thesis will provide an introduction to acoustics, including the fundamentals of acoustic propagation, pressure waves, and transmitters and receivers for acoustic signals. The work may also include an introduction to underwater acoustic propagation and to the transmitters and receivers used in underwater environments. Some concepts, such as communication channels and time and frequency selectivity, are not yet covered in the Bachelor’s degree curriculum and can therefore be introduced only at a basic level (for bachelors). The thesis may also include simple experimental activities using readily available equipment, such as smartphones or PCs running MATLAB, together with loudspeakers and microphones. Free software tools such as REW or Audacity can also be used to perform basic measurements and analyze acoustic signals.
   
10. Detection of Multiple Chipless RFID Tags within the Same Scene: The objective of the thesis is to investigate algorithms capable of separating the responses of multiple chipless RFID tags located simultaneously within the reading range of the reader device. Different approaches may be considered, including spatial matched filtering for moving tags, variants of the Fourier transform, and other signal processing techniques.
    
11. Simultaneous Detection of Multiple Chipless RFID Tags Enabled by Acoustic Waves: The objective of the thesis is to develop a system capable of separating the responses of multiple chipless RFID tags by combining electromagnetic excitation with acoustic excitation. The additional acoustic stimulus is intended to provide an extra degree of diversity that may help distinguish and identify multiple tags located within the same reading area.
    
12. Integrated Sensing and Communication (ISAC) Systems: The thesis will focus on an analysis of the state of the art in Integrated Sensing and Communication (ISAC) systems, followed by an experimental study of waveforms suitable for localization applications. Particular attention may be devoted to waveform design and to the trade-offs between communication and sensing performance.
    
13. Extension of Backscatter Communications through Non-Foster Circuits and Advanced Architectures:
    The thesis focuses on the study and development of advanced techniques for backscatter communication systems, with particular attention to tunnel diodes, non-Foster circuits, and antenna architectures aimed at improving operating range, bandwidth, and control of the backscattered signal. Solutions based on Van Atta arrays and Rotman lenses will be investigated, together with active or non-Foster electronic techniques to overcome some of the typical limitations of purely passive systems. The work may include a state-of-the-art review, electromagnetic and circuit-level modelling, and, where feasible, experimental validation through prototype implementations.

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Bio: Andrea Motroni (S’17, M’20) received the M.E. (with honors) degree in Telecommunication Engineering and the Ph.D. (with honors) degree in Information Engineering from the University of Pisa, Pisa, Italy, in 2017 and 2021, respectively, where he is currently a Tenure Track Assistant Professor in Electromagnetism. In 2020, he was a Visiting Ph.D. Student with the Graz University of Technology, Graz, Austria. Dr. Motroni was a Finalist at the IEEE CRFID Educational Mega Challenge (2018), a recipient of the Best Paper Award and Best Student Paper Award at IEEE RFID-TA 2019, and a recipient of the Young Scientist Award from the International Union of Radio Science, Commission B in 2021 and 2023. In 2022, Dr. Motroni was awarded the IEEE/ABB Italy Section award for PhD Thesis and the “2021 Best PhD Dissertation in the field of Information and Industrial Engineering” from the University of Pisa. He won the Best Poster Award at IEEE M&N 2022 and at IEEE RFID 2023 conferences, and the Best Paper Award at IEEE GreenCom 2024. In 2024, he was also awarded the “Barzilai Award” by SIEm (Italian Society of Electromagnetism), and in 2026 he was awarded the “Best Paper Young Scientist Award entitled to Prof. Roberto Sorrentino” from the URSI Italian National Committee. He currently serves as Associate Editor for the IEEE Journal of Radio Frequency Identification (IEEE JRFID), and he is an executive member of the IEEE CRFID’s Technical Committee on Motion Capture and Localization. He is the Publicity Chair of the IEEE CRFID. He has joined the Organizing Committee and has been Session Chair of several IEEE international conferences, being as well nominated as Technical Program Chair for IEEE RFID 2027. In 2019, he was the President of the IEEE Student Branch of the University of Pisa, for which he now serves as Counselor. His current research interests include indoor radiolocalization systems, with a specific focus on UHF-RFID and UWB technology for robot and vehicle localization, the integration of robotic systems with RFID towards new systems for industry and logistics, UHF-RFID smart gates and other RFID-based applications for the Internet of Things, Industry 4.0, and people safety in both indoor and outdoor environments. His research activity is evidenced by more than 80 scientific contributions in International Journals and Conferences, European and National patents, and leading positions in research projects.