Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2015/2016
Tipo incarico Dottorato
Docente Bascetta Luca
Cfu 5.00 Tipo insegnamento Monodisciplinare

Corso di Dottorato Da (compreso) A (escluso) Insegnamento

Programma dettagliato e risultati di apprendimento attesi

Aims and learning outcomes

The course is aimed at providing students (with basic knowledge about robotics and control) with theoretical and practical instruments, related to modelling and identification, perception, control, path/trajectory and mission planning, required to understand this evolution, and set up unmanned autonomous vehicles in the air, land and sea domains.


The course presents the knowledge required to better understand the commonalities and specificities of unmanned autonomous vehicles design in the different domains of air, land, and sea.

To provide a common base to better understand the specificities induced by the particular domain, the course will provide basic knowledge about the general tools and common components that are involved in the design of an unmanned autonomous vehicle. After an initial introduction of the current state of the art and potential applications of unmanned autonomous vehicles, the course will introduce:

  • the most common vehicle kinematic and dynamic models;
  • the fundamentals on path/trajectory and mission planning;
  • the fundamentals on vehicle model identification and state estimation;
  • the most common sensors for vehicle localization, control, obstacle avoidance;
  • fundamentals of model predictive control applied to vehicle trajectory tracking, stabilization and obstacle avoidance.

The previous topics will be complemented by a description of a complete application case study for each domain (air, marine and land) with the purpose to highlight how each of the components has been applied or it has required some specific adaptation to cope with its peculiarity. In particular, we will discuss applications in the following domain

  • air: fixed wing and rotary unmanned aerial vehicles;
  • land: off-road unmanned vehicles;
  • sea: surface and underwater unmanned vehicles.

Current trends and future applications will be presented and discussed in a final panel with people from academia and industry.


Alfredo Martins, is Senior Researcher at INESC TEC in the Robotics and Intelligent Systems Group and Adjoint Professor at ISEP Engineering School of Porto Polytechnic Institute. His research interests are in the areas of perception, navigation, control and coordination of mobile robots with particular emphasis on marine robots.


Luca Bascetta, is Associate Professor at the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano. He is actually working in human-robot interaction, vehicle path control and stability, modeling and control of flexible robots, visual servoing, mechatronics and motion control.


Matteo Matteucci, is Associate Professor at the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano. He is actually working in Robotics and Machine Learning, mainly applying techniques for adaptation and learning to autonomous systems in real world dynamic environments.


Marcello Farina, is Associate Professor at the Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano. His research interests include distributed and decentralized state estimation and control with application to mobile robots and sensor networks, modeling and control of energy supply systems.


Marco Lovera, is Full Professor at the Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano. His research interests include system identification and advanced modeling and control methods for aerospace applications, with specific reference to helicopter dynamics and to modeling and control issues in space vehicles.

Note Sulla Modalità di valutazione

PhD students will be asked to study one or two scientific papers and prepare a 20-30 minutes presentation summarizing the content of the papers with reference to the course syllabus. The presentation will be evaluated by the course Professor in Charge for their content.

Master studens will be asked to carry out a project using one of the techniques presented during the course.

Intervallo di svolgimento dell'attività didattica
Data inizio
Data termine

Calendario testuale dell'attività didattica

Risorsa bibliografica facoltativaB. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics Modelling, Planning and Control, Editore: Springer, Anno edizione: 2009, ISBN: 978-1-84628-642-1
Risorsa bibliografica facoltativaMark W. Spong, Seth Hutchinson, M. Vidyasagar, Robot Modeling and Control, Editore: John Wiley and Sons, Anno edizione: 2015, ISBN: 978-0471649908
Risorsa bibliografica facoltativaSteven M. LaValle, Planning Algorithms, Editore: Cambridge University Press, Anno edizione: 2006 http://planning.cs.uiuc.edu/

Online available

Risorsa bibliografica facoltativaL. Magni, R. Scattolini, Advanced and Multivariable Control, Editore: Pitagora Ed., Anno edizione: 2014

Mix Forme Didattiche
Tipo Forma Didattica Ore didattiche
laboratorio informatico
laboratorio sperimentale
laboratorio di progetto

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese

Note Docente
The course will be a one week course to be held at Dipartimento di Elettronica, Informazione e Bioingegneria (Seminar Room), Via G. Ponzio 34/5, Milan. Period: 6-10 June 2016
schedaincarico v. 1.6.6 / 1.6.6
Area Servizi ICT