OBIETTIVI E CONTENUTI

OBIETTIVI FORMATIVI

The class first develops the kinematic modeling and motorization of mobile robots, illustrated by the full study of the differential drive robot. Then localization based on the Extended Kalman Filter is addressed, is illustrated by a lab which uses real data and presents a tuning methodology. Observability issues are also addressed, with practical examples. Planning methods applicable to mobile robots are studied, in particular potential field methods and the Rapidly exploring Random Tree. Control then focuses on direct applications to mobile robots: static and dynamic feedback control and Lyapunov based control, illustrated on the case of the differential drive robot.

DOCENTI E COMMISSIONI

Commissione d'esame

GAETAN GARCIA (Presidente)

MARCO BAGLIETTO

ANTONIO SGORBISSA (Presidente Supplente)

ENRICO SIMETTI (Presidente Supplente)

LEZIONI

INIZIO LEZIONI

https://corsi.unige.it/10635/p/studenti-orario

Orari delle lezioni

L'orario di questo insegnamento è consultabile all'indirizzo: Portale EasyAcademy

ESAMI

MODALITA' D'ESAME

The exam is based on exercises that remain fairly close to class examples and homework examples. The exam typically is a mix of questions that must be solved by calculation, and questions that must not. The exam also contains questions that are meant to evaluate the knowledge gained from the labs.

MODALITA' DI ACCERTAMENTO

Final exam 100%, but as stated above, the exam contains questions to evaluate the understanding of the labs.

Calendario appelli