Studying at the University of Verona

Here you can find information on the organisational aspects of the Programme, lecture timetables, learning activities and useful contact details for your time at the University, from enrolment to graduation.

Study Plan

A.A. 2023/2024 A.A. 2022/2023 A.A. 2021/2022 A.A. 2020/2021

The Study Plan includes all modules, teaching and learning activities that each student will need to undertake during their time at the University.
Please select your Study Plan based on your enrollment year.

1° Year

ModulesCreditsTAFSSD
9
B
ING-INF/05
9
B
ING-INF/05
9
B
ING-INF/04
9
C
ING-IND/13 ,ING-IND/35
Compulsory courses for Embedded & IoT Systems
6
B
ING-INF/05
6
B
ING-INF/05
Compulsory courses for Robotics systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory courses for Smart systems &data analytics
6
B/C
INF/01 ,ING-INF/06
6
B/C
ING-INF/05

2° Year  activated in the A.Y. 2021/2022

ModulesCreditsTAFSSD
Compulsory courses for Embedded & IoT Systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory courses for Robotics systems
6
B/C
ING-INF/04
6
B/C
ING-INF/05
Compulsory courses for Smart systems &data analytics
6
B/C
ING-INF/05
6
B/C
ING-INF/05
Final exam
24
E
-
ModulesCreditsTAFSSD
9
B
ING-INF/05
9
B
ING-INF/05
9
B
ING-INF/04
9
C
ING-IND/13 ,ING-IND/35
Compulsory courses for Embedded & IoT Systems
6
B
ING-INF/05
6
B
ING-INF/05
Compulsory courses for Robotics systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory courses for Smart systems &data analytics
6
B/C
INF/01 ,ING-INF/06
6
B/C
ING-INF/05
activated in the A.Y. 2021/2022
ModulesCreditsTAFSSD
Compulsory courses for Embedded & IoT Systems
6
B/C
INF/01
6
B/C
ING-INF/05
Compulsory courses for Robotics systems
6
B/C
ING-INF/04
6
B/C
ING-INF/05
Compulsory courses for Smart systems &data analytics
6
B/C
ING-INF/05
6
B/C
ING-INF/05
Final exam
24
E
-
Modules Credits TAF SSD
Between the years: 1°- 2°
3 courses to be chosen among the following
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
INF/01
6
C
ING-INF/01
6
C
INF/01
6
C
ING-IND/16
6
C
INF/01
6
C
INF/01 ,ING-IND/34
6
C
INF/01
6
C
INF/01
6
C
SECS-P/10
Between the years: 1°- 2°
12
D
-
Between the years: 1°- 2°
Other activities
3
F
-
Between the years: 1°- 2°
Training
3
F
-

Legend | Type of training activity (TTA)

TAF (Type of Educational Activity) All courses and activities are classified into different types of educational activities, indicated by a letter.

A Basic activities
B Characterizing activities
C Related or complementary activities
D Activities to be chosen by the student
E Final examination
F Other training activities
S Placements in companies, public or private institutions and professional associations

Physical human-robot interaction  (2021/2022)

Teaching code

4S009007

Academic staff

Riccardo Muradore, Andrea Calanca

Coordinator

Riccardo Muradore

Credits

6

Language

English en

Scientific Disciplinary Sector (SSD)

ING-INF/05 - INFORMATION PROCESSING SYSTEMS

Period

Primo semestre dal Oct 4, 2021 al Jan 28, 2022.

Lessons timetable MoodleMoodle Seminars 0

Learning outcomes

The course aims to provide the following knowledge: theoretical foundation of physical human-robot interaction (e.g. bilateral teleoperation and force control), with particular attention to the design of control architectures capable of guaranteeing stability even in the presence of uncertainties and communication delays.

At the end of the course the student will have to demonstrate that s/he has the following skills to apply the acquired knowledge: analyze the technical characteristics and structural properties of a control system for direct or teleoperated interaction with the environment; derive the mathematical model of the physical robot-environment interaction (direct or teleoperated); design a control architecture to ensure stability, performance and safety; implement the control architecture in simulators (e.g. Matlab/Simulink) and in operating systems tailored to robotic application (e.g. ROS).

Student must also have the ability to define the technical specifications for a physical human robot-interaction system a (direct or teleoperated) and the ability to choose the most appropriate way to design the control architecture.

Student will have to be able to deal with other engineers (e.g. electronic, automatic, mechanical) to design advanced control architectures for complex physical human-robot interaction systems.

Student will have to show ability to continue its studies independently in the context of the design of architectures based on non-linear and adaptive techniques.

Program

Topics that will be addressed during the course:
- passivity theory
- advanced algorithms for teleoperation
- communication time delay compensation
- physical human-robot interation
Topics that will be addressed during the lab activity:
- Tuning of PID controllers
- Implementation of velocity estimators
- Data-driven system identification
- Implementation of bilateral teleoperation algorithms in ROS/Matlab-Simulink

Examination Methods

The exam will consist of a project addressing the topics discussed during the course. The student should have to implement in ROS (and/or in Matlab/Simulink) a few teleoperation algorithms, test them, and prepare a brief technical document explaining his/her work.

To pass the exam, the student should:
- have understood the principles related to the design of a bilateral teleoperation system and to the physical human-robot interaction,
- be able to use the knowledge acquired during the course to solve the assigned problem,
- be able to describe their work by explaining and motivating the design choices.

Students with disabilities or specific learning disorders (SLD), who intend to request the adaptation of the exam, must follow the instructions given HERE