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
This information is intended exclusively for students already enrolled in this course.If you are a new student interested in enrolling, you can find information about the course of study on the course page:
Laurea magistrale in Ingegneria e scienze informatiche - Enrollment from 2025/2026The 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
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2° Year activated in the A.Y. 2019/2020
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2 modules among the following
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.
Physical human-robot interaction (2018/2019)
Teaching code
4S007197
Credits
6
Language
Italian
Also offered in courses:
- Advanced Robotics of the course Master's degree in Computer Science and Engineering
- Advanced Robotics of the course Master's degree in Computer Science and Engineering
- Advanced Robotics of the course Master's degree in Computer Science and Engineering
Scientific Disciplinary Sector (SSD)
INF/01 - INFORMATICS
The teaching is organized as follows:
Laboratorio
Teoria
Learning outcomes
The course aims to provide the theoretical foundations of teleoperation systems and physical interaction with the environment, with particular focus on the design of control architectures able to guarantee the stability of such systems even in the presence of uncertainty and communication delay.
At the end of the course the student should demonstrate that s/he has acquired the knowledge to analyze the technical characteristics and structural properties of a control system for direct or teleoperated interaction with the environment.
This knowledge will allow the student: i) to build the mathematical model of a teleoperation system; ii) to model physical human-robot interaction systems; iii) to design a control architecture to guarantee the stability; iv) to implement the control structure in Matlab/Simulink and/or in ROS (Robot Operating System).
At the end of the course the student will have acquired the ability to define the technical specifications for physical human-robot interaction systems and for bilateral teleoperation systems, and consequently to choose the most appropriate approach of designing the control architecture.
It will also be able: i) to work together with other engineers (e.g. electronic, control, mechanical engineers) to design advanced control architectures for complex physical human-robot interaction systems and teleoperation systems; ii) to enhance his/her knowledge on the design of control architectures based on stochastic and non-linear methods.
Program
Advanced topics that will be addressed during the course:
- manipulator dynamics
- motion control (PID)
- force control (force and impedance)
- passivity theory
- advanced algorithms for teleoperation
- communication time delay compensation
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
TEACHING AIDS: During the course, lecture notes, slides and scientific papers will be provided.
Examination Methods
The exam will consist of a project addressing some topics discussed during the course. The student should have to implement in ROS (and/or in Matlab/Simulink) a teleoperation algorithm, test it, 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,
- 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.
Teaching materials e documents
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Chapter Bode Diagram (it, 353 KB, 3/31/19)
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Chapter Nyquist (it, 482 KB, 4/15/19)
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Chapter PID (it, 244 KB, 3/31/19)
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Chapter Specifications (it, 329 KB, 3/31/19)
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Chopra-Spong-Lozano Algorithm (it, 544 KB, 5/11/19)
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Dati Banchetto teleoperazione (it, 2248 KB, 4/8/19)
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DC motors (it, 2149 KB, 3/25/19)
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Franken et Al Algortihm (it, 1281 KB, 5/26/19)
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Intro Teleoperation Part I (it, 2578 KB, 3/6/19)
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Intro Teleoperation Part II (it, 1224 KB, 3/6/19)
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Lee-Huang Algortihm (it, 961 KB, 5/26/19)
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Lee-Spong Algorithm (it, 725 KB, 5/11/19)
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Niemeyer-Slotine Algorithm (it, 641 KB, 4/29/19)
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Passivity (it, 390 KB, 4/15/19)
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PID controllers (it, 566 KB, 5/11/19)
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Ryu-Artigas-Preusche Algorithm (it, 831 KB, 5/11/19)
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Statistical filtering (it, 333 KB, 4/8/19)
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Teleoperation without comm. delay (it, 464 KB, 3/31/19)