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:
Master's Degree in Computer Engineering for Intelligent Systems - 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
| Modules | Credits | TAF | SSD |
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2° Year activated in the A.Y. 2025/2026
| Modules | Credits | TAF | SSD |
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3 modules among the following
(A.A. 2025/2026 Internet of medical things not activated)| Modules | Credits | TAF | SSD |
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| Modules | Credits | TAF | SSD |
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3 modules among the following
(A.A. 2025/2026 Internet of medical things not activated)| Modules | Credits | TAF | SSD |
|---|
4 modules among the following:
- 1st year: Advanced visual computing and 3d modeling, Computer vision, Embedded & IoT systems design, Embedded operating systems, Robotics
- 2nd year: Advanced control systemsLegend | 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.
Medical Robotics - MEDICAL ROBOTICS (2025/2026)
Teaching code
4S012370
Teacher
Credits
5
Language
English
Scientific Disciplinary Sector (SSD)
ING-INF/04 - SYSTEMS AND CONTROL ENGINEERING
Period
1st semester dal Oct 1, 2025 al Jan 30, 2026.
Courses Single
Authorized
To show the organization of the course that includes this module, follow this link: Course organization
Program
The course introduces the main foundations of medical robotics, with particular emphasis on physical interaction, bilateral teleoperation, and passivity-based control. It also covers estimation and statistical filtering methods, including the Kalman filter, smoothing, and regression and regularization techniques, as useful tools for monitoring, control, and data interpretation in robotic systems for healthcare applications.
Didactic methods
The course is organized through lectures, complemented by assignments aimed at deepening and applying the main theoretical concepts covered during the course. The teaching activities combine methodological and applied aspects, with particular attention to modeling, control, and estimation in robotic systems for medical applications.
Learning assessment procedures
The assessment is based on the assignments completed during the course and on a final report. The assignments are intended to evaluate the student’s progressive learning of the course contents, while the final report allows the student to further develop and critically discuss a topic consistent with the course programme.
Evaluation criteria
The final assessment is based on the correctness and completeness of the assignments, the ability to appropriately apply the methods and tools presented in the course, and the quality of the final report in terms of clarity of presentation, organization of contents, and critical discussion.
Exam language
English
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