ALL blocks

MEASUREMENT SYSTEMS FOR MECHATRONICS –> COMPUTER VISION (2024-25)

Simona Ranieri 2nd year, 6 CFU, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, II semester, Subjects , ,
MEASUREMENT SYSTEMS FOR MECHATRONICS –> COMPUTER VISION (2024-25)
2 YEAR II semester  6 CFU
Arianna Mencattini A.Y. 2021-22

A.Y. 2022-23
A.Y. 2023-24

Computer Vision A.Y. 24-25
Code: 8039787
SSD: ING/INF/07

LEARNING OUTCOMES: Learning basic concepts in digital image processing and analysis as a novel measurement system in biomedical fields. The main algorithms will be illustrated particularly devoted to the image medical fields.

KNOWLEDGE AND UNDERSTANDING: The student acquires knowledge related to the possibility to use an image analysis platform to monitor the dynamics of a given phenomenon and to extract quantitative information from digital images such as object localization and tracking in digital videos.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student acquires the capability to implement the algorithms in Matlab through dedicated lessons during the course with the aim of being able to autonomously develop new codes for the solution of specific problems in different application fields.

MAKING JUDGEMENTS: :
The student must be able to integrate the basic knowledge provided with those deriving from the other courses such as probability, signal theory, and pattern recognition. some fundamentals of measurement systems as well as basic metrological definitions will be provided in support of background knowledge.

COMMUNICATION SKILLS:
The student solves a written test and develops a project in Matlab that illustrates during the oral exam. The project can be done in a group to demonstrate working group capabilities.

LEARNING SKILLS:
Students will be able to read and understand scientific papers and books in English and also to deepen some topics. In some cases, students will develop also experimental tests with time-lapse microscopy acquisition in the department laboratory.

 

SYLLABUS:

Fundamentals of metrology. Basic definitions: resolution, accuracy, precision, reproducibility, and their impact over an image based measurement system. Image processing introduction. Image representation. Spatial and pixel resolution. Image restoration. Deconvolution. Deblurring. Image quality assessment. Image enhancement. Image filtering for smoothing and sharpening. Image segmentation: pixel based (otsu method), edge based, region based (region growing), model based (active contour, Hough transform), semantic segmentation. Morphological operators. Object recognition and image classification. Case study: defects detection, object tracking in biology, computer assisted diagnosis, facial expression in human computer interface.
Matlab exercises.

ELECTRONICS OF IOT AND EMBEDDED SYSTEMS

Simona Ranieri 12 CFU, 2nd year, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, I sem, Subjects ,
ELECTRONICS OF IOT AND EMBEDDED SYSTEMS

 

2 YEAR 1 semester 12 CFU
Patrick LONGHI (3cfu)

Giancarlo ORENGO (3cfu)

Gian Carlo CARDARILLI (4cfu)

Luca DI NUNZIO (2cfu)

 A.Y. 2021-22

A.Y. 2022-23

A.Y. 2023-24
MODULI:

M-5519 – ELECTRONICS OF IOT (6cfu)

M-5520 – DESIGN OF EMBEDDED SYSTEMS FOR MECHATRONICS (6cfu)
Code: 8039795
SSD: ING-INF/01

EDUCATIONAL OBJECTIVES:
The objectives of the course are:
1) to provide the tools to carry out a radio link assessment in a real application context.
2) learn the fundamental parameters of the antennas used in IoT applications
3) provide the tools to interpret the electrical diagram of the RF front end of a typical trans receiver.

KNOWLEDGE AND UNDERSTANDING:
Provide the fundamental tools to understand the most advanced and updated content from publications, magazines, forums, blogs, etc., to always be updated on the state of the art.

ABILITY TO APPLY KNOWLEDGE AND UNDERSTANDING:
Practical radio link budget, electronic noise evaluation on receiver behaviour, installation effects of the antennas, understanding of key parameters of commonly used antennas in the targeted scenario, analysis of an RF transceiver block diagram

AUTONOMY OF JUDGMENT:
In the enormous amount of information that is available today to developers of IoT applications, the course seeks to develop in the student the ability to select the highest quality and most validated content.

COMMUNICATION SKILLS:
The final test is based on an oral exam in which the student illustrates a part of the module

LEARNING ABILITY:
The course aims to develop in the student the ability to independently learn new and constantly updated content because the knowledge acquired today soon becomes obsolete.

SYLLABUS:

(Longhi):

Introduction to radiating elements and their key parameters.
Ideal and practical link budget.
The effect of noise in electronic receivers, figures of merit and mathematical modelling. Receiver G/T.
Practical aspects of IoT RF systems
RFID
Radiating elements key parameters, gain, directivity, HPBW, nulls, radiation pattern, polarization, and input impedance. Some practical cases: the mono/di-pole family, microstrip antennas, parabolic reflector, wearables
Introduction to RF transceiver systems and key-components (switches, HPA, LNA, mixers, frequency generators).

(G.Orengo):

Summary of Digital Electronics: digital encoding of information, binary (fixed and floating point), hexadecimal and ASCII; operators and main logic circuits, registers and memories, programmable devices. Prototyping boards for IoT (Arduino, Rasberry), Systems on Chip (SoC), architecture of a microcontroller, description of the Arduino Uno board. Programming languages ​​(assembly, compiled, interpreted), structure of an Arduino sketch (libraries, setups, loops, functions, interrupts), programming elements in C (variables, math and logical operations, cycles, conditional statements). Use of digital and analog I/O ports (A/D conversion, PWM output). Synchronous and asynchronous serial communication modes, wired (USB) and wireless with Bluetooth, RF and WiFi modules. Remote control of electronic modules (sensors, dc stepper and servo motors, LED/LCD displays etc.) from portable devices (Windows, IoS), through applications developed in Processing and Python, and mobile (Android), through Apps developed with the MIT App Inventor platform. Internet protocols for device local/remote control through WiFi modules connected as access points/clients to web platforms or public/private cloud servers controlled by laptops and/or mobile devices.

(G.Cardarilli):

– Introduction to the Internet of Things (IoT) and embedded systems
– Wireless and mobile communications
– The Sensors
– Low power processing
– IoT and machine learning applications
– Future developments in the field of IoT and embedded systems

 

CONTROL OF MECHANICAL SYSTEMS

Simona Ranieri 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, I sem, Subjects ,
CONTROL OF MECHANICAL SYSTEMS
2 YEAR
 1 semester 9 CFU
Riccardo MARINO Since 2019-20
Code: 8039823
SSD: ING-INF/04

LEARNING OUTCOMES:

Ability to understand scientific papers on the control of mechanical systems

KNOWLEDGE AND UNDERSTANDING:

Knowledge of dynamic modeling of mechanical systems. Knowledge of basic feedback control techniques for single input single output systems and of decoupling techniques for multi input multi output nonlinear systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to simulate using Matlab Simulink complex controlled mechanical systems

MAKING JUDGEMENTS:

Ability to evaluate stability, robustness, and performance of a control system

COMMUNICATION SKILLS: Ability to present and discuss an autonomous design project

LEARNING SKILLS: Ability to fully understand a scientific paper on the control of mechanical systems

SYLLABUS:

BASIC CONTROL TOOLS
Bounded- input bounded- output linear systems. Pole placement theorem for controllable and observable linear systems. Luenberger observers for observable systems. Design of dynamic compensators for linear systems. Integral feedback control to reject constant disturbances. PID control. System inverses for minimum phase linear systems. The combination of feedback and feedforward control actions.
ADVANCED CONTROL TOOLS
Linear approximations of nonlinear control systems about operating conditions. The definition of region of attraction for an operating condition. Output feedback compensators with integral actions to control nonlinear systems about a given operating condition. Liapunov matrix equations to determine quadratic Liapunov functions and assess the region of attraction. The definition of the sensitivity transfer function and its properties. The gang of four: sensitivity, complementary sensitivity, load sensitivity and noise sensitivity functions. How to determine the robustness of a control loop using the gang of four functions. Bode’s integral formula and the limitations imposed by unstable open loop poles. Youla parametrization to design stable compensation. Kalman filters, Riccati equations and robust control design.

CONTROL DESIGN FOR MULTIVARIABLE NONLINEAR SYSTEMS
Relative degree for a single input single output nonlinear system. State feedback control design for input-output linearization. State feedback linearization when the relative degree is equal to the state space dimension. The definition of nonlinear inverse systems. Relative degrees or decoupling indices for multivariable (multi-input, multi-output) nonlinear systems. The definition of the decoupling matrix. State feedback control design for input-output linearization when the decoupling matrix is full rank using the Penrose pseudoinverse. State feedback linearization when the sum of relative degrees is equal to the state space dimension and the decoupling matrix is full rank.

CASE STUDIES OF NONLINEAR MECHANICAL CONTROL SYSTEMS
Control of bycicles, robots, vehicles and aircrafts

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)

Simona Ranieri 1st year, 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, II semester, Subjects , , ,
POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY (ex Internal Combustion Engines)
1 YEAR (Block C)

2 YEAR (Blocks A|B|D|E)

 II semester  9 CFU
Stefano CORDINER (6/9 cfu)
Lorenzo BARTOLUCCI (3/9 cfu)
 A.Y. 2021-22

Internal Combustion Engines
Since A.Y. 2022-23

POWERTRAIN TECHNOLOGIES FOR FUTURE MOBILITY
Code: 80300079
SSD: ING/IND/08
(by Mechanical Engineering)

 

LEARNING OUTCOMES:
The aim of the course is to provide students with in-depth scientific training to properly address the design, selection and management of internal combustion engines and their interaction with the environment, as well as to create the conditions for the development of innovative solutions. To this aim, students will develop in-depth knowledge of the principles of engine operation and learn simulation procedures for testing and sizing an alternative internal combustion engine and its main components. Special attention is also given to the latest technological development of internal combustion engine technology aimed at exceeding current limits in terms of emissions and efficiency and defining innovative scenarios of sustainable mobility.

KNOWLEDGE AND UNDERSTANDING:
The course aim is to provide the students with tools for the analysis of the performances and the evaluation of proper design solutions for internal combustion engines and their core components. At the end of the course, the student will be able to independently understand the functional link between design variables and the performance of internal combustion engines also in case of innovative design,

APPLYING KNOWLEDGE AND UNDERSTANDING:
The course, through the analysis of specific problems and quantitative data, is aimed at providing the tools for analysis and evaluation of the effects of different design choices. The theme of energy efficiency and pollution reduction are at the heart of the teaching organization. The student will be able to interpret and propose design solutions, even innovative ones, adapted to the specificity of the problems that are presented to him.

MAKING JUDGEMENTS:
By studying theoretical and practical aspects of engine design and critically assessing the influence of different design variables, the student will be able to improve his judgment and proposal in relation to design. and the management of internal combustion engines.

COMMUNICATION SKILLS:
The presentation of the theoretical and application profiles underlying the operation of internal combustion engines will be carried out to allow the knowledge of the technical language of the appropriate specialist terminology; The development of communication skills, both oral and written, will also be stimulated through classroom discussion, participation in seminary activities and through final tests.

LEARNING SKILLS:
The learning capacity, even individual, will be stimulated through numerical exercises, the drafting of papers on specialized topics, the discussion in the classroom, also aimed at verifying the actual understanding of the topics treated. The learning capacity will also be stimulated by integrative educational aids (journal articles and economic newspapers) in order to develop autonomous application capabilities.

SYLLABUS:

General information on internal combustion engines: Characteristics and Classification, thermodynamic and performance analysis. Experimental analysis of the performance of an internal combustion engine Air Supply for 4-stroke engines: volumetric efficiency and its evaluation, quasi-stationary effects; valve sizing; the influence of other engine parameters; Variable Valve Actuation systems; non-stationary phenomena in the intake and exhaust: inertia and wave propagation; variable valve geometry systems, computational models; 2-stroke engines: construction schemes; Supercharging; In cylinder charge motion: Turbulence; swirl, squish, tumble, stratified charge engines Traditional and alternative fuels; Fuels general properties: fuel, air stoichiometric; calorific value gaseous fuels: natural gas, hydrogen and mixtures thereof. bioethanol , bio-diesel and DME. Features and their use in engines: technical solutions, performance and emissions Fuel metering. Otto engines: carburetor; injection systems; lambda probe. Diesel engines: fuel injectors and injection systems, dimensioning. Experimental tests on a diesel injection system Common Rail Combustion: Fundamentals of analytical study of combustion, thermodynamics of combustion processes, calculation of the chemical composition and temperature in adiabatic equilibrium transport phenomena (notes), chemical kinetics (notes). Combustion in Otto and Diesel engines. Emissions and their control systems: emissions formation mechanisms, effects on health and environment, measurement of emissions; influence of engine parameters, test cycles and legislation; procedures and systems for the reduction of emissions in engines. Experimental tests. Cooling system: Heat flows, heat transfer in the engine cooling systems, liquid and air: structural layouts and sizing; thermal stress of the mechanical parts. Sustainable mobility. Principles of operation of hybrid vehicles: series and parallel solution; engines there and electrical workers, regenerative braking, lithium batteries, performance and prospects. Plug-in hybrid vehicles, engines c.i. ” Range extender “. Electric vehicles, characteristics and perspectives For all the topics of the course the numerical simulation tools will be presented

 

NANOTECHNOLOGY

Simona Ranieri 1st year, 6 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, II semester, Subjects ,
NANOTECHNOLOGY
1 YEAR II semester  6 CFU
Antonio Agresti (3cfu)

Francesca De Rossi (3cfu)

 A.Y. 2021-22
Antonio Agresti (3cfu)

Fabio Matteocci (3cfu)

 A.Y. 2022-23

A.Y. 2023-24
Antonio Agresti A.Y. 2024-25
Code:
SSD: ING-INF/01

LEARNING OBJECTIVES AND EXPECTED LEARNING OUTCOMES:

LEARNING OUTCOMES:
The first part of the Nanotechnology course introduces thin film depositions using both physical and chemical vapour depositions. The main objective is the knowledge of the potential and limits of the different thin film depositions in the nanotechnology field. Particular attention is destinated to the deposition technique used in micro and nanoelectronics based on semiconductors using top-down and bottom-up approaches. The interaction of both approaches has been discussed with the student in order to share the importance of multidisciplinary knowledge (physics, chemistry and engineering) where the nanotechnology field is based. The final part of module 1 is destinated to the introduction of the case study of the course about the thin film fabrication of an emergent photovoltaic technology: the perovskite solar cells. In particular, the study of the optoelectronic properties of the materials and the fabrication of several device architectures is important to understand the important role of the manufacturing design in thin film photovoltaic technologies destinated at the industrial level.

KNOWLEDGE AND UNDERSTANDING:
Regarding the first module, at the end of the course, the student will have a clear overview of the main deposition technique studied and applied in nanotechnology for different application fields.
Regarding the second module, at the end of the course, the student will know the main characterization techniques for nanostructured materials and electronic and optoelectronic devices till nanometric size.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The student will be able to recognize the applicability areas for the various characterization and realization techniques at nanometric scales. She/He will also be able to apply the knowledge and understanding developed during the course to study and understand recent literature.

MAKING JUDGEMENTS:
The transversal preparation provided by the course implies
1) the student’s capability to integrate knowledge and manage complexity
2) the student’s ability to deal with new and emerging areas in nanotechnology application to energy and nanoelectronics.

COMMUNICATION SKILLS:
The student will be able to clearly and unequivocally communicate the course content to specialized interlocutors. He will also be able to communicate the main physico-chemical characteristics of nanostructured materials and to indicate the most appropriate deposition/processing technique of these materials to technical interlocutors (example: other engineers, physicists, chemists) but not specialists in the field of electronics or devices. The student will also have a sufficient background to undertake a thesis/research work in modern nanotechnology laboratories.

LEARNING SKILLS:
The structure of the course contents, characterized by various topics apparently separated but connected by an interdisciplinary and modular vision, will contribute to developing a systemic learning capacity that will allow the student to approach in a self-directed or autonomous way to other frontier problems on nanotechnology application to energy and nanoelectronics. Furthermore, the student will be able to read and understand recent scientific literature.

 

SYLLABUS

 

First Module: 1 Prof. Antonio Agresti (3 cfu)

1) Quantum Mechanics and p-n junction

2 )Solar Cells: main electrical characterization techniques

3) Absorbance and Fluorescence Spectroscopy

4) Electron scanning microscopy (SEM)

5) Electron transmission microscopy (TEM)

6) Scanning tunneling microscopy (STM)

7) Atomic force microscopy (AFM)

8) Kelvin Probe Microscopy (KPFM)

9) Raman spectroscopy

10) Bi-Dimensional Materials

 

Second module – Prof. Fabio Matteocci (3cfu)

 

1) Introduction to nanotechnology and thin film properties;
2) Thin Film Deposition: the importance of vacuum and plasma;
3) Thermal Evaporation: Working mechanism, material properties, deposition parameters and applications;
4) DC and RF Sputtering: Working mechanism, material properties, deposition parameters and applications;
5) Pulsed Laser Deposition: Working mechanism, material properties, deposition parameters and applications;
6) Chemical Vapour Deposition: Working mechanism, material properties, deposition parameters and applications;
7) Atomic Layer Deposition: Working mechanism, material properties, deposition parameters and applications;
8) Solution Processing: Spin coating, Screen Printing, Blade Coating, Slot die coating;
9) Patterning Procedures: Photolithography and Laser Ablation;
10) Introduction to Perovskite Solar Cell: Working mechanism, material properties, deposition techniques, up-scaling process and applications;
11) Building Integration Photovoltaics;

VLSI CIRCUIT AND SYSTEM DESIGN

Simona Ranieri 1st year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, II semester, Subjects ,
VLSI
1 YEAR II semester  9 CFU
Luca DI NUNZIO A.Y. 2021-22
Luca DI NUNZIO (5 cfu)

Vittorio MELINI (2 cfu)

Sergio SPANO’ (2 cfu)

 since A.Y. 2022-23
Code:
SSD: ING-INF/01

PREREQUISITES:

It is strictly suggested to take the “Digital Electronics” exam before attending this course. You can contact Prof. Luca DI NUNZIO for any doubts regarding the topic.

LEARNING OUTCOMES:

The VLSI CIRCUIT AND SYSTEM DESIGN course aims to teach the basics of combinational and sequential circuits that represent the basic blocks of any modern digital system. In addition, the course will provide the basic concepts of the VHDL language

KNOWLEDGE AND UNDERSTANDING:

At the end of the course, the student will learn the basic concepts of combinational and sequential circuits that are the basis of any system and the basic concepts of the VHDL language useful for the design of digital systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to analyze the characteristics of digital circuits with particular emphasis on timing and power consumption.

MAKING JUDGEMENTS:

The student will understand the acquired knowledge independently and critically to be able to connect and integrate the various aspects related to the design of digital systems

COMMUNICATION SKILLS:

The student must be able to communicate their knowledge acquired during the course in clear, correct, and technical language.

LEARNING SKILLS:

Ability to critically approach a digital circuit design problem, know how to manage it, and find implementation solutions using the VHDL language

SYLLABUS:

(L. DI NUNZIO)

Digital electronics basic concepts
Floating-point and fixed-point numeric representation formats
Combinatorial circuits: encoders, decoders, multiplexers
Sequential circuits: flip flops, latch registers, counters, memories
Introduction to VHDL: entity and architecture, levels of abstraction, HDL design flow, combinatorial and sequential processes, objects in VHDL test bench
Practical activities of circuit design in VHDL

(S. SPANO’)

Central unit
ALU
System registers
Address logic
System buses
Scheduler
Branching of instructions
Interrupts
Bus synchronization
RAM memories
ROM memories
Flash memories
CAM memories

 

POWER ELECTRONICS AND ELECTRICAL DRIVES

Simona Ranieri 2021, 2022, 2nd year, 9 CFU, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, II semester, Subjects , ,
POWER ELECTRONICS AND ELECTRICAL DRIVES
2 YEAR 2 semester 9 CFU
Stefano Bifaretti
 A.Y. 2021-22
Stefano Bifaretti (7cfu)

Cristina Terlizzi (2cfu)

 A.Y. 2022-23 1st Year I semester

A.Y. 2023-24  (NOT HELD)

A.Y. 2024-25
Code: 8039781
SSD: ING-INF/01

LEARNING OUTCOMES:
The Power Electronics and Electrical Drives course aims to provide a basic understanding of the power semiconductors of the main electronic circuits used for the static conversion of electrical energy as well as the electrical drives. The student will acquire the ability to analyse and perform an initial sizing of power electronic converters operating in either direct or alternating current.

KNOWLEDGE AND UNDERSTANDING:
The student will be gradually guided to the knowledge of the functional characteristics and behavior of the main static power converters used, in particular, in industrial applications, in Distributed Generation Systems and in power trains of electical vehicles. In order to improve the topics understanding, the use of Matlab-Simulink specific packages for the simulation of electronic power converters is illustrated.

APPLYING KNOWLEDGE AND UNDERSTANDING:
The knowledge acquired during the course allows the student to select the topology and size of the power converter in relation to the final design.
Different application examples, in particular devoted to distributed energy generation plants, uninterruptible power supplies and electric mobility will allow the student to improve his ability to apply the acquired knowledge.

MAKING JUDGEMENTS:
The student will be able to collect and process specialized technical information on power converters and verify their validity.

COMMUNICATION SKILLS:
The student will be able to relate with power electronics specialists in order to request the technical information necessary for the development of a project activity.

LEARNING SKILLS:
The skills acquired during the course will allow the student to undertake, with a high degree of autonomy, subsequent studies or apply for technical roles in companies working in the field.

 

SYLLABUS:

POWER SEMICONDUCTORS

Power Semiconductors employed in Power Electronics converters: Diodes, BJT, MOSFET, IGBT, Thyristors, Wide Bandgap Semiconductors).

Static and dynamic behavior. Thermal behavior. Conduction and switching losses.

Technical specifications provided by manufacturers’ datasheets. Driving circuits.

POWER CONVERTER TOPOLOGIES

Behavioral characteristics: unidirectional and bidirectional energy transfer, controlled voltage sources. Analysis method of power converters.

DC-DC Converters. Buck, Boost, Buck-Boost. Switching losses reduction. Average Model. Modulation techniques (PWM, PFM, PRM). Output voltage open-loop control. Closed-loop control. Current control.Half and Full Bridge DC-DC converters.

DC-AC Converters (Inverters). Half and Full Bridge DC-AC single-phase converters based on static switches. Three-phase converters. Modulation techniques. Selective Harmonic Elimination (SHE). Sinusoidal Pulse Width Modulation (SPWM).

Rectifiers: Single-phase and three-phase diode rectifiers. Single-phase and three-phase force-commutated PWM rectifiers: topologies, voltage and current controls. Power Factor Corrector (PFC). Effects on grid side of power converters. Generalized power factor. Compliance with grid codes.
Isolated DC-DC converter.

ELECTRICAL DRIVES
Introduction to Electrical Drives. DC, Permanent Magnet Synchronous Motors and Induction Motors. DC motors model.

Power Electronics Applications

Power Converters simulation using Matlab-Simulink/Simpowersystem.
Photovoltaic Conversion Systems.
Power trains for electrical vehicles. Battery chargers.

 

ROBOT MECHANICS

Simona Ranieri 1st year, 2023, 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, I sem, Subjects , ,
ROBOT MECHANICS

 

1 YEAR (Blocks B|C)
2 YEAR (Blocks A)
 1 semester 9 CFU
Marco Ceccarelli (6/9 cfu)

Matteo Russo (3/6 cfu)

 A.Y. 2021-22

A.Y. 2022-23
Matteo Russo A. Y. 2023-24
A.Y. 2024-25
Code: 8039785
SSD: ING-IND/13

LEARNING OUTCOMES:

 The aims of the course are related to explaining the modeling and algorithms for the analysis and design of the functioning of robot mechanisms in terms of mechanical performance. The students will learn how to handle the mechanics of robot by acquiring skills in analyzing and design robots for manipulation tasks in industrial and service applications.

KNOWLEDGE AND UNDERSTANDING:

during the course, problems and characteristics of robotic systems structures and operations are presented to increase students’ knowledge and to allow them to understand problems and solutions in the specific area of ​​robotics

APPLYING KNOWLEDGE AND UNDERSTANDING:

Students are required to apply the characteristics and algorithms for the analysis of manipulations and robotizations of specific robotic systems for merit assessments and demonstrate specific presentation and discussion skills of robotics issues.

MAKING JUDGEMENTS:

Students are involved in the presentation of the modeling and in the discussion of the problems to learn to examine in an autonomous and critical way the problems of analysis of robotic systems.

COMMUNICATION SKILLS:

During the course, the students take part in the discussion of the presented topics and at the end of the course present a report of manipulation and robotization analysis of their choice.

LEARNING SKILLS:

During the course, the students are involved in the discussion for a continuous stimulus to verify the learning and presentation of robot mechanics. the learning achieved is also verified in the presentation of the elaboration of manipulation and robotization analysis of their choice

SYLLABUS:

types of robots and industrial and service applications; components, technical characteristics, and evaluation; analysis and evaluation of manipulative movements; types of manipulators; Denavit-Hartenberg’s notation; fundamentals of direct kinematics; workspace analysis, trajectory planning; fundamentals of statics and dynamics: modeling, actions, equilibrium conditions; equation of motion; fundamentals of the regulation and control of the motion; types and functionality of grippers; grasp mechanics: modeling, actions, equilibrium conditions; mobile service robots: structures and operation; parallel architecture robots; service robots for medical applications: structures and operation; preparation of performance analysis reports of a robot.

INTEGRATED SENSORS

Simona Ranieri 1st year, 2nd year, 9 CFU, a.a. 2023-2024, a.a. 2024-25, a.a.2022-2023, ALL blocks, Block A, Block B, Block C, Block D, Block E, I sem, Subjects , ,
INTEGRATED SENSORS
1 YEAR (Block A|C|D|E)
2 YEAR (Block B)		 1 semester 9 CFU
Corrado Di Natale A.Y. 2019-20 (new name, ex Electronic Devices and Sensors )

A.Y. 2021-22
Alexandro Catini (6cfu)

Corrado  Di Natale (3cfu)

 A.Y. 2022-23

A.Y. 2023-24
Alexandro Catini A.Y. 2024-25
Code: 8039927
SSD: ING-INF/01

LEARNING OUTCOMES:

To introduce the student to modern sensor technologies and their major applications.

KNOWLEDGE AND UNDERSTANDING:

To make the student condition to analyze the sensor performance and to design simple sensors’ interface circuit.

APPLYING KNOWLEDGE AND UNDERSTANDING:

Capability to select sensors for each specific application MAKING JUDGEMENTS:
Evaluate in the different contexts which are the most suitable sensors and evaluate the performance using a standardized parameters set.

COMMUNICATION SKILLS:

Capability to write synthetic reports about the working principles of sensors

LEARNING SKILLS:

To learn how to solve sensors’ circuits to determine their performance and to optimally design sensor systems.

SYLLABUS:

Electronic properties of materials: semiconductors.

General properties of sensors;

Sensitivity and resolution.

Temperature sensors: thermistors, integrated sensors, thermocouples;
Mechanic sensors: Strain gauges: Introduction to MEMS: accelerometer, gyroscope, pressure and flow sensors;

Magnetic sensors;

Optical sensors: photodiodes and image sensors;

infrared sensors; interface circuits for resistive and capacitive sensors