logo-polimi
Loading...
Risorse bibliografiche
Risorsa bibliografica obbligatoria
Risorsa bibliografica facoltativa
Scheda Riassuntiva
Anno Accademico 2022/2023
Scuola Scuola di Ingegneria Industriale e dell'Informazione
Insegnamento 052368 - CONTROL OF INDUSTRIAL AND MOBILE ROBOTS
  • 052355 - CONTROL OF MOBILE ROBOTS
Docente Bascetta Luca
Cfu 5.00 Tipo insegnamento Modulo Di Corso Strutturato

Corso di Studi Codice Piano di Studio preventivamente approvato Da (compreso) A (escluso) Insegnamento
Ing Ind - Inf (Mag.)(ord. 270) - MI (473) AUTOMATION AND CONTROL ENGINEERING - INGEGNERIA DELL'AUTOMAZIONE*AZZZZ052366 - CONTROL OF MOBILE ROBOTS
052368 - CONTROL OF INDUSTRIAL AND MOBILE ROBOTS
Ing Ind - Inf (Mag.)(ord. 270) - MI (481) COMPUTER SCIENCE AND ENGINEERING - INGEGNERIA INFORMATICA*AZZZZ052366 - CONTROL OF MOBILE ROBOTS

Obiettivi dell'insegnamento

The aim of this course is to introduce the student to the fundamental aspects of modeling and simulation, planning and control, for mobile robots.

The course covers the main aspects of mobile robotics, making reference to indoor, outdoor and off-road environments. Classical and advanced planning and control techniques are introduced.

At the end of the course, a case study is presented to show the application of planning and control methodologies to a realistic problem, emphasizing the role of mobile robotics in different fields of automation.


Risultati di apprendimento attesi

After the course, the student should be able to:

- describe and explain how the kinematic and dynamic behaviour of a mobile robot can be represented using a mathematical model;

- describe and explain how a path/trajectory planning problem for a mobile robot can be solved, possibly considering the robot model and a multi-robot scenario;

- describe and explain how a regulation or a trajectory tracking control system for a mobile robot can be designed, using linear and nonlinear control techniques;

- develop a kinematic or a dynamic model of a mobile robot, using suitable simulation tools;

- design the navigation system, i.e., a planning and a control algorithms, for a mobile robot.


Argomenti trattati

The course is structured in seven modules. Four core modules act as the foundations of the course, developing students’ understanding of key aspects of mobile robotics, i.e., kinematics, dynamics, planning and control. Three further modules build students’ understanding on how mobile robotics fit into the context of automation in many different application fields.

 

Module 1: Introduction

Applications of mobile robots in indoor, outdoor and off-road scenarios

Ground and aerial mobile manipulation

Classical problems of mobile robotics

Fundamentals of hardware, software and control architectures


Module 2: Kinematics of mobile robots

Kinematic configurations for indoor, outdoor, and off-road mobile robots

Characterisation of kinematic constraints: holonomic and nonholonomic configurations

Using kinematic constraints to derive a kinematic model

Kinematic models of mobile robots

A system theory interpretation of holonomy and nonholonomy


Module 3: Dynamics of mobile robots

Fundamentals of dynamic modeling for mobile robotics

Fundamentals of wheel-ground interaction modeling for indoor, outdoor, and off-road applications

Fundamentals of mobile robot multi-body simulation


Module 4: Path/trajectory planning

Planning and control, a global and local perspective

Fundamentals of search based, sampling based, and model based planners

Planning in Cartesian and configuration space with sampling based techniques

Introducing robot kinodynamic and actuation constraints in the planning problem


Module 5: Trajectory tracking control

Control of omnidirectional mobile robots

A canonical model for nonholonomic mobile robots

Exact linearization and flatness form of classical mobile robot models

Trajectory tracking control based on canonical model and exact linearization

Fundamentals of odometric localization


Module 6: ROS for mobile robot modelling, planning and control

Fundamentals of ROS programming: nodes, messages and topics, services, ROS master, parameters and parameter server, stacks and packages

A mobile robot simulator using ROS and Odeint

A mobile robot trajectory tracking controller using ROS


Module 7: Case study

Examples of application of modelling, planning and control techniques to case studies in different application domains


Obiettivi di sviluppo sostenibile - SDGs
Questo insegnamento contribuisce al raggiungimento dei seguenti Obiettivi di Sviluppo Sostenibile dell'Agenda ONU 2030:
  • SDG2 - ZERO HUNGER
  • SDG9 - INDUSTRY, INNOVATION AND INFRASTRUCTURE
  • SDG11 - SUSTAINABLE CITIES AND COMMUNITIES

Mobile robot modelling, and design of planning an control algorithms to support autonomous navigation in indoor and outdoor environments, are the key enabling methodologies to develop autonomous agricultural robots (SDG2), and personal mobility devices that allow to promote sustainble mobility (SDG9 and SDG11).


Prerequisiti

Students attending this course are expected to know basics of modelling of mechanical systems and automatic control.


Modalità di valutazione

For students attending lectures, exercises, and laboratories in person, the final assessment can be:
a) only a mandatory written exam, consisting of both numerical exercises and theoretical questions;
b) a mandatory written exam, consisting of both numerical exercises and theoretical questions, and a practical project, that each student can partially develop during laboratories and partially at home (project description and corresponding submission rules are introduced during laboratories).
For case (a), the grade includes only the marks from the written exam, and can be up to 28.
For case (b), the grade includes the marks from the written exam (up to 28) and the marks from the practical project (up to 4 additional points). In order to pass the exam, however, the marks taken in the written exam should be greater or equal to 18. In this case the grade can be up to 30 cum laude.
Furthermore, during the course 4 problems are assigned, one for each of the main chapters (kinematics, dynamics, planning, control). Only students attending lectures, exercises, and laboratories in person can propose a solution to these problems. For each problem, to the students proposing a correct solution a bonus mark is assigned. These bonus marks are then added to the marks of the written exam, either in case (a) or (b), but again to pass the exam the marks taken in the written exam should be greater or equal to 18.

 

For students not attending lectures, exercises, and laboratories in person, the final assessment can be:
a) only a mandatory written exam, consisting of both numerical exercises and theoretical questions;
b) a mandatory written exam, consisting of both numerical exercises and theoretical questions, and a practical project, that each student develops at home (project description and corresponding submission rules should be asked by email to the teacher in due time).
For case (a), the grade includes only the marks from the written exam, and can be up to 28.
For case (b), the grade includes the marks from the written exam (up to 28) and the marks from the practical project (up to 4 additional points). In order to pass the exam, however, the marks taken in the written exam should be greater or equal to 18. In this case the grade can be up to 30 cum laude.

 

In the written exam the student should be able to:
- write the kinematic model of a mobile robot, including holonomic and nonholonomic configurations;
- write the dynamic model of a mobile robot, including wheel-ground interaction;
- describe and explain basic concepts and problems within path/trajectory planning, such as Cartesian/configuration space sampling based planning, kinodynamic planning, multi-robot planning;
- describe and explain basic concepts and problems within mobile robot trajectory tracking, such as linear and nonlinear trajectory tracking control, exact linearization, etc.;
- design simple feedback control laws for trajectory tracking of mobile robots;
- give examples on applications of mobile robots in different application domains.

 

In the practical project the student should be able to:
- implement a kinematic model of a mobile robot as a simple ROS node;
- implement a dynamic model of a mobile robot as a simple ROS node;
- planning a path or a trajectory using a Matlab implementation or RRT/RRT*;
- implement a trajectory tracking controller for a mobile robot as a simple ROS node;
- simulate a simple planning and control problem for a mobile robot using the previous tools.


Bibliografia
Risorsa bibliografica obbligatoriaB. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotics: Modelling, Planning and Control, Editore: Springer, Anno edizione: 2009, ISBN: 9781846286414 http://www.springer.com/engineering/robotics/book/978-1-84628-641-4
Note:

3rd Edition

Risorsa bibliografica facoltativaB. Siciliano, L. Sciavicco, L. Villani, G. Oriolo, Robotica: modellistica, pianificazione e controllo, Editore: McGraw-Hill Italia, Anno edizione: 2008, ISBN: 9788838663222 https://www.mheducation.it/9788838663222-italy-robotica-3ed
Note:

3a Edizione

Risorsa bibliografica facoltativaPeter Corke, Robotics, Vision and Control: Fundamental Algorithms in MATLAB, Editore: Springer, Anno edizione: 2011, ISBN: 978-3-642-20143-1 https://doi.org/10.1007/978-3-642-20144-8
Risorsa bibliografica facoltativaKevin M. Lynch and Frank C. Park, Modern Robotics: Mechanics, Planning, and Control, Editore: Cambridge University Press, Anno edizione: 2017, ISBN: 9781107156302 http://hades.mech.northwestern.edu/index.php/Modern_Robotics

Software utilizzato
Software Info e download Virtual desktop
Ambiente virtuale fruibile dal proprio portatile dove vengono messi a disposizione i software specifici per all¿attività didattica
PC studente
Indica se è possibile l'installazione su PC personale dello studente
Aule
Verifica se questo software è disponibile in aula informatizzata
Altri corsi
Verifica se questo software è utilizzato in altri corsi
MATHWORKS Matlab SI SI

Forme didattiche
Tipo Forma Didattica Ore di attività svolte in aula
(hh:mm)
Ore di studio autonome
(hh:mm)
Lezione
32:00
48:00
Esercitazione
6:00
9:00
Laboratorio Informatico
12:00
18:00
Laboratorio Sperimentale
0:00
0:00
Laboratorio Di Progetto
0:00
0:00
Totale 50:00 75:00

Informazioni in lingua inglese a supporto dell'internazionalizzazione
Insegnamento erogato in lingua Inglese
Disponibilità di materiale didattico/slides in lingua inglese
Disponibilità di libri di testo/bibliografia in lingua inglese
Possibilità di sostenere l'esame in lingua inglese
Disponibilità di supporto didattico in lingua inglese
schedaincarico v. 1.7.2 / 1.7.2
Area Servizi ICT
03/10/2022