The course on Robotics will be held by Prof. Tullio Facchinetti.
I recommend to carefully read the information reported in this page.
- Tue 11-13 (Aula E1)
- Wed 11-13 (Aula E3)
To request a meeting, and for any other issue, please send me an email.
Since I held/hold many different courses, I kindly ask to specify in the email the following information: name, course name, identification number, and – possibly – the year when the course was attended.
- In Tuesday 15-11-2016 there will be regular lessons.
- The lesson about the project work will be delivered in January
Organization of the exam
The exam consists of a written test regarding the topics coered during the course. The duration of the test is 2 hours. The slides linked in this page contain all the material that is necessary for preparing the exam.
The exam also requires a mandatory practical part, which consists in the development of a program that implement a control algorithm for a simulated mobile robot.
The two parts of the exam are independent from each other; there are no precedence constraints and once a part has been passed, its validity does not expire.
The didactic material is based on the slides shown during lessons. Presentations will be made available during the course.
ATTENTION: since slight changes to the slides are possible, it is recommended to periodically check this site for updates. The date indicated for each presentation represents the latest update of the corresponding file.
- [18/10/2016] Introduction : historical origins of robotics; overview of a robotics system; hardware and software components of a robot;
- [18/10/2016] Robot navigation : introduction; bugs algorithms: Bug 1, Bug 2, Tangent Bug; potential fields method;
- [18/10/2016] Map-based robot navigation : roadmaps; basics about graphs; visibility maps; grid-occupancy maps; wave-front algorithm; A* algorithm; probabilistic planners; Voronoi maps; cell decomposition maps;
Finite State Machines
- [04/11/2015] Finite State Machines : introduction; Mealy and Moore FSM; formal model; composition of state machines; hybrid systems; examples.
- [30/10/2016] Introduction : definitions; examples; terminology, definitions and notation; taxonomy;
- [08/11/2016] Classical algorithms : First-Come First-Served (FCFS), Shortest Job First (SJF), Round-Robin (RR), Earliest Due Date (EDD), Earliest Deadline First (EDF), optimality of EDF, non-preemptive scheduling.
- [31/10/2016] Periodic tasks : task model, Rate Monotonic (RM), Earliest Deadline First (EDF), Deadline Monotonic (DM).
- [15/11/2016] Aperiodic tasks : task model, background scheduling, Polling Server (PS), Sporadic Server (SS), Total Bandwidth Server (TBS), TBS*, Constant bandwidth Server (CBS).
- [11/12/2013] Shared resources : critical sections, Priority Inheritance Protocol (PIP).
- [28/11/2016] Measures : measurements, errors, propagation of errors, sources of errors.
- [28/11/2016] Introduction to sensors : type of sensors, characteristics of intelligent sensors.
- [29/11/2016] Sensors – part 1 : linear and angular position sensors; resistive (potentiometers and strain gauges), capacitive, inductive and optical (encoders) technologies; Gray code; gyroscopes; proximity sensors; ultrasonic sensors; touchscreen; GPS; trilateration and multilateration.
- [06/12/2016] Sensors – part 2 : pressure sensors; accelerometers; force sensors and cantilevers; load cell.
- [13/12/2016] Sensors – part 3 : flow sensors (Venturi and Pitot tubes); temperature sensors: thermocoupled resistive thermometers, thermistors; current sensors.
- [13/12/2016] Image sensors : relevance of image processing; CCD and CMOS sensors; efficient image processing algorithm.
- [17/01/2014] Time sensors : oscillators: equivalent circuit, clock, clock drift, parameters and properties, distributed synchronization; Network Time Protocol (NTP).
- [17/01/2014] Errors and compensation : types of errors; compensation techniques; polynomial functions; Look Up Table; Wheatstone bridge.
The course also includes a short introduction to MEMS sensors. The presentations regarding the MEMS technology and the relevant compensation techniques of MEMS accelerometers and gyroscopes, can be provided upon request on a USB drive. Please send an email to Prof. Tullio Facchinetti for an appointment to obtain this material.
The practical project requires to implement a path planning and navigation algorithm in C, Java or Python under a simulation environment based on the MORSE simulator. The simulation requires a mobile robot to move in a 2D environment to accomplish a given task.
In particular, the eduMorse framework is used for the project. The simulation environment runs under Linux (tested with XUbuntu). It must be a Debian-based distribution, since the installer provided by eduMorse makes use of the `apt` command. Its features, characteristics, install instructions and usage are described in a lecture by Daniele De Martini. Detailed information on project goals and constraints can be found here.
- students are invited to form teams of up to 3 members
- the team composition must be communicated to Prof. Facchinetti by email
- if someone has problems in finding a team, please let it know to Prof. Facchinetti, who could put him/her in contact with a team composed by less than 3 members
- the use of git and related tools is optional
- a good management of the software project will be considered in the final evaluation, but it is not mandatory for passing the exam
Additional information, tools and help for the practical project are provided by Daniele De Martini.
The Robotics Student competition Hall of Fame is now available.
The following text books are helpful to expand the topics covered in the course.
- John Brignell, Neil White, “Intelligent Sensor System”, Institute of Physics Publishing, Bristol and Philadelphia, 1996. ISBN 0-7503-0389-1.
- Paulo Verissimo, Luis Rodriguez, “Distributed Systems for System Architects”, Kluwer Academis Publishers, 2000. ISBN 0-7923-7266-2.
- Giorgio C. Buttazzo, “Hard Real-time Computing System” Second Edition, Springer, 2005. ISBN 0-387-23137-4.
- Howie Choset, Kevin M. Lynch, Seth Hutchinson, George Kantor, Wolfram Burgard, Lydia E. Kavraki, Sebastian Thrun, “Principles of Robot Motion: Theory, Algorithms, and Implementations”, The MIT Press, Cambridge, Massachussets, 2005. ISN 0-262-03327-5.
- John R. Taylor, “An Introduction to Error Analysis: The Study of Uncertainties in Physical Measurements”, University Science Books, 1997.
- Edward A. Lee and Sanjit A. Seshia, Introduction to Embedded Systems, A Cyber-Physical Systems Approach, ISBN 978-0-557-70857-4, 2011.