ppt - LaDiSpe - Politecnico di Torino

ROBOTICS
01PEEQW
Basilio Bona
DAUIN – Politecnico di Torino
Course presentation
Schedule
March – June 2016
 Mon
 Tue
 Wed
Basilio Bona
08:30 – 11:30
08:30 – 11:30
10:00 – 11:30
Room 12D
Room 12D
Laboratory (@ LAIB 1)
ROBOTICS 01PEEQW - 2015/2016
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Textbooks and prerequisites
 Textbooks
 B. Bona, Modellistica dei Robot Industriali, CELID, (in Italian)
 B. Bona, Metodi di Controllo per Manipolatori Industriali, notes (in
Italian)
 Slides (in English) are available at the course web page
 Other optional textbooks
 B. Siciliano, L. Sciavicco, L.Villani, G. Oriolo, Robotics: Modelling,
Planning and Control, Springer, 2009
 G. Legnani, Robotica Industriale, Casa Editrice Ambrosiana, 2003
 G. Gini, V. Caglioti, Robotica, Zanichelli, 2003
 Prerequisites
 Selected topics from first semester MSMS
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Exams are written
No books or notes are allowed
Multiple answer
questions
1 hour (40%)
Basilio Bona
Open questions
1 hour (60%)
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Laboratories
 Two types of Laboratories
 Simulation Lab @LAIB 1 (software used: Matlab, Simulink,
SimMechanics)
 Real systems @LaDiSpe (Comau Robot) in May
In the Simulation Lab, two or more Lab projects will be proposed;
Matlab, Simulink or SimMechanics will be available
The LadiSpe Lab is only devoted to show a real working robot.
There is no time and support to develop motion or control algorithms
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Web page of the course
 www.ladispe.polito.it/corsi/meccatronica/01PEEQW/201516/index.htm
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Online video courses
 Following online video
courses is encouraged, but
does not count for the final
mark
 One of the most
appreciated online video
course is that of professor
Khatib, Stanford University
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Online video courses
Another interesting course elated to
service robotics is
Artificial Intelligence for Robotics
by Sebastian Thrun
Sebastian Thrun is a Research Professor of Computer
Science at Stanford University, a Google Fellow, a
member of the National Academy of Engineering and
the German Academy of Sciences
Thrun is best known for his research in robotics and
machine learning, specifically his work with selfdriving cars
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MOOC (Massive Open Online Courses)




These are some web pages of MOOC providers
Udacity: https://www.udacity.com/
Coursera: https://www.coursera.org/
edX: https://www.edx.org/
 How to find Open Online Courses
 mooc.ca: http://www.mooc.ca/courses.htm
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