First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Engineering
MECHATRONIC ENGINEERING
Course unit
INDUSTRIAL ROBOTICS
INL1000874, A.A. 2019/20

Information concerning the students who enrolled in A.Y. 2018/19

Information on the course unit
Degree course Second cycle degree in
MECHATRONIC ENGINEERING
IN0529, Degree course structure A.Y. 2011/12, A.Y. 2019/20
N0
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Number of ECTS credits allocated 6.0
Type of assessment Mark
Course unit English denomination INDUSTRIAL ROBOTICS
Department of reference Department of Management and Engineering
Mandatory attendance No
Language of instruction Italian
Branch VICENZA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge GIOVANNI BOSCHETTI ING-IND/13

Mutuated
Course unit code Course unit name Teacher in charge Degree course code
INL1000874 INDUSTRIAL ROBOTICS GIOVANNI BOSCHETTI IN0522

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Core courses ING-IND/13 Applied Mechanics for Machinery 6.0

Course unit organization
Period First semester
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Lecture 6.0 48 102.0 No turn

Calendar
Start of activities 23/09/2019
End of activities 18/01/2020
Show course schedule 2019/20 Reg.2011 course timetable

Syllabus
Prerequisites: Basics of Mechanics of Machines (kinematics and dynamics of rigid bodies and mechanisms)
Target skills and knowledge: The aim of the course consists in providing students with technical and practical knowledge in the field of robotics; knowledge on the main issues related to the use of robots in the industrial fields; capability in the use and in programming robots
Examination methods: The assessment of knowledge and abilities is carried out through an exam divided into two parts done in the same day:
Written test: Students are requested to write a program in order to make the robot perform a specific task.
Oral test: Students are requested to discuss in more detail the written test and the topics of the course.
Assessment criteria: The evaluation criteria with which the knowledge and abilities acquired will be verified are:
Completeness of the theoretical knowledge acquired on robot kinematics, dynamics and programming.
Ability to apply theoretical knowledge to concrete applications.
Level of autonomy acquired in the interpretation and solution of kinematics, dynamics and programming problems.
presentation capabilities and rigorousness in the discussion and in the exposure of the course topics.
Ability in robot programming
Course unit contents: DEFINITION AND CLASSIFICATION: definition of industrial robot, classification of robots and end-effectors, typical problems in robotics, parameters for the performance evaluation.
ROBOT POSITION KINEMATICS: rotation matrix, transformation matrix, application to mechanisms and robots, Denavit-Hartenberg notation, forward kinematic problem, inverse kinematic problem, closed-form solution and numerical iterative solution
ROBOT DIFFERENTIAL KINEMATICS AND DYNAMICS: relative velocity method, Jacobian matrix computation, kinematic singularity, relative acceleration method, inverse dynamic problem.
ROBOT MOTION PLANNING AND PROGRAMMING: motion planning in Cartesian-space and joint-space, self-learning programming, off-line programming and V+ language programming.
LABORATORY: sample of high-level robotic task, on-line and off-line programming of serial and parallel robots.
Planned learning activities and teaching methods: Lectures developed on the blackboard.
Experimental laboratories (at a departmental research laboratory)
Seminars held by experts in the field.
Additional notes about suggested reading: All teaching material is made available by the "moodle" platform
Textbooks (and optional supplementary readings)
  • Craig, John J., Introduction to roboticsmechanics and controlJohn J. Craig. Harlow: Pearson Education Limited, 2014. Cerca nel catalogo

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Laboratory
  • Problem based learning
  • Case study
  • Problem solving
  • Use of online videos

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)
  • Matlab

Sustainable Development Goals (SDGs)
Industry, Innovation and Infrastructure