You need to activate javascript for this site.
Menu Conteúdo Rodapé
  1. Home
  2. Courses
  3. Electrical and Computer Engineering
  4. Industrial Robotics

Industrial Robotics

Code 15396
Year 2
Semester S1
ECTS Credits 6
Workload PL(15H)/T(30H)/TP(15H)
Scientific area Informatics, Automation and Control
Entry requirements Not applicable.
Mode of delivery Face-to-face
Work placements Not applicable
Learning outcomes This Course Unit aims to make an introduction to the study of the multidisciplinary field of Industrial Robotics, featuring the various functional subsystems that make up a robot in an individualized and integrated way, as well as topics of robotic manipulation and navigation through path planning.
At the end of the course unit the student should be able to:
- Identify different types of robots with respect to its anatomy and actuators, as well as to discuss the operation and/or development of robotic applications;
- Apply the equations and calculation techniques for determining the Cartesian position as well as the position and angle of the prismatic and rotational joints of a robot.
- Identify the basic characteristics of locomotion for mobile robots;
- Describe the main types of sensors used in robotics;
- Implement algorithms for trajectory planning/paths in mobile robot navigation;
- Apply the knowledge to construct a robot, being also able to work in team.
Syllabus 1. Introduction to robotics
2. Types of robots: robots anatomy and actuators. Introduction on computer-controlled robotic manipulators and examples
3. Position and motion of robotic manipulators: Coordinate frames and transformations
4. Forward kinematics, the Denavit-Hartenberg convention
5. Inverse kinematics
6. The Jacobian, singularities
7. Motion and path planning
8. Robotic manipulators dynamics
9. Control and programming
Special topics:
10. Sensors and actuators
11. Mobile agents, SLAM
12. Computer vision
13. MEMS, microrobotics
14. Medical/Surgical robotics, teleoperation
15. Biomimetic systems
16. Intelligent robotics. Concepts of artificial intelligence and intelligent systems
17. Fuzzy logic. Fuzzy control, fuzzy logic controllers
18. Artificial Neural Networks: Models and architecture of artificial neural networks. Learning in robotics
Main Bibliography 1. Primary:
- "Apontamentos de Robótica Industrial", Pedro Dinis Gaspar. Universidade da Beira Interior, 2011.
- "Robot Modeling and Control", Mark W. Spong, Seth Hutchinson, M. Vidyasagar. Wiley, John & Sons Inc., 2005. ISBN: 0-471-64990-2.
- "Introduction to Robotics", Philip John McKerrow. Addison-Wesley, 1991. ISBN: 0-20-118240-8.
- "Robot Technology Fundamentals", James G Keramas. Delmar Learning, 1998. ISBN: 0-8273-8236-7.

2. Secondary:
- "Introduction to Robotics: Mechanics and Control", John J. Craig, Addison-Wesley, 1986. ISBN: 0-20-154361-3.
- "Robotics for Engineers", Yoram Koren, McGraw-Hill, 1986. ISBN: 0-07-035399-9.
- "Modelling and Control of Robot Manipulators", Series: Advanced Textbooks in Control and Signal Processing Sciavicco, Lorenzo, Siciliano, Bruno Springer-Verlag London Berlin Heidelberg, 2nd ed. 2000. ISBN: 1-85233-221-2.
- "Robot Manipulators: Mathematics, Programming and Control", Paul, R.P., MIT Press, Cambridge, 1981.
Teaching Methodologies and Assessment Criteria The teaching/learning activities for the contents seizure regarding skills to be acquired are distributed along: theoretical, theoretical-practical and laboratory lectures.
Teaching methodologies:
- Theoretical exposure of course contents;
- Theoretical-practical lectures for problem solving in the various topics covered in the syllabus, making some use of computers using specific software, and in the context of group work;
- laboratory classes for application of concepts and of acquired knowledge as well as developing new skills in group work context;
- Development of synthesis works related to topics addressed in the course unit.

Assessment methods and criteria:
SW (15%): Development of a literature synthesis work
EX (15%): Exercises.
LAB (35%): Laboratory: Programming/control/simulation of robotic arms
TEST (35%): Exam of knowledge assessment

Final mark = SW + EX + LAB + TEST
Language Portuguese. Tutorial support is available in English.
Last updated on: 2023-10-11

The cookies used in this website do not collect personal information that helps to identify you. By continuing you agree to the cookie policy.