Official course description, subject to change:

Basic info last published 15/03-24
Course info
Language:
English
ECTS points:
15.0
Course code:
KSADROB1KU
Participants max:
33
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price for EU/EEA citizens (Single Subject):
21250 DKK
Programme
Level:
MSc. Master
Programme:
MSc in Computer Science
Staff
Course manager
Professor, Head of the PhD School
Teacher
Postdoc
Course semester
Semester
Efterår 2024
Start
26 August 2024
End
24 January 2025
Exam
Abstract

This course introduces students to the broad field of robotics predominately from an artificial intelligence perspective.

Description

This course is the last course in the robot specialization. The course provides an introduction to robotics and starts by answering general questions such as what a robot is, their origins, types, and applications. It then introduces the key approaches to robot control and explores the pros and cons of each.  The course finally covers the advanced topics of robot learning and bio-inspired robots in addition to current robot research topics at ITU. In addition to the theory, the course also has a significant practical, hands-on dimension that comprises introduction to relevant software tools (simulators and operating systems) and hands-on experiments with simulated and physical robots.


Formal prerequisites

Robotics is interdisciplinary by nature and research topics range from fundamental modelling of robot physics over programming and design all the way to ethical and philosophical questions. Hence, students with highly diverse backgrounds are welcome on this course. However, the course as taught at ITU has its root in Computer Science and will be taught predominately from this perspective. Hence, it is required that the student has basic programming skills (e.g. obtained from an introduction to programming course). Although not required, it is also recommended and useful to have taken the sister course:"How to build almost anything" which largely covers how robots are built. The course also includes some machine learning hence knowledge in this area is also useful, but not mandatory.

Intended learning outcomes

After the course, the student should be able to:

  • Describe what a robot is, their origin, types, and applications
  • Describe, compare, and apply robot control stategies
  • Apply robot software tools (simulation, operating systems)
  • Apply bio-inspired solutions and machine learning appropriately in robotics
  • Formulate and reflect on robot solutions to real-world problems
Ordinary exam
Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.