Official course description:

Full info last published 17/05-21
Course info
ECTS points:
Course code:
Participants max:
Offered to guest students:
Offered to exchange students:
Offered as a single subject:
Price for EU/EEA citizens (Single Subject):
21250 DKK
MSc. Master
MSc in Computer Science
Course manager
Full Professor
Research Assistant
PhD student
Course semester
Efterår 2021
30 August 2021
31 January 2022
Exam type
ekstern censur
Grade Scale
Exam Language

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


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
Learning activities

The learning activities will be tailored such that there is a suitable balance between obtaining knowledge, applying it, and reflecting on the knowledge. Hence, the learning activities changes between lectures, small exercises, guided introductions to tools and robots, and larger report to allow for deeper reflection of the learned material.

Mandatory activities

The students have to get two mandatory reports approved to attend the exam. The reports will be based on mini-projects made in small groups and will typically cover design, implementation, and experimentation with simulated or physical robots.

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

The course literature is published in the course page in LearnIT.

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 15%
  • Lectures: 15%
  • Exercises: 15%
  • Assignments: 15%
  • Project work, supervision included: 35%
  • Exam with preparation: 5%
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.
Exam submission description:
The final project and the resulting exam report will be made in the context of a robot competition. The exam report will describe the group's robotic solution, document the developed robotic solution using experimetal data, and finally reflect on the solution based on the theoretical material of the course.
Group submission:
  • Group size: 1- 4 students, preferably 3.
Exam duration per student for the oral exam:
20 minutes
Group exam form:
Individual exam : Individual student presentation followed by an individual dialogue. The student is examined while the rest of the group is outside the room.

Time and date