Program Overview

Course Overview

The course DD2413 Social Robotics provides an overview of the state-of-the-art algorithms, computational techniques, and paradigms used to build robots that interact with people.

Information per Course Offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Information for Autumn 2026 Start

• Course location: KTH Campus
• Duration: 26 Oct 2026 - 11 Jan 2027
• Periods: Autumn 2026: P2 (7.5 hp)
• Pace of study: 50%
• Application code: 11245
• Form of study: Normal Daytime
• Language of instruction: English
• Course memo: Not published
• Number of places: Minimum 1
• Target group: Students admitted to a master's programme, as long as it can be included in your programme.

Part of Programme

The course is part of the following programmes:

• Master's Programme, Systems, Control and Robotics, year 2, RASM
• Master's Programme, Computer Science, year 2, CSDA
• Master of Science in Engineering and in Education, year 6, TEDA
• Master's Programme, Computer Science, year 1, CSCS
• Master's Programme, Systems, Control and Robotics, year 1, RASM
• Master of Science in Engineering and in Education, year 5, TEDA
• Master's Programme, Industrial Engineering and Management, year 1, IAVN
• Master's Programme, Industrial Engineering and Management, year 1, MAIG
• Master's Programme, Computer Science, year 2, CSCS
• Master's Programme, Interactive Media Technology, year 1
• Master's Programme, Interactive Media Technology, year 2

Contact

• Examiner: Iolanda Leite
• Course coordinator: Iolanda Leite
• Teachers: Iolanda Leite

Course Syllabus

The course syllabus is available as a PDF.

Content and Learning Outcomes

Course Contents

• Introduction to the field: types of interaction, anthropomorphism and embodying, design principles of social robotics.
• Building of social robots: generic system design, software components and systems.
• The robot perception of the user: different modalities and sensor fusion.
• Verbal and non-verbal communication: dialogue, movement and animation.
• Social reasoning and decision making.
• Experiment design: how to design and carry out HRI-experiments, common measurements for HRI, annotation of data and behavioural analysis.
• Social learning.
• Cooperation between humans and robots.
• Application areas: remote-controlled robots from control to semi-autonomous, social assistent robots for education and healthcare.
• Social and ethical considerations of use in social environments.

Intended Learning Outcomes

On completion of the course, students should be able to:

• Apply different concepts within social robotics.
• Choose and justify efficient calculation methods for the ability of social robots to perceive, make decisions and move.
• Use suitable software design and tools to develop applications for social robotics.
• Design, analyse and document experiments in human-robot-interaction (HRI).
• Demonstrate understanding of the social and ethical aspects of the design, the development and the use of social robots.

Literature and Preparations

Specific Prerequisites

Knowledge in foundations of computer science, 6 credits, equivalent to completed course DD1338/DD1320-DD1327/DD2325/ID1020/ID1021.

Literature

Information about course literature can be found in the course memo for the course offering or in the course room in Canvas.

Examination and Completion

Grading Scale

A, B, C, D, E, FX, F

Examination

• LABA - Laboratory work, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• LABB - Laboratory work, 1.5 credits, grading scale: A, B, C, D, E, FX, F
• PROA - Project work, 4.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH's coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

If the course is discontinued, students may request to be examined during the following two academic years.

Examiner

Iolanda Leite

Ethical Approach

• All members of a group are responsible for the group's work.
• In any assessment, every student shall honestly disclose any help received and sources used.
• In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further Information

Course Room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas.

Offered by

EECS/Intelligent Systems

Main Field of Study

Computer Science and Engineering

Education Cycle

Second cycle

Supplementary Information

In this course, the EECS code of honor applies.