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Introduction to Robotics Course

The Introduction to Robotics course, DD2410, is a 7.5-credit course that provides a wide introduction to robotics. It covers the mechanics of mobile robots and manipulators, robot hardware and software, and algorithms and methods for kinematics, control, navigation, and planning.

Course Description

This course serves to give a general understanding of robotics as a field of study and provides a foundation for further studies of the different included topics in greater depth in other, more specialized courses. The course consists of lectures, lab assignments, and a wide selection of reading materials.

Examination and Grading

The course is examined with assignments and a larger project (LAB1), and a written exam (TEN1). The final grade is determined by the performance on the practical assignments, LAB1, while the exam TEN1 is pass/fail.

Recommended Prerequisites

Recommended prerequisites are basic skills in linear algebra, multivariate calculus, control theory, and programming (Python), equivalent to the KTH courses SF1624, SF1626, EL1110, and DD1343.

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

• Course location: KTH Campus
• Duration: 24 Aug 2026 - 23 Oct 2026
• Periods: Autumn 2026: P1 (7.5 hp)
• Pace of study: 50%
• Application code: 11243
• Form of study: Normal Daytime
• Language of instruction: English
• Target group: Searchable for all programmes from year 3 and for students admitted to a master's programme, as long as it can be included in your programme.

Part of Programme

This course is part of the following programmes:

• Master's Programme, Computer Science, year 1, CSCS
• Master's Programme, ICT Innovation, year 1, AUSY, Mandatory
• Master's Programme, ICT Innovation, year 1, AUSM, Mandatory
• Master's Programme, Industrial Engineering and Management, year 1, MAIG
• Master's Programme, Computer Science, year 2, CSCS
• Master's Programme, Machine Learning, year 2
• Master's Programme, Machine Learning, year 1
• Master's Programme, Systems, Control and Robotics, year 1, Mandatory

Course Syllabus

The course syllabus is available as a PDF.

Content and Learning Outcomes

Course Contents

• Kinematics and dynamics for mobile and articulated robots
• Description models applicable for robot system, such as Denavit-Hartenberg notation, homogeneous transforms, etc.
• Sensors, actuators, and other robot hardware
• Algorithms for calculation of inverse kinematics, robot dynamics, trajectories, and planning
• Software architectures for robot systems and simulators

Intended Learning Outcomes

After completing the course with a passing grade, the student should be able to:

• Use basic theoretical tools from robotics to describe and calculate kinematics and dynamics for robot systems with several degrees of freedom
• Account for and apply algorithms to generate path plans
• Account for and apply algorithms for high-level task switching
• Account for and apply algorithms for mapping
• Account for different methods for exteroceptive sensors as well as navigation and localization
• Use modern software architectures for development of robot applications
• Summarize the included subject areas in robotics
• Account for different types of hardware and software that are used in robot systems

Literature and Preparations

Specific Prerequisites

• Knowledge in linear algebra, 7.5 credits, equivalent to completed course SF1624/SF1672/SF1684
• Knowledge in multivariable calculus, 7.5 credits, equivalent to completed course SF1626/SF1674
• Knowledge and skills in programming, 6 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/DD100N/ID1018
• Knowledge in basic computer science, 6 credits, equivalent to completed course DD1338/DD1320-DD1328/DD2325/ID1020/ID1021
• And at least one of the following:
  • Knowledge in automatic control, 6 credits, equivalent to completed course EL1000/EL1010/EL1110/EL1120
  • Knowledge of mechanics, 6 credits, equivalent to completed course SG1120/SG1130/SG1132
  • Additional skills in independent software development, 12 credits, from completed courses in computer science, computer technology, or numerical methods with laboratory elements that are not carried out in groups larger than two people

Recommended Prerequisites

Basic knowledge of linear algebra, multivariable calculus, automatic control, and programming corresponding to the courses SF1624, SF1626, EL1020, and DD1310.

Examination and Completion

Grading Scale

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

Examination

• TEN1 - Written examination, 2.5 credits, grading scale: P, F
• LAB1 - Laboratory assignments, 5.0 credits, grading scale: A, B, C, D, E, FX, F

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.