Robotics, 7.5 credits

Main field of study with advanced study

Bachelor of Science degree (or equivalent) in an engineering subject or in computer science. Courses in computer science, computer engineering or electrical engineering of at least 90 credits, including thesis. Courses in mathematics of at least 30 credits or courses including calculus, linear algebra and transform methods and Intelligent Vehicles 7.5 credits. Exemption of the requirement in Swedish is granted. English 6.

The course is included as an elective course in the Master's Programme in Embedded and Intelligent Systems 120 credits and in the program Computer Science and Engineering, 300 credits. The course is also offered as a freestanding course.

The goal of the course is for students to gain knowledge on how to design and control an autonomous mobile robot. This includes: mechanical design, sensor selection for measuring internal state of robot and sensors for acquire information from the robot’s environment, selection of navigation and control strategies for solving a predefined task autonomously.

Upon completion of the course the student shall be able to:

Knowledge and understanding

• Explain different methods for global and local path-planning works and when different methods are appropriate.
• Describe how motion control of a mobile robot is done by using a kinematic model.
• Explain how low-level control of actuators is done using positionand speed and acceleration profiles.

Skills and ability

• Design and implement an autonomous robot,including mechanics, computersoftware and hardware.
• Design and implement a complete navigation system including perception, localization, path-planning and motion control.

Judgement and approach

• Judge whether a particular solution is appropriate for a given task, and suggest alternative solutions if appropriate, both on system and sub-system level.

The lectures present different methods for design and control of an autonomous mobile robots; techniques for path-planning and motion control (kinematic model, control of position, velocity and acceleration); perception (cameras, range sensors, encoders); obstacle avoidance strategies; navigation architectures.

Lectures introduce concepts and methods, simulator based exercises serve to deepening the understanding of theory and develop practical skills needed for the project. An evaluated team-based project completes the practical part of the course. Project implementations will run on a real robot and shall solve apredefined task.

Som electures are given, but the major part of theteaching is laboratory exercisesand projectwork including supervision.

The students working group of 2 or 3 students per project.

The requirement to pass this course is to present the project and show that the robot solves the predefined task autonomously and presenting code (grade 3).

To get grade 4 the additional requirements are to participate with a working robot in the final contest, pass all exercise examinations or hand in a written report that describes the complete robotic system.

To get grade 5 the additional requirements are to pass all exercise examinations and hand in a written report that describes the complete robotic system.

If there are special reasons, the examiner may make exceptions from the specified examination format and allow a student to be examined in another way. Special reasons can e.g. be study support for students with disabilities.

Course evaluation is part of the course. This evaluation offers guidance in the future development and planning of the course. Course evaluation is documented and made available to the students.