Patrik Gustavsson
Associate Senior Lecturer in Production Engineering
School of Engineering Science
Autonomous Systems A1F
Course, Master's (2nd cycle),
6 credits,
VP718A
Application
Choose a course instance to see course syllabus and admission requirements.
Autumn 2024, Location: Skövde, Pace of study: 40%
Application
Application is done after nomination.
Course syllabus, with reading list
When? Where? How?
Study period: 4 November 2024 - 19 January 2025
Location: Skövde, Campus, Daytime
Pace of study: 40%
Admission Requirements
A Bachelor’s degree equivalent to a Swedish kandidatexamen of 180 credits, within the main fields of integrated product development, production engineering, automation engineering, mechanical engineering or information technology (or the equivalent) and passed courses VP702A Computational Intelligence A1N and VP711A Virtual Intelligent Machines A1N (or the equivalent).
A further requirement is proof of skills in English equivalent of studies at upper secondary level in Sweden, known as the Swedish course English 6. This is normally demonstrated by means of an internationally recognized language test, e.g. IELTS or TOEFL.
Selection
Guaranteed admission.
Language
The courses are conducted in English.
The course addresses autonomous systems in the context of production, factory environments and automation. Autonomy can exist in varying degrees in a system subject to the problem that is expected to be solved and it can also exist at various levels within the control software of a system. With this in mind the course will cover a range of example situations, algorithms and techniques related to autonomy. These topics may include the following: the meaning and definitions of autonomy and autonomous systems, types of sensors and their uses, types of robots and how they can be made autonomous, algorithms for Path planning/navigation and optimisation, algorithms for Collision avoidance, including feedback from sensors, algorithms for factory wide autonomy, virtual development of autonomous systems, implementation strategies for autonomous systems.