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Course syllabus - Design of Autonomous Systems

Scope

7.5 credits

Course code

DVA485

Valid from

Autumn semester 2020

Education level

Second cycle

Progressive Specialisation

A1F (Second cycle, has second-cycle course/s as entry requirements)

Main area(s)

Computer Science

Organisation

School of Innovation, Design and Engineering

Ratified

2020-01-24

Literature lists

Course literature is preliminary up to 8 weeks before course start. Course literature can be valid over several semesters.

    • Ratified date: 2020-11-20
    • Latest update: 2025-05-27

    Books

    Thrun, Sebastian; Burgard, Wolfram; Fox, Dieter

    Probabilistic robotics

    Chapter 3

    ISBN: 0262201623

    LIBRIS-ID: 10196274

    Cambridge, Mass., MIT Press, xx, 647 s.

    Articles

    AutoRIO: An Indoor Testbed for Developing Autonomous Vehicles

    International Japan-Africa Conference on Electronics, Communications and Computations (JAC-ECC),

    Web Addresses

    Deep Learning

    URL: Link

    MIT Press,

Objectives

The aim with the course is to give the students ability to control dependability for autonomous systems built with essential building blocks such as data fusion, computer vision, and artificial intelligence for perception and decision making.

Learning outcomes

After completing the course, the student shall be able to:

  1. explain guidance strategies for autonomous vehicles
  2. summarize the theory behind and the implementation of sensing and perception of autonomous vehicles
  3. exemplify how data fusion of different sensor data can be applied
  4. compare possible architectures for autonomous systems with long response times
  5. program heterogeneous embedded systems for autonomous applications, and
  6. discuss methods for analysis and verification of autonomous systems

Course content

Data fusion and computer vision, Artificial intelligence for perception and decision making, Redundancy techniques for reliability and fail-safe designs for autonomous systems, Heterogeneous sensing and computing systems, and energy management.

Specific requirements

At least 160 credits of which at least 30 credits computer science, and/or 30 credits in electronics, and Autonomous vehicles 5 credits or equivalent.

In addition, Swedish course B/Swedish course 3 and English course A/English course 6 are required. For courses given entirely in English, exemption is made from the requirement in Swedish course B/Swedish course 3.

Examination

Laboratory work (LAB1), 3 credits, examines the learning objectives 2, 3, 4 and 5, marks Fail (U) or Pass (G)
Project (PRO1), 3 credits, examines the learning objectives 1-6, marks Fail (U), 3, 4 or 5
Written assignment (INL1), 1,5 credits, examines the learning objectives 1 and 6, marks Fail (U), 3, 4 or 5

A student who has a certificate from MDU regarding disability study support, can request adaptions for the examination. It is the examiner who takes decisions on any adaptions, based on the certificate and other conditions.

Grade

Grading scale: 5, 4, 3

Interim Regulations and Other Regulations

The course completely overlaps with DVA472 Design of autonomous systems.

The course can be included in the technology field for dependable systems.