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Course syllabus - Mobile Robotics

Scope

7.5 credits

Course code

ELA419

Valid from

Autumn semester 2026

Education level

Second cycle

Progressive Specialisation

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

Main area(s)

Organisation

Department of Computer Science & Engineering

Ratified

2025-12-19

Literature lists

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

Objectives

The purpose of the course is to provide fundamental knowledge on how the different typologies of mobile robots are designed and controlled to perform autonomous tasks in the different areas like field robotics, service robotics, medial robotics, bio-inspired robotics, etc. The focus on the course will be on wheeled robots.

Differently from industrial robots, localization and pose estimation is a crucial problem in mobile robotics, so methods for sensors fusion and mapping will be presented. Once the robot is localized, fundamental methods for path planning, trajectory tracking and obstacle detection/avoidance will be needed and provided by the course.

Learning outcomes

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

  1. Model a mobile robot using different kinds of kinematic structures,
  2. Describe and implement fundamental algorithms for localization and mapping,
  3. Motion planning for wheeled robots,
  4. Implement basic methods for obstacle detection and avoidance and
  5. Describe and implement fundamental algorithms for trajectory tracking.

Course content

Mobile robots' typologies, non-holonomic constraints, wheeled robot configurations, legged robots, hybrid robots, flying robots. SLAM (simultaneous localization and mapping), odometric localization, probabilistic localization, EKF (extended Kalman filtering), particle filtering. 
Path planning, obstacle avoidance fundamentals, potential fields, trajectory tracking. Roboethics.

Specific requirements

Calculus of Several Variables 7.5 credits, Robotic Systems 7.5 credits, Probability Theory and Statistical Inference 7.5 credits and Control Theory 7.5 credits or corresponding. In addition Swedish course 3 or Swedish level 3 and English course 6 or English level 2 are required. For courses given entirely in English exemption is made from the requirement in Swedish course 3 or Swedish level 3.

Examination

LAB1, Laboratory session, 1.5 credits, examines the learning outcomes 1 and 2, marks Fail (U) or Pass (G).
LAB2, Laboratory session, 1.5 credits, examines the learning outcomes 3 and 4, marks Fail (U) or Pass (G).
LAB3, Laboratory work, 1.5 credits, examines the learning outcomes 1 and 5, marks Fail (U) or Pass (G).
PRO1, Project, 3 credits, examines the learning outcomes 1-5, marks 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 overlaps 7,5 credits with ELA408 Mobile Robotics.