Intelligent RoboticsLaajuus (5 cr)

Objective

After passing the course successfully, the students will be aware of Intelligence in robotics and its relation to industrial automation and feedback systems. In feedback systems, including robots, data is collected, analysed, and applied using machine learning and automatic control decision tools. The course provides various examples of human skills adaptive machinery, intelligent machines, and system of systems.

Content

Historical review of automation development. Basics of automatic control to provide intelligence in robotics. Machine learning divided into supervised learning, unsupervised learning, reinforcement learning, and further deep neural networks, and fuzzy logic. Machine learning applied to intelligent robotics. Examples of intelligent machines and system of systems: Self-driving cars, intelligent mining vehicles, autonomous ships, intelligent ports, maritime technology - system of system including ships and ports.

Qualifications

Basic knowledge of electronics, linear algebra, linear systems, and the basics of Matlab.

Materials

Lecture notes, MathWork's material.

Execution methods

Lectures 24 h. Exercises 24 h, including use of MATLAB Simulink, Machine Learning, Robot Toolboxes.

Accomplishment methods

Take-home exam, and project work Grading: On scale 1-5 or fail