Module 06-30227 (2022)

Artificial Intelligence is concerned with the design and use of computer systems to understand and mimic human-level decision making. These systems represent, reason with, and learn from, different descriptions of knowledge and uncertainty. In this module we will address these issues in the context of intelligent mobile robots. The lectures will teach theories of perception, estimation, prediction, decision- making, learning and control, all from the perspective of robotics. In the laboratory sessions students will implement some of these theories on simulated or real robots to see how theory can be applied in practice.

• Demonstrate an understanding of algorithms for perception, reasoning and control
• Implement some of these algorithms to generate intelligent behaviour on a robot
• Describe and analyse the performance of algorithms, system components and complete robot systems using appropriate methods
• Design, execute and write up appropriate experiments and use their results to inform robot design

• There is a limited number of places determined by the number of robot platforms available. This will be determined each September in combination with Intelligent Robotics (Extended). Students who have either module as COMPULSORY have, by definition, priority. The Module leader will then assess and allocate any remaining spaces to students who have chosen either module as an OPTION.
• This module expects students to be proficient in linear algebra, calculus, probability theory, and statistics. A high level of proficiency is also expected in object oriented programming and in using (e.g., installing and debugging software packages, programming in) the Linux operating system. This module is time-intensive.

• Main Assessments: Continuous assessment (100%)
• Supplementary Assessments: Continuous assessment (100%) over the Summer period