1. The scientific method
2. Hypothesis testing
3. Classification and maximum likelihood learning
4. Simple Sensor Models
5. Validating learning methods (Slides)
6. Lego Engineering introduction. Lego Structures and Gears (note: taken from Wellesley College.) Also see the course notes from MIT's course 6.270.
7. Control Theory 1
8. Control Theory 2
9. Robot Control Architectures
10. Decision Making 1 (Slides)
11. Bandit Algorithms Continued: UCB1
12. Markov Decision Processes
13. Localisation
14. LIDAR Naive Bayes code
15. LIDAR Feature Extraction
16. LIDAR Feature Extraction 2
17. Scan Alignment

These are the lecture notes from the 2009 course year. They are in powerpoint.

• Introduction (note that the project illustrated in this slide is from previous years)
• Shakey: initial planning approaches
• Behaviour Based Robotics
• Signal Processing
• Control Theory 1
• Control Theory 2
• Navigation
• Robot Learning
• Robot Mapping

These are the notes for guest lectures. They are in various formats.

• (2009) D.J.Duff: Scientific Methods & Mobile Robots [slides:odp] [handout:odp]