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Lecture Notes

  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]
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