Lectures

2025/09/29: Intro, Sensors, Probabilities

• Introduction to the course (slides)

• Robots and Sensors (slides)

• Probability Recap (slides)

2025/09/30: Dependancy, DBN, Inference

• Bayesian Networks (slides)

• Dynamic Bayesian Networks and Inference (slides)

2025/10/06: Gaussian Distribution + Exercise

• Gaussian Distribution (slides)

• Exercise (pdf)

2025/10/07: [Exercise] Discrete Localization

• Grid Orazio Localization (slides)(source)

• Grid Orazio Localization w/ Orientation (slides)(source)

2025/10/13: Kalman Filters

• (E)KF (slides) 

• Exercises on filtering (notes)

  • methodology

  • various examples

  • unycicle model

2025/10/14: EKF Localization

• Localizing in a landmark world (slides)(source)(solution)

2025/10/20: EKF Localization + SLAM

• Localizing bearing only (slides)(source)(solution)

• SLAM with EKF (slides)(source)

• 2025/10/21: Data Association

• Handling Unknown Correspondences (slides)