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)(solution)

2025/10/21: Data Association

• Handling Unknown Correspondences (slides)

2025/10/27: EKF SLAM with unknown Association

• EKF SLAM with Unknown Correspondences (slides)(source)

• Unscented Transform (slides)

2025/10/28: Unscented Transform and Autodiff

• UKF Localization (slides)(source)

• Autodiff (slides)(source)

2025/11/03: Particles and Neighbors

• Particle Distributions and Particle Filters (slides)

• Finding Neighbors (slides)(source)

2025/11/04: Particle Localization

• Localization with Particle Filters [exercise] (slides)(source)(solution)

2025/11/10: Least Squares

• Least Squares Intro (slides)(source)

• Uncertainty in Least Squares (slides)

2025/11/17: Filtering Wrapup

• Blackboard Exercises on

  •  bearing localization

    •  w/wo initial guess

    • w/wo DA

  • bearing SLAM  w/wo DA

  • role of initializers

• Odometry Calibration (slides)(source)

• ICP Registration and Linear Relaxation (slides) (icp_source)(lin_rel_source)

2024/11/18: Iterative Reweighed Least Squares on a Manifold

• Robustifiers (slides)

• Manifolds (slides)