Exercise Solutions and implementation (Python & C++) for the book Probabilistic Robotics

(This is an ongoing work.)

Content

1. Perception

• Chapter 3 Gaussian Filters: Kalman Filter, Extended Kalman Filter (in Python).

• Chapter 4 Nonparameteric Filters: Histgram and Particle Filters (in Python).

• Chapter 5 Motion models (on-going).

• Chapter 6 Measurement models.

• Chapter 7 Localization: Markov and Gaussian

• Chapter 8 Localization: Grid and Monte Carlo

• Chapter 9 Occupancy Grid Mapping

• Chapter 10 EKF-SLAM; EKF-SLAM with Unknown Correspondence

• Chapter 11 GraphSLAM

• Chapter 12 (Skipped for now)

• Chapter 13 FastSLAM

2. Planning

To be continued ...