Probabilistic Robotics — Thrun, Burgard & Fox

Sebastian Thrun, Wolfram Burgard, Dieter Fox (MIT Press)

The standard text for probabilistic state estimation in robotics: Bayes filters, Kalman filters (EKF, UKF), particle filters, occupancy grid mapping, simultaneous localization and mapping (SLAM), robot motion models, and sensor models.

Referenced in Course 1 (Week 1 — rigid-body transforms appendix; Week 15 — Bayes filter, Kalman filter, IMU motion and sensor models) and Course 2 (Week 7 — motion models for traffic agents, abbreviated PR).

Chapters

Exercises added as I work through each chapter.