Further reading
These aids for further study will let you read on and dive deeper into the Monte Carlo algorithm and its quirks:
- Probabilistic Robotics by Sebastian Thrun, Wolfram Burgard, and Dieter Fox, published by MIT Press, covers the Monte Carlo particle filter, along with the Kalman filter and other probability-based models in far more depth.
- I strongly recommend the Khan Academy material on modeling data distributions for learning and practicing data distributions.
- A playlist of 21 videos from Bonn University and Cyrill Stachniss at https://www.youtube.com/playlist?list=PLgnQpQtFTOGQEn33QDVGJpiZLi-SlL7vA covers the topics used here in detail. I recommend them if you want to dive far deeper into this topic.
