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This is a very nice breakdown of Kalman Filtering. One slight correction - Kalman Filtering is one approach to solving the SLAM problem, but SLAM doesn’t require a KF. A particle filter, for example, can be used to solve the SLAM problem.

For anyone interested in further resources to better understand the intuition behind KFs, I’ve found this resource incredibly valuable (although a little pricey): https://www.amazon.com/Kalman-Filter-Beginners-MATLAB-Exampl...



Another absolutely fantastic resource is this Jupyter Notebook based textbook on Kalman Filters and related topics: https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Pyt...

An addition to your correction: there are many other ways to solve the SLAM problem beyond (kalman/information/particle) filters. Optimization based approaches are very popular (search terms: Graph SLAM, Factor Graphs, Pose Graphs).


True! I don’t find too many people out there who know about this stuff. Any interest in trading battle stories through DM? Would be interested to know what you’re working on and where you’ve been!


Good point, I'll update the article to reflect that Kalman is not the only approach to solve SLAM.




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