Comment by AlotOfReading
3 days ago
In my domain, I see lots of people reaching immediately for "AI" techniques to solve sensor fusion and state estimation problems where a traditional Kalman filter type solution would be faster and much more interpretable.
Incidentally, I worked on the exact same thing - Kalman filtering for tracking objects in hard real-time systems. And it is not quite as simple as one would think - developing mathematical models for all kinds of different objects that one might wanna track is far from trivial, and it was difficult to model the real-world with more or less simplistic discrete equations. And it didn't work completely reliably so we needed an extra layer of confidence - I don't remember what we used back then but it was yet another algorithm with yet another source of data.
There's a lot of situations where you genuinely need more sophisticated algorithms. I'm talking about people reaching for those kinds of things before they determine the traditional algorithms won't work.
Sigma point filters ? The escalation ladder is usually KF, EKF, unscented KF, sigma point ...
I believe it was random forest that we combined with EKF.