[moffkalast]

Yeah, I try to err on the side of not using them unless the accuracy obtained through more robust methods is just a no-go, because there are so many ways they can suddenly and irrecoverably fail if some sensor randomly produces something weird that wasn't accounted for. Which happens all the time in practice.

[alex_be]

It is always a good idea to include outliers treatment in KF algorithm to filter out weird measurements.

[moffkalast]

Ah but then you just move the error case to outlier detection.

[alex_be]

True. It's about managing the risk rather than eliminating it. If you remove an outlier, you get a missing measurement and, as a result, higher uncertainty (error). But it is still better than keeping the outlier.