Comment by jongraehl

I like particle filtering because it's easy to understand and implement - https://en.wikipedia.org/wiki/Monte_Carlo_localization - and it's correct even for non-gaussian uncertainty.

Is Kalman filtering computationally more efficient (obviously particle filtering is stochastic and so trades off accuracy for compute) or does it have some other advantage?