Particle Filter

A sequential Monte Carlo method that approximates a probability distribution with a set of weighted samples (particles). Each particle is a possible system state; particles are propagated through the dynamics model and reweighted based on measurement likelihood. Particle filters are used for robot localization (AMCL), tracking, and non-Gaussian state estimation.