# difference between particle filter in slam and normal particle filter

I would like to ask you about what is the difference between particle filter when we use it in Slam methods and when we use it normally to correct our sensor measurement.

I mean, is there any difference in purpose or how we use this method (PF)

for example, I use a particle filter to localize my robot. Is it the same if I run PF SLAM to localize the robot or they have other uses aspect rather then localize.

• As I see it, the particle filter in localization is the same as for sensor tracking. However, the measurement likelihood $p(z|x, M)$ in localization depends on the map $M$, which is typically not the case with normal sensor fusion where it often just is $p(z|x)$. Still, nobody keeps you from adding a map or other auxiliary data to a "normal" PF. Was that your question? Jun 18 at 11:24