 In fact, any particle filter algorithm may accidentally discard all particles near the correct state during the resampling step.One way to mitigate this issue is to randomly add extra particles on every iteration.This is equivalent to assuming that, at any point in time, the robot has some small probability of being kidnapped to a random position in the map, thus causing a fraction of random states in the motion model.