 Each particle contains a state, and can thus be considered a hypothesis of the robot's state.Regions in the state space with many particles correspond to a greater probability that the robot will be there—and regions with few particles are unlikely to be where the robot is.The algorithm assumes the Markov property that the current state's probability distribution depends only on the previous state (and not any ones before that), i.e., formula_8 depends "only" on formula_9.