The traditional particle filtering simultaneous localization and mapping（ SLAM） algorithm in the construction of mapping and autonomous positioning

usually need large number of particles and take up a lot of memory

particles appear deprivation after the resampling process

in order to improve the efficiency of robot autonomous positioning

aiming at particle filtering algorithm

propose an improved resampling strategy and particle update strategy

fuse system model. By testing the algorithm on a mobile robot equipped with robot operating system（ ROS）

the algorithm is validated by experimental method. The experimental results show that the method can improve the efficiency of particle filtering positioning.