The mapping inconsistency and particle degradation problems occur in Rao-Blackwellized particle filter algorithm are studied. On the basis of Rao-Blackwellized particle filter

the sampling is concentrated on the possible areas of the observed information

so that the sampled particles are more fit to the real environment state;and the layered resampling optimization strategy is introduced to maintain as many diversity of particles as possible by controlling the threshold. The problem of particle degradation is effectively solved. Finally

the experimental verification is carried out on the Bulldog mobile robot platform equipped with a 16-line lidar sensor. The results show that the optimized algorithm reduces the number of particles

increases particle diversity

and creates a consistent environmental map.