For　an　accurate　position　and　orientation　estimation　of　Lunar　Rover,　a　method　of　SLAM　based　on　Rao-Blackwellised　Particle　Filter　is　introduced　in　this　article.　In　this　approach　environment　measurements　obtained　by　high　speed　Laser　Range　Finder　is　aligned　with　the　constructed　grid　map.　As　the　position　estimation　by　SLAM　based　on　particle　filter　is　hard　to　eliminate　the　error　accumulated　in　traveling,　we　proposed　an　estimation　method　for　translation　velocity　of　Lunar　Rover,　which　is　validated　by　simulation　experiments.　To　improve　real-time　performance,　we　propose　that　all　the　particles　maintain　a　common　map.　Simulation　experiment　reveals　that　this　map　management　method　does　not　degenerate　filter　effect　while　dramatically　enhancing　its　real-time　performance.