This　paper　presents　an　effective　Simultaneous　Localization　and　Map　Building　(SLAM)　technique　for　indoor　mobile　robot　navigation　based　on　OpenMP.　Particle　Filter　(PF)　based　SLAM　provides　an　effective　indoor　mobile　robot　navigation　framework,　but　real-time　performance　of　PF　needs　improving　due　to　their　inherent　complex　and　intensive　computation.　OpenMP　is　the　product　of　the　multi-core　technology　development　and　has　been　widely　accepted　by　both　industry　and　academia.　We　propose　a　multi-thread　particles　filter　algorithm　based　on　OpenMP　to　reduce　computation　time　of　PF　and　execution　time　of　SLAM.　The　results　in　real　experiments　and　simulations　show　that　the　parallel　PF-SLAM　algorithm　based　on　OpenMP　could　reduce　the　SLAM　execution　time　while　guaranteeing　the　accuracy　of　SLAM.