In　dense　3D　SLAM　(simultaneous　localization　and　mapping),　the　use　of　RGB-D　data　to　realize　SLAM　has　become　more　widespread.　In　this　paper,　PRKF　(the　precise　and　robust　KinectFusion)　is　proposed.　On　the　basis　of　KinectFusion,　the　graph　optimization　based　on　g2o　(general　graph　optimization)　is　added　to　the　PRKF.　In　the　g2o　optimization　policy,　in　order　to　achieve　the　rapid　optimization　of　error　accumulation,　this　paper　proposes　a　model　based　on　the　registration　model　for　model　loop　optimization.　The　Kinect　sensor　is　carried　by　the　Pioeer3-DX　to　establish　the　map　of　LAB　in　real　time.　In　addition,　public　data　sets　FR1　is　used　to　compare　KinectFusion　with　the　PRKF　in　this　paper.　The　experiments　have　proved　that　the　algorithm　is　robust　and　has　high　precision.　©　2016　IEEE.