To　reduce　the　interference　of　dynamic　environment　on　the　pose　estimation　of　vision　simultaneous　localization　and　mapping(SLAM),　a　method　to　combine　object　detection　network　with　ORB-SLAM2　system　was　proposed.　In　the　inter　frame　motion　estimation　stage,　the　bounding　box　of　potential　movable　objects　was　obtained　by　using　object　detection　network　to　acquire　the　semantic　information　of　the　current　frame.　Combined　with　the　depth　image　and　according　to　the　maximum　between-class　variance　algorithm,　the　foreground　in　the　bounding　box　was　segmented,　the　dynamic　feature　points　in　the　foreground　were　deleted,　and　the　remaining　feature　points　were　used　to　estimate　the　pose.　In　the　loop　closure　detection　stage,　the　bounding　box　was　used　to　construct　image　semantic　features,　and　query　similar　key　frames　compared　with　historical　frames.　Compared　with　Bag　of　Visual　Word,　the　method　has　faster　query　speed　and　less　memory　consumption.　The　method　on　TUM　dataset　was　evaluated,　and　the　results　show　that　the　proposed　method　can　effectively　improve　the　performance　of　ORB-SLAM2　in　high　dynamic　scene.　©　2022,　Editorial　Department　of　Journal　of　Beijing　University　of　Technology.　All　right　reserved.