In　order　to　solve　the　problem　that　tracking　drift　and　localization　failure　caused　by　pose　estimation　error　in　orb-slam　(simultaneous　localization　and　mapping),　an　improved　orb　feature　point　extraction　algorithm　called　RFISslam(Region　Focusing　Image　Segmentation　slam)　is　proposed.　Firstly,　when　extracting　feature　points,　the　image　is　divided　into　several　areas　and　feature　points　which　to　be　extracted　is　equally　distributed　into　each　area　to　improve　the　feature　points　to　be　more　representative.　Secondly,　an　evaluation　system　is　added　to　evaluate　each　area,　and　some　areas　with　low　contrast　that　are　not　easy　to　extract　highly　identifiable　feature　points　are　excluded　to　obtain　more　robust　feature　points.　Finally,　the　experimental　results　were　verified　that　the　RFIS-slam　improves　the　feature　point　matching　by　4.1%　and　5.8%　respectively　compared　to　orb-slam　and　orb-slam2;　in　terms　of　initialization,　111　and　65.4　frames　were　improved　respectively.　Better　results　have　also　been　achieved　in　position　estimation　and　real-time　positioning,　so　as　to　improve　the　precision　of　feature　point　matching　and　positioning　without　losing　speed.