An　AMR　mapping　method　is　proposed　based　on　a　high-efficiency　recursive　filtering　fusion　algorithm.　Specifically,　this　method　utilizes　the　extended　kalman　filter　to　combine　the　data　of　the　mileage　measurement　and　the　inertial　measurement　unit　with　the　lidar　calibration,　which　improves　the　accuracy　of　the　initial　attitude　value　and　solves　the　problem　of　high　computational　complexity,　poor　real-time　performance,　and　inaccurate　attitude　estimation　at　subsequent　moments.　Physical　experiments　demonstrate　the　effectiveness　and　superiority　of　the　proposed　method,　and　the　comparison　results　with　the　original　algorithm　are　given.　©　2023　IEEE.