In　degeneration　circumstance　such　as　corridor,　due　to　lacking　environmental　features,　the　traditional　laser　SLAM　cannot　locate　the　position　of　the　mobile　robot　precisely　during　the　scan　matching,　and　further　lead　the　mapping　does　not　confirm　to　the　reality.　Aim　at　this　problem,　this　paper　proposes　an　improved　Hector　SLAM　algorithm　based　on　information　fusion　for　mobile　robot.　Odometry　can　accurately　reflect　the　distance　of　robot　movement　and　Inertial　Measurement　Unit　(IMU)　can　exactly　show　the　angle　of　robot　movement.　So　an　improved　SLAM　algorithm　framework　is　set　up.　In　the　process　of　information　collection　and　handling,　based　on　extending　Kalman　Filtering　(EKF)　fusing　the　information　of　odometry,　IMU　and　laser　scanning,　to　raise　the　accuracy　of　the　change　of　point　cloud　to　provide　precise　input　information　for　scan　matching　process.　In　the　scanning　matching　process,　Hector　SLAM　algorithm　is　used　to　project　the　scan　information　onto　grid　map.　In　the　last,　according　to　the　proposed　method,　the　algorithm　function　packages　are　written　under　the　Robot　Operating　System　(ROS).　The　effectiveness　of　the　method　is　verified　by　simulation　experiment　and　robot　platform　physics　experiments.　©　2018　IEEE.