Aiming at the problem of low locationing accuracy and incomplete mapping in simultaneous localization and mapping(SLAM) using single sensor of mobile robot, a SLAM algorithm based on the information fusion of Kinect vision sensor and laser sensor was proposed. Firstly, the depth image from Kinect sensor are converted to a 3D point cloud through the coordinate system conversion, and the height information of the 3D point cloud is filtered by vertical limit filter. Then the remaining 3D point cloud is projected to the horizontal plane and the boundary point cloud information are extracted to convert into the laser scan data. After that the converted laser scan data fused with the scan data from laser sensor at the data-level. Finally, output unified data to realizing the mapping and autonomous navigation of mobile robot. The experimental results show that this method can accurately detect small and complex features obstacles, create accurately and fully environment map, and also better complete the task of the mobile robot autonomous navigation.