Aiming at the poor robustness that SLAM system only depends on a single sensor in weak texture environment,a robot SLAM algorithm combining vision,single-line lidar and inertia was proposed.In the pre-processing stage of vision and radar,the feature of point and line was extracted by vision,and the error equation was constructed by the distance between the laser point and its nearest two points in the matching process of radar frames,so as to achieve higher precision matching effect.Inertial sensor and wheel speed odometer were used to correct radar motion distortion,and radar estimation information provided good depth value for triangulation of monocular point-line features.Then,the precision of robot SLAM was improved by using the close coupling optimization mechanism of point-line visual information,radar point cloud information and inertial measurement unit.Finally,the method was tested in simulation environment and real weak texture environment.The results show that the positioning accuracy of this method reaches 986%,and the positioning effect in weak texture environment is robust and accurate,which meets the actual needs.