Abstract: Laser and inertial measurement unit (IMU) fusion is a hot research direction in multi-sensor fusion SLAM (simultaneous localization and mapping) for mobile robots. In view of the advantages and disadvantages of different current coupling methods, a double-coupled laser and IMU fusion SLAM method is proposed. Factor maps were used to achieve a back-end tight coupling. At the same time, extended Kalman filtering was used to loosely coupled the laser odometry and IMU prediction results. The problem of poor scalability and low robustness of tight coupling was improved, as well as the accuracy of loosely coupled pose estimation. The algorithm was validated on the KITTI dataset. The experimental results show that the algorithm effectively improves the mobile robot’s positioning accuracy and robustness.