In order to solve the problem that the vision sensor performance degrades in dim or low-texture environment, which leads to the failure of mapping and localization for mobile robots, a method of simultaneous localization and mapping (SLAM) algorithm based on infrared enhanced vision/laser radar/inertial combination is proposed. The image fusion method based on two-dimensional discrete wavelet transform is used to realize the feature-level fusion of visible image and infrared image, so as to improve the correlation effect between the front-end feature points of the visual inertial SLAM algorithm and the three-dimensional point cloud data of the laser radar inertial SLAM, avoid matching too many irrelevant features, and reduce the computational complexity and storage space requirements. The experimental results show that the proposed algorithm is superior to the original algorithm in terms of robustness and accuracy in dim and low-texture environments.