Multi-Sensor Fusion for LiDAR SLAM: A Survey of Development

Simultaneous Localization and Mapping (SLAM) has become a cornerstone technology for Autonomous control of unmanned vehicles. However, single-sensor SLAM systems often struggle to meet the demands of high-precision and robust perception in complex environments. This survey provides a comprehensive review of recent developments in multi-sensor fusion SLAM. We analyze the core framework and key research directions such as Visual SLAM, Lidar SLAM and Multi-sensor fusion SLAM. In addition, we highlight major datasets and evaluation metrics that have driven benchmarking efforts in the community. Finally, we identify existing challenges in dynamic environments, computational efficiency, and large-scale deployment, and outline future trends for advancing SLAM towards greater autonomy, robustness, and intelligence.