FusionGS-SLAM: Multiple Sensors Fusion for Localization and Real-Time Photorealistic Mapping

Abstract

This work presents a FusionGS-SLAM, a robust framework for simultaneous localization and real-time photorealistic mapping leveraging the power of sensor fusion techniques. To achieve this, the proposed method employs a tightly-coupled technique to effectively combine multiple factors from improved subsystems, thereby generating a robust odometry for the downstream tasks. Moreover, a dense 3D Gaussian map is constructed by leveraging geometric information across sensor modalities, with real-time mapping strategies designed to enhance robustness and rendering quality in large-scale and challenging environments. Experimental evaluation of various challenging scenes, including the public and self-collected datasets, showcases the superior performance compared to the current state-of-the-art 3DGS SLAM.