Integrating VLM Perception and Geometric-Semantic SLAM for Indoor Environment Recognition
This paper presents a semantic mapping system that integrates Vision-Language Models (VLMs) with Simultaneous Localization and Mapping (SLAM) to enhance the understanding of indoor environments. While traditional SLAM systems primarily focus on geometric occupancy, they often lack the semantic context needed for high-l...