This project explores robot navigation using modern mapping and perception techniques. The system focuses on enabling a robot to understand and navigate its environment using technologies such as SLAM (Simultaneous Localization and Mapping) and semantic mapping to build meaningful representations of indoor spaces. The project also investigates the potential use of Large Language Models (LLMs) for interpreting high-level navigation commands. By combining spatial mapping with semantic understanding, the goal is to improve how robots perceive environments and execute navigation tasks in a more intuitive and adaptable way.