NAIS: A Modular ROS 2 Framework for Real-Time Scene Graph Construction and Language-Guided Navigation

Indoor robot navigation in unfamiliar environments requires accurate mapping, contextual understanding, and semantic reasoning to interpret user intent. While ROS 2 navigation frameworks provide strong 3D SLAM capabilities, they lack an integrated, modular approach that unifies perception, semantic representation, and high-level reasoning in a single, real-time system. We present Navigation AI Impulse by Scene Graph (NAIS), the first ROS 2 framework to continuously fuse SLAM, dynamic open-vocabulary scene graph construction, and foundation-model reasoning into a deployable and modular pipeline for mobile robots. NAIS operates online, using VLMs to describe objects and LLMs to infer spatial relations and resolve ambiguous natural language requests. This unified design links environment understanding directly to navigation planning, enabling context-aware goal selection without manual configuration or static class lists. Demonstrations on a TurtleBot 4 in office environments show NAIS handling high-level, context-dependent commands such as "I’m thirsty" or "I’m tired", illustrating its potential for robust, adaptable indoor navigation.