This article presents an egocentric mapless navigation approach for cognitive robotics that avoids pre-built maps and explicit localization. Using LiDAR embeddings and vector search, the system learns navigation commands through human-guided training and adapts in real time via cosine similarity comparing real-time measurements with the vector memory. A FlowProtocol-based architecture with Moliris and SkRobot enables distributed control, supporting robust, efficient, and adaptive autonomous navigation in dynamic environments.