Demonstrating our latest localization system in action. At bootup, the robot has no prior position estimate, but within seconds it autonomously localizes itself using a fusion of three algorithms. Unlike our previous version, this updated system incorporates vision, allowing the robot to adapt to real-world changes (e.g., moved furniture) by recognizing previously seen environments. In this demo, we repeatedly reset navigation and reposition the robot to random locations, showing robust, repeatable localization. The robot then executes a full patrol, following a planned path (visualized in RViz) with real-time path tracking. Because our software is hardware-agnostic, it brings the same reliable performance to any robot it runs on.