This paper presents an adapter for RTLola that simplifies the integration of runtime verification into Robot Operating System (ROS) applications. While ROS is the standard middleware for robotic development, ensuring the safety and reliability of high-level tasks such as navigation and object recognition remains challenging. The adapter facilitates the use of RTLola, a stream-based specification language for defining complex real-time properties, by automatically connecting a generated RTLola monitor to ROS topics and services. As a use case, the adapter was deployed onboard of an unmanned aircraft to reduce false positives in detecting people near the landing site. Specifically, our RTLola monitor cross-validates machine-learning-based person detections against objects in LiDAR depth images using classical computer vision techniques. This experiment demonstrates that runtime verification improves robotic safety while requiring minimal integration effort.