Abstract
This paper presents a weather-adaptive SLAM system for Unmanned Ground Vehicles (UGVs) equipped with lidar, radar, and RGBD-camera sensors. These sensors and functionalities are built in Robot Operating System (ROS) Noetic. The system dynamically selects the best sensor combination along with the corresponding slam strategies based on real-time weather data acquired through the Python web crawler. Our work ensures accurate mapping and localization in various and fast-changing weather conditions, enhancing SLAM reliability and accuracy.
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