Design and Realization of an Autonomous Ground Vehicle with Advanced Sensing for Landslide Prediction

Abstract

Landslides cause $2-4 billion in annual damages and 4,500 fatalities globally, yet current satellite monitoring lacks the resolution and temporal flexibility for early detection. We present an autonomous robotic platform with advanced perception integrating hyperspectral VNIR/SWIR imaging, 16-channel LiDAR, and RGB camera system for comprehensive slope stability assessment. The system enables soil moisture quantification, vegetation stress detection, and deformation monitoring through novel sensor fusion algorithms targeting both creep and earth flow landslides. The platform operates in manual, teleoperated, or autonomous modes to accommodate hazardous terrain conditions. Preliminary validation demonstrates data processing capabilities and successful terrain traversability.