Automatic path planning for low-altitude aircraft based on geological hazard data

To address the requirement for low-altitude unmanned aerial vehicles to perform emergency rescue missions safely and efficiently within geological hazard zones, this study designed an adaptive path planning method based on an enhanced A* algorithm. This approach integrates multi-dimensional constraints including topography, meteorological conditions, and performance parameters, while incorporating high-precision remote sensing data and real-time photogrammetric processing to enhance terrain perception and obstacle detection capabilities. The automated path planning system, developed using a microservices architecture, employs computer vision algorithms to achieve real-time terrain feature extraction and classification. Practical application has validated the algorithm's reliability and the system's practical value, providing a novel technical solution for low-altitude UAV path planning with enhanced environmental perception capabilities.