The UAV-VLA (Visual-Language-Action) system is a tool designed to facilitate communication with aerial robots. By integrating satellite imagery processing with the Visual Language Model (VLM) and the powerful capabilities of GPT, UAV-VLA enables users to generate general flight paths-and-action plans through simple text requests. This system leverages the rich contextual information provided by satellite images, allowing for enhanced decision-making and mission planning. The combination of visual analysis by VLM and natural language processing by GPT can provide the user with the path-and-action set, making aerial operations more efficient and accessible. The newly developed method showed the difference in the length of the created trajectory in 22% and the mean error in finding the objects of interest on a map in 34.22 m by Euclidean distance in the K-Nearest Neighbors (KNN) approach.

该研究针对无人机任务生成中的沟通问题，提出了一种创新的无人机-视觉语言-行动(UAV-VLA)系统。通过结合卫星图像处理和视觉语言模型(VLM)，该系统不仅提高了任务规划的效率，还显著减少了创建航迹长度的22%和目标定位的误差，展示了其在空中作战中的重要价值。

无人机-视觉语言-行动系统：大规模空中任务生成