In this paper, we explore the application of Unmanned Aerial Vehicles (UAVs) in maritime search and rescue (mSAR) missions, focusing on medium-sized fixed-wing drones and quadcopters. We address the challenges and limitations inherent in operating some of the different classes of UAVs, particularly in search operations. Our research includes the development of a comprehensive software framework designed to enhance the efficiency and efficacy of SAR operations. This framework combines preliminary detection onboard UAVs with advanced object detection at ground stations, aiming to reduce visual strain and improve decision-making for operators. It will be made publicly available upon publication. We conduct experiments to evaluate various Region of Interest (RoI) proposal methods, especially by imposing simulated limited bandwidth on them, an important consideration when flying remote or offshore operations. This forces the algorithm to prioritize some predictions over others.

翻译：本文探讨了无人机（UAV）在海上搜救（mSAR）任务中的应用，重点关注中型固定翼无人机和四旋翼飞行器。我们分析了不同类别无人机在执行搜救操作（尤其是搜索任务）时面临的挑战与局限性。研究开发了一套综合性软件框架，旨在提升搜救操作的效率与效能。该框架结合了无人机机载初步探测与地面站高级目标检测技术，旨在减轻操作人员的视觉疲劳并优化决策能力。该框架将在论文发表后公开提供。我们通过实验评估了多种感兴趣区域（RoI）提议方法，尤其通过施加模拟有限带宽条件进行测试——这对远程或离岸作业中的关键考虑因素具有重要影响，迫使算法优先选择部分预测结果而非其他。