Abstract
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.
Abstract (translated)
在本文中，我们探讨了在海上搜索和救助（mSAR）任务中应用无人机（UAVs）的应用，重点关注中大型固定翼无人机和四旋翼。我们解决了操作不同种类UAV固有的挑战和局限性，特别是搜索操作。我们的研究包括开发一个全面软件框架，旨在提高SAR操作的效率和效果。该框架将无人机上初步的检测与地面站的高级物体检测相结合，旨在减少视觉疲劳并提高操作者的决策能力。在发表后，该框架将公开可用。我们进行实验来评估各种兴趣区域（RoI）提案方法，尤其是通过模拟有限的带宽来对待它们，这是在飞行远程或海上操作时需要考虑的重要问题。这迫使算法优先考虑某些预测而不是其他预测。
URL
https://arxiv.org/abs/2403.14281
