TSAR: Trustworthy Search And Rescue uncrewed aerial vehicle

最近全球各地的自然灾害和人为灾害夺走了100多万人的生命，造成数万亿美元的经济损失。尽管灾难可能无法避免，但救援行动可以极大地减少生命损失。搜救是灾后迅速执行的首要任务。在灾难情况下，特别是在有争议的地区(障碍物和雾气条件)和战区，急救人员的搜索工作进展缓慢，因为他们彻底检查了周围环境，以避免不必要的碎片转移，同时保护自己。现有的最先进的SAR无人驾驶飞行器(UAV)只能使用人工智能(AI)算法识别开阔地区的人。该项目旨在开发一种智能的、值得信赖的、可靠的、高性价比的合成孔径雷达无人机，能够在有争议的区域定位受害者并评估他们的健康状况。这样的无人机可以加快搜索进程，并对多人伤亡的救援任务进行优先排序，提高成功救援和拯救生命的能力。沙皇的研究目标：1)设计一种新型的无人机，考虑垂直起降能力、高耐力和航程、机动性、容错性和可靠性因素；2)开发创新的计算机视觉算法，将竞争区域与开放区域分开，并采用Voronoi镶嵌算法在开放区域生成低空搜索轨迹，以便更近距离地查看竞争区域；3)开发多模式人工智能算法，融合和处理来自听觉和视觉传感器的数据，对受害者进行地理定位；4)通过分析热特征，通过新算法提供最大程度的视觉覆盖，提供受害者及其健康状态的最大视觉覆盖；5)沙皇的可信度将通过考虑在设计、开发和测试阶段嵌入的法律、伦理、制度和人的因素来实现。

Recent disasters around the globe, natural and manmade, claimed over a million lives and cost trillions of dollars in economic losses. Although disasters may not be prevented, rescue operations can considerably reduce the loss of life. Search And Rescue (SAR) is the foremost mission to be swiftly carried out in the aftermath of a disaster. First responders' search efforts in disaster situations, especially in contested areas (obstacles and foggy conditions) and war zones, are slow as they thoroughly examine the surroundings to avoid unnecessary debris shifts while protecting themselves. The existing state-of-the-art SAR Uncrewed Aerial Vehicles (UAVs) can only identify people in open areas using Artificial Intelligence (AI) algorithms. The proposed project, TSAR (Trustworthy SAR UAV), intends to develop an intelligent, trustworthy, reliable, and cost-effective SAR UAV that locates victims in contested areas and assesses their health. Such a UAV can expedite the search process and prioritize rescue missions for multiple casualties, enhancing successful rescue and saving lives. TSAR's research objectives: 1) Design a novel UAV for SAR operations considering vertical take-off and landing capability, high endurance and range, maneuverability, fault tolerance, and reliability factors; 2) Develop innovative computer vision algorithms to separate the contested areas from open areas, and adapt Voronoi tessellations to generate low-altitude search trajectories in the open areas to get a closer look at the contested areas; 3) Develop multimodal AI algorithms to fuse and process the data from the auditory and visual sensors to geo-locate victims; 4) Non-disruptive health check maneuvers providing maximum visual coverage of victims and their health status via a novel algorithm by analyzing heat signatures; and 5) TSAR's trustworthiness will be achieved by considering legal, ethical, system and human elements embedded through design, development and testing phases.