The ability to efficiently plan and execute automated and precise search missions using unmanned aerial vehicles (UAVs) during emergency response situations is imperative. Precise navigation between obstacles and time-efficient searching of 3D structures and buildings are essential for locating survivors and people in need in emergency response missions. In this work we address this challenging problem by proposing a unified search planning framework that automates the process of UAV-based search planning in 3D environments. Specifically, we propose a novel search planning framework which enables automated planning and execution of collision-free search trajectories in 3D by taking into account low-level mission constrains (e.g., the UAV dynamical and sensing model), mission objectives (e.g., the mission execution time and the UAV energy efficiency) and user-defined mission specifications (e.g., the 3D structures to be searched and minimum detection probability constraints). The capabilities and performance of the proposed approach are demonstrated through extensive simulated 3D search scenarios.
翻译:自动规划和执行无人机(UAV)嵌入式的精确搜寻任务,是应急响应任务中至关重要的。在应急响应任务中,精准地在障碍物之间导航以及高效地在三维结构和建筑物中进行搜寻,是定位幸存者和需要援助的人员的关键。在本论文中,我们通过提出一个统一的搜索规划框架来解决这个具有挑战性的问题,该框架自动化地规划无人机在三维环境中的搜索任务。具体而言,我们提出了一个新颖的搜索规划框架,通过考虑低级任务限制(例如,UAV 动力和感知模型)、任务目标(例如,任务执行时间和 UAV 能源效率)和用户定义的任务规范(例如,要搜索的三维结构和最低检测概率限制)来实现三维中自动规划和执行无碰撞的搜索轨迹。该方法的能力和性能通过大量的模拟三维搜索场景得到了证明。