Theability 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.

在紧急响应情况下使用无人驾驶飞行器 (UAV) 有效规划和执行自动化和精确搜索任务的能力至关重要。障碍物之间的精确导航以及对 3D 结构和建筑物的高效搜索对于在紧急响应任务中定位幸存者和有需要的人至关重要。在这项工作中，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，该框架可以在 3D 环境中自动执行基于无人机的搜索规划过程。具体而言，我们提出了一种新颖的搜索规划框架，该框架通过考虑低级任务约束（例如，无人机动力学和传感模型）、任务目标（例如，任务执行时间和无人机能源效率）和用户定义的任务规范（例如，要搜索的 3D 结构和最小检测概率约束）。通过广泛的模拟 3D 搜索场景证明了所提出方法的能力和性能。