The ability to efficiently plan and execute search missions in challenging and complex environments during natural and man-made disasters is imperative. In many emergency situations, precise navigation between obstacles and time-efficient searching around 3D structures is essential for finding survivors. In this work we propose an integrated assessment and search planning approach which allows an autonomous UAV (unmanned aerial vehicle) agent to plan and execute collision-free search trajectories in 3D environments. More specifically, the proposed search-planning framework aims to integrate and automate the first two phases (i.e., the assessment phase and the search phase) of a traditional search-and-rescue (SAR) mission. In the first stage, termed assessment-planning we aim to find a high-level assessment plan which the UAV agent can execute in order to visit a set of points of interest. The generated plan of this stage guides the UAV to fly over the objects of interest thus providing a first assessment of the situation at hand. In the second stage, termed search-planning, the UAV trajectory is further fine-tuned to allow the UAV to search in 3D (i.e., across all faces) the objects of interest for survivors. The performance of the proposed approach is demonstrated through extensive simulation analysis.

翻译：在自然与人为灾害中，高效规划并执行复杂环境下的搜索任务至关重要。许多紧急情况下，在障碍物间精准导航并在三维结构周围进行时间高效的搜索是寻找幸存者的关键。本文提出了一种集成的评估与搜索规划方法，使自主无人机（UAV）代理能够在三维环境中规划并执行无碰撞搜索轨迹。具体而言，所提出的搜索规划框架旨在整合并自动化传统搜索与救援（SAR）任务的前两个阶段（即评估阶段与搜索阶段）。在第一阶段（称为评估规划），我们旨在找到一个高级评估计划，使无人机代理能够执行该计划以访问一系列兴趣点。该阶段生成的计划引导无人机飞越兴趣目标，从而对当前情况提供初步评估。在第二阶段（称为搜索规划），进一步优化无人机轨迹，使其能在三维空间（即所有表面）中搜索兴趣目标内的幸存者。通过广泛的仿真分析验证了所提方法的性能。