Landing safety is a challenge heavily engaging the research community recently, due to the increasing interest in applications availed by aerial vehicles. In this paper, we propose a landing safety pipeline based on state of the art object detectors and OctoMap. First, a point cloud of surface obstacles is generated, which is then inserted in an OctoMap. The unoccupied areas are identified, thus resulting to a list of safe landing points. Due to the low inference time achieved by state of the art object detectors and the efficient point cloud manipulation using OctoMap, it is feasible for our approach to deploy on low-weight embedded systems. The proposed pipeline has been evaluated in many simulation scenarios, varying in people density, number, and movement. Simulations were executed with an Nvidia Jetson Nano in the loop to confirm the pipeline's performance and robustness in a low computing power hardware. The experiments yielded promising results with a 95% success rate.

翻译：着陆安全是近年来由于飞行器应用日益普及而备受研究界关注的挑战。本文提出一种基于最新目标检测器和八叉树地图的安全着陆流水线。首先生成地表障碍物的点云，并将其插入八叉树地图中。通过识别未被占用的区域，得到一系列安全着陆点。得益于最新目标检测器的低推理时间和八叉树地图的高效点云处理能力，本方法可在低重量嵌入式系统上部署。该流水线已在多种仿真场景中进行了评估，这些场景包括不同的人员密度、数量及运动状态。仿真实验采用Nvidia Jetson Nano进行验证，以确认流水线在低计算能力硬件上的性能与鲁棒性。实验取得了令人满意的结果，成功率达到95%。