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:由于对航空飞行器应用的兴趣日益浓厚,着陆安全最近成为研究界的一大挑战。在本论文中,我们提议根据先进的物体探测器和奥克托马普(OctoMap)的状态建立一个着陆安全管道。首先,产生了表面障碍的点云,然后将其插入奥克托马普(OctoMap)中。确定了未占用区域,从而得出了安全着陆点清单。由于先进的物体探测器和使用奥克托马普(OctoMap)的有效点云操纵的发回时间较低,我们采用低重量嵌入系统的方法是可行的。在很多模拟情况下,对拟议的管道进行了评估,在人员密度、数量和移动方面各不相同。在环绕中用Nvidia Jetson Nano(Nano) 进行了模拟,以证实管道的性能和低计算功率硬件的坚固性。实验取得了95%的成功率。</s>