Rodrigues Lucas, Riker André, Ribeiro Maria, Both Cristiano, Sousa Filipe, Moreira Waldir, Cardoso Kleber, Oliveira-Jr Antonio
Institute of Informatics (INF), Universidade Federal de Goiás (UFG), Goiânia 74690-900, Brazil.
Institute of Exact and Natural Sciences (ICEN), Federal University of Pará, Belém 66075-110, Brazil.
Sensors (Basel). 2021 Nov 20;21(22):7735. doi: 10.3390/s21227735.
This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm's behavior in generating routes, and the model is evaluated using a reliability metric.
本文提出了一种将无人机作为物联网数据收集器进行自主飞行规划的方法。我们提出了一个适用于单架飞机以及多架飞机的模型。文中还探讨了一种扩展无人机访问的物联网设备(如传感器)数量范围的聚类技术。该模型生成的飞行计划着重于防止因电池电量不足而导致故障,以最大限度地增加访问的节点数量。除了无人机自主飞行规划外,还考虑了数据存储限制方面。我们基于飞机类型的空气动力学特性展示了无人机的能耗情况。仿真展示了该算法在生成路线时的表现,并使用可靠性指标对模型进行了评估。