Real-time image processing in a multi-UAV system for structural surveillance through IoT platform
Real-time image processing in a multi-UAV system for structural surveillance through IoT platform
复制标题
DOI：
10.1117/12.2622362
复制
发表时间：
2022-05
期刊：
影响因子：
--
通讯作者：
J. Falcón;M. Mehrubeoglu;Pablo Rangel
中科院分区：
文献类型：
--
作者：
J. Falcón;M. Mehrubeoglu;Pablo Rangel
在任何一组无人机系统任务中，使用位置和指令标记来增强多路径规划对单个无人机的协调和有效性至关重要。本研究实现了OpenCV算法，该算法允许多架无人机使用ArUco标记来接收与位置和指令相关的数据，以实现多路径规划。OpenCV算法被用于开发基于视觉的解决方案，以增强无人机的实时能力。多无人机系统的最终目标是检查和测量物体的结构损伤，并将开发的图像处理算法应用于收集的图像，以确定损伤的重要性。该项目利用OpenCV和Python库进行多无人机路径规划，通过网络基础设施收集、传输和显示现实世界的工业有价值数据，作为物联网（IoT）的应用。
The use of location and instruction markers for multi-path planning enhancement in any set of unmanned aerial systems’ tasks is crucial to the coordination and effectiveness of the individual unmanned aerial vehicles (UAVs). This research implements OpenCV algorithms that allow multiple UAVs to use ArUco markers to receive data related to location and instruction for the purposes of multi-path planning. OpenCV algorithms are utilized to develop vision-based solutions that will enhance the real-time capabilities of the UAVs. The final goal for the multi-drone system entails inspecting and surveying objects for structural damage and applying the developed image processing algorithms to collected images to determine the significance of damage. This project utilizes OpenCV and Python libraries for multi-drone pathway planning by collecting, transmitting, and displaying real-world industrially valuable data over the network infrastructure as an application of Internet of Things (IoT).