A Simulation-Driven Data Collection Method of External Wall by Integrating UAV and AR

With the development of urban construction, the number of high-rise buildings is increasing, and the diseases of external wall appeared over time. Conventional high-rise building wall inspection is usually inefficient. Unmanned aerial vehicle (UAV) with cameras improves the efficiency of wall inspection, however existing complete data collection method of the whole external wall without any focus is time-consuming. Augmented reality (AR) with simulation can drive the real equipment to execute expected task properly. Therefore, this paper proposes a simulation-driven data collection method of external wall by integrating UAV and AR. This method firstly imports building model and UAV model into AR operation system, and relevant components are added to construct AR interface. After that, the grid map is generated and the voxelized building point cloud data is imported, and the map is integrated into the UAV control system to realize the path search algorithm. Then, a special network connection protocol between Robot Operating System (ROS) and AR is used to link them and realize the control and information transmission between UAV and AR. Finally, a scenario model is built in simulation environment to verify the feasibility of this method. The results show that this method can successfully control the UAV in the AR equipment and obtain the required information and improve work efficiency. This method aims to verify the use of AR to control equipment to achieve intelligent building external wall data collection. In the future, this technology will continue to be expanded and applied in practice.