Lidar-Based Real-Time Mapping for Digital Twin Development

Game engines are effective in generating and visualizing digital twins of urban environment in real time. However, current game engines are not built to handle the influx of real time data streams from a diverse array of IoT devices, nor can they render a real-time dynamic mesh streamed from a scanning device such as a Light Detection and Ranging (LIDAR) system. In this paper, a combination of pre-processing and post-processing techniques are considered in variably processed batches of point-cloud data. Additionally, we propose a quantitative error analysis for points generated on our experimental aerial mapping platform, as well as an analysis for the accuracy improvement after post-processing. Experimental results show that the proposed rendering algorithm and post-processing could enable a game engine to efficiently generate a highly accurate digital twin of urban environment.