Postgraduate Programme in Metrology, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro, 22451-900 RJ, Brazil.
Tecgraf Institute, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Gávea, Rio de Janeiro, 22451-900 RJ, Brazil.
Sensors (Basel). 2020 Dec 15;20(24):7186. doi: 10.3390/s20247186.
Three-dimensional (3D) imaging technologies have been increasingly explored in academia and the industrial sector, especially the ones yielding point clouds. However, obtaining these data can still be expensive and time-consuming, reducing the efficiency of procedures dependent on large datasets, such as the generation of data for machine learning training, forest canopy calculation, and subsea survey. A trending solution is developing simulators for imaging systems, performing the virtual scanning of the digital world, and generating synthetic point clouds from the targets. This work presents a guideline for the development of modular Light Detection and Ranging (LiDAR) system simulators based on parallel raycasting algorithms, with its sensor modeled by metrological parameters and error models. A procedure for calibrating the sensor is also presented, based on comparing with the measurements made by a commercial LiDAR sensor. The sensor simulator developed as a case study resulted in a robust generation of synthetic point clouds in different scenarios, enabling the creation of datasets for use in concept tests, combining real and virtual data, among other applications.
三维（3D）成像技术在学术界和工业领域得到了越来越多的探索，特别是那些能够生成点云的技术。然而，获取这些数据仍然可能很昂贵和耗时，降低了依赖大型数据集的流程的效率，例如机器学习训练数据的生成、森林冠层计算和海底勘测。一个流行的解决方案是为成像系统开发模拟器，对数字世界进行虚拟扫描，并从目标生成合成点云。本工作提出了一种基于平行射线投射算法的模块化光探测和测距（LiDAR）系统模拟器开发指南，其传感器由计量参数和误差模型建模。还提出了一种基于与商业 LiDAR 传感器测量值进行比较的传感器校准程序。作为案例研究开发的传感器模拟器能够在不同场景下稳健地生成合成点云，从而能够创建用于概念测试、真实数据和虚拟数据结合以及其他应用的数据集。
