A Comparison of Point Cloud Data from an iPad Pro LiDar Sensor to a Terrestrial Scanner

Light detection ranging (LiDAR) is commonly used to make high-resolution maps by using ultraviolet, visible, or near-infrared light to image objects. It can target a wide range of materials, with many applications, such as in surveying and accident reconstruction. LiDAR-like systems combine laser-focused imaging with the ability to calculate distances by measuring the time for a signal to return using various electronic sensors. LiDAR data capturing has been conducted and verified from many types of equipment manufacturers, however, little research has compared the FARO Terrestrial Laser Scanner and the LiDAR sensor of an iPad Pro. This study compares these two types of equipment addressing ease-of-use, effectiveness, and cost; where the Terrestrial Laser Scanner will be the control for this study. A statistical evaluation was performed of LiDAR data acquired from nine damaged vehicles and one undamaged vehicle. The damaged vehicles varied in damage condition, color, and configuration. The results revealed an average difference was ±0.4 in. between the point clouds acquired from the two methods. The point clouds were then used for a sample calculation of Delta-V for accident reconstruction purposes. When utilizing the EDCRASH simulation program to determine Delta-V, the percent error was less than 1% between the two sets of point clouds.