Abstract
Sensor calibration is a crucial step to ensure the proper functioning of advanced driver assistance systems (ADAS), and vehicle coordinate system reconstruction is an indispensable part of this process. However, the currently mainstream vehicle alignment platforms are characterized by high costs, complex structures, and immobility, making them unsuitable for the rapid upgrade and transformation pace of modern automotive manufacturers. To address these limitations, this paper proposes a low-cost, flexible solution based on extracting key feature points from the car body-in-white. First, the paper introduces the reconstruction principles based on rigid body transformation. Then, the method for selecting the necessary feature points and its general applicability are discussed. Third, the paper describes how to mitigate the influence of vehicle body color by choosing appropriate light sources, and it employs suitable algorithms to complete the feature point extraction process. Finally, validation experiments were designed to verify the accuracy of the proposed method, demonstrating that it achieves better reconstruction precision compared to the vehicle alignment platforms.