一种用于3D四轮定位的RANSAC改进算法

An improved RANSAC algorithm for 3D wheel alignment

针对传感器多、操作复杂、检测速度慢等传统四轮定位仪的缺陷,研究了一种快速准确的3D四轮定位检测方法。首先设计了一种全新特殊的圆心标靶进行相机的标定,然后使用改进的RANSAC算法结合设计的特殊标靶对单应性矩阵的配准进行了优化,利用空间矢量原理对车轮定位系统的参数进行精确测量,得到四轮定位的参数。设计传统标靶与新型标靶之间的标定对比实验,与车厂现有四轮定位仪进行对比测试。实验结果表明,使用新型标靶结合优化算法能够提升标定效率约9%-21%,同时,提高了标定精度约10.6%-17.8%;并通过实车测试证明,使用新型标靶结合优化算法可保证四轮定位的准确性和可靠性。该方法在汽车四轮定位参数的快速检测方面具有一定的意义。

Aiming at the defects of traditional four-wheel aligner such as many sensors,complex operation and slow detection speed,a fast and accurate 3D four-wheel alignment detection method is studied.Firstly,a new and special circle center target board is designed to calibrate the camera,and then the registration of the homography matrix is optimized by using the improved RANSAC(Random sample consensus)algorithm combined with the designed special target board,and the parameters of the wheel alignment system are adjusted by using the space vector principle.Accurate measurements are made to obtain the parameters of the four-wheel alignment.Design a calibration comparison experiment between the traditional target board and the new type of target board,and conduct a comparative test with the existing four-wheel aligner of the depot.The experimental results show that the use of the new target board-binding optimization algorithm can improve the calibration efficiency by about 9%to 21%,while improving the calibration accuracy by about 10.6%to 17.8%.And through the real vehicle test,it is verified that the use of the new target combined with the optimization algorithm can ensure the accuracy and reliability of the four-wheel positioning.This method has a certain significance in the rapid detection of vehicle four-wheel alignment parameters.