公开(公告)号：WO2014062877A1

公开(公告)日：2014-04-24

申请号：PCT/US2013/065361

申请日：2013-10-17

Applicant: HUNTER ENGINEERING COMPANY

Inventor： SHYLANSKI, Mark S. ,  DORRANCE, Daniel R. ,  BERNARD, Bruce E. ,  GOLAB, Thomas J. ,  STIEFF, Michael T. ,  MCCLENAHAN, James W. ,  SILVER, J. Kaleb ,  STREGE, Timothy A. ,  COLARELLI, III, Nicholas J.

IPC: G01B11/275

CPC classification number: G01B11/27 ,  G01B11/275 ,  G01B11/2755 ,  G01B2210/12 ,  G01B2210/143 ,  G01B2210/303 ,  G06T7/0004 ,  G06T7/0006 ,  G06T7/30 ,  G06T7/32 ,  G06T7/33 ,  G06T7/73 ,  G06T7/85 ,  G06T7/97 ,  G06T2207/10012 ,  G06T2207/30164

Abstract: A process for calibrating and evaluating a machine-vision vehicle wheel alignment system having front and rear imaging components associated with each of the left and right sides of a vehicle support structure. Each pair of imaging components defines a front and rear field of view, with a common overlapping region associated with each respective side of the vehicle support structure. Optical targets disposed within each of the overlapping field of view regions are observed by the imaging components to establish performance ratings for the system as a whole, for groups of components within the system, and for individual components within the system.

Abstract translation: 一种用于校准和评估机器视觉车轮对准系统的方法，该系统具有与车辆支撑结构的左侧和右侧中的每一个相关联的前后成像部件。 每对成像组件限定前视场和后视场，其中共同重叠区域与车辆支撑结构的每个相应侧相关联。 通过成像部件来观察设置在每个重叠视野区域内的光学目标，以建立系统整体的性能等级，对于系统内的组件组以及系统内的各个部件。

公开(公告)号：WO2020181077A1

公开(公告)日：2020-09-10

申请号：PCT/US2020/021174

申请日：2020-03-05

Applicant: HUNTER ENGINEERING COMPANY

Inventor： CEJKA, Brian M. ,  DORRANCE, Daniel R. ,  CALLANAN, Patrick G. ,  STIEFF, Michael T.

IPC: G01B11/00 ,  G01B11/275 ,  G01C15/00 ,  G01S7/40

Abstract: A vehicle service system incorporating a pair of gimbal-mounted optical projection systems enables an operator to selectively orient each optical emitter of the optical projection system to illuminate a location on a vehicle surface in proximity to the system. Signals indicative of an orientation of each optical emitter about three-axes of rotation are received at a controller programmed with software instructions to utilize the received signals, together with known locations for the systems, to calculate a three-dimensional coordinate for the illuminated location within an established frame of reference. The controller is further programmed to utilize the calculated three-dimensional coordinate of the illuminated location as an origin point for determining one or more placement locations within the established frame of reference for ADAS sensor calibration or alignment targets.

公开(公告)号：WO2014151666A1

公开(公告)日：2014-09-25

申请号：PCT/US2014/026211

申请日：2014-03-13

Applicant: HUNTER ENGINEERING COMPANY

Inventor： DORRANCE, Daniel R. ,  SHYLANSKI, Mark S.

IPC: G01B11/275

CPC classification number: G06K9/60 ,  G01B11/2755 ,  G01B2210/20 ,  G01B2210/286 ,  G06T7/73 ,  G06T2200/04 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/20221

Abstract: A method for contactless measurements of a vehicle wheel assembly by acquiring a sequence of images as the vehicle wheel assembly moves within a projected pattern of light. Images of the vehicle wheel assembly are acquired and processed to identify the portions of the images corresponding to the wheel assembly, such as by recognition of the wheel rim edge. The identified portion of each image is cropped and a resulting point cloud of data rotational aligned by an optimization procedure to remove the effect of wheel translation and rotation between each image, as well as to identify a center of rotation and amount of rotation for each image which yields a best-fit result. Superimposing the resulting point clouds produces an image with a high density of data points on the optimally fit surfaces of the wheel assembly, which can be used to further refine the axis of rotation determination.

Abstract translation: 一种用于在车轮组件在投影图案内移动的情况下通过获取图像序列来非车载车轮组件的非接触式测量的方法。 获取并处理车轮组件的图像，以便例如通过识别轮缘边缘来识别对应于车轮组件的图像的部分。 裁剪每个图像的识别部分，并通过优化程序旋转对齐数据的结果点云，以消除每个图像之间的轮平移和旋转的影响，以及识别每个图像的旋转中心和旋转量 这产生最佳匹配结果。 叠加产生的点云会在轮组件的最佳配合表面上产生具有高密度数据点的图像，可用于进一步细化旋转轴确定。