Method for measuring a fender edge of a vehicle in a test stand

Abstract

The invention relates to a method for measuring the fender edge of a vehicle on a test stand, wherein the test stand has a coordinate system in which the Z axis is a vertical axis, the X axis is an axis in the test stand which extends in a horizontal plane in the longitudinal direction of the vehicle which is in the test stand for testing, and the Y axis is an axis which extends in a horizontal plane perpendicular to the X axis. It is proposed within the scope of the invention to move a light pattern projected onto the vehicle by an illumination unit and to take this light pattern by two imaging units. From the 3D point cloud determined by the stereoscopic photography of the taking, a subset is formed for evaluation. The method allows a higher measurement rate when determining the position and orientation of the fender edge.

Description

Technical Field

[0001] This invention relates to a method for measuring the fender edge of a vehicle in a test bench. Background Technology

[0002] As known from US2014 / 267699A1, a 3D point cloud is projected onto a wheel and detected and evaluated using stereo photogrammetry. Evaluation is achieved by continuously capturing and evaluating the corresponding 3D point cloud multiple times while the wheel is rotating. Here, only points scattered by the wheel in the 3D point cloud are considered during evaluation. Therefore, the wheel's geometric parameters (track angle and camber angle) must be determined.

[0003] As known from US2014 / 267699A1, in order to measure various parts of a vehicle, a light pattern formed by structured light is projected onto the vehicle. The evaluation is performed using stereophotometry. The emitted light pattern is emitted within a narrow band of longitudinal waves. Similarly, the detection of scattered light is also performed only within a narrow band of wavelengths. Therefore, interference from external light (ambient light) should be minimized.

[0004] To better illustrate the present invention, the coordinate system of the test bench is first defined as follows. The test bench has a coordinate system,

[0005] In this coordinate system, the Z-axis is the vertical axis.

[0006] In this coordinate system, the X-axis is the axis extending in the horizontal plane along the longitudinal direction of the vehicle positioned on the test bench for testing purposes, and...

[0007] In this coordinate system, the Y-axis is an axis that extends perpendicular to both the X-axis and the Z-axis.

[0008] For example, fender edges are measured in applications such as development, production, and after-sales service, or in technical monitoring as part of periodic inspections of vehicles in operation to ensure their traffic safety. Measuring the fender edges determines their position and orientation. The position and orientation of the fender edges can be determined absolutely in the coordinate system of the test bench or relative to other components of the vehicle. These other components may include, for example, wheels, rims, and / or brake discs.

[0009] The position and orientation of the fender edges are used to determine the vehicle's so-called "ride height." This involves the spring displacement travel of the vehicle body. The ride height is the distance between the fender edge (or a feature point on the fender edge) and the center of the wheel. The Z-coordinate of the fender edge position and orientation data determines the vehicle's ride height.

[0010] In addition to determining the horizontal height, the determined position and orientation data of the fender edges can also be used to determine the vehicle width. This can be done using the Y-coordinates of the position and orientation of the fender edges of the two fenders facing each other on the sides of the vehicle.

[0011] Apparatus for photogrammetry of an object is known in that it comprises an illumination unit and multiple imaging units. Light is emitted by the illumination unit. This light is scattered by the object to be measured. The scattered light is received by the imaging units. The images captured by the imaging units are evaluated. This evaluation produces a point cloud as a dataset, representing a three-dimensional arrangement of points. The points in this point cloud correspond to points on the surface of the object from which the light was scattered. The calculation of the point cloud is performed using two or more imaging units for photogrammetry.

[0012] The imaging unit is a camera. Calculations and evaluations can be performed in an evaluation device, which can be a separate component located downstream of the imaging unit. In this case, the signal from the imaging unit is transmitted to the evaluation device as an input signal. Alternatively, the evaluation device can be integrated with the imaging unit as a component. Software that performs the calculations and evaluations is executed within the evaluation device.

[0013] In photogrammetry, a planar-coded texture is placed on the surface of the 3D object to be measured using illumination units. In this paper, "texture" refers to a specific light pattern. This texture serves as an aid in evaluating images captured by imaging units. Imaging units observe the object from different directions. Therefore, these imaging units "see" the same light pattern on the surface from different directions. Based on the planar-coded illumination texture, the individual, consistent points of the imaging units can be correlated during evaluation. The positions of these points are calculated in space relative to the coordinate system of the photogrammetric apparatus using image information from the imaging units. The position and orientation of the coordinate system of the photogrammetric apparatus are calibrated relative to the coordinate system of the vehicle test bench. Therefore, a 3D point cloud of the object in the coordinate system of the photogrammetric apparatus is obtained from these points. This also yields a 3D point cloud of the object in the coordinate system of the vehicle test bench.

[0014] To achieve high measurement accuracy when detecting the position and orientation of fender edges, a high point density is required in the point cloud. With higher point density, the number of points included in the calculations for evaluating the position and orientation of the fender edges increases. This necessitates significant computation time at correspondingly high point densities. Especially in production vehicles, computations at high point densities require substantial time during the evaluation process, negatively impacting cycle time.

[0015] EP0757229B1 discloses an apparatus for non-contactly determining the position and orientation of a vehicle's fender edge. The apparatus includes a first device for determining the position of a defined point on the vehicle body in the z-direction, a second device for determining the position of the wheel center in the z-direction, and an evaluation unit connected to the first and second devices for calculating the vehicle's height level from the positions determined by the first and second devices. Summary of the Invention

[0016] The present invention aims to provide a method by which the position and orientation of the fender edge can be easily determined.

[0017] According to the present invention, this task is solved by a method for measuring the fender edge of a vehicle in a test bench. The test bench has a coordinate system in which the Z-axis is a vertical axis, the X-axis is an axis extending in a horizontal plane in the longitudinal direction of the vehicle placed in the test bench for testing, and the Y-axis is an axis extending perpendicular to both the X-axis and the Z-axis. The method includes the following steps:

[0018] A constant light pattern is projected onto the vehicle using at least one illumination unit. This light pattern can be divided into sub-regions of equal size, making each sub-region of the light pattern individual. This means that each sub-region is unique within the light pattern.

[0019] - The light pattern projected onto the vehicle is captured by two imaging units, each capturing the current light pattern projected onto the vehicle.

[0020] - The light pattern projected onto the vehicle is moved by exciting the lighting unit or at least one component of the lighting unit to vibrate.

[0021] - A 3D point cloud is determined stereoscopically from the capture of light patterns projected onto the vehicle during vibration of the illumination unit or at least one component of the illumination unit by two imaging units.

[0022] - Identify a subset of points from a 3D point cloud, the subset being formed by the intersection of points in the point cloud with multiple volumes, each volume being defined by two planes extending not only in the Y-axis direction but also in the Z-axis direction, the two planes being spaced apart from each other in the X-axis direction by a distance Δx, the multiple volumes being located at adjacent positions x on the X-axis. n Therefore, the subset only includes points within the volume.

[0023] - A subset of points based on 3D point clouds is used to determine the position and orientation of the fender edge as the resulting dataset.

[0024] These features indicate that the light pattern itself is constant. In addition to the points in the point cloud generated by the projection of the light pattern onto the object from its static emission, according to the invention, other points generated by photography are added to the point cloud during which the same (unchanging) light pattern is projected onto the object, but the entire illumination unit or at least one component of the illumination unit is excited to vibrate. This vibration causes the projected light pattern to shift. Thus, the points in the point cloud are "supplemented" in that the points captured at the instant the light pattern shifts accordingly due to vibration are also "integrated" into the point cloud.

[0025] The illumination unit can be excited to vibrate as a whole. The illumination unit can be constructed, for example, such that an image, such as a slide, is illuminated by a light source and placed on the illumination unit. In this case, it is sufficient to excite the slide to vibrate. Exciting only the slide is advantageous because the slide has a smaller mass and therefore less inertia compared to the illumination unit as a whole. The vibration of at least one component of the illumination unit is performed such that the light pattern projected onto the object moves within its position on the object.

[0026] Therefore, the density of the calculated 3D point cloud can be advantageously increased by moving the light pattern projected onto the vehicle. This increase in point cloud density implies a decrease in the average spacing between the points. The movement is caused by the vibration of the illumination unit or at least one component of the illumination unit. For example, the movement of the light pattern can be achieved by the vibration of a photographic film / plate illuminated by a light-emitting device. Vibration can be caused, for example, by an electric vibration motor, and particularly preferably by a piezoelectric element.

[0027] A constant light pattern is projected onto the surface of the vehicle by the at least one illumination unit. The edge of the fender to be measured is located in the area of ​​the vehicle on which the light pattern is projected.

[0028] A light pattern can be divided into sub-regions of equal size, making each sub-region of the light pattern individual. This means that each sub-region is unique within the light pattern. Particularly advantageous is that these sub-regions can be uniquely identified within the light pattern. A light pattern can also consist of multiple light patterns, each with its own individualized sub-regions. For example, two identical light patterns with individualized sub-regions can be combined into a single overall light pattern. The uniqueness of the sub-regions within the overall light pattern arises from their association with one of the two light patterns.

[0029] An example of such a light pattern is the overall arrangement of illuminated and unilluminated points. This overall arrangement can be divided such that the partial arrangement of the point pattern for each point in the overall arrangement is personalized for each point, taking into account other points adjacent to the respective points. This overall arrangement of illuminated and unilluminated points can be achieved as a simultaneous and monochromatic projection of the illuminated and unilluminated points onto the edge of the fender to be measured.

[0030] Another example of a light pattern within the scope of this invention is a texture composed of individual planar elements of identical shape. These planar elements can, for example, be squares. The planar elements can be directly adjacent to each other, such that the side of one square simultaneously forms the side of an adjacent planar element. The uniqueness of the planar elements can be achieved through the lack of periodicity in the markings, such that the state of each planar element is not periodic in the sense of being "illuminated" or "unilluminated." Thus, for example, a texture is produced whose optical impression is comparable to that of a QR code, at least when viewed only briefly. If this texture is divided into small sub-regions, such as a square along with its eight adjacent squares, then for these nine squares, a total of 2 9 There are 512 possible combinations of illuminated and unilluminated squares. This allows for the realization of 2... 9 Each subregion is unique and can be uniquely associated. If the subregions are further expanded and detected, such as subsequent squares, this number doubles for each additional square.

[0031] The projected light pattern serves as a marker on the vehicle surface. This marker is captured by two imaging units. Therefore, during evaluation, the points on the vehicle surface can be correlated using these markers. This is because the individual subsets are individualized.

[0032] Advantageously, illumination can be performed with an invariant light pattern. This reduces the complexity of the illumination unit because there is no need to generate dynamic light patterns or sequences of light patterns. In particular, there is no need for an identification phase, in which parts of the light pattern are altered and / or faded in and out. This is sometimes necessary in the prior art to enable the correlation of these parts. Advantageously, all points in the point cloud are detected simultaneously. The absence of an identification phase increases the measurement rate. "Simultaneously" in this case means that continuous measurements while the illumination unit or at least one component of the illumination unit vibrates should be understood as uniform measurements in this case. The method of vibrating the illumination unit or at least one component of the illumination unit described herein is intended to increase the point density in this method. Therefore, vibration is not at all for the purpose of being able to correlate points on the vehicle surface. Vibration is used to generate additional points on the surface, thereby achieving a higher point density overall.

[0033] Advantageously, a light pattern with high contrast is selected to improve the recognition of the light pattern projected onto the vehicle surface by the imaging unit. In particular, binary patterns (in which the surface with the highest intensity (i.e., the illuminated surface) alternates with the surface with the lowest intensity (i.e., the unilluminated surface)) provide high contrast and are therefore particularly suitable.

[0034] The light emitted by the illumination unit can be monochromatic. Advantageously, this means that, for the method according to the invention, even without special darkening measures and under limited emitted light intensity, the emitted light and the scattered light have sufficient contrast compared to the scattered light in the environment.

[0035] If the lighting unit uses LEDs as the light-emitting device, it proves advantageous that only a short heating time is required to put it into operation. The equipment can then typically be used within minutes without the need for prolonged heating of the components. This is particularly advantageous once the equipment is operational, as it avoids operational delays and associated cycle times during vehicle manufacturing.

[0036] 3D point clouds are determined stereoscopically from images captured by two imaging units of light patterns projected onto the vehicle during the vibration of the illumination unit. Here, 3D point clouds can be stereoscopically determined from image pairs taken instantaneously by the two imaging units in each moving state. The obtained individual 3D point clouds can be combined into a common 3D point cloud with a higher point density. Alternatively, image pairs from the two imaging units in multiple moving states can be combined using a stereo matching algorithm, thereby obtaining a point cloud with a higher point density compared to individual point clouds determined stereoscopically from only one image pair.

[0037] A subset of points in a 3D point cloud is determined by the intersection of points in the point cloud with multiple volumes. The result is a 3D point cloud containing points within a volume. The number of points in the subset can be increased by increasing the distance Δx between the two planes of the volume in the X-axis direction and by using a larger number of volumes.

[0038] Preferably, the distance Δx between the two planes is greater than the average distance between the points in the point cloud, but less than twice the average distance between the points in the point cloud. Advantageously, this ensures that there is at least one row of points in the Z direction for each volume in this subset. Thus, the points in a volume form a substantially vertical line that curves along the surface of the vehicle. The number of volumes can reach up to 120.

[0039] Of particular advantage is the reduction in the number of points used for evaluation by using a subset of the point cloud. The reduced number of points in the subset allows for particularly rapid and efficient determination of the position and orientation of the fender edge. Simultaneously, the increased density of the point cloud in the subset allows for improved measurement accuracy. As mentioned above, the density of the point cloud is also advantageously increased by vibration of the illumination unit or at least one component of the illumination unit.

[0040] Of particular advantage is that the fender edge can be determined very simply by a point on a curved, essentially vertical line. For example, the fender edge can be determined by the change in the Y-coordinate from one point to the next on a line. This improves the measurement rate of the position and orientation of the fender edge, as it is a very efficient and rapidly implementable method for determining the position of the fender edge within a given volume.

[0041] In another embodiment of the method according to the invention, the data used for evaluation is selected as follows before determining the position and orientation of the fender edge.

[0042] - Generate a first reduced subset of points from the set of points in the point cloud.

[0043] -Considering only points in a portion (in the sense of this invention) of the point cloud volume,

[0044] - In the first evaluation step, the position and orientation data of the fender edge are determined based on the points of the first reduced subset as the first dataset.

[0045] - The position and orientation data of the fender edges in the second dataset are determined by extrapolating the position and orientation data of the fender edges in the first dataset for volumes not considered when generating the first reduced subset. The second dataset is formed by the union of the position and orientation data of the fender edges in the first dataset and the supplementary position and orientation data of the fender edges.

[0046] - A second reduced subset is generated from the subset by forming an intersection between the points in the point cloud of the subset and the defined environment surrounding the points in the second dataset.

[0047] - Determine the position and orientation of the fender edges in the resulting dataset based on the data from the second reduced subset.

[0048] The same terminology as that used in some embodiments of the invention is used conceptually in association with some embodiments of the invention. In this regard, the first reduced subset, the first dataset, the second reduced subset, and the second dataset in some embodiments of the invention, while conceptually the same as in other embodiments of the invention, have different meanings in association with some embodiments of the invention, arising from the corresponding association of features in some embodiments of the invention or features in other embodiments of the invention.

[0049] Advantageously, the evaluation of the first dataset (in some embodiments of the invention) is accelerated by using points in the first reduced subset (in some embodiments of the invention) with a smaller number of points compared to the subset.

[0050] Particularly advantageously, the data in the first dataset (in some embodiments of the invention) can also be supplemented by extrapolating the data in the first dataset (in some embodiments of the invention) for volumes not considered when determining the position and orientation of the fender edges. Here, this data extrapolation is faster than determining the position and orientation of the fender edges based on unconsidered volumes. In this regard, the second dataset is formed by the union of points from the first dataset and the additional points obtained through this extrapolation.

[0051] To more accurately determine the position and orientation of the fender edge, a second reduced subset (in some embodiments of the invention) is generated from the subset. Here, the intersection of points from the subset and the defined environment surrounding points in the second dataset (in some embodiments of the invention) is formed.

[0052] The environment can be designed, for example, as a cuboid. Alternatively, the environment can be defined as a torus having the fender edge line determined in the second dataset as its centerline. Advantageously, the environment includes all points at a specific distance from the points in the second dataset. Particularly advantageously, this distance depends on the average spacing of the points in the first reduced subset. The environment can also be defined such that the numerical deviation between the Z-coordinates of these points and the Z-coordinates of the points in the first dataset no longer exceeds a predetermined limit. Therefore, the Y-coordinates are not considered when “selecting points.” The distribution of these Y-coordinates is considered in the subsequent evaluation so that the position and orientation of the fender edge can be inferred from the abrupt changes in the Y-coordinates of adjacent points in the Z direction.

[0053] The points in the second reduced subset are used to determine the position and orientation of the fender edge. Particularly advantageous is that the second reduced subset has the same point density (point spacing) as the subset. This maintains measurement accuracy when evaluating the position and orientation of the fender edge. By reducing the number of points to the area surrounding the points in the second dataset (in the sense of some embodiments of the invention), the number of points to be evaluated is reduced compared to the subset. This allows for particularly rapid determination of the fender edge's position and orientation. Nevertheless, high measurement accuracy is maintained in the final evaluation step by selectively choosing data from important regions for this evaluation. Advantageously, this enables a higher measurement rate.

[0054] As an extension of some embodiments of the invention, according to other embodiments of the invention, it is suitable to include only a portion of the points of the subset within the volume considered during subset generation into the first reduced subset. The point spacing between the points included in the first reduced subset is greater than the point spacing within the subset.

[0055] Advantageously, this further reduces the number of points in the first reduced subset, thereby enabling a faster evaluation of the data in the first dataset (in the sense of some embodiments of the invention).

[0056] This invention includes, according to other embodiments of the invention, selecting data for evaluation prior to determining the position and orientation of the fender edge.

[0057] The method involves generating a first reduced subset of points in the point cloud from the subset in the following manner: only a portion of the points in the subset are included in the first reduced subset, and the distance between points included in the first reduced subset is greater than the distance between points in the subset.

[0058] - In the first evaluation step, the position and orientation data of the fender edge are determined based on the points of the first reduced subset as the first dataset.

[0059] - A second reduced subset is generated from the subset by forming an intersection between the points in the point cloud of the subset and the defined environment surrounding the points in the first dataset.

[0060] - Determine the position and orientation of the fender edges in the resulting dataset based on the data from the second reduced subset.

[0061] The same terminology as that used in some embodiments of the invention is used conceptually in association with other embodiments of the invention. In this regard, the first reduced subset, the first dataset, the second reduced subset, and the second dataset in other embodiments of the invention, while conceptually the same as those in some embodiments of the invention, have different meanings in association with other embodiments of the invention, which arise subsequently in the discussion of other embodiments of the invention in relation to the features of other embodiments of the invention.

[0062] Compared to the method according to the invention, the processing method according to other embodiments of the invention has proven advantageous. In the processing method according to the invention, there is a high point density in the subset across the entire region of the coordinates along the Z-axis in each volume. This means that the subset also contains a large number of data points that are relatively far from the fender edge in the Z-axis direction. In this regard, some calculations are still performed, but these calculations do not lead to meaningful results in locating the fender edge.

[0063] By using a first reduced subset in the sense of some other embodiments of the invention, the position and orientation of the fender edge can be determined initially with a less precise evaluation at a lower point density (larger point spacing between points). Here, the point spacing between points in the first reduced subset is greater than the point spacing within the subset. This can be achieved, for example, by removing some points from the subset. For example, every second point can be removed from the subset. The point spacing can also be further increased. With the larger point spacing and associated smaller point density in the first reduced subset, the initial determination of the fender edge's position and orientation can be made particularly quickly in a first dataset.

[0064] The approximate location and orientation of the fender edge are first obtained using a first dataset. Points in the first dataset corresponding to the location and orientation of the fender edge can then be calculated. This calculation is based on a first reduced subset in the test bench's coordinate system. To more accurately determine the location and orientation of the fender edge, a second reduced subset is generated from this subset, formed by the intersection of the points in the second subset with the defined environment surrounding the points in the first dataset.

[0065] The environment can be designed, for example, as a cuboid. Alternatively, the environment can be defined as a torus, with the fender edge line determined in the first dataset as its centerline. Advantageously, the environment includes all points at a specific distance from the points in the first dataset. Particularly advantageously, this distance depends on the average spacing of the points in the first reduced subset. The environment can also be defined such that the numerical deviation of the Z-coordinates of these points from the Z-coordinates of the points in the first dataset no longer exceeds a predetermined limit. Therefore, the Y-coordinates are not considered when “selecting points.” The distribution of these Y-coordinates is considered in the subsequent evaluation so that the position and orientation of the fender edge can be inferred from the abrupt changes in the Y-coordinates of adjacent points in the Z direction.

[0066] The points in the second reduced subset are used to determine the position and orientation of the fender edge. Advantageously, the second reduced subset has the same point density (point spacing) as the subset. This maintains the high-resolution measurement accuracy of the points in the point cloud when determining the position and orientation of the fender edge. By reducing the points in the second reduced subset to only those in the environment surrounding the previously determined position and orientation of the fender edge (at a reduced measurement resolution), the number of points to be evaluated is reduced compared to the subset. However, this reduction is targeted to areas important for more accurate evaluation. In summary, this allows for particularly fast, yet highly accurate, determination of the fender edge position and orientation.

[0067] Advantageously, this enables higher measurement rates. This proves particularly advantageous when the method is used in vehicle production, where short cycle times, along with simultaneously high resolution and accuracy, are crucial. Attached Figure Description

[0068] Embodiments of the present invention are illustrated in detail with the aid of the accompanying drawings. The drawings are as follows:

[0069] Figure 1 A perspective view of a vehicle fender and equipment used for photogrammetry of the object are shown.

[0070] Figure 2 A side view of a vehicle fender and equipment used for photogrammetry of the object are shown.

[0071] Figure 3 Showing another side view of the vehicle fender and the equipment used for photogrammetry of the object;

[0072] Figure 4 This shows another side view of the vehicle's fender and the equipment used for photogrammetry of the object. Detailed Implementation

[0073] Figure 1 , 2Figures 3 and 4 show two imaging units 2a and 2b and an illumination unit 3 for photogrammetry of object 1. A light pattern 4 is projected onto the fender 12 of vehicle 8 by the illumination unit 3. The light pattern 4 is captured by the two imaging units 2a and 2b. The light pattern 4 projected onto vehicle 8 is moved by exciting the illumination unit 3 or at least one component of the illumination unit 3 to vibrate. In the evaluation unit, a 3D point cloud is stereoscopically determined from the captures of the light pattern 4 projected onto the vehicle during the vibration of the illumination unit 3 by the two imaging units 2a and 2b. This point cloud corresponds to the positions of points on the surface of the object to be measured.

[0074] Vehicle 8 has wheels 6 mounted on vehicle 8. Fender 12 is part of the body of vehicle 8. Fender 12 terminates at the lower end of fender edge 7 in the direction toward wheel 6.

[0075] Vehicle 8 is placed in a test bench with a coordinate system in which the Z-axis is a vertical axis, the X-axis is an axis extending in the horizontal plane of the test bench in the longitudinal direction of the vehicle placed on the test bench for testing, and the Y-axis is an axis extending in the horizontal plane of the test bench perpendicular to the X-axis. Figure 2 The diagram shows the Z-axis and X-axis. The Y-axis extends into the drawing plane.

[0076] like Figure 2 As further shown, in the first step, a subset of points is identified from the points of the 3D point cloud 9. This subset is formed by the intersection of the points of the point cloud 9 with multiple volumes 10. Each volume 10 is defined by two planes extending not only in the Y-axis direction but also in the Z-axis direction. These two planes have a distance Δx between them in the X-axis direction. These volumes 10 are located at adjacent positions x on the X-axis. n Points within this volume 10 of the point cloud 9 are represented by crosses, and points outside this volume 10 of the point cloud 9 are represented by circles.

[0077] The distance Δx between the two planes is greater than the average distance between the points in point cloud 9, but preferably less than twice the distance between the points in point cloud 9. Advantageously, each volume 10 in this subset has at least one point in its Z coordinate. Thus, the points in a volume 10 form a curved and substantially vertical line following the surface of the vehicle. The points of this curved line are essentially located in a plane that extends in the Y and Z directions. The position and orientation of the fender edge 7 are determined based on the subset of points in the 3D point cloud 9 as the resulting dataset.

[0078] In this regard, Figure 2 The formation of a subset according to the present invention is shown.

[0079] like Figure 3As shown, in the second step, a first reduced subset is generated from the points in the point cloud of the subset. Only a portion of the points in the subset are included in the first reduced subset. The distance between points included in the first reduced subset is greater than the distance between points in the subset itself.

[0080] Points within a subset that are accepted into the first reduced subset are represented by a cross. Points within a subset that are not accepted into the first reduced subset are represented by a circle. Figure 3 In the illustration, every second point is removed from the subset upon being admitted to the first reduced subset. The larger point spacing and associated smaller point density in the first reduced subset allow for a particularly rapid, preliminary, and coarse determination of the position and orientation of the fender 7 within the first dataset.

[0081] In this regard, Figure 3 The illustration relates to a visualization of determining a first reduced subset in the sense of some embodiments of the invention. That is, determining a first dataset (in the sense of some embodiments of the invention) that corresponds to the position and orientation data of the fender edge 7 based on the data of the first reduced subset.

[0082] like Figure 4 As shown, in the next step relative to Figure 3 The diagram generates a second reduced subset. This is done as follows: the points in the point cloud 9 of the subset intersect with the defined environment surrounding the points in the first dataset. Points within the subset that are admitted to the second reduced subset are represented by crosses. Points within the subset that are not admitted to the second reduced subset are represented by circles. Based on the data from the second reduced subset, the position and orientation of the fender edge 7 are determined in the resulting dataset.

Claims

1. A method for measuring the fender edge (7) of a vehicle (8) in a test bench, wherein, The test bench has a coordinate system in which the Z-axis is the vertical axis of the test bench, the X-axis is the axis of the test bench extending in the longitudinal direction of the vehicle (8) placed on the test bench for testing in a horizontal plane, and the Y-axis is an axis extending perpendicular to both the X-axis and the Z-axis. The method includes the following steps: - An invariant light pattern (4) is projected onto the vehicle (8) by means of at least one illumination unit (3), the light pattern (4) being divisible into sub-regions of equal size, such that each sub-region of the light pattern (4) is individualized in such a way that each sub-region of the light pattern (4) is unique within the light pattern (4). -The light pattern (4) projected onto the vehicle (8) is captured by two imaging units (2a, 2b), and the two imaging units (2a, 2b) capture the light pattern (4) currently projected onto the vehicle (8) respectively. -The light pattern (4) projected onto the vehicle (8) is moved by exciting the vibration of the lighting unit (3) or at least one component of the lighting unit (3). -A 3D point cloud is determined stereoscopically from the capture of a light pattern (4) projected onto the vehicle (8) during vibration of the illumination unit (3) or at least one component of the illumination unit (3) by the two imaging units (2a, 2b). - Identify a subset of points from a 3D point cloud (9), the subset being formed by the intersection of points of the point cloud (9) with a plurality of volumes (10), each volume (10) being defined by two planes extending not only in the Y-axis direction but also in the Z-axis direction, the two planes being spaced apart from each other in the X-axis direction, the plurality of volumes (10) being located at adjacent positions x on the X-axis. n Therefore, the subset includes only points within the volume. - The location and orientation of the fender edge (7) are determined by a subset of points based on the 3D point cloud as the result dataset.

2. The method according to claim 1, characterized in that, Before determining the location and orientation of the fender edge (7), select the data for evaluation. The method is to generate a first reduced subset of points of the point cloud (9) from the subset of points of the 3D point cloud, in such a way that only points of the point cloud in a portion of the volume (10) are considered. In the first evaluation step, the position and orientation data of the fender edge (7) are determined based on the points of the first reduced subset as the first dataset. The position and orientation data of the fender edge (7) in the second dataset are determined from the position and orientation data of the fender edge (7) in the first dataset in the following manner: In addition to the position and orientation data of the fender edge (7) in the first dataset, supplementary position and orientation data of the fender edge (7) are determined by extrapolating the position and orientation data of the fender edge (7) in the first dataset for the volume (10) not considered when generating the first reduced subset, and the second dataset is formed by the union of the position and orientation data of the fender edge (7) in the first dataset and the supplementary position and orientation data of the fender edge (7). Specifically, a second reduced subset is generated from the subset of points in the 3D point cloud by forming an intersection between the points in the subset's point cloud and the defined environment surrounding the points in the second dataset. The location and orientation of the fender edge (7) in the result dataset are determined based on the data from the second reduced subset.

3. The method according to claim 2, characterized in that, When generating the first reduced subset, only a portion of the points of the subset in the volume (10) considered when generating the subset will be admitted into the first reduced subset, and the point spacing between the points admitted into the first reduced subset is greater than the point spacing in the subset.

4. The method according to claim 1, characterized in that, Before determining the location and orientation of the fender edge (7), select the data for evaluation. - The method is to generate a first reduced subset of points of the point cloud (9) from the subset of points of the 3D point cloud, by admitting only a portion of the points of the subset into the first reduced subset in such a way that the point spacing between the points admitted into the first reduced subset is greater than the point spacing in the subset. - In the first evaluation step, the position and orientation data of the fender edge (7) are determined based on the points of the first reduced subset as the first dataset. - A second reduced subset is generated from the subset of points in the 3D point cloud by forming an intersection between the points in the subset and the defined environment surrounding the points in the first dataset. - Determine the position and orientation of the fender edge (7) in the result dataset based on the data from the second reduced subset.

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