Abstract: Detecting a damage angle between a vehicle and a trailer. One example system includes an electronic controller and a rear-view camera configured to obtain video of the trailer. The electronic controller is configured to receive the video of the trailer from the rear-view camera and determine a damage point based upon the video of the trailer. The electronic controller is further configured to determine a change in a rotation angle of the trailer and determine a changed location of the damage point of the trailer based upon the change in the rotation angle of the trailer. The electronic controller is also configured to determine a damage angle based upon the changed location of the damage point relative to the vehicle and determine at least one maneuver to avoid collision between the damage point and the vehicle based upon the damage angle.

Abstract: A method for detecting information about at least one object and/or at least a part of the free space in a representation (4) of the environment of a system. The method comprises: a) performing ground truth generation; b) performing an obstacle and clearance detection; c) performing a generalization across different cameras and/or different digital image representations.

Abstract: Detecting a damage angle between a vehicle and a trailer. One example system includes an electronic controller and a rear-view camera configured to obtain video of the trailer. The electronic controller is configured to receive the video of the trailer from the rear-view camera and determine a damage point based upon the video of the trailer. The electronic controller is further configured to determine a change in a rotation angle of the trailer and determine a changed location of the damage point of the trailer based upon the change in the rotation angle of the trailer. The electronic controller is also configured to determine a damage angle based upon the changed location of the damage point relative to the vehicle and determine at least one maneuver to avoid collision between the damage point and the vehicle based upon the damage angle.

Abstract: A method for tire inspection which includes taking at least one image of at least one first area of a tread of a tire that is to be inspected; determining the profile depth of a second area of the tread of the tire, the second area being included in the first area; and displaying the profile depth of the at least one image of the at least one first area and the position of the second area in the first area. The method may additionally include automatically analyzing the images taken of the tread, so as to arrive at statements on the condition of the tread.

Abstract: A method for producing a masking instruction for a camera of a vehicle, the method including a setting step, a transforming step, and a storing step. In the setting step, interpolation points of a field-of-view boundary are set in a vehicle coordinate system using three-dimensional model data of the vehicle, the interpolation points being set from a camera perspective that is modeled in the model data. In the transforming step, vehicle coordinates of the interpolation points from the vehicle coordinate system are transformed into a spherical coordinate system to obtain spherical coordinates of the interpolation points. In the storing step, a mask curve defined by the interpolation points, is stored in the spherical coordinate system in order to produce the masking instruction.

Abstract: A method for producing a masking instruction for a camera of a vehicle, the method including a setting step, a transforming step, and a storing step. In the setting step, interpolation points of a field-of-view boundary are set in a vehicle coordinate system using three-dimensional model data of the vehicle, the interpolation points being set from a camera perspective that is modeled in the model data. In the transforming step, vehicle coordinates of the interpolation points from the vehicle coordinate system are transformed into a spherical coordinate system to obtain spherical coordinates of the interpolation points. In the storing step, a mask curve defined by the interpolation points, is stored in the spherical coordinate system in order to produce the masking instruction.

Abstract: A method for processing image data of two sensors of a stereo sensor system that are suitable for recording images, each of the sensors being configured to record the image data section by section in sensor sections of the sensor that are situated at different positions. The method includes providing information on a geometrical offset between the positions of two sensor sections of the first sensor and the second sensor which have corresponding image data, and reading out image information of the first sensor and image information of the second sensor, the reading out taking place with reference to the positions of the sensor sections, from which the image data are read out, using the offset.

Abstract: A method for determining characteristics of an axle geometry of a vehicle including the following: steering a wheel mounted on an axle of the vehicle to various steering positions having different steering angles; determining the spatial position of the wheel at the different steering positions; determining the particular axis of rotation of the wheel in the different steering positions from the results of the determination of the spatial position; modeling a parametric model of the steering axis; adapting the parametric model of the steering axis to the axes of rotation of the wheel determined from the measurement of the spatial position; and determining characteristics of the axle geometry from the adapted parametric model of the steering axis.

Abstract: A method for determining distances for chassis measurement of a vehicle having a body and at least one wheel includes determining a center of rotation of a wheel of the vehicle by projecting a structured light pattern at least onto the wheel, recording a light pattern reflected by the wheel using a calibrated imaging sensor system, determining a 3D point cloud from the reflected light pattern, and determining the center of rotation of the wheel from the 3D point cloud. The method also includes determining a point on the body by evaluating the previously determined 3D point cloud or by evaluating a plurality of grey-scale images recorded under unstructured illumination. A height level is determined as a vertical distance between the center of rotation of the wheel and the point on the body.

Abstract: A method and device are described for measuring a chassis and for measuring the chassis geometry of a vehicle, which includes providing a chassis measurement system having four measurement heads situated in known positions relative to one another, of which each has a monocular image recording device, the position of the measurement heads relative to one another being known, and the distance of the front measurement heads from one another differing from the distance of the rear measurement heads from one another.

Abstract: A laser projector for chassis alignment has a laser light source emitting a laser light beam, an optical element which generates a structured laser light pattern when it is irradiated by the laser light beam, a detector which is situated in such a way that it is irradiated by a sub-area of the structured laser light pattern and generates an output signal which is correlated with the radiation, and an evaluation unit which compares the output signal generated by the detector with at least one predefined setpoint value and turns off the laser light source if it detects a significant deviation of the output signal from the setpoint value.

Abstract: A manual distance measuring apparatus includes at least one computing unit, an image acquisition means and a laser measuring device, which determines a distance of a measurement point on a measurement object in a measurement direction during a measuring process. The computing unit is configured to control, at least by open-loop control, the measurement direction depending at least on an output characteristic variable of the image acquisition means.

Abstract: A method for determining the tumbling motion of a vehicle wheel and/or a measurement object attached to the vehicle wheel in the context of an axle measurement. The tumbling motion is executed relative to the precise wheel axis of rotation of the vehicle wheel and at least one orientation value is determined between the precise wheel axis of rotation and a reference axis. Using at least one image recording unit, at least two wheel features that are present on the vehicle wheel or are attached for the measurement are acquired as the vehicle travels past and are evaluated by an evaluation device situated downstream. Using the wheel features recorded as the vehicle travels past, a wheel coordinate system and a feature coordinate system are determined. The wheel coordinate system and the feature coordinate system are set into relation to one another in order to determine the orientation value.

Abstract: A chassis testing unit (2) according to the present invention, in particular a shock absorber testing unit, for a vehicle on a test set-up (4) includes at least one correlation sensor (14-18), having an associated lens, situated at the side of the test set-up (4). The correlation sensor (14-18) is directed toward the test set-up (4), and is designed to detect a time sequence of images of a section of a motor vehicle (6), in particular of the body of the motor vehicle (6) and of the motor vehicle wheel, moving on the test set-up (4), and to determine directional velocity components therefrom. The chassis testing unit also includes a data processing unit which is connected to the correlation sensor or correlation sensors (14-18), and which is designed to determine the motion of the motor vehicle, in particular of the body of the motor vehicle (6) and of the motor vehicle wheel, on the basis of the directional velocity components of the correlation sensor or correlation sensors (14-18).

Abstract: In a method for determining a wheel or axle geometry of a vehicle, the following steps are provided: illuminating a wheel region with structured and with unstructured light during a motion of at least one wheel and/or of the vehicle; acquiring multiple images of the wheel region during the illumination, in order to create a three-dimensional surface model having surface parameters, a texture model having texture parameters, and a motion model having motion parameters of the sensed wheel region; calculating values for the surface parameters, the texture parameters, and the motion parameters using a variation computation as a function of the acquired images, in order to minimize a deviation of the three-dimensional surface model, texture model, and motion model from image data of the acquired images; and determining a rotation axis and/or a rotation center of the wheel as a function of the calculated values of the motion parameters.

Abstract: A method for tire inspection which includes taking at least one image of at least one first area of a tread of a tire that is to be inspected; determining the profile depth of a second area of the tread of the tire, the second area being included in the first area; and displaying the profile depth of the at least one image of the at least one first area and the position of the second area in the first area. The method may additionally include automatically analyzing the images taken of the tread, so as to arrive at statements on the condition of the tread.

Abstract: A method for rectifying a camera image includes: receiving a plurality of distorted pixels of a distorted camera image; receiving a compressed rectifying rule, via an interface; and performing a decompression of the compressed rectifying rule, in order to obtain a decompressed rectifying rule for rectifying the distorted camera image. A plurality of rectified pixels of a distorted camera image is determined from the plurality of distorted pixels, using the decompressed rectifying rule.

Abstract: A method for processing image data of two sensors of a stereo sensor system that are suitable for recording images, each of the sensors being configured to record the image data section by section in sensor sections of the sensor that are situated at different positions. The method includes providing information on a geometrical offset between the positions of two sensor sections of the first sensor and the second sensor which have corresponding image data, and reading out image information of the first sensor and image information of the second sensor, the reading out taking place with reference to the positions of the sensor sections, from which the image data are read out, using the offset.

Abstract: The following features may be carried out: providing a wheel suspension alignment system having four measuring heads situated in a known position with respect to one another; recording a wheel or a measuring target mounted on it in an initial position of the vehicle; shifting the vehicle from the initial position to at least one further position; recording a wheel, or a measuring target mounted on it, of the vehicle standing in the further position; recording a reference target in at least one of the initial position and the further position of the vehicle, and determining from this an absolute scale; carrying out local 3D reconstructions for determining the translation vectors, the rotation vectors and the wheel rotational angles as well as the wheel rotational centers and the wheel rotational axes of the wheels; and determining the wheel suspension alignment parameters of the vehicle.

Abstract: A method for wheel suspension alignment includes: providing four measuring heads each having a monocular picture recording device; recording at least three geometrical details of one wheel, respectively, of a vehicle in an initial position, using each of the four measuring heads; carrying out relative motion between the vehicle and the measuring heads from the initial position into at least one further position; recording at least three geometrical details of one wheel, respectively, of the vehicle in the further position, using each of the four measuring heads; carrying out local 3D reconstructions for determining translation vectors, rotation vectors and wheel rotational angles between the at least two positions, and wheel rotational centers and wheel rotational axes from the recorded geometrical details; determining a global scale for the measuring heads by scaling the translation vectors to have the same length; and determining camber, single toe and/or total toe of the vehicle.