Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: Vehicle alignment systems and methods are disclosed which operate based on a calculation of “drive direction,” or the direction in which a vehicle is moving. Since a vehicle can be assumed to be a rigid body, each wheel has the same drive direction. Consequently, an alignment parameter of one wheel can be compared to the same parameter of another wheel by equating their drive direction, eliminating the need for the aligner to “see” both sides of the vehicle at the same time. Embodiments include a system having one or more cameras on a fixture carrying a calibration element for an ADAS system, and one or more targets placed on the vehicle to measure the drive direction of the vehicle. The drive direction is assumed to be parallel to the vehicle thrust line and can be used as the line for orientation of the fixture to the vehicle.

Abstract: Vehicle alignment systems and methods are disclosed which operate based on a calculation of “drive direction,” or the direction in which a vehicle is moving. Since a vehicle can be assumed to be a rigid body, each wheel has the same drive direction. Consequently, an alignment parameter of one wheel can be compared to the same parameter of another wheel by equating their drive direction, eliminating the need for the aligner to “see” both sides of the vehicle at the same time. Embodiments include a system having one or more cameras on a fixture carrying a calibration element for an ADAS system, and one or more targets placed on the vehicle to measure the drive direction of the vehicle. The drive direction is assumed to be parallel to the vehicle thrust line and can be used as the line for orientation of the fixture to the vehicle.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: Systems and methods are disclosed for calibrating and aligning automotive sensors, such as advanced driver assistance system (ADAS) sensors. Embodiments include a system having an image sensor mounted on a fixture in a known pose relative to the fixture. The image sensor is for viewing a target disposed on a vehicle and having a known pose relative to the vehicle, and for capturing image data of the target. A data processor is provided for performing the steps of calculating, using the image data, a pose of the target; calculating a pose of the image sensor relative to the vehicle using the calculated pose of the target; and generating instructions for positioning the fixture at a predetermined pose relative to the vehicle using the calculated pose of the image sensor relative to the vehicle.

Abstract: A vibrotactile support with suppressed distortion and destructive interference having a rigid frame within which is tensioned a high-density material panel in a supportive configuration. A low-durometer, high specific gravity material user interface pad is placed on the high-density panel on the user-supporting side and a plurality of acoustic drivers are attached to the opposing side of the high-density material panel to transmit vibrations through the high-density material panel, the pad, and the user's skin. The acoustic drivers are supplied from an amplifier which is supplied from an electronic audio source. The amplifier may also drive a set of headphones for the user. The audio source may be from any known electronic audio source, including audio-visual presentations. Various shapes and configurations of the vibrotactile support are possible. For non-limiting examples, the vibrotactile support may be configured as a lounge chair, upright chair, baby cradle, or flat bed.

Abstract: A vehicle wheel alignment system includes a pair of wheel mounted targets, a pair of reference targets mounted to a stationary reference, a pair of gravity sensors, and a pair of vehicle-mounted active heads mounted on first and second sides of the vehicle. The active heads each have an image sensor for producing image data of one of the reference targets and one of the wheel mounted targets. The gravity sensors are disposed on each side of the vehicle in a known relationship to either the respective reference targets or the image sensors. A data processor calculates, using the image data, a plurality of poses of the wheel mounted targets as the vehicle wheels rotate; calculates a vehicle drive direction using the target poses and a measured orientation relative to gravity from the gravity sensors; and calculates a wheel alignment measurement using the vehicle drive direction.

Abstract: A portable vehicle alignment system has a vertical central column with a carriage movable along its length, and a pair of camera arms pivotably attached to the carriage, each with a camera pod. The camera pods each have a camera for capturing image data of a respective vehicle-mounted target. One pod also has a calibration target disposed in a known relationship to its camera, and the other pod has a calibration camera disposed in a known relationship to its camera for capturing images of the calibration target. The camera arms pivot between an extended position where the cameras are disposed to capture image data of the vehicle targets and the calibration camera is disposed to capture images of the calibration target, and a folded position where the aligner has a width smaller than the width between the camera pods.

Abstract: A wheel alignment system includes a side-to-side reference including an active reference pod and a passive reference pod disposed on opposite sides of the vehicle. The active reference pod includes a reference image sensor fixedly attached to a reference target, for mounting on a first side of the vehicle such that the reference image sensor produces image data including a perspective representation of the passive reference pod disposed on a second/opposite side of the vehicle. In operation, alignment cameras on the opposite sides of the vehicle capture perspective representations of targets mounted to vehicle wheels and of targets of the active and passive reference pods. A computer processes the image data to compute an alignment measurement of the vehicle based on a spatial relationship between the active reference pod and the passive reference pod determined according to the image data produced by the reference image sensor.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: A wheel alignment system includes a side-to-side reference including an active reference pod and a passive reference pod disposed on opposite sides of the vehicle. The active reference pod includes a reference image sensor fixedly attached to a reference target, for mounting on a first side of the vehicle such that the reference image sensor produces image data including a perspective representation of the passive reference pod disposed on a second/opposite side of the vehicle. In operation, alignment cameras on the opposite sides of the vehicle capture perspective representations of targets mounted to vehicle wheels and of targets of the active and passive reference pods. A computer processes the image data to compute an alignment measurement of the vehicle based on a spatial relationship between the active reference pod and the passive reference pod determined according to the image data produced by the reference image sensor.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: Vehicle alignment systems and methods are disclosed which operate based on a calculation of “drive direction,” or the direction in which a vehicle is moving. Since a vehicle can be assumed to be a rigid body, each wheel has the same drive direction. Consequently, an alignment parameter of one wheel can be compared to the same parameter of another wheel by equating their drive direction, eliminating the need for the aligner to “see” both sides of the vehicle at the same time. Embodiments include a system having one or more cameras on a fixture carrying a calibration element for an ADAS system, and one or more targets placed on the vehicle to measure the drive direction of the vehicle. The drive direction is assumed to be parallel to the vehicle thrust line and can be used as the line for orientation of the fixture to the vehicle.

Abstract: Embodiments include a method for autonomous camera pod tracking of a vehicle during vehicle alignment. The method can include receiving, at a processor of an autonomous camera pod, at least one of vehicle target image data from a vehicle target camera or calibration target image data from a calibration camera, the vehicle target camera being adapted to acquire images of a target mounted to the vehicle, and the calibration camera being adapted to acquire images of a calibration target mounted to a sister autonomous camera pod. An optimal location of the autonomous camera pod can be calculated based on the received vehicle target image data or calibration target image data. The method can include transmitting, when it is determined to move the autonomous camera pod, a motor command to a motor drive of the autonomous camera pod, thereby causing the autonomous camera pod to move to the optimal location.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: A portable vehicle alignment system has a vertical central column with a carriage movable along its length, and a pair of camera arms pivotably attached to the carriage, each with a camera pod. The camera pods each have a camera for capturing image data of a respective vehicle-mounted target. One pod also has a calibration target disposed in a known relationship to its camera, and the other pod has a calibration camera disposed in a known relationship to its camera for capturing images of the calibration target. The camera arms pivot between an extended position where the cameras are disposed to capture image data of the vehicle targets and the calibration camera is disposed to capture images of the calibration target, and a folded position where the aligner has a width smaller than the width between the camera pods.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.

Abstract: A portable vehicle alignment system has a vertical central column with a carriage movable along its length, and a pair of camera arms pivotably attached to the carriage, each with a camera pod. The camera pods each have a camera for capturing image data of a respective vehicle-mounted target. One pod also has a calibration target disposed in a known relationship to its camera, and the other pod has a calibration camera disposed in a known relationship to its camera for capturing images of the calibration target. The camera arms pivot between an extended position where the cameras are disposed to capture image data of the vehicle targets and the calibration camera is disposed to capture images of the calibration target, and a folded position where the aligner has a width smaller than the width between the camera pods.

Abstract: A vehicle wheel alignment system has a plurality of cameras, each camera for viewing a respective target disposed at a respective wheel of the vehicle and capturing image data of the target as the wheel and target are continuously rotated a number of degrees of rotation without a pause. The image data is used to calculate a minimum number of poses of the target of at least one pose for every five degrees of rotation as the wheel and target are continuously rotated the number of degrees of rotation without a pause. At least one of the cameras comprises a data processor for performing the steps of preprocessing the image data, and calculating an alignment parameter for the vehicle based on the preprocessed image data.