Snap-on Inc.

Snap-on Technologies, Inc.

Fmc Corporation

Other

Steven W Rogers

Adam C Brown

David A Jackson

George Michael Gill

Eric R Sellers

Robert J D'Agostino

Michael L Baird

Bradley R Lewis

Ronald D Swayne

Michael J Kling

Eric F Bryan

Brian K Gray

Donald J Christian

James L Dale, Jr

Bryan C Minor

David R Coburn, Ii

James Rodney Harrell

Alan David Casby

Rajani K Pulapa

Rodney Harrell

Jean De Bellefeuille

Jean De Belleuille

Chance Robinson

Robert O Moran

Hanford D Monroe

Darwin Y Chen

Michael J Kling, Iii

Richard J Poe

Joel A Kunert

Brandon J McGinley

Mike Kling

Matthew T Foreman

Sean P Lecrone

Larry D Klotz

Jonathan A Sperry

Elizabeth Anne Downing

Stephen L Glickman

Raymond Titsworth

Donald L Walchuk

Carl W Pruitt

John C Brennan

Patrick Brendan O'Mahony

Ju Zheng

Gary L Sandusky

James F Mashburn

Joe Gibbs

Brian O'Sullivan

Jean deBelleuille

Ronald C Swayne

Jeffery G Craig

Sherman Paul

Jean O De Bellefeuille

Anthony Carroll

Brian McAuliffe

Eric Bryan

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.

Wheel aligner with advanced diagnostics and no-stop positioning

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.

Wheel aligner with improved accuracy and no-stop positioning using a drive direction calculation

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.

Apparatus and method for calibrating and aligning automotive sensors

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.

Wheel aligner with improved accuracy and no-stop positioning, using a drive direction calculation

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.

Self-calibrating wheel aligner with improved portability

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.

Vehicle wheel alignment methods and systems

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.

Motor control system for a self-calibrating multi-camera alignment system

Growing community of inventors

Conway, AR, United States of America

Steven W Rogers