Snap-on Inc.

Other

Snap-on Technologies, Inc.

Eric F Bryan

Steven W Rogers

Adam C Brown

David A Jackson

George Michael Gill

Eric R Sellers

Patrick O'Mahony

Michael J Kling

Michael J Robb

Manjula Gururaj

Steve L Glickman

Brandon J McGinley

James L Dale, Jr

Darwin Y Chen

Steve W Rogers

Niall Davidson

Steven C Rogers

Ronald C Swayne

Patrick Brendan O'MAHONY

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

Inventory control systems for monitoring the removal and replacement of objects are described. An exemplary system includes at least one storage drawer, each storage drawer includes at least one storage location for storing objects, and configured to move in a first direction allowing increasing access to storage locations of the drawer, and a second direction allowing decreasing access to storage locations of the drawer. An image sensing device is provided to form at least one first image of the storage locations when a respective storage drawer moves in the second direction. The system includes a data processor configured to receive information representing images of the storage locations generated by the image sensing device, and determine an inventory condition of the objects stored in the respective storage drawer according to the at least one first image.

Image-based inventory control system

A position measurement apparatus and methodology is provided. Embodiments include a probe including an acoustic signal source, an optical signal source, and a probe processor for driving the signal sources such that the signals of the acoustic source and the optical source have a known temporal relationship to each other. A receiver receives the optical and acoustic signals, and a processor communicates with and controls the probe and the receiver, and processes data from the receiver. The acoustic signal source is a sinusoidally varying acoustic energy source, and the acoustic signal received by the receiver comprises a sinusoidal signal. The processor correlates the received sinusoidal signal to a mathematical reference sinusoidal signal, and determines a specific cycle and a specific phase as a time of flight measurement point based on the correlation.

Position measurement for collision repair systems

A wheel alignment head and system use advanced power management to reduce non-essential power consumption, to extend operation time between charges. The wheel alignment head is operable in a first operation state and a second operation state that consumes less power than the first operation state. In response to an occurrence of at least one of preset events, the wheel alignment head switches its operation from the first operation mode to the second operation mode.

Wheel alignment head and system with advanced power management

An integrated circuit (IC), for use in an imaging module of a wheel alignment system, incorporates an image sensor as well as a number of other features. Some of the added features are implemented within the integrated circuit. The IC also incorporates interfacing for signaling or communication with other devices in the imaging module or elsewhere in the wheel alignment system. Some examples of added internal features include a temperature sensor, unique chip ID, and chip power control. The addition of analog and/or digital I/O to the integrated circuit enables control of an image module illumination function, control of an imaging module positioning function, various cooling functions, and operator interface control. A communications hub may be added to the IC, to enable operation in a networked system environment.

Integrated circuit image sensor for wheel alignment systems

A sensing head and system utilizes fault tolerant design and self-diagnosis. Alternative operation modes are provided when one or more functional modules or components fail. Unique designs provide redundant system resources. Self-diagnoses and tests are provided to isolate and identify sources of malfunctions.

Fault tolerant wheel alignment head and system

Methods and systems for measuring and calculating wheel alignment angles are disclosed. The measuring methods include mitigating alignment error by compensating for wheel runout, and further include measuring wheel runout while the wheel maintains contact with an alignment surface.

Wheel alignment with surface-oriented runout determination

Methods and devices for measuring and calculating wheel alignment angles. Light weight and mechanically robust accelerometers in measurement heads are attached to a vehicle's wheels during an alignment procedure. The output of the accelerometers may be compensated for effects of temperature or thermal hysteresis by memory lookup or a temperature based feedback control loop.

Sensing steering axis inclination and camber with an accelerometer

In a machine vision system utilizing computer processing of image data, an imaging module incorporates the image sensor as well as pre-processing circuitry, for example, for performing a background subtraction and/or a gradient calculation. The pre-processing circuitry may also compress the image information. The host computer receives the pre-processed image data and performs all other calculations necessary to complete the machine vision application, for example, to determine one or more wheel alignment parameters of a subject vehicle. In a disclosed example useful for wheel alignment, the module also includes illumination elements, and the module circuitry provides associated camera control. The background subtraction, gradient calculation and associated compression require simpler, less expensive circuitry than for typical image pre-processing boards. Yet, the pre-processing at the imaging module substantially reduces the processing burden on the host computer when compared to machine vision implementations using direct streaming of image data to the host computer.

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Conway, AR, United States of America

Eric F Bryan