Caterpillar Inc.

Caterpillar Paving Products Inc.

Progress Rail Services Corporation

Lawrence Andrew Mianzo

Tod Andrew Oblak

John Michael Plouzek

Shawn Nainan Mathew

Raymond Alan Wise

Mark E Hartman

Joseph E Forcash

Jeffrey Thomas Stringer

Paul Edmund Rybski

Daniel Paul Adler

Michael Hoffelder

Narayana G Nadukuru

Nathaniel S Doy

Todd Alex Impola

James Peterson

Bradley Scott Kriel

Marc David Miller

Shastri Ram

Joe E Forcash

Robert C McCall

Jeffrey J Carter, Jr

Jeff T Stringer

John F Halterman

Sri Sekharan

Carl Hendricks

Lyle Taylor

Siddarth Desikan

Shanmukha Bhumireddy

Derrill J Koelz

Darrell Cantrell

Mike Hoffelder

Chad A Moore

An example wear detection system receives a plurality of images from a plurality of sensors associated with a work machine. Individual sensors of the plurality of sensors have respective fields-of-view different from other sensors of the plurality of sensors. The wear detection system identifies a first region of interest and second region of interest associated with the at least one GET. The wear detection system determines a first set of image points and a second set of images points for the at least one GET based on geometric parameters associated with the GET. The wear detection system determines a wear level or loss for the at least one GET based on the GET measurement.

Ground engaging tool wear and loss detection system and method

An intelligent three dimensional scanner system mountable on a movable machine, including three dimensional scanner, a camera, and control circuitry. The control circuitry is configured to receive three dimensional point data from the three dimensional scanner, receive two dimensional image data from the camera, input the two dimensional image data to a machine learning model, which identifies objects in the two dimensional image data, fuse the three dimensional point data with the identified objects in the two dimensional image data in order to identify the objects in the three dimensional point data, and control a scan pattern to direct scanning resolution of the three dimensional scanner based on the identified objects.

Intelligent LiDAR scanning

An example wear detection system receives first image data related to at least one ground engaging tool (GET) of a work machine from one or more sensors at a first time instance in a dig-dump cycle of the work machine. The wear detection system processes the first image data to determine a first wear measurement and first wear level for the at least one GET. The wear detection system determines whether the first wear level is indicative of a GET replacement condition. The wear detection system generates an alert when the first wear level is indicative of the GET replacement condition. The wear detection system receives second image data related to the at least one GET a second time instance different from the first time instance when the first wear level is not indicative of the GET replacement condition and determines a second wear measurement and second wear level for the at least one GET. The wear detection system generates an alert indicative of the first wear level and the second wear level based on determining that the first wear level and the second wear level are indicative of the GET replacement condition.

A system and method for detecting buckled rail and for predicting a risk for rail buckling is disclosed. The method may comprise receiving data from a camera mounted on locomotive traveling on the railroad track. The data may include images of the buckled rail and dimensions of the buckled rail when the camera detects the buckled rail. The data may further include images of the ballast and condition of the ballast. The method may further comprise receiving data from a thermal camera mounted to the locomotive indicating the temperature of the rails. The method may further comprise transmitting an alarm signal to a display interface of a remote unit if the dimensions of the buckled rail meet a predetermined threshold, and predicting a risk for rail buckling based at least on the temperature of the rails and the condition of the ballast.

Rail buckle detection and risk prediction

An example wear detection system receives a left image and a right image of a bucket of a work machine having at least one ground engaging tool (GET). The example system identifies a first region of interest from the left image corresponding to the GET and a second region of interest from the right image corresponding to the GET. The example system also generates a left-edge digital image corresponding to the first region of interest and a right-edge digital image corresponding to the second region of interest. Further, the example system determines a sparse stereo disparity between the left-edge digital image and the right-edge digital image, and also determines a wear level or loss for the at least one GET based on the sparse stereo disparity.

A work machine, light detection and ranging (LiDAR) system, and method of reducing false object detections are disclosed. The work machine may include a frame, a power unit, a locomotive device, and the LiDAR system. The LiDAR system may include at least one laser, at least one sensor, a bracket, and a control unit configured to execute an object detection program. The LiDAR system is configured to exclude from its object detection program a plurality of beams emitted toward the work machine through a design of the bracket and/or software methods of the control unit. The method may include storing a database of exclude coordinates and using the database to filter out undesirable data samples from the object detection program.

Work machine with LiDAR having reduced false object detection

An example wear detection system receives first imaging data from one or more sensors associated with a work machine. The first imaging data comprises data related to at least one ground engaging tool (GET) of the work machine. The example system identifies a region of interest including data of the at least one GET within the first imaging data. Based on the identified region of interest, the example system controls a LiDAR sensor to capture second imaging data capturing the at least one GET that is of higher resolution than the first imaging data. The example system generates a three-dimensional point cloud of the at least one GET based on the second imaging data and determines a wear level or loss for the at least one GET based on the three-dimensional point cloud.

A system, method, and apparatus for real-time characterization of drilled particles during a drilling operation can be comprised of a light illumination source to output short-wave-infrared (SWIR) light toward the drilled particles as the drilled particles exit a drill hole being drilled by a drilling machine; a sensor to sense reflected short-wave-infrared (SWIR) light reflected from the drilled particles exiting the drill hole; and processing circuitry operatively coupled to at least the sensor. The processing circuitry can be configured to determine a spectrum of the reflected short-wave-infrared light sensed by the sensor, and determine particle characterization for a portion of the drilled particles by performing hyperspectral analysis on the determined spectrum and based on predetermined candidate particle characterizations.

Systems, methods, and apparatuses for real-time characterization of rock cuttings during rock drill cutting

A vision system for assisting an operator of a machine is provided. An image capturing device, mounted on the machine, is configured to capture an image of an environment of the machine. The vision system includes a controller configured to apply an object detection process to detect an object in the image. The controller determines a bounding box comprising one or more pixels associated with the object. The controller determines a height and a range associated with the object based on the bounding box. The controller extracts the one or more pixels within the bounding box. The controller is further configured to generate a three-dimensional (3D) view comprising the object based on the image captured by the image capturing device. The controller reinserts the one or more pixels as a vertical pop-up element with respect to a ground plane in the 3D view. A display is provided to display the 3D view to the operator of the machine.

Operator assistance vision system

A display system for displaying image data of an environment of a machine includes an imaging device. The imaging device generates image data of the environment of the machine. The imaging device stores the image data in an uncompressed form. The imaging device compresses the image data and generates signals indicative of the compressed image data. The display system further includes a display screen communicably coupled to the imaging device. The display screen receives the signals indicative of the compressed image data from the imaging device and displays the compressed image data on the display screen. The imaging device and the display screen identify whether a region of interest exists in the image data. The display screen displays the image data corresponding to the region of interest in the uncompressed form.

Display system for machine

A method for monitoring the movement of a work tool of a machine using a work tool vision a comprises sensing data related to the image of a work tool, selecting a template of an image of a work tool, and displaying the sensed image of the work tool after modifying the sensed image of the work tool by at least zooming on a portion of the sensed data of the image if the sensed data of the image of a work tool matches the template of an image of a work tool.

Work tool vision system

A method for testing a perception system is disclosed. The method includes detecting, by a processor, one or more objects in a composite image, the composite image including a first image and at least a portion of a second image. A first set of objects are detected in the first image. Further, the method includes comparing, by the processor, a second set of objects of the one or more objects detected in the portion of the second image with a set of previously detected objects in the portion of the second image. Furthermore, the method includes validating, the performance of the processor in the detection of the first set of objects in the first image by ensuring the second set of objects detected in the at least a portion of a second image matches the set of previously detected objects in the portion of the second image.

Systems and methods for testing an automatic perception system

A display system for displaying image data of an environment of a machine includes a display screen and a plurality of imaging devices communicably coupled to the display screen. Each of the plurality of imaging devices generates image data of the environment of the machine and has an associated operating parameter. The plurality of imaging devices stores the image data in an uncompressed form. The plurality of imaging devices compresses the image data and generates signals indicative of the compressed image data. The plurality of imaging devices receives the operating parameter associated with at least one another imaging device. The plurality of imaging devices transmits the compressed image data to the display screen based on the associated operating parameter and the received parameter of the at least one another imaging device. The plurality of imaging devices displays an image on the display screen based on the transmitted image data.

A method of classifying a work machine within a worksite is provided. The method may include receiving one or more captured images of the work machine from one or more image capture devices, identifying at least two classifiers within the captured images of the work machine, determining spatial relationships between the classifiers within the captured images, determining a classification and a pose of the work machine based on the spatial relationships, and displaying analytics based on the classification and the pose of the work machine.

Vehicle classification and vehicle pose estimation

A system for monitoring an implement of a work machine is provided. The system may include one or more image sensors mounted on the work machine configured to capture one or more images of a field of view associated with the implement, and an implement controller in electrical communication with the image sensors. The implement controller may be configured to receive the images from the image sensors, identify one or more interactive targets within the images, select one of the interactive targets based on proximity, and align the implement to the selected interactive target.

Growing community of inventors

Pittsburgh, PA, United States of America

Lawrence Andrew Mianzo