Abstract: 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.

Abstract: A mounting system for a work machine includes a first member extending along a vertical axis of the mounting system, and a second member extending along the vertical axis and spaced apart from the first member along a lateral axis of the mounting system. The mounting system also includes a bracket assembly extending between the first member and the second member. The bracket assembly is disposable at a location along the vertical axis based on a removable coupling of the bracket assembly with each of the first member and the second member. The mounting system further includes an imaging device coupled with the bracket assembly. A position of the imaging device is adjustable with respect to the lateral axis of the mounting system and the vertical axis, such that a portion of a work implement of the work machine lies in a field of view of the imaging device.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method for loading a payload carrier of a machine includes receiving, from a camera on the machine, a two-dimensional image of an interior of the payload carrier as material is loaded into the payload carrier. The method further includes filtering the image to identify a contour of the loaded material and determining an area of the contour. The method further includes controlling a display device indicate the determined area.

Abstract: A method for loading a payload carrier of a machine includes receiving, from a camera on the machine, a two-dimensional image of an interior of the payload carrier as material is loaded into the payload carrier. The method further includes sectioning the two-dimensional image into a plurality of regions, and determining, for individual of the regions, whether the region includes a representative of fill material. The method may also include determining a fill volume based on the regions having fill and those not having fill.

Abstract: A method for loading a payload carrier of a machine includes receiving, from a camera on the machine, a two-dimensional image of an interior of the payload carrier as material is loaded into the payload carrier. The method further includes sectioning the two-dimensional image into a plurality of regions, and determining, for individual of the regions, whether the region includes a representative of fill material. The method may also include determining a fill volume based on the regions having fill and those not having fill.

Abstract: A method for loading a payload carrier of a machine includes receiving, from a camera on the machine, a two-dimensional image of an interior of the payload carrier as material is loaded into the payload carrier. The method further includes filtering the image to identify a contour of the loaded material and determining an area of the contour. The method further includes controlling a display device indicate the determined area.