Abstract: A method for determining an angle of a tip of a ripper shank includes a controller receiving an input command. The controller estimates an angle of the tip based on one or more parameters of the input command. Further, the controller acquires a video feed of the ripper shank and detects an object in the video feed. The controller identifies the object as one of the ripper shank or a component movable with a movement of the ripper shank based on a match of a color of the object to a predefined color and a match of a profile of the object to a predefined profile. The controller co-relates the profile to an angular value in a map table and sets the angular value to be an actual angle of the tip over the angle of the tip estimated based on the input command.

Abstract: A method for determining an angle of a tip of a ripper shank includes a controller receiving an input command. The controller estimates an angle of the tip based on one or more parameters of the input command. Further, the controller acquires a video feed of the ripper shank and detects an object in the video feed. The controller identifies the object as one of the ripper shank or a component movable with a movement of the ripper shank based on a match of a color of the object to a predefined color and a match of a profile of the object to a predefined profile. The controller co-relates the profile to an angular value in a map table and sets the angular value to be an actual angle of the tip over the angle of the tip estimated based on the input command.

Abstract: A device is disclosed. The device may obtain a machine model of a machine and associated motion data for the machine model of the machine. The device may render the machine model into a rendered environment associated with a set of characteristics. The device may capture a set of images of the machine model and the rendered environment based on rendering the machine model into the rendered environment. The device may determine bounding box data for the set of images of the machine model and the rendered environment based on the position of the machine model within the rendered environment relative to an image capture orientation within the rendered environment. The device may provide the set of images of the machine model and the rendered environment and the bounding box data as a data set for object detection.

Abstract: A device for measuring wear is disclosed. The device may receive images associated with a component, and may receive a three-dimensional (3D) model of the component. The device may generate an image point cloud based on the images, and may generate a model point cloud based on the 3D model of the component. The device may perform a first alignment of the image point cloud and the model point cloud to generate first-aligned point clouds, and may perform a second alignment of the first-aligned point clouds to generate second-aligned point clouds. The device may generate 3D mask regions based on the second-aligned point clouds, and may project the 3D mask regions on the images. The device may process the 3D mask regions, projected on the images, to determine reference points in the images, and may determine an amount of wear associated with the component based on the reference points.

Abstract: A device is disclosed. The device may obtain a machine model of a machine and associated motion data for the machine model of the machine. The device may render the machine model into a rendered environment associated with a set of characteristics. The device may capture a set of images of the machine model and the rendered environment based on rendering the machine model into the rendered environment. The device may determine bounding box data for the set of images of the machine model and the rendered environment based on the position of the machine model within the rendered environment relative to an image capture orientation within the rendered environment. The device may provide the set of images of the machine model and the rendered environment and the bounding box data as a data set for object detection.

Abstract: A method for tracking workers at a worksite is disclosed. The method includes acquiring a video of the worksite and detecting a movement of objects in the video. Each object is represented by a plurality of pixels. The method includes identifying an item associated with at least one object by clustering a set of pixels of the plurality of pixels based on a color of the set of pixels. Next, the method includes determining the item as a hard hat based on at least a shape of the set of pixels, and identifying the object as a specific worker based on the color of the set of pixels. The method also includes generating a movement data associated with the specific worker based on a tracking of the hard hat.

Abstract: A device for measuring wear is disclosed. The device may receive images associated with a component, and may receive a three-dimensional (3D) model of the component. The device may generate an image point cloud based on the images, and may generate a model point cloud based on the 3D model of the component. The device may perform a first alignment of the image point cloud and the model point cloud to generate first-aligned point clouds, and may perform a second alignment of the first-aligned point clouds to generate second-aligned point clouds. The device may generate 3D mask regions based on the second-aligned point clouds, and may project the 3D mask regions on the images. The device may process the 3D mask regions, projected on the images, to determine reference points in the images, and may determine an amount of wear associated with the component based on the reference points.

Abstract: A device for measuring wear is disclosed. The device may receive images associated with a component, and may receive a three-dimensional (3D) model of the component. The device may generate an image point cloud based on the images, and may generate a model point cloud based on the 3D model of the component. The device may perform a first alignment of the image point cloud and the model point cloud to generate first-aligned point clouds, and may perform a second alignment of the first-aligned point clouds to generate second-aligned point clouds. The device may generate 3D mask regions based on the second-aligned point clouds, and may project the 3D mask regions on the images. The device may process the 3D mask regions, projected on the images, to determine reference points in the images, and may determine an amount of wear associated with the component based on the reference points.

Abstract: A method for tracking workers at a worksite is disclosed. The method includes acquiring a video of the worksite and detecting a movement of objects in the video. Each object is represented by a plurality of pixels. The method includes identifying an item associated with at least one object by clustering a set of pixels of the plurality of pixels based on a color of the set of pixels. Next, the method includes determining the item as a hard hat based on at least a shape of the set of pixels, and identifying the object as a specific worker based on the color of the set of pixels. The method also includes generating a movement data associated with the specific worker based on a tracking of the hard hat.

Abstract: A method for path detection associated with ground engaging teeth of an implement is the provided. The method includes receiving, by a controller, an image feed of a dump operation being performed by the implement. The method includes detecting the ground engaging teeth in each of the plurality of frames. The method includes analyzing a path traced by the ground engaging teeth over the plurality of frames. The method includes determining the path traced by the ground engaging teeth based on aggregated path information. The method includes comparing the determined path traced by the ground engaging teeth with a pre-determined path. The method includes identifying if at least one of the ground engaging teeth is missing based on the comparison The method includes providing a notification of the missing ground engaging teeth based on the identification.