Abstract: A camera calibration tool for calibrating one or more cameras of a mobile machine comprising calibration targets and a net. Each of the calibration targets comprises identifiable indicia. The net is adapted to be coupled to the mobile machine. The net has one or more configurations that define predetermined target locations, with location markers, in a predetermined layout. The calibration targets are positioned respectively at the predetermined target locations in the predetermined layout to calibrate the one or more cameras by use of the calibration targets.

Abstract: An upper point cloud estimator is configured to estimate a three-dimensional representation of the crop canopy based on collected stereo vision image data. A lower point cloud estimator is configured to estimate a ground three-dimensional representation or lower point of the ground based on the determined average. The electronic data processor is configured to determine one or more differences between the upper point cloud (or upper surface) of the crop canopy and a lower point cloud of the ground, where each difference is associated with a cell within a grid defined by the front region. The electronic data processor is capable of providing the differences to a data processing system to estimate a yield or differential yield for the front region, among other things.

Abstract: Methods, systems, apparatus, and articles of manufacture for camera calibration are disclosed. An example apparatus includes memory, instructions, and programmable circuitry to execute the instructions to detect, based on video frames captured by a camera positioned on a vehicle, a ground plane of the vehicle, determine, based on the ground plane, a first position parameter of the camera with respect to a coordinate system of the vehicle, track a plurality of features between ones of the video frames, and determine, based on the plurality of features, a second position parameter of the camera with respect to the coordinate system of the vehicle, the first position parameter different from the second position parameter.

Abstract: An upper point cloud estimator is configured to estimate a three-dimensional representation of the crop canopy based on collected stereo vision image data. A lower point cloud estimator is configured to estimate a ground three-dimensional representation or lower point of the ground based on the determined average. The electronic data processor is configured to determine one or more differences between the upper point cloud (or upper surface) of the crop canopy and a lower point cloud of the ground, where each difference is associated with a cell within a grid defined by the front region. The electronic data processor is capable of providing the differences to a data processing system to estimate a yield or differential yield for the front region, among other things.

Abstract: A camera calibration tool for calibrating one or more cameras of a mobile machine comprising calibration targets and a net. Each of the calibration targets comprises identifiable indicia. The net is adapted to be coupled to the mobile machine. The net has one or more configurations that define predetermined target locations, with location markers, in a predetermined layout. The calibration targets are positioned respectively at the predetermined target locations in the predetermined layout to calibrate the one or more cameras by use of the calibration targets.

Abstract: A camera calibration tool for calibrating one or more cameras of a mobile machine comprising calibration targets and a net. Each of the calibration targets comprises identifiable indicia. The net is adapted to be coupled to the mobile machine. The net has one or more configurations that define predetermined target locations, with location markers, in a predetermined layout. The calibration targets are positioned respectively at the predetermined target locations in the predetermined layout to calibrate the one or more cameras by use of the calibration targets.

Abstract: A perception system coupled to a harvesting head that includes row units, and slip clutches configured to couple the row units to a drive shaft and automatically disengage a jammed row unit. The perception system includes vision sensors collecting image data in front of the head, and a processor that processes the image data, and notifies the operator when it detects excessive crop buildup in front of one of the row units based on the image data. The perception processor can activate a notification device, and it can indicate which row unit has the detected crop buildup. The vision sensors can be positioned to have separate or overlapping fields of view covering the row units. A method of collecting image data in front of the row units, processing the image data to detect excessive crop buildup, and notifying the operator of detected buildups.

Abstract: A computer-implemented method includes obtaining harvest data indicative of a prior harvesting operation on a field, identifying a region of the field having already-harvested crop plants based on the harvest data, detecting a characteristic of crop plants in a field in a path of an agricultural harvesting machine in a direction of travel, generating, based on the detected characteristic, a height metric representing a height of the crop plants on a particular area of the field, and generating a control signal to control the agricultural harvesting machine based on the height metric and the identified region.

Abstract: A camera calibration tool for calibrating one or more cameras of a mobile machine comprising calibration targets and a net. Each of the calibration targets comprises identifiable indicia. The net is adapted to be coupled to the mobile machine. The net has one or more configurations that define predetermined target locations, with location markers, in a predetermined layout. The calibration targets are positioned respectively at the predetermined target locations in the predetermined layout to calibrate the one or more cameras by use of the calibration targets.

Abstract: A computer-implemented method includes obtaining harvest data indicative of a prior harvesting operation on a field, identifying a region of the field having already-harvested crop plants based on the harvest data, detecting a characteristic of crop plants in a field in a path of an agricultural harvesting machine in a direction of travel, generating, based on the detected characteristic, a height metric representing a height of the crop plants on a particular area of the field, and generating a control signal to control the agricultural harvesting machine based on the height metric and the identified region.