A first in-situ sensor detects a characteristic value as a mobile machine operates at a worksite. A second in-situ sensor detects a material dynamics characteristic value as the mobile machine operates at the worksite. A predictive model generator generates a predictive model that models a relationship between the characteristic and the materials dynamics characteristic based on the characteristic value detected by the first in-situ sensor and the material dynamics characteristic value detected by the second in-situ sensor. The predictive model can be output and used in automated machine control.

A combine includes: a reaper to reap planted grain culms in a field; a threshing apparatus to thresh the reaped grain culms and separate the reaped grain culms into separated material containing normal grain and material to be discharged other than the separated material; a grain tank in which the separated material is storable; a conveying apparatus to convey the separated material from a separation section to the grain tank; a temporary storage section to take out and store some of the separated material that is being conveyed by the conveying apparatus; an image capture unit to capture an image of the separated material stored in the temporary storage section; and an image analysis module to analyze the image captured by the image capture unit, and perform distinguishing processing for distinguishing the normal grain in the separated material stored in the temporary storage section from foreign matter.

An agricultural work machine includes a geographic position sensor that detects a geographic location of the agricultural work machine. An in-situ sensor detects a value of a dynamic response characteristic of the agricultural work machine corresponding to the geographic location. A predictive model generator generates a predictive model that models a relationship between the terrain feature characteristic and the dynamic response characteristic based on a value of the terrain feature characteristic in a prior information map at the geographic location and a value of the dynamic response characteristic sensed by the in-situ sensor at the geographic location. A predictive map generator generates a functional predictive dynamic response map of the field, that maps predictive values of the dynamic response characteristic to the different geographic locations in the field, based on the values of the terrain feature characteristic in the prior information map and based on the predictive model.

An automatic fill control system on a material loading vehicle generates an output indicative of a current fill level of a receiving vehicle into which the material loading vehicle is loading material. A fill level processing system generates a fill parameter indicative of when the receiving vehicle will reach a target capacity. The fill parameter is communicated to a mobile application on a mobile device in a receiving vehicle.

An apparatus is presented that receives first and second parameters including first parameters from plural harvesting machines, determines a batch unload for a specified quantity of material to unload from each of the harvesting machines, requests permission to receive the batch unload from one of the harvesting machines, and communicates a control signal to trigger the requested batch unload from the one of the harvesting machines.

An agricultural system for determining crop loss of an agricultural harvester may include a support beam extending along a lateral direction between first and second lateral ends, and one or more impact sensors supported on the support beam. Each of the one or more impact sensors is configured to generate data indicative of a crop impact location of each crop impact of a plurality of crop impacts on the support beam between the first and second lateral ends. Additionally, the agricultural system may include a computing system communicatively coupled to the one or more impact sensors, where the computing system is configured to determine the crop impact location of each crop impact of the plurality of crop impacts on the support beam between the first and second lateral ends based at least in part on the data from the one or more impact sensors.

A detector detects an overall fill level of a receiving vehicle. A mobile device on the receiving vehicle includes a mobile application that receives and displays the overall fill level of the receiving vehicle. The overall fill level can be overlaid on a geographic map that shows locations of multiple receiving vehicles, in which case an overall fill level indicator for each receiving vehicle is displayed on the geographic map as well.

An embodiment includes a system for sensing harvested grain levels within an agricultural harvester. The system including a grain tank configured to receive harvested grain, a sensor configured to emit a sensor beam into the grain tank for reflection off of the top surface of the harvested grain, and a reflective target integrated into a bottom surface of the grain tank at a minimum detectable grain level within the grain tank. The bottom surface of the grain tank being angled towards the sensor, the minimum detectable grain level being defined by a minimum grain level within the grain tank at which the top surface of the harvested grain is contacted by the sensor beam, and the reflective target being configured to reflect the sensor beam when the current grain level is vertically below the minimum detectable grain level.

Described herein are technologies that use LIDAR and computer vision to detect a location of a receiving vehicle relative to a forage harvester, fill levels of crop material within the receiving vehicle, and path and landing position of material expelled from the forage harvester and received by a bin of the receiving vehicle. The technologies use such information as feedback for operating the harvester or the receiving vehicle. Some embodiments detect ground level in front of the harvester or the receiving vehicle, and such information is used as feedback too. Some embodiments include a link to communicate the feedback to a GUI for user visualization of the feedback and semi-automated operations of the harvester or the receiving vehicle. For example, readings from LIDAR and a camera of the harvester detect a topography of the material deposited in the bin of the receiving vehicle, and a GUI outputs the topography.

A receiving vehicle is automatically identified and the number of times it is filled is automatically counted. Control signals can be generated based on the number of times the receiving vehicle is filled.