Deere + Company

Matthew J Flood

Mark John Cherney

Andrew W Kahler

Richard John Lawler

Robert A Hamilton

Alek D Jerauld

Thomas Andrew Knopp

William K Borrenpohl

A work cycle detection and control system includes an angle detector that detects an angular position of an implement, operably coupled to a mobile machine, relative to a base of the mobile machine. The system also includes a range detector that detects a degree range of rotation, about the base, in which the angular position of the implement is located. Work cycle logic identifies a particular work cycle, from a plurality of different work cycles, that the mobile machine is performing, based on the degree range. An action signal generator generates an action signal, based on the particular work cycle.

Controlling a machine based on detected machine work cycles

A machine output detection and control system includes machine metric logic that detects a plurality of quantity metrics, each quantity metric corresponding to sensor information associated with at least one mobile machine in a plurality of different mobile machines. The system also includes normalization logic that aggregates the plurality of different quantity metrics to generate, for each mobile machine, a normalized production unit that is normalized across the plurality of different mobile machines. Dependency logic correlates the normalized production unit, for each mobile machine, to a machine dependency that identifies an order in which the plurality of different mobile machines operate at a jobsite. Further, action signal logic generates an action signal, based on the correlation.

Controlling forestry machines across a jobsite

A method includes controlling an unmanned aerial vehicle (UAV) to collect and forward information pertaining to a forestry worksite area. The UAV is controlled to fly to a first location and capture image information at the first location. The UAV is also controlled to fly to a second location, establish a communication connection between the UAV and a communication system at the second location, and send the captured image information to the communication system via the established connection. In another example, the UAV uploads (e.g., sends) the data to a communication system (e.g., computing device operated by an operator), and the uploaded data is further sent to a remote computing system (e.g., a forestry analysis system).

Using unmanned aerial vehicles (UAVs or drones) in forestry machine-connectivity applications

A method includes controlling an unmanned aerial vehicle to fly over a forestry worksite and capture imagery information with an image capture component. The imagery information is used to generate a set of ground disturbance metrics, each having a value indicative of a measure of ground disturbance at a different geographic location in the forestry worksite. Alternatively, the imagery information is used to generate a set of slope metrics or a firefighting metric. According to the ground disturbance, slope, and firefighting metrics, the method is used to generate an action signal, such as an action signal that controls movement of a mobile machine operating at the forestry worksite, among others.

Using unmanned aerial vehicles (UAVs or drones) in forestry imaging and assessment applications

A method includes generating an unmanned aerial vehicle (UAV) control signal to fly the UAV over a worksite and capture imagery information at different geographic locations. The imagery information is used to generate a tree inventory metric that indicates a tree inventory at the worksite, or is used to generate a productivity metric that identifies a productivity category for a geographic location at the worksite. The method also generates an action signal based on the tree inventory metric or productivity metric, such as an action signal to deploy machines to different geographic location, or an action signal to update a worksite completion metric.

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Dubuque, IA, United States of America

Matthew J Flood