Patent classifications
A01B63/14
SYSTEM AND METHOD FOR CONTROLLING THE DIRECTION OF TRAVEL OF AN AGRICULTURAL IMPLEMENT
In one aspect, a system for controlling the direction of travel of agricultural implements may include a work vehicle having a vehicle-based controller configured to control an operation of a valve provided in operative association with the work vehicle. The system may also include an agricultural implement configured to be towed by the work vehicle. The implement may include a sensor configured to detect an operational parameter indicative of a direction of travel of the implement. The implement may also include an actuator configured to adjust the direction of travel of the implement, with the actuator being fluidly coupled to the valve such that the valve is configured to control an operation of the actuator. The implement may further include an implement-based controller configured to initiate control of the operation of the valve based on sensor data received from the sensor to adjust the direction of travel of the implement.
SYSTEM AND METHOD FOR CONTROLLING THE DIRECTION OF TRAVEL OF AN AGRICULTURAL IMPLEMENT
In one aspect, a system for controlling the direction of travel of agricultural implements may include a work vehicle having a vehicle-based controller configured to control an operation of a valve provided in operative association with the work vehicle. The system may also include an agricultural implement configured to be towed by the work vehicle. The implement may include a sensor configured to detect an operational parameter indicative of a direction of travel of the implement. The implement may also include an actuator configured to adjust the direction of travel of the implement, with the actuator being fluidly coupled to the valve such that the valve is configured to control an operation of the actuator. The implement may further include an implement-based controller configured to initiate control of the operation of the valve based on sensor data received from the sensor to adjust the direction of travel of the implement.
Agricultural toolbar apparatus, systems, and methods
An agricultural implement configured to shift weight between a center toolbar and left and right wing sections. Each wing section includes inner and outer sections pivotally coupled about a horizontal axis. Left and right wing flex actuators pivot the outer wing sections with respect to the inner wing sections about the respective left and right horizontal axes. Each of the inner wing sections is pivotally coupled to the center toolbar about respective left and right vertical axis. The center toolbar section is supported by a center wheel assembly and distal ends of the left and right outer wing sections are supported by respective left and right wing wheel assemblies. A monitor is in signal communication with load sensors on each of the wheel assemblies and a fluid control system to actuate the wing flex actuators so the measured center wheel load approaches a center wheel target load.
SYSTEM FOR CONNECTING IMPLEMENT TO MOBILE MACHINERY
A system is suitable for connecting multiple implements to a three-point hitch of mobile machinery for controllable side-shifting movement of the connected implements. The system comprises first, second and third apparatuses, each apparatus comprising a first framework, a slidable second framework laterally slideable relative to the first framework, at least one connector supported by the slidable second framework for connecting the slidable second framework to one of the implements, and at least one driver connected to the first framework and the slidable second framework for driving the slidable second framework laterally back and forth relative to the first framework. The second apparatus is attached to one side of the first apparatus and the third apparatus is attached to the other side of the first apparatus.
SYSTEM FOR CONNECTING IMPLEMENT TO MOBILE MACHINERY
An apparatus for connecting an implement to a three point hitch of mobile machinery comprises two frameworks, a first framework and a second framework. The first framework is disposed in a first plane and comprises at least two parallel, vertically-spaced apart, laterally extending rails. There are three attachments supported by the first framework for attachment to the three-point hitch. The second framework is slidable generally in the plane of the first framework and is mounted on the rails to slide laterally along the rails. At least two connectors are supported by the slidable second framework for connecting the second framework to an implement that can be pulled or pushed by the mobile machinery. A driver is connected to the first framework and connected to the second framework for driving the second framework laterally back and forth along the rails of the first framework.
DETECTING AND MEASURING THE SIZE OF CLODS AND OTHER SOIL FEATURES FROM IMAGERY
The present disclosure provides systems and methods that measure soil roughness in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned clod detection model to determine a soil roughness value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.
DETECTING AND MEASURING THE SIZE OF CLODS AND OTHER SOIL FEATURES FROM IMAGERY
The present disclosure provides systems and methods that measure soil roughness in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned clod detection model to determine a soil roughness value for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.
REAL-TIME ARTIFICIAL INTELLIGENCE CONTROL OF AGRICULTURAL WORK VEHICLE OR IMPLEMENT BASED ON OBSERVED OUTCOMES
Systems and methods for real-time, artificial intelligence control of an agricultural work vehicle and/or implement based on observed outcomes are provided. In particular, example aspects of the present subject matter are directed to systems and method that sense field conditions (also known as field finish) both before and after adjustable ground-engaging tools encounter the soil and that update a site-specific control model that provides control settings based on the observed anterior and posterior conditions. Thus, a control system can obtain sensor data descriptive of upcoming field conditions and can perform predictive adjustment and control of tools based the upcoming field conditions. The system can then use additional sensors to observe the outcome of the employed control settings. Based on a comparison of the observed outcome to a target outcome, the system can adjust for the next encounter of similar field conditions.
REAL-TIME ARTIFICIAL INTELLIGENCE CONTROL OF AGRICULTURAL WORK VEHICLE OR IMPLEMENT BASED ON OBSERVED OUTCOMES
Systems and methods for real-time, artificial intelligence control of an agricultural work vehicle and/or implement based on observed outcomes are provided. In particular, example aspects of the present subject matter are directed to systems and method that sense field conditions (also known as field finish) both before and after adjustable ground-engaging tools encounter the soil and that update a site-specific control model that provides control settings based on the observed anterior and posterior conditions. Thus, a control system can obtain sensor data descriptive of upcoming field conditions and can perform predictive adjustment and control of tools based the upcoming field conditions. The system can then use additional sensors to observe the outcome of the employed control settings. Based on a comparison of the observed outcome to a target outcome, the system can adjust for the next encounter of similar field conditions.
MEASURING CROP RESIDUE FROM IMAGERY USING A MACHINE-LEARNED CONVOLUTIONAL NEURAL NETWORK
The present disclosure provides systems and methods that measure crop residue in a field from imagery of the field. In particular, the present subject matter is directed to systems and methods that include or otherwise leverage a machine-learned convolutional neural network to determine a level of crop residue for a portion of a field based at least in part on imagery of such portion of the field captured by an imaging device. For example, the imaging device can be a camera positioned in a downward-facing direction and physically coupled to a work vehicle or an implement towed by the work vehicle through the field.