A combination of a tractive machine and plow, has a driver assistance system having an input/output unit. The plow is adjustable with machine parameters, wherein a portion is manually adjustable and/or automatically adjustable by means of the tractive machine. A plow adjust assistant determines in a dialog with an operator in a plurality of dialog steps, optimized machine parameters of the plow and/or of the tractive machine that are to be adjusted. The plow adjust assistant automatically adjusts a portion of the machine parameters determined in the first dialog step and/or gives the operator a portion for adjusting and determines further optimized machine parameters of the plow based on these machine parameters and gives these further optimized machine parameters of the plow to the operator for adjustment of the plow in a second dialog step and/or automatically adjusts them at the plow.

In one aspect, a system for controlling the position of an agricultural implement being towed by an agricultural vehicle may include first and second wheels and first and second non-contact-based braking devices. As such, the first braking device may be configured to apply a braking force to the first wheel, and the second braking device may be configured to apply a braking force to the second wheel. Furthermore, the system may include a controller configured to control an operation of the first braking device or the second braking device when it is determined that the position of the implement differs from a predetermined position for the implement such that the braking force is applied to the corresponding wheel in a manner that adjusts the position of the implement towards the predetermined position.

Methods, apparatus, and systems are disclosed to record and execute mission plans. An example apparatus includes a data collection memory to collect first and second data, the first data corresponding to a machine and the second data corresponding to an implement, a mission aggregator to determine a machine path based on the first data, determine an implement path based on the second data, and determine a machine speed and an implement action based on the first and second data, a mission generator to generate a three-dimensional mission plan including the machine path, the implement path, the machine speed, and the implement action for subsequent use, and a mission application controller to, when an interface determines the mission plan is available, instruct the machine and the implement to follow the machine path, the implement path, the machine speed, and the implement action to execute the mission plan.

The disclosed apparatus, systems and methods relate to a steerable toolbar. The toolbar is able to rotate relative to the tractor or other driving vehicle to reduce misalignment and/or cross-track error. Actuators can be utilized with draft links to pivot the toolbar around a central pivot point and improve the following path of the toolbar implement.

Agricultural electronics include many components. The components can be connected via an electronic link that connects the various components to components of an agricultural implement. This can include the use of a component type identifier and a master module. The identifier and the module can communicate data, including identification data and instructional data, to easily acknowledge and operate various electrical components of the agricultural implement. Additional sensors can be included to provide even additional data that is communicated between the module and the components of the agricultural implement to aid in providing instructions for operation and to provide additional data information.

A method for detecting real lateral locations of target plants includes: recording an image of a ground area at a camera; detecting a target plant in the image; accessing a lateral pixel location of the target plant in the image; for each tool module in a set of tool modules arranged behind the camera and in contact with a plant bed: recording an extension distance of the tool module; and recording a lateral position of the tool module relative to the camera; estimating a depth profile of the plant bed proximal the target plant based on the extension distance and the lateral position of each tool module; estimating a lateral location of the target plant based on the lateral pixel location of the target plant and the depth profile of the plant bed surface proximal the target plant; and driving a tool module to a lateral position aligned with the lateral location of the target plant.

An agricultural vehicle-trailer combination includes a traction module including a drive element for engaging in a ground, a working appliance coupled to the traction module by a coupling apparatus, and a folding axle supporting the working appliance relative to the ground at least during a transport mode. A slewing mechanism of the coupling apparatus provides a degree of freedom of rotation between the traction module and the working appliance along a longitudinal axis of the working appliance. A pivot joint provides a degree of freedom of pivoting between the traction module and the working appliance along a vertical axis of the traction module. The pivot joint is adjustable relative to its pivot angle by a steering actuator for influencing the direction of travel of the vehicle-trailer combination.

A method for determining residue coverage within a field after a harvesting operation may include receiving yield data associated with an estimated crop yield across a field and generating an estimated residue coverage map for the field based at least in part on the yield data. The method may further include receiving residue data associated with residue coverage across a surface of the field following the performance of a harvesting operation within the field. Additionally, the method may include generating an updated residue coverage map for the field based at least in part on the estimated residue coverage map and the residue data.

One or more information maps are obtained by an agricultural work machine. The one or more information maps map one or more agricultural characteristic values at different geographic locations of a field. An in-situ sensor on the agricultural work machine senses an agricultural characteristic as the agricultural work machine moves through the field. A predictive map generator generates a predictive map that predicts a predictive agricultural characteristic at different locations in the field based on a relationship between the values in the one or more information maps and the agricultural characteristic sensed by the in-situ sensor. The predictive map can be output and used in automated machine control.

A vegetative health mapping system which creates two- or three-dimensional maps and associates moisture content, soil density, ambient light, surface temperature, and/or additional indications of vegetative health with the map. Moisture content is inferred using radar return signals of near-field and/or far-field radar. By tuning various parameters of the one or more radar (e.g. frequency, focus, power), additional data may be associated with the map from subterranean features (such as rocks, soil density, sprinklers, etc.). Additional sensors (camera(s), lidar, IMU, GPS, etc.) may be fused with radar returns to generate maps having associated moisture content, surface temperature, ambient light levels, additional indications of vegetative health (as may be determined by machine learned algorithms), etc. Such vegetative health maps may be provided to a user who, in turn, may indicate additional areas for the vegetative health device to scan or otherwise used to recommend and/or perform treatments.