Abstract: An agricultural harvesting machine having a cutting unit for cutting harvested material and a driver assistance system is disclosed. The driver assistance system includes a memory in which control strategies for the operation of the cutting unit are stored and a computing device for controlling a cutting angle of the cutting unit in accordance with the control strategies. The computing device is configured to link first and second control strategy to one another via a weighting variable, with the weighting variable being adjustable by a driver. The driver assistance system uses at least one of the control strategies and sensed forefield information to automatically determine the cutting angle of the cutting unit and to automatically control the cutting unit based on the determined cutting angle.

Abstract: A system for determining a crop edge and a self-propelled harvester using the system for automatic control are disclosed. The system comprises a camera that generates optical information of a front environment of the harvester. The system further includes a computing unit that analyzes the images using artificial intelligence so that a planted area of a field on which a plant crop is located may be delimited from a remaining residual area of the field, thereby determining the plant crop. In turn, the computing unit is further configured to determine the crop edge of the plant crop based on the determination of the plant crop and to automatically control the harvester based on the determination of the crop edge.

Abstract: An agricultural harvester is disclosed. The agricultural harvester includes a cutting unit that has a cutting table adjustable in its cutting table length, a reel adjustable to a reel vertical position and reel longitudinal position, an inclined conveyor downstream from the cutting unit, and a driver assistance system. The driver assistance system autonomously determines, using at least one input variable, at least one machine parameter and specifies the machine parameter to the cutting unit. The machine parameter can include one or more of the cutting table length, the reel vertical position, or the reel longitudinal position. In particular, the driver assistance system may determine a harvested material throughput and a vibration coefficient describing the fluctuation in the harvested material throughput in a region lying in front of the threshing system and adapt or modify the cutting table length based on the determined vibration coefficient.

Abstract: A swarm assistance system for autonomous agricultural universal production machines is disclosed. The swarm assistance system is integrated into an agricultural work network. The agricultural work network connects autonomous agricultural universal production machines as providers of agricultural jobs and customers of agricultural jobs with each other and with the swarm assistance system. The autonomous agricultural universal production machines are configured to perform a plurality of different agricultural jobs by being equipped with changing work assemblies. The swarm assistance system receives request data relating to a requested agricultural job from the customers, matches the request data with capacity data of at least one of the agricultural universal production machines and, based on the result of the matching, rents at least one agricultural universal production machine to perform the requested agricultural job.

Abstract: An assistance system based on electronic data exchange for enabling an autonomous vehicle to act as an autonomous agricultural production machine and an autonomous agricultural production machine is disclosed. The assistance system is configured to plan the deployment of at least one autonomous vehicle, to transmit the information required for the deployment to the autonomous vehicle, to at least partially control the autonomous vehicle during working mode and to monitor the working mode of the autonomous vehicle.

Abstract: A method for monitoring autonomous agricultural production machines is disclosed. The autonomous agricultural production machine autonomously performs an agricultural job. When an anomaly occurs, the autonomous agricultural production machine performs a response routine, interrupting the performance of the agricultural job. The autonomous agricultural production machine senses anomaly data during and/or after the response routine and transmits the anomaly data to a remote monitoring center in a reporting routine that a user may access in the remote monitoring center. The remote monitoring center generates, based on the anomaly data, a control instruction and transmits the control instruction to the autonomous agricultural production machine to execute in order to further respond to the anomaly and thereafter continue to perform the agricultural job.

Abstract: A method and a system for deployment planning and coordinating a vehicle fleet comprising a plurality of agricultural work vehicles is disclosed. Different agricultural work processes may be performed on a field with the work vehicles having a work unit for performing at least one of the agricultural work processes. At least one work vehicle of the vehicle fleet is operated autonomously. Further, the database-driven management system may generate the deployment plan. For example, while planning a particular agricultural work process comprising a sequence of work steps, the work vehicles in the vehicle fleet are coordinated with one another by assigning at least one autonomous work vehicle to a respective work step of the agricultural work process with operational parameters being transmitted to the autonomous work vehicle in order to perform the assigned respective work step.

Abstract: A method and a system for monitoring the operation of at least one autonomous agricultural production machine is disclosed. The method comprises collecting data representing the operating parameters and environmental parameters of the autonomous agricultural production machine and detecting an irregularity based on the data. Once an irregularity is determined, the collected data are transmitted to a database and saved there. The irregularity is identified by processing the collected data in an analysis routine, and an instruction is generated for switching the autonomous agricultural production machine from a safe operating state to a normal operating state depending on the identified irregularity, and the instruction is executed.

Abstract: An agricultural work machine and a method for operation an agricultural work machine are disclosed. The agricultural work machine includes a driver’s cab with an interior space spatially partially delimited by a front window and at least one side window, a driver’s seat arranged in the interior space, an input device for entering input by an operator, a visualization system for visualizing information for an operator sitting on the driver’s seat, and a control device which is communication with the visualization system. The control device controls the visualization system in such a way that process information relevant to the selected work process is visualized.

Abstract: A self-propelled forage harvester is disclosed that includes a blade sharpening and shear bar adjusting device, a monitoring device configured to cyclically generate information on the state of the cutterhead chopping glades and the distance of the shear bar to the cutting edge, and a control unit. The control unit evaluates the information provided by the monitoring device about the state of wear of the chopping blades and the distance, compares it with a limit value for the state of wear and/or the distance, where the limit value forms a lower limit for an optimum range to be maintained by the blade sharpening and shear bar adjusting device, of the instantaneous cutting sharpness of the chopping blades or of the distance and, when the limit value is reached, automatically triggers a sharpening process and/or of a shear bar adjustment by the blade sharpening and shear bar adjusting device.

Abstract: A method for the operation of a self-propelled agricultural working machine has at least one working element and a driver assistance system for generating control actions within the working machine. A sensor arrangement for generating surroundings information is provided, and the driver assistance system generates the control actions based on the surroundings information. The sensor arrangement comprises a camera-based sensor system and a laser-based sensor system, each of which generates sensor information regarding a predetermined, relevant surroundings area of the working machine. The sensor information of the camera-based sensor system is present as starting camera images. The starting camera images are segmented into image segments by an image processing system according to a segmentation rule, and the segmented camera images are combined by a sensor fusion module with the sensor information from the laser-based sensor system.

Abstract: A driver assistance system of an agricultural harvesting machine with a harvesting header designed as a draper is disclosed. The driver assistance system comprises a memory for storing data and a computing device for processing the data saved in the memory. The draper comprises a central belt and at least one transverse conveyor belt arranged on the left side and the right side of the central belt for conveying the harvested material to the central belt. The draper forms, together with the driver assistance system, an automatic draper. The computing device operates the automatic draper as a characteristic diagram controller using the saved characteristic diagrams, with the automatic draper optimizing operating parameters of the draper and specifying the optimized operating parameters for the draper. The characteristic diagrams describe the relationship between the operating parameters and quality parameters, and a control characteristic curve is assigned to the particular characteristic diagram.

Abstract: A driver assistance system of an agricultural harvesting machine with a harvesting header designed as a draper is disclosed. The driver assistance system comprises a memory for storing data and a computing device for processing the data saved in the memory. The draper comprises a central belt and at least one transverse conveyor belt arranged on the left side and the right side of the central belt for conveying the harvested material to the central belt. The draper forms, together with the driver assistance system, an automatic draper. The computing device operates the automatic draper as a characteristic diagram controller using the saved characteristic diagrams, with the automatic draper optimizing operating parameters of the draper and specifying the optimized operating parameters for the draper. The characteristic diagrams describe the relationship between the operating parameters and quality parameters, and a control characteristic curve is assigned to the particular characteristic diagram.

Abstract: An agricultural production machine comprising a characteristic diagram control is disclosed. The characteristic diagram control comprises one or more characteristic diagrams. Each characteristic diagram is configured to optimize operating parameters of the process units of the agricultural production machine. The particular characteristic diagram is designed as an initial characteristic diagram. In the initial characteristic diagram, at least the relationship between operating parameters of a process unit and quality parameters is described by initial operating points. A control characteristic curve is associated with the particular characteristic diagram, and the control characteristic curve lies around the minimum or maximum of the particular quality parameter.

Abstract: A method for executing an agricultural work process on a field by means of a group of agricultural work machines. The work machines each have work assemblies which are adjustable with machine parameters for adapting to the respective agricultural conditions. The work machines of the group communicate with one another via a wireless network. The work machines of the group are configured as self-optimizing work machines which each have a driver assistance system for generating and adjusting machine parameters in an automated manner. These machine parameters are optimized with respect to the agricultural conditions. The work machines of the group cooperate collectively in the manner of a virtual work machine.

Abstract: An agricultural harvesting machine has a cutting apparatus formed as a header for cutting and picking up crop of a crop stand, an inclined conveyor downstream of the cutting apparatus and in which a temporal layer height flow is adjusted, and a driver assistance system for controlling the cutting apparatus. The driver assistance system has a computing device and a sensor arrangement with a crop sensor system for generating crop parameters of the crop stand and a layer height sensor for generating the temporal layer height flow. The computing device simultaneously generates the cutting apparatus parameters of the cutting table length, horizontal reel position and vertical reel position so as to be adapted to one another and conveys them to the cutting apparatus to implement a harvesting process strategy in ongoing harvesting operation.

Abstract: A self-propelled forage harvester and a method for controlling said forage harvester are disclosed. A measuring device of the forage harvester may have a plurality of electrodes spaced at a distance from each other. These electrodes may be arranged or positioned in an intermediate channel of a harvested material processing channel of the forage harvester and may form a plurality of capacitors. Further, delivery-specific parameters and/or material-specific parameters may be discernible from the measurements of the electrical capacitances of the plurality of capacitors.

Abstract: A method for operating a self-propelled agricultural harvester with a cutting unit and a self-propelled agricultural harvester are disclosed. A driver assistance system associated with the agricultural harvester includes a memory that saves data and a computing unit for processing data saved in the memory. The driver assistance system and the cutting unit form an automated cutting unit. A harvesting process strategy is selected from a plurality of harvesting process strategies saved in the memory and at least one cutting unit parameter is selected. The at least one cutting unit parameter may be determined autonomously by the computing unit to implement the at least one selected harvesting process strategy and may be specified to the cutting unit.

Abstract: A detection arrangement for detecting a wear status of a chopping knife arrangement of a chopping device provided for processing a product flow, wherein the chopping device has a revolving chopping drum receiving the chopping knife arrangement and at least one shear bar which cooperates with the chopping knives, with a sensor arrangement which has a magnetic exciter arrangement and a flux conducting device magnetically coupled thereto. The sensor arrangement provides a pole arrangement which forms at least one magnetic pole with a pole surface for conducting magnetic flux, wherein at least a portion of the chopping knife passes the pole arrangement during a rotation of the chopping drum. A voltage induced when a chopping knife arrangement passes the sensor arrangement forms the measured magnetic value, which is used by the evaluation unit to determine the state of wear of the chopping knife arrangement.

Abstract: A method and a self-propelled forage harvester for determining the need for grinding chopping blades of a chopping device of the self-propelled forage harvester is disclosed. A monitoring device determines, such as cyclically, the state of wear of the chopping blades. The monitoring device comprises an input/output unit through which to enter or select a target state of the chopping blades to be produced by a grinding device as a target. The monitoring device generates, such as continuously, information depending on the target state and the determined state of wear, and causes an output on the input/output unit to visualize the extent to which the currently determined state of wear deviates from the target state.