Abstract: An assistance system for generating driving routes for one or more driver-controlled or autonomous agricultural work machines. The assistance system includes a computer configured to create a driving route for an agricultural work machine configured to work an agricultural area on the basis of a saved strategy, which may take into account features of areas adjacent to the agricultural area which are not to be worked.

Abstract: A device for detecting a windrow deposited on an agricultural area to be worked is disclosed. The device includes a camera configured to generate an image of the windrow deposited on the agricultural area and a computing unit that is configured to use artificial intelligence in order to evaluate the image. The artificial intelligence may be configured to identify a harvested material windrow in the image. The computing unit may be configured to determine a position of the harvested material windrow on the agricultural area to be worked.

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 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 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: An agricultural work system for optimizing agricultural work flows has at least one agricultural work unit and a plurality of functional units, each having a control device for controlling the respective functional unit based on a stored set of rules. The agricultural work system has a central pattern recognition system which stores at least one agricultural work situation as a situation pattern. Work situation-specific information is transferrable to the pattern recognition system which identifies a stored work situation and the associated situation pattern based on the obtained information and transmits meta-information (M) characterizing the identified work situation to the functional units. The pattern recognition system and/or the control devices coordinate the cooperation of those functional units which work together in the identified work situation based on the meta-information so that the control devices carry out corresponding parameter adjustments of the associated functional unit.

Abstract: A method and system for identifying lengths of a particle in a flow of harvested material comprising particles in an agricultural harvester is disclosed. The agricultural harvester has at least one work assembly for harvesting a crop or for processing harvested material of the crop and can be adjusted using machine parameters. The harvested material is transported as a flow of harvested material through the agricultural harvester while the agricultural harvester is operating. The agricultural harvester has a camera that takes images of the flow of harvested material, with a computing unit of the agricultural harvester analyzing the images of the flow of harvested material in an analytical routine thereby finding particle lengths of particles of the flow of harvested material that are an excess length.

Abstract: A method and system for identifying, using a computing unit, lengths of a particle in a material flow is disclosed. The computing unit is configured to analyze images of the material flow (13) in an analytical routine and to derive particle lengths of particles of the material flow contained in the images. The particle length derived in the analytical routine may comprise an excess length, with the analytical routine being based on a machine learning method trained to find or identify particles with the excess length.

Abstract: An agricultural machine for conducting an agricultural working process includes a combustion engine (2), electrical consumers (3-8), a chargeable electrical battery (9) for electrically supplying the consumers (3-8) and a monitor module (10) for monitoring the charging level of the battery (9). It is proposed that some of the electrical consumers (3-8) of the agricultural machine (1) are peripheral consumers (3-8) for providing functions in a parking state of the agricultural machine (1), in which the combustion engine (2) is shut off, that a power management module (11) is provided, which in the parking state of the agricultural machine (1) monitors the charging level of the battery (9) via the monitor module (11) and deactivates at least one peripheral consumer (3-8), when the charging level falls below a threshold level.

Abstract: An agricultural working machine including at least one optical sensor apparatus, an image processing system, a work lighting system that includes one or more light sources, and a regulation and control device configured to control the work lighting system is disclosed. The image processing system, using the optical sensor apparatus, detects the occurrence of one or more obstacles in an obstacle region in the forefield of the agricultural working machine. The regulation and control device generates control signals that control orientation the one or more light sources in order to orient light beam(s) generated by the one or more lights sources toward the obstacle region.

Abstract: An agricultural work system for optimizing agricultural work flows has at least one agricultural work unit and a plurality of functional units, each having a control device for controlling the respective functional unit based on a stored set of rules. The agricultural work system has a central pattern recognition system which stores at least one agricultural work situation as a situation pattern. Work situation-specific information is transferrable to the pattern recognition system which identifies a stored work situation and the associated situation pattern based on the obtained information and transmits meta-information (M) characterizing the identified work situation to the functional units. The pattern recognition system and/or the control devices coordinate the cooperation of those functional units which work together in the identified work situation based on the meta-information so that the control devices carry out corresponding parameter adjustments of the associated functional unit.

Abstract: An agricultural working machine, in particular a tractor, has at least one agricultural working unit for working a crop field including a multitude of useful plants, and a camera system which includes a 3D camera. The camera system is configured for generating with the 3D camera 3D information regarding the crop field by recording stereoscopic image pairs along two different viewing axes. The viewing axes proceed from optical centers of the 3D camera, which are connected to each other by a baseline that is inclined relative to the horizontal.