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 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: 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 configured to avoid anomalies is disclosed. Agricultural work machines may encounter anomalies, such as obstacles (e.g., tires) or irregularities in the crop (e.g., weeds), which can reduce the quality of the harvested crop. Manually steering the agricultural work machine requires the constant attention of the vehicle operator. Thus, the agricultural work machine is configured to include sensors to generate one or more images (such as images of various regions of the agricultural work machine), an image processing system to process the images and a control unit to avoid the anomalies (e.g., avoid the identified anomalies, to drive in tracks, and/or to stop the agricultural work machine).

Abstract: An agricultural work machine configured to avoid anomalies is disclosed. Agricultural work machines may encounter anomalies, such as obstacles (e.g., tires) or irregularities in the crop (e.g., weeds), which can reduce the quality of the harvested crop. Manually steering the agricultural work machine requires the constant attention of the vehicle operator. Thus, the agricultural work machine is configured to include sensors to generate one or more images (such as images of various regions of the agricultural work machine), an image processing system to process the images and a control unit to avoid the anomalies (e.g., avoid the identified anomalies, to drive in tracks, and/or to stop the agricultural work machine).