Method for executing an agricultural work process on a field

Patent metadata

Field	Value
Publication number	US-11612103-B2
Application number	US-202016897507-A
Country	US
Kind code	B2
Filing date	Jun 10, 2020
Priority date	Jul 15, 2019
Publication date	Mar 28, 2023
Grant date	Mar 28, 2023

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.

First claim

What is claimed is:

1. A method for executing an agricultural work process on a field comprising:
providing a group of agricultural work machines, each work machine having work assemblies that are adjustable with machine parameters for adapting to respective agricultural conditions,
communicating between the work machines of the group via a wireless network, wherein the work machines of the group are configured as self-optimizing work machines which each have a driver assistance system, and
generating and adjusting machine parameters via the driver assistance system in an automated manner, wherein the machine parameters are optimized with respect to the agricultural conditions,
wherein the work machines of the group collectively cooperate between each other as a virtual work machine, wherein the optimized machine parameters of a plurality of work machines of the group are fed back into the group and are further used by other work machines of the group, such that a plurality of work machines of the group each generate optimized machine parameters for a portion of their respective work assemblies and make the optimized machine parameters available to other work machines of the group and receive optimized machine parameters from these other work machines of the group for another portion of the respective work assemblies, which optimized machine parameters were generated by these other work machines of the group,
wherein the group has a fleet process supervisor for increasing a harvest output and/or harvest quality, which fleet process supervisor coordinates and/or delegates the generation of optimized machine parameters among the work machines of the group, wherein the fleet process supervisor divides the generation of the optimized machine parameters into optimization tasks and distributes the optimization tasks to a plurality of work machines of the group, wherein the optimization tasks are distributed based on an outfitting of the driver assistance system of each work machine of the group.

2. The method according to claim 1 , wherein the work machines of the group generate sensor data, and wherein a plurality of work machines of the group take into account sensor data of other work machines of the group when generating the respective optimized machine parameters, and/or wherein the work machines of the group jointly collect sensor data and these sensor data are aggregated into virtual sensor data.

3. Method according to claim 1 , wherein a plurality of work machines of the group have like work assemblies, wherein the like work assemblies are combined to form a virtual work assembly, and wherein optimized machine parameters are generated for the respective virtual work assembly, and the optimized machine parameters are subsequently utilized for the respective work assembly by a plurality of work machines of the group which have this work assembly.

4. The method according to claim 1 , wherein some of the work machines of the group autonomously generate optimized machine parameters for all of their work assemblies on the basis of data received from other work machines of the group.

5. The method according to claim 1 , wherein the work machines of the group, each or collectively, generate the optimized machine parameters based on field conditions, wherein the field conditions are measured at different sampling points on the field, wherein different work machines of the group are moved to the different sampling points and the respective work machines of the group measure the respective field conditions at each sampling point.

6. The method according to claim 1 , wherein the work machines of the group cooperate jointly in the manner of a virtual work machine so as to exchange work process data, particularly so as to be georeferenced, wherein the work process data comprise crop conditions and/or crop data and/or current quality data and performance data of the work machines of the group and/or process models.

7. The method according to claim 1 , wherein the work machines of the group execute a synchronization routine at a start of execution of the agricultural work process, wherein in the synchronization routine, configurations of the work machines are compared with one another and/or correction factors are determined for converting the respective optimized machine parameters between the work machines, wherein conflicts between the configurations of the work machines of the group are determined, and wherein the conflicts are conveyed to a user and/or automatically resolved.

8. The method according to claim 5 , wherein a preprocessing routine is run on a back end computer external to the group, before a start of the execution of the agricultural work process, wherein the correction factors are determined in the preprocessing routine, and moving to the sampling points is planned in the preprocessing routine, and/or wherein the optimized machine parameters are generated based on a model of the virtual work machine, and wherein the model is prepared or parameterized in the preprocessing routine.

9. The method according to claim 7 , wherein the correction factors are adapted continuously and/or cyclically and/or in an event-based manner during the execution of the agricultural work process based on the sensor data, particularly virtual sensor data, wherein a maintenance requirement of a work machine is inferred from the correction factors.

10. The method according to claim 7 , wherein the correction factors are determined on the basis of externally collected reference information about the work machines of the group.

11. The method according to claim 2 , wherein sensors of the work machines of the group are adjusted and/or calibrated based on the sensor data of other work machines of the group.

12. The method according to claim 11 , wherein, in the event of a sensor outage of a work machine of the group, the work machine having the sensor outage uses sensor data of at least one other work machine of the group or virtual sensor data of the group of work machines in order to at least partially compensate for the sensor outage.

13. The method according to claim 1 , wherein data of another group are used during the execution of the agricultural work process and/or in the synchronization routine and/or in the preprocessing routine, wherein correction factors of the other group are used and wherein the correction factors of the other group are adapted in the preprocessing routine and/or in the synchronization routine.

14. The method according to claim 1 , wherein a contribution of a work machine to the virtual work machine can be paused by a user.

15. The method according to claim 1 , wherein the group has a quality assurance which can exclude and/or pause contributions of a work machine of the group to the virtual work machine, wherein the quality assurance evaluates the contributions of a work machine of the group to the virtual work machine according to quality criteria and excludes the contribution or pauses the contribution based on the quality criteria, wherein the quality criteria relate to outfitting of the work machine of the group and/or local field conditions of the work machine of the group.

16. The method according to claim 1 , wherein a user can control and/or check the execution of the agricultural process by means of a mobile device.

17. The method according to claim 1 , wherein the work machines of the group are agricultural work machines of the same type and accordingly have similar work assemblies and cooperate as a virtual work machine of this type, or wherein the work machines of the group c

Assignees

• Claas Selbstfahrende Erntemaschinen Gmbh

Inventors

• Bormann Bastian
• Baumgarten Joachim
• Wilken Andreas
• Neitemeier Dennis

Classifications

• A01B79/005 Primary

  Precision agriculture · CPC title

• A01D41/1278 Primary

  for automatic steering · CPC title

• A01D41/127

  Control or measuring arrangements specially adapted for combines · CPC title

• A01B69/004

  automatic · CPC title

• G05D2201/0201

  Physics · mapped topic