Map based farming for windrow merger operation
One or more information maps are obtained by an agricultural system. The one or more information maps map one or more characteristic values at different geographic locations in a worksite. An in-situ sensor detects a mass flow value as a mobile machine operates at the worksite. A predictive map generator generates a predictive map that maps predictive mass flow values or predictive yield values at different geographic locations in the worksite based on a relationship between the values in the one or more information maps and the mass flow value detected by the in-situ sensor or the yield value based on the detected mass flow value. The predictive map can be output and used in automated machine control.
1 . An agricultural windrowing system comprising:
a geographic position sensor configured to detect a machine geographic location of a mobile windrowing machine;
an in-situ sensor configured to detect a value of a mass flow corresponding to a geographic location of a plurality of different geographic locations, in a worksite;
one or more processors; and
memory storing instructions executable by the one or more processors that, when executed by the one or more processors, configure the one or more processors to:
obtain an information map that includes values of a first characteristic corresponding to the plurality of different geographic locations in the worksite;
generate a functional predictive map of the worksite that maps predictive values of a second characteristic to one or more geographic locations of the plurality of different geographic locations in the worksite, based, at least, on a value of the first characteristic in the information map corresponding to the geographic location in the worksite and based on the detected value of mass flow corresponding to the geographic location;
obtain follow-on machine and operation data representing operational characteristics of a follow-on machine, different than the mobile windrowing machine, configured to perform a windrow processing operation on a windrow formed by the mobile windrowing machine; and
control the mobile windrowing machine to form, on the worksite, the windrow based on the functional predictive map and the follow-on machine and operation data representing the operational characteristics of the follow-on machine.
2 . The agricultural windrowing system of claim 1 , wherein the instructions, when executed by the one or more processors, configure the one or more processors to control the mobile windrowing machine by controlling a merger subsystem of the mobile windrowing machine based on the follow-on machine and operation data.
3 . The agricultural windrowing system of claim 1 , wherein the instructions, when executed by the one or more processors, configure the one or more processors to control the mobile windrowing machine by controlling at least one of a size or a position of the windrow formed by the mobile windrowing machine based on the follow-on machine and operation data.
4 . The agricultural windrowing system of claim 1 , wherein the mobile windrowing machine includes a merger belt, and the instructions, when executed by the one or more processors, configure the one or more processors to control the mobile windrowing machine by controlling, based on the follow-on machine and operation data, at least one of:
a direction of movement of the merger belt of the mobile windrowing machine; or
a position of the merger belt of the mobile windrowing machine.
5 . The agricultural windrowing system of claim 1 , wherein the instructions, when executed by the one or more processors, further configure the one or more processors to:
generate a route for the mobile windrowing machine based on the functional predictive map and the follow-on machine and operation data; and
control the mobile windrowing machine by controlling a steering subsystem of the mobile windrowing machine based on the route.
6 . The agricultural windrowing system of claim 1 and further comprising a speed sensor configured to detect a speed of the mobile windrowing machine and wherein the instructions, when executed by the one or more processors, further configure the one or more processors to:
generate a value of yield corresponding to the geographic location based on the detected value of mass flow corresponding to the geographic location and the detected speed of the mobile windrowing machine; and
generate a predictive yield model indicative of a relationship between values of the first characteristic in the information map and values of yield based, at least, on the value of yield corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location to which the value of yield corresponds.
7 . The agricultural windrowing system of claim 6 , wherein the functional predictive map of the worksite comprises a functional predictive yield map that maps predictive values of yield, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and based on the predictive yield model.
8 . The agricultural windrowing system of claim 1 , wherein the instructions, when executed by the one or more processors, further configure the one or more processors to:
generate a predictive mass flow model indicative of a relationship between values of the first characteristic in the information map and values of mass flow based, at least, on the detected value of mass flow corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location to which the detected value of mass flow corresponds; and
wherein the functional predictive map of the worksite comprises a functional predictive mass flow map that maps predictive values of mass flow, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and based on the predictive mass flow model.
9 . The agricultural windrowing system of claim 1 , wherein the information map comprises one of:
a topographic map that maps, as the values of the first characteristic, topographic characteristic values corresponding to the plurality of different geographic locations in the worksite;
a vegetative index map that maps, as the values of the first characteristic, vegetative index values corresponding to the plurality of different geographic locations in the worksite; or
a crop genotype map that maps, as the values of the first characteristic, crop genotype values corresponding to the plurality of different geographic locations in the worksite.
10 . The agricultural windrowing system of claim 1 , wherein the follow-on machine is different than the mobile windrowing machine and wherein the follow-on machine and operation data indicates at least one of:
(i) a type of the follow-on machine;
(ii) a capacity or capability of the follow-on machine; or
(iii) a combination of (i) and (ii).
11 . A computer implemented method of controlling a mobile windrowing machine, the computer implemented method comprising:
receiving an information map that maps values of a first characteristic to a plurality of different geographic locations in a worksite;
detecting, with an in-situ sensor, a value of a mass flow corresponding to a geographic location of the plurality of different geographic locations;
generating a predictive model indicative of a relationship between values of the first characteristic and values of a second characteristic based, at least, on the value of the mass flow detected by the in-situ sensor corresponding to the geographic location and a value of the first characteristic in the information map corresponding to the geographic location;
generating a functional predictive map of the worksite that maps predictive values of the second characteristic to one or more geographic locations of the plurality of different geographic locations in the worksite based on values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and the predictive model;
obtaining follow-on machine and operation data representing operational characteristics of a follow-on machine, different than the mobile windrowing machine, configured to perform a windrow processing operation on a windrow formed by the mobile windrowing machine; and
controlling the mobile windrowing machine to form, on the worksite, the windrow based on the functional predictive map and the follow-on machine and operation data representing the operational characteristics of the follow-on machine.
12 . The computer implemented method of claim 11 , wherein controlling the mobile windrowing machine comprises controlling a merger subsystem of the mobile windrowing machine.
13 . The computer implemented method of claim 11 and further comprising:
generating a route for the mobile windrowing machine based on the functional predictive map; and
wherein controlling the mobile windrowing machine comprises controlling a steering subsystem of the mobile windrowing machine based on the route.
14 . The computer implemented method of claim 11 , wherein generating the predictive model comprises generating a predictive mass flow model indicative of a relationship between values of the first characteristic and values of mass flow, as the second characteristic, based, at least, on the value of mass flow detected by the in-situ sensor corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location; and
wherein generating the functional predictive map comprises generating a functional predictive mass flow map of the worksite that maps predictive values of mass flow, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on the values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and the predictive mass flow model.
15 . The computer implemented method of claim 11 and further comprising:
detecting, with an in-situ speed sensor, a speed of the mobile windrowing machine;
generating, with a processing system, a value of yield corresponding to the geographic location based on a cut width of the mobile windrowing machine, the detected speed of the mobile windrowing machine, and the detected value of mass flow corresponding to the geographic location; and
wherein generating the predictive model comprises generating a predictive yield model indicative of a relationship between values of the first characteristic and values of yield, as the second characteristic, based, at least, on the generated value of yield corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location; and
wherein generating the functional predictive map comprises generating a functional predictive yield map of the worksite that maps predictive values of yield, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on the values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations and the predictive yield model.
16 . A mobile agricultural windrowing machine comprising:
an in-situ mass flow sensor configured to detect a value of mass flow corresponding to a geographic location of a plurality of different geographic locations in a worksite;
one or more processors; and
memory storing instructions executable by the one or more processors that, when executed by the one or more processors, cause the one or more processors to:
obtain an information map that maps values of a first characteristic to the plurality of different geographic locations in the worksite;
generate a predictive model indicative of a relationship between the first characteristic and a second characteristic based, at least, on the value of mass flow detected by the in-situ mass flow sensor corresponding to the geographic location and a value of the first characteristic in the information map corresponding to the geographic location;
generate a functional predictive map of the worksite that maps predictive values of the second characteristic to one or more geographic locations of the plurality of different geographic locations in the worksite based on values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and based on the predictive model;
obtain follow-on machine and operation data representing operational characteristics of a follow-on machine, different than the mobile agricultural windrowing machine, configured to perform a windrow processing operation on a windrow formed by the mobile agricultural windrowing machine; and
control the mobile agricultural windrowing machine to form, on the worksite, the windrow based on the functional predictive map and the follow-on machine and operation data representing the operational characteristics of the follow-on machine.
17 . The mobile agricultural windrowing machine of claim 16 , wherein the instructions, when executed by the one or more processors, cause the one or more processors to control the mobile agricultural windrowing machine by controlling a merger subsystem of the mobile agricultural windrowing machine.
18 . The mobile agricultural windrowing machine of claim 16 , wherein the instructions, when executed by the one or more processors, further cause the one or more processors to generate a route for the mobile agricultural windowing machine based on the functional predictive map and to control the mobile agricultural windrowing machine by controlling a steering subsystem of the mobile agricultural windrowing machine based on the route.
19 . The mobile agricultural windrowing machine of claim 16 and further comprising a speed sensor configured to detect a speed of the mobile agricultural windrowing machine and wherein the instructions, when executed by the one or more processors, further cause the one or more processors to generate a yield value corresponding to the geographic location based on the detected value of mass flow corresponding to the geographic location and the detected speed of the mobile agricultural windrowing machine; and
wherein the predictive model comprises a predictive yield model indicative of a relationship between the first characteristic and yield, as the second characteristic, based, at least, on the generated value of yield corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location; and
wherein the functional predictive map comprises a functional predictive yield map of the worksite that maps predictive values of yield, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on the values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and based on the predictive yield model.
20 . The mobile agricultural windrowing machine of claim 16 , wherein the predictive model comprises a predictive mass flow model indicative of a relationship between the first characteristic and mass flow, as the second characteristic, based, at least, on the detected value of mass flow corresponding to the geographic location and the value of the first characteristic in the information map corresponding to the geographic location; and
wherein the functional predictive map comprises a functional predictive mass flow map of the worksite that maps predictive values of mass flow, as the predictive values of the second characteristic, to the one or more geographic locations of the plurality of different geographic locations in the worksite based on the values of the first characteristic in the information map corresponding to the one or more geographic locations of the plurality of different geographic locations in the worksite and based on the predictive mass flow model.