The present disclosure relates generally to multiple machines participating in the same task, and more particularly to multi-machine collaborative farming.
Farms, construction sites, and other locations typically require the performance of one or more tasks. Such tasks include, for example, harvesting of grain, applying a solid or liquid treatment to an area, or smoothing of a surface. Each of those tasks takes a particular amount of time to complete.
Machines are often used to complete such tasks. A single machine can quickly complete a task compared to use of manual methods. Multiple machines can be used to complete a task faster than a single machine can perform that task.
The use of multiple machines to complete a task can also result in a waste of time and/or resources. Multiple machines can cause the over application of treatments due to more than one machine applying a treatment to a particular area. Multiple machines may also cause a task to take a longer time to be completed than would be expected due to overlap of operations of the machines.
A method for coordinating machines to perform a task includes establishing a plurality of communication channels between a plurality of machines located in a geographic area. Data pertaining to capabilities of each of the plurality of machines, and location of each of the plurality of machines in some cases, is received and a collaborative plan to complete a task using the plurality of machines is determined. At least a portion of the collaborative plan is transmitted to each of the plurality of machines. The collaborative plan can be based on the location and capabilities of each of the plurality of machines. The collaborative plan can include a plurality of operations for each of the plurality of machines to perform. The operations can include a path, a speed, and operation of an implement of a machine. The collaborative plan can include start and end times of machine operations and/or a period of time for a machine to operate.
Tasks can include one or more activities such as application of a liquid or solid material (e.g., fertilizer or pesticide), harvesting, planting, etc. As shown in
Multi-machine collaborative farming (“MMCF”) is a method that uses multiple machines operating in a coordinated manner to complete a particular task faster than a single machine can complete the task. Although many of the embodiments herein pertain to farming, the methods and techniques described can be applied to other tasks such as those pertaining to construction and/or surface modification.
Coordination among machines requires communication among those machines. Because of the mobility of the machines, communication among the machines is wireless. In one embodiment, communication among machines is facilitated by each machine communicating via a device to devices of other machines within range of a wireless transceiver of each device. A collaborative plan for a plurality of machines to complete a task (e.g., farming, construction, surface modification, etc.) can be determined by a device located one of the plurality of machines. A collaborative plan can also be determined by using two or more of the devices associated with the plurality of machines (e.g., distributed computing). Alternatively, a collaborative plan can be determined by a computing device located remote from each of the plurality of machines. For example, a computer that is in wireless communication with one or more of the plurality of machines can determine a collaborative plan.
Returning to
The bandwidth of data transmission between the devices is limited. In one embodiment, both a subscription model and a request-receive model is used for communications among the devices in order to lower bandwidth demand. This is important for maximizing the value of the limited bandwidth expected. For example, consider devices A, B & C. Device A is producing streams of data for resources X, Y, & Z. The communication channel between devices A, B & C becomes saturated at some data rate R. The data rate of the streams for resources X, Y & Z are represented by Rx, Ry & Rz respectively, and Rx+Ry+Rz>R. In this case, it is not possible for device A to communicate the data for all resources. The subscription model permits the devices B & C to register with device A which resources they require. If B & C subscribe only to X, then A only has to transmit Rx<R automatically. This data arrives at B & C with minimal latency. If B or C have need of the current state of Y, but do not need continuous updates on the state of Y, B or C may request using the request-receive model on a singular occasion. There is inherent latency as B or C have not received new information for Y at the exact point that it changed, but this is appropriate in cases for resources of lower priority or importance, and preserves bandwidth availability for higher priority resource X.
Consider the case as above, and assume that Rx+Ry<R. Also assume that C is not within communication range of A, and must communicate via device B, which is in communication range of both A & C. If C requires resource Y, it cannot request a subscription from A as it is not in communication range. Instead, it may request a subscription from B, which in turn must request a subscription for Y from A.
Returning to
At step 408, a collaborative plan is determined to complete the identified task based on data received in step 404 pertaining to each of the plurality of machines and information related to the identified task. For example, if a harvesting task is selected, it is determined how many combine harvesters are available to perform the harvesting and a collaborative plan is determined for performing harvesting of a field based on the number of combine harvesters available.
Determining a collaborative plan, in one embodiment, is based on a location of each of the plurality of machines and the capabilities of each of the plurality of machines. For example, combine harvesters located near a field that needs to be harvested can be included in a collaborative plan to harvest the field while combine harvesters located far away from the field may not be included. The collaborative plan, in one embodiment, includes determining a plurality of operations for each of the plurality of machines. The plurality of operations can include determining a speed for each machine and an operation of an implement of each of the machines. In one embodiment, determining the path for each of the plurality of machines comprises determining a start time and a start location for each machine and a time period during which each machine should traverse its path.
In one embodiment, determining a collaborative plan to complete the task includes determining a spacing of the machines. Front-to-back spacing of the machines can be based on a speed of the machines, stopping ability of the machines, visibility from the cab of the machine, etc. Side-to-side spacing of the machines can be based on implement geometry and the task to be performed. For example, harvesting machines can overlap the portion of the field that they harvest while pesticide or fertilizer application machines should typically not overlap in order to prevent over application of material.
In one embodiment, a collaborative plan for a plurality of storage-capable machines (e.g., grain or harvest bins) is based on a collaborative plan for a plurality of harvesters. For example, a combine harvester can determine a collaborative plane for a plurality of combine harvesters to harvest a field. The collaborative plan for the combine harvesters can then be used to determine a collaborative plan for a plurality of storage-capable machines for receiving material harvested by the combine harvesters. The collaborative plan generated for the storage-capable machines uses information about the physical location & spacing of all machines, current capacity data of the combine harvesters and storage-capable machines, and instructs the storage-capable machines to follow the combine harvesters (in an automatic steering sense) so that harvested material can be unloaded in a somewhat optimal way. This embodiment can be used to minimize the downtime of the combine harvesters.
At step 410, the collaborative plan is transmitted from the device or devices that determined the collaborative plan to each device of the plurality of machines via each of a plurality of communication channels. In one embodiment, the plurality of machines are the machines that are to perform the identified task. Machines that will not perform the task may also receive the collaborative plan so that operators of those machines are aware of tasks being performed near their location. Each device for use in the MMCF network can store various information.
In one embodiment, the collaborative plan that is transmitted to each device of the plurality of machines is displayed to an operator of a respective machine so that the operator can operate the machine in accordance with the collaborative plan. In another embodiment, the collaborative plan is automatically performed by each machine involved with the collaborative plan. In one embodiment, the collaborative plan is accomplished by a combination of both automatic control of a machine as well as operator input. For example, a machine may be automatically controlled to perform a collaborative plan and an operator can override automatic operation of the machine when an unexpected situation occurs, such as unexpected hazardous terrain, an object that needs to be avoided, etc.
Devices that are capable of joining an MMCF network may be referred to as MMCF devices.
In one embodiment, various elements described above can be implemented using computers. A high-level block diagram of such a computer is illustrated in
The foregoing Detailed Description is to be understood as being in every respect illustrative and exemplary, but not restrictive, and the scope of the inventive concept disclosed herein is not to be determined from the Detailed Description, but rather from the claims as interpreted according to the full breadth permitted by the patent laws. It is to be understood that the embodiments shown and described herein are only illustrative of the principles of the inventive concept and that various modifications may be implemented by those skilled in the art without departing from the scope and spirit of the inventive concept. Those skilled in the art could implement various other feature combinations without departing from the scope and spirit of the inventive concept.
This application claims the benefit of prior-filed U.S. Provisional Patent Application No. 62/902,452 filed Sep. 19, 2019, the disclosure of which is incorporated herein by reference in its entirety.
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