JP7617829B2 - Aircraft Control System - Google Patents

Description

The present invention relates to a control system for an aircraft that sprays pesticides on agricultural crops.

In farm fields, various pesticides are sprayed to ensure proper growth of crops. As shown in Patent Document 1, pesticides may be sprayed from the air using an aircraft such as a drone.

In Patent Document 1, the drone sprays pesticides based on a work plan that is set based on pesticide identification information, such as the amount of pesticide to be sprayed, the name of the pesticide, and the product number, that has been input in advance. The type of pesticide to be sprayed (name, product number) and the amount of pesticide to be sprayed can be uniform across the entire field, but can also be different for each specified section or ridge/row.

JP 2021-40598 A

However, pesticide spraying plans, which consist of the type of pesticide to be sprayed and the amount of pesticide to be sprayed, are determined based on the experience of the worker, taking into account the type of pesticide and the amount of pesticide sprayed in the past, and, if possible, the yield and quality of past agricultural crops. As a result, it is difficult to determine pesticide spraying plans with high accuracy.

In this case, it is difficult to take into account the cost of spraying pesticides and the flight costs of drones and other aerial vehicles, so even if the harvest volume or quality improves as a result of spraying pesticides, the increase in sales (profits) of agricultural products may be smaller than the increased costs of spraying pesticides and flying the aerial vehicle.

Therefore, there is a need to develop more accurate pesticide spraying plans.

The present invention aims to develop a drug spraying plan with high accuracy.

In order to achieve the above object, an aircraft control system according to one embodiment of the present invention is an aircraft control system that controls an aircraft that sprays a pesticide in a field, and includes a quality information acquisition unit that acquires quality information relating to the measured quality of crops harvested in a specified area of the field from a quality measuring device that measures the quality of the crops, linking the measured quality with the area, and a plan calculation unit that calculates a spraying plan for the pesticide and a flight plan for the aircraft based on the quality information and the area, and the aircraft sprays the pesticide in the field based on the spraying plan and flight plan.

With this configuration, it is possible to calculate a pesticide spraying plan for each area by linking and taking into account quality information related to the quality of previously harvested agricultural crops and the area in which the crops were harvested, and further to calculate a flight plan for the aircraft. Therefore, it is possible to create a plan for spraying pesticides with high accuracy based on past pesticide spraying results, and to spray pesticides in a way that improves the quality and yield of harvested agricultural crops.

It is also preferable that the plan calculation unit calculates the spraying plan and the flight plan by taking into account at least one of the price of each quality of the agricultural product, the spraying cost of the pesticide, and the flight cost of the aircraft.

By spraying agricultural crops with pesticides, it is expected that the yield or quality of the crops will increase, resulting in increased profits. However, spraying pesticides using an aircraft requires costs for spraying the pesticide and costs for flying the aircraft, which reduces the increase in profits.

Therefore, by taking into account the price of each quality of crop, the cost of spraying the pesticide, and the flight cost of the aircraft when calculating the spraying plan and flight plan, it is possible to calculate a pesticide spraying plan and an aircraft flight plan that are expected to fully increase profits, and it is possible to create a more accurate plan for spraying pesticides that is expected to increase profits.

The agricultural product may be rice, the color sorter may sort the rice kernels into one of a number of pre-set product levels, and the quality may include the product level of the kernels and the ratio of the amount of the kernels sorted into each of the product levels to the total amount.

This configuration allows the system to take into account the proportion of each product level present, allowing more accurate drug spraying planning.

The quality measuring device may also be a color sorter.

This configuration makes it easy to measure the quality of agricultural crops.

It is also preferable that the spraying plan includes at least one of the type of pesticide to be sprayed, the amount of the pesticide to be sprayed, and the number of times the pesticide is to be sprayed, and that the flight plan includes a flight path.

This configuration allows for accurate planning of spraying plans and flight plans that fully incorporate all necessary information.

The area may be each section into which the field is divided, or each ridge or row of the field, and the quality information may be information on the quality measured for each section, each ridge, or each row.

This configuration allows spraying plans and flight plans to be created for each finer area, enabling spraying plans and flight plans to be created with greater accuracy.

The device may further include a memory unit, which stores a spraying management table in which the spraying plan for the harvested crop and the quality information of the harvested crop are linked to the area each time the crop is harvested, and the plan calculation unit may calculate the flight plan by referring to the spraying management table and the transition between the quality information of the harvested crop and the spraying plan for each area.

This configuration makes it possible to refer to the relationship between the pesticide spraying status recorded in the spraying management sheet (spraying status based on the pesticide spraying plan) and the quality information of the crops harvested as a result of the pesticide spraying. As a result, by referring to the trends in the pesticide spraying status and quality information, it is possible to create more accurate spraying plans and flight plans that reflect the actual pesticide spraying results.

FIG. 1 is a diagram illustrating a configuration for spraying pesticides using a drone. FIG. 2 is a diagram illustrating functional blocks of the drone control system. FIG. 13 is a diagram illustrating an example of a spraying management table. FIG. 1 is a diagram illustrating an example of an operation flow of the drone control system. FIG. 1 is a diagram illustrating an example of a plot of a farm field. FIG. 1 is a diagram illustrating a configuration for measuring rice quality using a color sorter.

[Spraying of drugs]
When growing crops in the field F, various pesticides are sprayed on the crops in the field F in order to increase the harvest yield of the crops and improve the quality of the harvested crops.

There are many different types of pesticides, and fertilizers are used to increase harvest yields. In order to suppress disease and pest damage in agricultural crops and improve the yield of harvested products (crops) of appropriate quality, pesticides are sprayed according to the disease or pest. In addition, pesticides need to be sprayed in appropriate amounts, at appropriate times, and with appropriate frequency.

As shown in Figure 1, the pesticide may be sprayed from the air onto crops 5, such as rice, in a field F, using a drone 1 (corresponding to an "aircraft"). The drone 1 is equipped with a tank 2 for storing the pesticide, and a spraying nozzle 3 for spraying the stored pesticide. The drone 1 sprays a predetermined amount of pesticide as it flies in a scanning manner above the field F. If the pesticide needs to be replenished during spraying, the drone 1 lands at a predetermined parking area 7 set up near the field F and is replenished with the pesticide from a supply tank 8.

The chemicals are sprayed based on a spraying plan 27 (see FIG. 2) in order to increase the harvest volume or improve the yield of crops of appropriate quality. The spraying plan 27 includes at least one of an appropriate type of chemical, an appropriate spraying amount, an appropriate number of sprays, an appropriate spraying time, etc., and is determined based on the quality of crops harvested in the past. In addition, the spraying plan 27 is determined for each field F or for each specified area within the field F.

[Drone control system]
Next, using Figures 1 to 3, we will explain a drone control system that determines a pesticide spraying plan 27 using a drone 1.

The quality of the harvested products (crops) is measured by a quality measuring device such as a color sorter 15. The color sorter 15 (quality measuring device) measures the quality of each harvested product harvested in the field F where the harvested products were harvested or in a specified area of the field F. Furthermore, the harvested products whose quality is being measured are accompanied by location information 17 that identifies the location of the field F or area. The color sorter 15 (quality measuring device) then links the location information 17 to output quality information 18, which is the result of the quality measurement.

The quality included in the quality information 18 may be any quality, such as the yield (weight), moisture content, size, whether the harvested product is defective or non-defective, depending on the quality measuring machine. A quality measuring machine such as the color sorter 15 judges whether the harvested product is good or defective, and discharges the harvested products as good or defective. Defects include, for example, damage by pests such as stink bugs, and in the case of rice, discolored rice and white rice. For example, the color sorter 15 can identify rice that has been damaged by stink bugs, discolored rice, white rice, etc. as defective.

In addition, a quality measuring machine such as a color sorter 15 records the amount of defects or the percentage of defects relative to the total amount of the harvested product whose quality was measured as quality information 18, linking it to location information 17 for each type of defect. For example, a quality measuring machine such as a color sorter 15 records the amount or percentage of rice damaged by stink bugs, the amount or percentage of discolored rice, and the amount or percentage of white rice, linking it to location information 17.

The drone control system illustrated in FIG. 2 includes a control unit 10 having a processor such as a CPU, and the control unit 10 includes a quality information acquisition unit 11, a plan calculation unit 12, and a memory unit 13.

The quality information acquisition unit 11 acquires quality information 18 measured by a quality measuring device such as a color sorter 15 and location information 17. The quality information acquisition unit 11 associates the quality information 18 with the location information 17 and stores them in the memory unit 13.

The plan calculation unit 12 calculates the dispersion plan 27 and the flight plan 28 based on the dispersion management table 21, taking into account at least one of the current purchase price 23, the dispersion cost 24, and the flight cost 25.

Specifically, when the yield (weight) of the harvested crop recorded in the spraying management table 21 is less than a predetermined yield, the plan calculation unit 12 selects fertilizer as the chemical, and calculates a spraying plan 27 and a flight plan 28 in accordance with the degree of yield deficiency, linking them to the location information 17, while taking into account at least one of the current purchase price 23, spraying cost 24, and flight cost 25. The plan calculation unit 12 also compares the moisture content and size recorded in the spraying management table 21 with predetermined values, and calculates a spraying plan 27 and a flight plan 28 in accordance with the comparison result, linking them to the location information 17, while taking into account at least one of the current purchase price 23, spraying cost 24, and flight cost 25. In addition, when a defect such as stink bug damage is recorded in the spray management table 21, the plan calculation unit 12 calculates a spray plan 27 and a flight plan 28 in accordance with the content and level of the defect, linking them to the location information 17, while taking into account at least one of the current purchase price 23, spray cost 24, and flight cost 25.

Then, the plan calculation unit 12 estimates the sales from the crops when the pesticide is sprayed and when it is not sprayed from the purchase price 23 and other prices, compares these with the total spraying cost 24 and flight cost 25, searches for the spraying plan 27 that will maximize the profit, and calculates the flight plan 28.

The plan calculation unit 12 may also calculate the dispersion plan 27 and the flight plan 28 using machine learning technology based on artificial intelligence.

The spraying plan 27 includes at least one of the following for each field F or area: the type of pesticide to be sprayed, the amount of pesticide to be sprayed, the number of times to spray, the time of spraying, etc. The flight plan 28 includes at least a flight path, which may include the flight route for spraying the pesticide as well as movement within the field F or area, movement for replenishing the pesticide, etc.

Purchase price 23 is not limited to the purchase price of agricultural products, and may be various prices such as market prices. Spraying cost 24 may include the cost of purchasing each pesticide to be sprayed, as well as labor costs associated with purchasing and spraying the pesticide. Flight cost 25 may include the cost of purchasing drone 1, fuel costs for drone 1, labor costs, and other costs incurred when flying drone 1.

The plan calculation unit 12 stores the calculated spraying plan 27 and flight plan 28 in the memory unit 13. The drone 1 sprays the pesticide on the crops in the field F in accordance with the spraying plan 27 and flight plan 28. In addition, the supply tank 8 is prepared with the amount of pesticide required for spraying based on the spraying plan 27.

As shown in FIG. 3, the spraying management table 21 records the quality, including past harvest volume results, and the spraying status of the pesticide (corresponding to the spraying plan 27 described below) for each field F or area each time a harvest is carried out, and stores the progress of the quality information 18 and the spraying status.

The spraying management table 21 illustrated in FIG. 3 records the area of the field F, the harvest volume (tan) from the time before last (two years ago), the target harvest volume (tan) from the time last (one year ago), the previous harvest volume (tan), the difference between the previous harvest volume (tan) and the target, the stink bug level, which is the level of damage caused by stink bugs as an example of the previous quality information 18, the target harvest volume (tan) for the current time (this year), the current harvest volume (tan), the difference between the current harvest volume (tan) and the previous year and the target, the current stink bug level, and the stink bug control status, which is the spraying status of the pesticide sprayed on the crops harvested this time. Here, the yield is the harvest volume per tan (10a). In the example of FIG. 3, the level of damage caused by stink bugs is recorded as quality information 18, but at least one of information related to pest damage such as stink bug damage, yield (weight), moisture content, size, discolored rice, white rice sap, etc. of the harvested product may also be recorded.

The control unit 10 updates the spraying management table 21 stored in the memory unit 13 based on the quality information 18 and location information 17 acquired by the quality information acquisition unit 11 and the spraying plan 27 from the previous time the pesticide was sprayed. As a result, the spraying management table 21 is updated and updated with quality information 18 of the crops to which the pesticide was sprayed based on the previous spraying plan 27 for each location information 17 (field F or area). Note that the spraying management table 21 may be configured so that information is added each time the pesticide is sprayed, harvested, or quality is measured, or it may be configured so that the oldest information is deleted when new information is added.

By spraying agricultural products with pesticides, it is expected that the yield will increase and the quality of the agricultural products will improve by preventing diseases and suppressing damage from pests. On the other hand, spraying pesticides with drone 1 requires the cost of spraying the pesticide (24) and the cost of flying drone 1 (25).

If the increase in profits due to improved crop yields and improved crop quality is sufficiently greater than the combined costs of spraying the pesticide 24 and flying the drone 1 25, it is worth spraying the pesticide, but if the increase in profits is less than the combined costs of spraying 24 and flying 25, there is less need to spray the pesticide.

The drone control system of the present invention can calculate a spraying plan 27 and a flight plan 28 for each field F or each area based on the quality information 18, thereby enabling accurate and appropriate pesticide spraying plans 27 and flight plans 28 to be created.

Furthermore, by using the spraying management table 21 to calculate the spraying plan 27 and flight plan 28 while taking into account past performance, a more accurate and appropriate spraying plan 27 for the pesticide can be created.

In addition, by calculating the spraying plan 27 and flight plan 28 taking into account the spraying cost 24 and flight cost 25, it is possible to accurately create a spraying plan 27 and flight plan 28 for the pesticide that will increase profits beyond the cost required for spraying the pesticide. Note that if the cost required for spraying the pesticide exceeds the increase in profits, the spraying plan 27 and flight plan 28 may be a plan that does not involve spraying the pesticide.

[Update of spray management sheet]
As described above, in the drone control system, the updating of the spraying management table 21 based on the spraying plan 27 and the calculation of the spraying plan 27 based on the spraying management table 21 are repeated. Below, the processing flow of the drone control system taking into consideration the updating of the spraying management table 21 will be described using Fig. 4 while also referring to Figs. 1 and 2.

First, the plan calculation unit 12 of the control unit 10 calculates the spray plan 27 and the flight plan 28 based on the spray management table 21 stored in the memory unit 13, taking into account the spray cost 24 and the flight cost 25 (step #1 in Figure 4). Then, the plan calculation unit 12 stores the spray plan 27 and the flight plan 28 in the memory unit 13.

Next, drone 1 is configured based on spraying plan 27 and flight plan 28 (step #2 in Figure 4), and sprays the pesticide on the crops in field F (step #3 in Figure 4).

When the crops in field F have grown sufficiently, they are harvested (step #4 in Figure 4).

When the crops are harvested, a color sorter 15 (quality measuring device) measures the quality of the harvested product (crops) for each field F or each area. Quality information 18 relating to the quality is linked to the location information 17 of the field F or area (step #5 in Figure 4).

The quality information acquisition unit 11 acquires quality information 18 linked to location information 17 from the color sorter 15 (quality measurement device) and stores it in the memory unit 13. The control unit 10 then updates the spray management table 21 based on the quality information 18 linked to location information 17 and the spray plan 27 stored in the memory unit 13 (step #6 in FIG. 4).

[Another embodiment]
(1) In the above embodiment, the area of the field F may be each of the sections f into which the field F is divided, as shown in Fig. 5. In this case, the quality information 18 is acquired for each section f, the quality information 18 is linked to the position information 17 that identifies the section f, and the spraying plan 27 and the flight plan 28 are calculated for each section f.

Furthermore, multiple fields F may be managed as a large-scale field, the large-scale field may be divided into areas each consisting of one or more fields F, quality information 18 may be acquired for each area, the quality information 18 may be linked to location information 17 that identifies the area, and a spraying plan 27 and a flight plan 28 may be calculated for each area.

Furthermore, one area may be one row in which seedlings are planted, and one area may be one ridge in which vegetables, etc. are grown. In this case, quality information 18 is acquired for each row or ridge, the quality information 18 is linked to position information 17 that identifies the row or ridge, and the spraying plan 27 and flight plan 28 are calculated for each row or ridge.

In addition, the area is not limited to the configuration defined by the plots f, rows, and ridges of the field F, but may be the range in which the harvested products (crops) are harvested at one time.

For example, as shown in FIG. 6, rice plants planted in rows are harvested by a harvester C in groups of several rows. At this time, the harvester C threshes the harvested stalks while traveling back and forth across the field F, and stores the resulting grains in a grain tank. When the grain tank is filled with grains, the harvester C discharges the grains into a grain transport vehicle T. When the grain transport vehicle T is filled with collected grains or has collected a predetermined amount of grains, it transports the grains to a dryer 29. The dryer 29 dries the transported grains. A color sorter 15 (quality measuring device) measures the quality of the dried grains in the form of brown rice or polished rice.

At this time, the harvester C, grain transport vehicle T, dryer 29, and color sorter 15 (quality measurement device) manage position information 17, which is information about the position in the field F where the grains (harvest product) were harvested. The color sorter 15 (quality measurement device) then outputs quality information 18 related to the measured quality, linked to the position information 17.

In this situation, the area can be the range of the harvested product (crops) harvested by the harvester C between the time the harvester C discharges grains and the time the harvester C discharges them again, the range of the harvested product (crops) related to the grains transported in one go by the grain transport vehicle T, the range of the harvested product (crops) related to the grains dried in one go by the dryer 29, and the range of the harvested product (crops) related to the grains whose quality is measured in one go by the color sorter 15 (quality measuring device).

As described above, by setting areas according to the work status, linking each area with the location information 17 to obtain quality information 18, and calculating a spray plan 27 and a flight plan 28 for each area, it is possible to accurately create an appropriate drug spray plan 27 and flight plan 28 according to the work status.

(2) In each of the above embodiments, the quality measuring device such as the color sorter 15 may not record the amount or percentage of defects, but may manually inspect the harvested product (crops) that has been rejected as defective, and determine the amount or percentage of defects for each type of defect as quality information 18, which may then be manually recorded in the spray management table 21 in association with the location information 17.

(3) In each of the above embodiments, the color sorter 15 (quality measuring device) may sort (category) the quality of the harvested product into one of a number of pre-set product levels. For example, if the agricultural product is rice, the product level may be categorized as finished product, middle rice, broken rice, etc. In this case, the quality may be the yield of each product level for each field F or area. The yield may be the ratio of the amount of harvested product categorized into each product level to the total amount (total amount) of harvested product sorted for each field F or area.

The yield may also be the ratio of the amount of harvested product classified as good to the total amount (total amount) of harvested product selected for each field F or region. In this case, the quality information 18 in the spraying management table 21 may be this yield (the ratio of good products in the harvested product).

(4) In each of the above embodiments, the plan calculation unit 12 may calculate the pesticide spraying plan 27 and the drone 1 flight plan 28 based on the quality information 18 and location information 17 of the agricultural crop to which the pesticide was previously sprayed, without using the spraying management table 21.

This makes it easy to create drug spray plans 27 and flight plans 28.

(5) In each of the above embodiments, the plan calculation unit 12 may calculate the drug spraying plan 27 and the drone 1 flight plan 28 without taking into account the spraying cost 24 and the flight cost 25.

This makes it easy to create drug spray plans 27 and flight plans 28.

(6) In each of the above embodiments, the control unit 10 is not limited to being composed of the functional blocks described above, and may be composed of any functional blocks. For example, each functional block of the control unit 10 may be further subdivided, or conversely, some or all of the functional blocks may be combined. Furthermore, the functions of the control unit 10 are not limited to the functional blocks described above, and may be realized by a method executed by any functional block. Furthermore, some or all of the functions of the control unit 10 may be composed of software. A program related to the software is stored in any storage device such as the storage unit 13, and is executed by a processor such as a CPU provided in the control unit 10, or a processor provided separately.

(7) In each of the above embodiments, the quality measuring device is not limited to the color sorter 15 and may be any measuring device, for example, a yield measuring device mounted on the harvester C or a measuring device that measures moisture, etc.

(8) In each of the above embodiments, the spraying of the pesticide is performed not only by drone 1 but also by any flying object such as a remote-controlled airplane, and the control system of the flying object may calculate spraying plan 27 and flight plan 28 for spraying the pesticide by the flying object.

The present invention can be applied to spraying pesticides using drones not only on rice, but also on vegetables such as carrots and various other agricultural crops.

1. Drone (flying object)
5 Agricultural products 11 Quality information acquisition unit 12 Plan calculation unit 15 Color sorter (quality measurement device)
17 Location information 18 Quality information 21 Spraying management sheet 23 Purchase price (price)
24 Spraying cost 25 Flight cost 27 Spraying plan 28 Flight plan F Field f Plot

Claims (7)

An aircraft control system for controlling an aircraft that sprays a pesticide in a field,
a quality information acquisition unit that acquires, from a quality measuring device that measures the quality of agricultural products harvested in a predetermined area of the farm field, quality information relating to the measured quality and the area in association with the measured quality information;
A plan calculation unit that calculates a spray plan for the drug and a flight plan for the aircraft based on the quality information and the area;
Equipped with
The aircraft sprays the agent on the field based on the spraying plan and the flight plan ;
Further comprising a storage unit,
The memory unit stores a spraying management table in which the spraying plan for the harvested crop and the quality information of the harvested crop are linked to the area each time the crop is harvested,
The plan calculation unit is an aircraft control system that calculates the flight plan by referring to the spraying management table and the transition between the quality information of the crops harvested in the past and the spraying plan for each area . The aircraft control system of claim 1, wherein the plan calculation unit calculates the spraying plan and the flight plan by taking into account at least one of the price of the crop for each quality, the spraying cost of the pesticide, and the flight cost of the aircraft. The crop is rice,
The quality measuring machine classifies the rice kernels into one of a plurality of pre-set product grades;
3. The aircraft control system of claim 1, wherein the quality includes classification of the kernels into product levels and a ratio of the amount of the kernels classified into each product level to the total amount of the kernels. An aircraft control system according to any one of claims 1 to 3, wherein the quality measuring device is a color sorter. The spraying plan includes at least one of the type of the drug to be sprayed, the amount of the drug to be sprayed, and the number of times the drug is sprayed,
The air vehicle control system of claim 1 , wherein the flight plan includes a flight path. The aircraft control system according to any one of claims 1 to 5, wherein the area is each section into which the field is divided, or each ridge or row of the field, and the quality information is information on the quality measured for each section, each ridge, or each row. An aircraft control system for controlling an aircraft that sprays a pesticide in a field,
a quality information acquisition unit that acquires, from a quality measuring device that measures the quality of agricultural products harvested in a predetermined area of the farm field, quality information relating to the measured quality and the area in association with the measured quality information;
A memory unit that stores the past quality information and the transition of the spraying status of the drug;
A plan calculation unit that calculates a spray plan for the drug and a flight plan for the aircraft based on the quality information and the change in the spray status read from the memory unit;
Equipped with
The aircraft is an aircraft control system that sprays the pesticide on the field based on the spraying plan and the flight plan.

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