A harvesting scheduling method, device and medium for joint operation of multiple agricultural machines

Abstract

The embodiments of the present specification disclose a harvesting scheduling method, device and medium for combined operation of multiple agricultural machines, which relates to the field of smart agricultural technology and is used to solve the problems of low efficiency and high labor cost of harvesting and unloading methods in the prior art. The method includes: determining the harvesters to be operated for combined harvesting and the grain transport vehicles to be operated based on the basic information of the current farm; monitoring the storage information of the built-in storage bins of the harvesters to be operated based on preset sensors, so as to predict the unloading time of the harvesters to be operated based on the storage information and the storage preset positions of the harvesters to be operated; determining the harvesting posture data of the harvesters to be operated through multiple types of sensors, so as to predict the harvesting work area at the next moment; determining the unloading position according to the positional relationship between the harvesting component and the unloading component; generating an unloading scheduling instruction according to the unloading time and the unloading position and broadcasting it to the grain transport vehicles to be operated, and controlling the grain transport vehicles to be operated to unload grain and transport based on the path planning results.

Description

Technical Field

[0001] The present invention relates to the field of smart agricultural technology, and in particular to a harvesting scheduling method, device and medium for combined operation of multiple agricultural machines. Background Art

[0002] The booming development of large farms has given rise to agricultural machinery service companies, which rely on agricultural machinery such as harvesters, drone seeders and other equipment to provide field operation services for large farms or agricultural cooperatives. Due to the large area of ​​arable land and complex plot types on farms, large combine harvesters and other agricultural machinery have been developed to improve the efficiency of agricultural machinery field operations. Combine harvesters are combined machines for harvesting crops. They are harvesting machines that can complete the processes of harvesting, threshing, separating stems, and removing debris from cereal crops at one time, and directly obtain grains from the field.

[0003] In the current traditional method, after the crops harvested by the combine harvester are harvested and stored in the storage bin of the combine harvester, due to the limited storage volume of the storage bin, in order to ensure the harvesting efficiency, it is necessary to unload the harvester that has reached the upper limit of the storage capacity in time, that is, the harvested crops are transferred and stored in the storage bin manually or mechanically to facilitate the continued operation of the harvester. However, when unloading grain based on the manual unloading method, the harvested crops are generally obtained through sacks at the unloading port. This manual unloading method consumes a lot of human resources and is prone to waste of crops due to the rupture of sacks. The method based on mechanical unloading is generally based on the harvester driver's judgment based on human experience that when unloading grain is needed, the grain transport vehicle is notified by phone or other communication methods for transportation. However, this method is difficult to obtain matching vehicles in time for efficient transportation when operating on large farms due to the large number and complex types of agricultural machinery, so as to achieve coordinated harvesting and unloading of crops. Summary of the invention

[0004] In order to solve the above technical problems, one or more embodiments of the present specification provide a harvesting scheduling method, device and medium for joint operation of multiple agricultural machines.

[0005] One or more embodiments of this specification adopt the following technical solutions:

[0006] One or more embodiments of this specification provide a harvesting scheduling method for multiple agricultural machinery joint operations, the method comprising:

[0007] Based on the basic information of the current farm, determine the harvesters and grain transport vehicles to be used for combined harvesting; wherein the basic information includes: terrain data, planting information, and equipment information;

[0008] Monitoring the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated;

[0009] Determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data;

[0010] Determining a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated;

[0011] A grain unloading scheduling instruction is generated according to the grain unloading time and the grain unloading location, and the grain unloading scheduling instruction is broadcast to the grain transport vehicle to be operated, and real-time path planning is performed according to the location of the grain transport vehicle to be operated and the grain unloading location to control the grain transport vehicle to be operated to carry out grain unloading transportation.

[0012] Optionally, in one or more embodiments of the present specification, based on the basic information of the current farm, determining the harvester to be operated for the combine harvest and the grain transport vehicle to be operated specifically includes:

[0013] Acquire terrain data of a current farm and crop planting information of the current farm; wherein the crop planting information includes: crop type, crop planting time, and crop planting cycle;

[0014] Dividing the current farm into a plurality of farmland operation areas based on the crop type, and determining a harvester type corresponding to each of the farmland operation areas; wherein the farmland operation areas correspond to the same crop type;

[0015] Acquire harvesters of different models corresponding to the harvester type, and acquire the lifting and lowering range of the linkage harvesting system of each harvester of the different models; wherein the linkage harvesting system is composed of a lifting system and a linkage system connected to the harvester chassis and the harvesting assembly;

[0016] Determine the harvester to be operated corresponding to the current farm based on the lifting range of the linked harvesting system of each harvester of different models and the terrain data corresponding to each farmland operation area;

[0017] The corresponding grain transport vehicle type is determined based on the discharge port structure information of each harvester to be operated, and the grain transport vehicle type is scheduled based on the grain transport vehicle type and the equipment information of the current farm to obtain the grain transport vehicle to be operated with the minimum cost on the current farm.

[0018] Optionally, in one or more embodiments of the present specification, based on the grain transport vehicle type and the equipment information of the current farm, the grain transport vehicle of the grain transport vehicle type is dispatched to obtain the grain transport vehicle to be operated with the minimum cost of the current farm, specifically including:

[0019] According to the type of grain transport vehicle and the equipment information of the current farm, the grain transport vehicle corresponding to each harvester to be operated is divided into a first grain transport vehicle and a second grain transport vehicle; wherein the first grain transport vehicle is an idle grain transport vehicle configured for the current farm, and the second grain transport vehicle is an unconfigured or non-idle grain transport vehicle for the current farm;

[0020] If it is determined that the grain transport vehicle corresponding to the harvester to be operated is the second grain transport vehicle, then determining an initial second grain transport vehicle within a preset range based on the location of the current farm;

[0021] Determine the distance cost of each of the initial second grain transport vehicles according to the distance between each of the initial second grain transport vehicles and the current farm within the preset range and the historical fuel consumption record of the initial second grain transport vehicles;

[0022] Based on the distance cost, a preset number of initial second grain transport vehicles are obtained as the second grain transport vehicles to be selected, a rental price of each of the second grain transport vehicles to be selected is obtained, and based on the rental platform corresponding to each of the second grain transport vehicles to be selected, a rental evaluation of each of the second grain transport vehicles to be selected is extracted;

[0023] Determine a first weighting coefficient of the distance cost based on the rental price, and determine a second weighting coefficient of the distance cost based on the rental evaluation, so as to perform weighted processing on the distance cost according to the first weighting coefficient and the second weighting coefficient, obtain the rental cost of each of the second grain transport vehicles to be selected, and obtain the second grain transport vehicle to be selected with the minimum cost;

[0024] The first grain transport vehicle and the second grain transport vehicle with the lowest cost are selected as the grain transport vehicles with the lowest cost to be operated in the current farm.

[0025] Optionally, in one or more embodiments of the present specification, before determining the harvester to be operated for the combine harvest and the grain transport vehicle to be operated based on the basic information of the current farm, the method further includes:

[0026] Acquire multispectral images of the current farm based on a drone, and determine the chlorophyll content of crops in each farmland operation area of ​​the current farm based on destructive sampling;

[0027] Performing continuous wavelet transform on the multispectral image data based on a preset wavelet basis function and a red edge wavelength range to obtain wavelet coefficients corresponding to the reflectivity of the red edge band image data;

[0028] Inputting the wavelet coefficients into a random forest model trained based on multispectral images of historical harvesting processes to predict the predicted chlorophyll content corresponding to the wavelet coefficients;

[0029] Based on the crop growth model corresponding to the farmland operation area, respectively determining the quantitative detection maturity corresponding to the chlorophyll content of the crop in the farmland operation area and the predicted maturity corresponding to the predicted chlorophyll content;

[0030] Determine the maturity of crops in each farmland operation area in the current farm based on the average of the quantitatively detected maturity and the predicted maturity;

[0031] If it is determined that the maturity of the crop reaches the maturity index value corresponding to the crop type, it is determined to harvest the farmland operation area.

[0032] Optionally, in one or more embodiments of the present specification, the storage information of the built-in storage bin of the harvester to be operated is monitored based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated, specifically including:

[0033] Acquire storage bin structure data of the built-in storage bin of the harvester to be operated, and detect grain collection data of the harvester to be operated and remaining space data of the storage bin based on the preset sensor;

[0034] The storage bin structure data, the grain collection data and the remaining space data are used as the storage information, so as to establish a geometric digital twin model corresponding to the storage bin of the harvester to be operated based on the storage information;

[0035] Based on the geometric digital twin model, the grain collection position of the storage bin is acquired in real time to determine whether the grain collection position reaches the storage preset position of the harvester to be operated;

[0036] If so, based on the grain collection position and the storage bin structure data, the remaining storage height of the storage bin is determined, and a grain collection simulation is performed in the geometric digital twin model according to the remaining storage height and the grain collection data to predict the grain unloading time of the harvester to be operated.

[0037] Optionally, in one or more embodiments of the present specification, the harvesting posture data of the harvester to be operated is determined by a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data, specifically including:

[0038] Based on the preset monitoring type of the attitude sensor, the attitude sensor is respectively installed at the preset position of the harvester to be operated; wherein the preset monitoring type can specify the corresponding attitude sensor to monitor at different positions;

[0039] Monitoring the steering angle of the steering mechanism of the harvester to be operated according to a first posture sensor of the harvester to be operated at a first preset position;

[0040] According to a second posture sensor of the harvester to be operated at a second preset position, monitoring the extension and contraction amount of the connecting oil cylinder corresponding to the harvester chassis of the harvester to be operated;

[0041] According to the third posture sensor of the harvester to be operated at the third preset position, the posture angle of each component in the harvesting assembly of the harvester to be operated is monitored, so as to determine the posture data of the harvester to be operated at the current moment according to the steering angle of the steering mechanism, the telescopic amount of the connecting cylinder and the posture angle of each component;

[0042] According to the position sensor on the harvester to be operated, the operating position of the harvester to be operated is obtained in real time, so as to mark the posture data at the current moment based on the operating position and obtain the harvesting posture data of the harvester to be operated;

[0043] Based on the harvesting action characteristics of the harvester to be operated, the harvesting action at the next moment corresponding to the harvesting posture data is determined, and the harvesting action at the next moment, the harvesting posture data and the driving speed of the harvester to be operated are input into a preset prediction model to output the harvesting working area of ​​the harvester to be operated at the next moment.

[0044] Optionally, in one or more embodiments of the present specification, determining the grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated specifically includes:

[0045] According to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated, the position of the grain unloading component relative to the harvesting working area at the next moment is determined to determine the grain unloading center point position of the grain unloading component;

[0046] The grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting work area at the next moment;

[0047] Wherein, after the grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting working area at the next moment, the method further includes:

[0048] Based on the built-in sensor of the grain transport vehicle to be operated, three-dimensional point cloud data of the storage area of ​​the grain transport vehicle to be operated is obtained;

[0049] The crop stacking distribution of the grain transport vehicle to be operated is determined in real time based on the three-dimensional point cloud data of the storage area, and the position of the grain transport vehicle to be operated is adjusted according to the crop stacking distribution and the grain unloading position.

[0050] Optionally, in one or more embodiments of the present specification, real-time path planning is performed according to the position of the grain transport vehicle to be operated and the grain unloading position, and the grain transport vehicle to be operated is controlled to unload grain for transportation, specifically including:

[0051] Acquire the position of the grain transport vehicle to be operated as the starting position, and acquire the grain unloading position as the end position;

[0052] Determine the road driving area and the farmland driving area between the grain transport vehicle to be operated and the grain unloading position based on the starting position and the end position;

[0053] Based on the road turning points in the road driving area and the obstacle nodes in the farmland driving area, the driving nodes of the grain transport vehicle to be operated are determined, and based on the driving nodes, the driving directed graph nodes corresponding to the grain transport vehicle to be operated are determined;

[0054] The optimal path corresponding to the node of the driving directed graph is determined by an ant colony algorithm, and the grain transport vehicle to be operated is controlled to reach the grain unloading location based on the optimal path for grain unloading and transportation.

[0055] One or more embodiments of this specification provide a harvesting scheduling device for combined operation of multiple agricultural machines, the device comprising:

[0056] The first determination unit is used to determine the harvester and the grain transport vehicle to be operated for the combine harvest based on the basic information of the current farm; wherein the basic information includes: terrain data, planting information, and equipment information;

[0057] A first prediction unit is used to monitor the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated;

[0058] A second prediction unit is used to determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data;

[0059] A second determining unit is used to determine a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated;

[0060] A control unit is used to generate a grain unloading scheduling instruction according to the grain unloading time and the grain unloading location, broadcast the grain unloading scheduling instruction to the grain transport vehicle to be operated, and perform real-time path planning according to the location of the grain transport vehicle to be operated and the grain unloading location, so as to control the grain transport vehicle to be operated to carry out grain unloading transportation.

[0061] One or more embodiments of this specification provide a non-volatile computer storage medium storing computer executable instructions, wherein the computer executable instructions are configured to:

[0062] Based on the basic information of the current farm, determine the harvesters and grain transport vehicles to be used for combined harvesting; wherein the basic information includes: terrain data, planting information, and equipment information;

[0063] Monitoring the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated;

[0064] Determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data;

[0065] Determining a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated;

[0066] A grain unloading scheduling instruction is generated according to the grain unloading time and the grain unloading location, and the grain unloading scheduling instruction is broadcast to the grain transport vehicle to be operated, and real-time path planning is performed according to the location of the grain transport vehicle to be operated and the grain unloading location to control the grain transport vehicle to be operated to carry out grain unloading transportation.

[0067] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0068] Determining the corresponding harvesters and grain transport vehicles to be operated based on the basic information of the farm facilitates effective harvesting based on the appropriate type of harvester, and also solves the problem of equipment damage to the harvester caused by mismatched harvesters when harvesting due to different requirements for harvester chassis in different terrains. By obtaining the storage information of the built-in storage bin of the harvester to be operated through sensor monitoring to predict the unloading time, the problem of unloading based on manual experience easily leading to harvesting suspension and thus affecting harvesting efficiency is avoided. By predicting the harvesting work area at the next moment, it is convenient to remind the operator in time the harvesting work area where the harvester needs to work, so that the operator can avoid and detour in time, and it is convenient for the driver to observe the dangerous area to avoid safety hazards during the harvesting process, and it is also convenient for the subsequent determination of the unloading location based on the harvesting work area. Notifying the grain transport vehicles to be operated to unload grain based on the broadcast method solves the delay problem existing in the existing notification method. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art description. Obviously, the drawings described below are only some embodiments recorded in this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. In the drawings:

[0070] Figure 1 A schematic flow chart of a harvesting scheduling method for a multi-agricultural machine joint operation provided in an embodiment of this specification;

[0071] Figure 2 A schematic diagram of the internal structure of a harvesting scheduling device for multiple agricultural machinery combined operations provided in an embodiment of this specification;

[0072] Figure 3 A schematic diagram of the internal structure of a non-volatile storage medium provided in an embodiment of this specification. DETAILED DESCRIPTION

[0073] The embodiments of this specification provide a harvesting scheduling method, device and medium for joint operation of multiple agricultural machines.

[0074] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0075] like Figure 1 As shown, the embodiment of this specification provides a flowchart of a harvesting scheduling method for a multi-agricultural machine joint operation. Figure 1 It can be seen that a harvesting scheduling method for multiple agricultural machinery combined operations in one or more embodiments of this specification includes the following steps:

[0076] S101: Based on the basic information of the current farm, determine the harvesters and grain transport vehicles to be used for combine harvesting; wherein the basic information includes: terrain data, planting information, and equipment information.

[0077] In order to achieve the purpose of combining the grain transport vehicles to be operated with the harvesters to be operated, thereby improving the harvesting efficiency and reducing the time cost, in an embodiment of this specification, the harvesters to be operated and the grain transport vehicles to be operated for combined harvesting are determined based on the basic information such as the current farm's terrain data, planting information, and equipment information. Prior to this, in order to determine that the maturity of the crops in the current farm has reached the harvesting standard and ensure that the harvested crops have a high quality, in an embodiment of this specification, before determining the harvesters to be operated and the grain transport vehicles to be operated for combined harvesting based on the basic information of the current farm, the method also includes the following steps:

[0078] Since the chlorophyll content of crops can reflect the current growth stage and maturity of crops, the method of manual judgment based on sampling alone is often too one-sided and lacks global reliability due to the problem of limited sampling samples and high analysis costs after large-scale sampling. Therefore, in the embodiment of this specification, on the one hand, the multispectral image of the current farm is obtained based on the drone, and on the other hand, the chlorophyll content of crops in each farmland operation area in the current farm is determined by destructive sampling. Then, in order to obtain the chlorophyll content of crops, in the embodiment of this specification, the multispectral image data is continuously transformed according to the pre-set wavelet basis function and the red edge wavelength range, and then the wavelet coefficient corresponding to the reflectivity of the red edge band image data is obtained. Then the wavelet coefficient is input into the random forest model obtained by multispectral image training based on the historical harvesting process, so as to predict the predicted chlorophyll content corresponding to the wavelet coefficient according to the random forest model. At this time, based on the crop growth model corresponding to the farmland operation area, the quantitative detection maturity corresponding to the chlorophyll content of the crop in the farmland operation area and the predicted maturity corresponding to the predicted chlorophyll content are determined respectively. Then, based on the average of the quantitatively detected maturity and the predicted maturity, the maturity of the crops in each farmland operation area in the current farm is determined. If it is determined that the maturity of the crops reaches the maturity index value corresponding to the crop type, it is determined that the farmland operation area will be harvested. Among them, it should be noted that there are differences in the maturity index values ​​corresponding to different types of crops, and the specific values ​​are set based on historical human experience. The maturity of the crops in each farmland operation area is determined by combining the predicted maturity obtained by the global chlorophyll content determination and the quantitative detection maturity obtained by local sampling. Both global and local characteristics are taken into account, making the maturity prediction more accurate and ensuring the maturity quality of the crops when they are harvested.

[0079] In one embodiment of the present specification, based on the basic information of the current farm, determining the harvester and the grain transport vehicle to be operated for the combine harvesting specifically includes the following steps:

[0080] First, the terrain data of the current farm and the crop planting information of the current farm are obtained. It should be noted that the crop planting information includes: crop type, crop planting time, and crop planting cycle. In order to enable the corresponding harvester to harvest the corresponding crops, the current farm is divided into several farmland operation areas according to the crop type in the embodiment of this specification, and the harvester type corresponding to each farmland operation area is determined; it should be understood that in order to facilitate the harvesting of the harvester, the farmland operation area corresponds to the same type of crop. By matching the corresponding harvester after dividing the farmland operation area, the problem of different types of harvesters corresponding to different crops is solved, and it is convenient to effectively harvest based on the appropriate type of harvester. Then, in order to solve the different requirements of different terrains for the harvester chassis, resulting in equipment damage to the harvester when the unmatched harvester is harvested, different types of harvesters corresponding to the harvester type are obtained in the embodiment of this specification, and the lifting range of the linkage harvesting system of each different type of harvester is obtained. Among them, it should be noted that the current traditional linkage harvesting system is generally composed of a lifting system and a linkage system connected to the harvester chassis and harvesting components. Based on the lifting range of the linkage harvesting system of each harvester of different models and the terrain data corresponding to each farmland operation area, the harvester to be operated corresponding to the current farm is determined. Then, according to the discharge port structure information of each harvester to be operated, the corresponding grain transport vehicle type is determined, and based on the grain transport vehicle type and the equipment information of the current farm, the grain transport vehicle type is dispatched to obtain the grain transport vehicle to be operated with the minimum cost on the current farm.

[0081] Further, in one or more embodiments of the present specification, based on the type of grain transport vehicle and the equipment information of the current farm, the grain transport vehicle of the grain transport vehicle type is dispatched to obtain the grain transport vehicle to be operated with the minimum cost of the current farm, which specifically includes the following process:

[0082] First, large farms sometimes equip themselves with general agricultural machinery in order to save the cost of renting agricultural machinery during operation. Therefore, when agricultural machinery is needed during the harvesting process, the grain transport vehicles corresponding to each harvester to be operated are first divided into the first grain transport vehicle and the second grain transport vehicle according to the type of grain transport vehicle and the equipment information of the current farm. It should be noted that the first grain transport vehicle is an idle grain transport vehicle configured by the current farm, while the second grain transport vehicle is a grain transport vehicle that is not configured or is not idle on the current farm.

[0083] If it is determined that the grain transport vehicle corresponding to the harvester to be operated is the second grain transport vehicle, that is, the grain transport vehicle is not equipped or is not idle in the current farm, then it is necessary to rent the corresponding grain transport vehicle from the car rental company. At this time, in order to obtain a grain transport vehicle with a lower cost, the embodiment of this specification determines the initial second grain transport vehicle within the preset range according to the location of the current farm. Then, based on the distance between each initial second grain transport vehicle and the current farm within the preset range and the historical fuel consumption record of the initial second grain transport vehicle, the distance cost of each initial second grain transport vehicle is determined. Then, based on the distance cost, a preset number of initial second grain transport vehicles with a smaller distance cost are obtained as the second grain transport vehicles to be selected, and then the rental price of each second grain transport vehicle to be selected is obtained, and the rental evaluation of each second grain transport vehicle to be selected is extracted based on the rental platform corresponding to each second grain transport vehicle to be selected. The first weighted coefficient of the distance cost is determined based on the rental price, and the second weighted coefficient of the distance cost is determined based on the proportion of negative evaluations in the rental evaluation, so that the distance cost is weighted according to the first weighted coefficient and the second weighted coefficient to obtain the rental cost of each second grain transport vehicle to be selected, and the second grain transport vehicle to be selected with the minimum cost can be obtained by sorting the second grain transport vehicles based on the rental cost. Then the first grain transport vehicle and the second grain transport vehicle to be selected with the minimum cost are used as the grain transport vehicles to be operated with the minimum cost of the current farm.

[0084] S102: Monitoring the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated.

[0085] Since the storage volume of the storage bin is limited, when operating in a large farm, in order to ensure harvesting efficiency, it is necessary to unload the grain from the harvester that has reached the upper limit of the storage capacity in a timely manner. Therefore, in order to solve the problem of the driver's judgment based on experience that it is easy to make mistakes when unloading grain, in the embodiments of this specification, the storage information of the storage bin stored in the harvester to be operated is monitored based on a pre-set sensor, so as to predict the unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated. Specifically, in one or more embodiments of this specification, the storage information of the built-in storage bin of the harvester to be operated is monitored based on the preset sensor, so as to predict the unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated, which specifically includes the following process:

[0086] First, the storage bin structure data of the built-in storage bin of the harvester to be operated is obtained, and the grain collection data of the harvester to be operated and the remaining space data of the storage bin are detected based on the preset sensor. Then the storage bin structure data, grain collection data and remaining space data are used as storage information to establish a geometric digital twin model corresponding to the storage bin of the harvester to be operated based on the storage information. Through the geometric digital twin model, the grain collection position of the storage bin can be determined in real time and intuitively, and then it can be determined whether the grain collection position has reached the storage preset position of the harvester to be operated. Among them, it should be noted that: the storage preset position is a position at a certain distance below the top of the storage bin. The setting process of the storage preset position can first determine the maximum arrival time based on twice the maximum diameter in the farmland operation area and the farmland driving speed of the transport vehicle, and at the same time determine the volume of crops that can be harvested within the maximum arrival time based on the maximum arrival time and the grain collection rate of the harvester, and determine the storage preset position based on the volume of crops that can be harvested and the cross-sectional area of ​​the storage bin. If the storage preset position is reached, the remaining storage height of the storage bin is determined based on the grain collection position and the storage bin structure data. Grain collection simulation is performed in the geometric digital twin model based on the remaining storage height and grain collection data to predict the grain unloading time of the harvester to be operated. The simulation of the grain collection scene based on the geometric digital twin model can intuitively display the grain storage status of the storage bin, reducing the problem of accuracy and reliability that is difficult to grasp due to manual experience judgment.

[0087] S103: Determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data.

[0088] Since the harvesting components of the harvester are harmful to a certain extent when it is harvesting, and the cab of the harvester is relatively high, there may be a blind spot for the rear harvesting components. When an operator appears in the blind spot, personal safety may be damaged. In the embodiments of this specification, the position sensor and attitude sensor installed on the harvester to be operated are used to determine the harvesting attitude data of the harvester to be operated, so as to predict the harvesting work area of ​​the harvester to be operated at the next moment based on the harvesting attitude data. By predicting the harvesting work area at the next moment, it is convenient to remind the operator in time the harvesting work area where the harvester needs to work, so that the operator can avoid and detour in time, and it is convenient for the driver to observe the dangerous area to avoid safety hazards during the harvesting process, and it is also convenient for the subsequent determination of the unloading position based on the harvesting work area. Specifically, in one or more embodiments of this specification, the harvesting attitude data of the harvester to be operated are determined by installing a position sensor and an attitude sensor on the harvester to be operated, so as to predict the harvesting work area of ​​the harvester to be operated at the next moment based on the harvesting attitude data, which specifically includes the following processes:

[0089] First, based on the preset monitoring type of the attitude sensor, the attitude sensor is installed at the preset position of the harvester to be operated. It should be noted that different monitoring types are used to detect different problems, so the corresponding attitude sensor can be specified to monitor at different positions according to the preset monitoring type. After different types of sensors are installed on the harvester to be operated, the steering angle of the steering mechanism of the harvester to be operated can be monitored according to the first attitude sensor of the harvester to be operated at the first preset position. At the same time, according to the second attitude sensor of the harvester to be operated at the second preset position, the telescopic amount of the connecting cylinder corresponding to the harvester chassis of the harvester to be operated is monitored. According to the third attitude sensor of the harvester to be operated at the third preset position, the attitude angle of each component in the harvesting assembly of the harvester to be operated is monitored, so as to determine the attitude data of the harvester to be operated at the current moment according to the steering angle of the steering mechanism, the telescopic amount of the connecting cylinder and the attitude angle of each component. Then, according to the position sensor on the harvester to be operated, the working position of the harvester to be operated is obtained in real time, so as to identify the attitude data at the current moment based on the working position, and obtain the harvesting attitude data of the harvester to be operated. Then, according to the harvesting action characteristics of the harvester to be operated, the harvesting action at the next moment corresponding to the harvesting posture data is determined, and the harvesting action at the next moment, the harvesting posture data and the driving speed of the harvester to be operated are input into the preset prediction model to output the harvesting work area of ​​the harvester to be operated at the next moment. It should be noted that the preset prediction model is based on the historical harvesting records of the current farm as training samples, and is obtained by inputting the training samples into the neural network model for iterative training. The training process of the existing neural network model will not be elaborated here.

[0090] S104: Determine a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated.

[0091] In order to solve the problem of crops being easily spilled and manual bagging being too inefficient during manual unloading in the prior art. In the embodiments of this specification, the unloading position corresponding to the harvesting work area at the next moment is determined according to the positional relationship between the harvesting component and the unloading component in the harvester to be operated. Specifically, in one or more embodiments of this specification, the unloading position corresponding to the harvesting work area at the next moment is determined according to the positional relationship between the harvesting component and the unloading component in the harvester to be operated, which specifically includes the following process:

[0092] First, according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated, the position of the grain unloading component relative to the harvesting work area at the next moment is determined to determine the grain unloading center point position of the grain unloading component. Then, the grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting work area at the next moment. Among them, in one embodiment of the present specification, after the grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting work area at the next moment, the method also includes the following process: First, based on the built-in sensor of the grain transport vehicle to be operated, the three-dimensional point cloud data of the storage area of ​​the grain transport vehicle to be operated is obtained. Therefore, the crop accumulation distribution of the grain transport vehicle to be operated is determined in real time based on the three-dimensional point cloud data of the storage area, and the position of the grain transport vehicle to be operated is adjusted according to the crop accumulation distribution and the grain unloading position. By timely adjusting the position of the grain transport vehicle to be operated based on the crop accumulation distribution, the problem of easy accumulation and overflow when the same position receives the crops output from the grain unloading position is avoided, and the utilization rate of the storage bin of the grain transport vehicle is improved.

[0093] S105: Generate a grain unloading scheduling instruction according to the grain unloading time and the grain unloading location, broadcast the grain unloading scheduling instruction to the grain transport vehicle to be operated, and perform real-time path planning according to the location of the grain transport vehicle to be operated and the grain unloading location, so as to control the grain transport vehicle to be operated to carry out grain unloading transportation.

[0094] In order to solve the problem that the harvester driver is prone to time difference when contacting the grain transport truck driver by phone, which makes the harvesting time too long, in the embodiment of this specification, the grain unloading scheduling instruction is generated according to the grain unloading time and grain unloading position, so as to broadcast the grain unloading scheduling instruction to the grain transport vehicle to be operated, and perform real-time path planning according to the position of the grain transport vehicle to be operated and the grain unloading position, and control the grain transport vehicle to be operated to unload grain and transport. Specifically, in one or more embodiments of this specification, real-time path planning is performed according to the position of the grain transport vehicle to be operated and the grain unloading position, and the grain transport vehicle to be operated is controlled to unload grain and transport, which specifically includes the following process:

[0095] First, the position of the grain transport vehicle to be operated is obtained as the starting position, and the grain unloading position is obtained as the end position. Therefore, the road driving area and the farmland driving area between the grain transport vehicle to be operated and the grain unloading position are determined based on the starting position and the end position. Then, based on the road turning points in the road driving area and the obstacle nodes in the farmland driving area, the driving nodes of the grain transport vehicle to be operated are determined, and the driving directed graph nodes corresponding to the grain transport vehicle to be operated are determined based on the driving nodes. In order to determine the corresponding driving path based on the driving directed nodes, the ant colony algorithm is used in the embodiment of this specification to determine the optimal path corresponding to the driving directed graph node, and the grain transport vehicle to be operated is controlled to reach the grain unloading position based on the optimal path to unload grain for transportation.

[0096] like Figure 2 As shown, the embodiment of this specification provides a harvesting scheduling device for multiple agricultural machinery combined operations. Figure 2 It can be seen that in one or more embodiments of this specification, a harvesting scheduling device for multiple agricultural machinery combined operations includes:

[0097] The first determination unit 201 is used to determine the harvester and the grain transport vehicle to be operated for the combine harvest based on the basic information of the current farm; wherein the basic information includes: terrain data, planting information, and equipment information;

[0098] The first prediction unit 202 is used to monitor the storage information of the built-in storage bin of the harvester to be operated based on the preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated;

[0099] The second prediction unit 203 is used to determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data;

[0100] The second determining unit 204 is used to determine the grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated;

[0101] The control unit 205 is used to generate a grain unloading scheduling instruction according to the grain unloading time and the grain unloading location, broadcast the grain unloading scheduling instruction to the grain transport vehicle to be operated, and perform real-time path planning according to the location of the grain transport vehicle to be operated and the grain unloading location, so as to control the grain transport vehicle to be operated to unload grain.

[0102] like Figure 3 As shown, the embodiment of this specification provides a non-volatile storage medium storing computer executable instructions. Figure 3 It can be seen that in one or more embodiments of this specification, a non-volatile storage medium stores computer executable instructions, and the computer executable instructions can:

[0103] Based on the basic information of the current farm, determine the harvesters and grain transport vehicles to be used for combined harvesting; wherein the basic information includes: terrain data, planting information, and equipment information;

[0104] Monitoring the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated;

[0105] Determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data;

[0106] Determining a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated;

[0107] A grain unloading scheduling instruction is generated according to the grain unloading time and the grain unloading location, and the grain unloading scheduling instruction is broadcast to the grain transport vehicle to be operated, and real-time path planning is performed according to the location of the grain transport vehicle to be operated and the grain unloading location to control the grain transport vehicle to be operated to carry out grain unloading transportation.

[0108] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0109] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0110] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A harvesting scheduling method for multiple agricultural machinery joint operations, characterized in that: The method comprises: Based on the basic information of the current farm, determine the harvesters and grain transport vehicles to be used for combined harvesting; wherein the basic information includes: terrain data, planting information, and equipment information; Monitoring the storage information of the built-in storage bin of the harvester to be operated based on a preset sensor, so as to predict the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated; Determine the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data; Determining a grain unloading position corresponding to the harvesting work area at the next moment according to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated; Generate a grain unloading scheduling instruction according to the grain unloading time and the grain unloading location, broadcast the grain unloading scheduling instruction to the grain transport vehicle to be operated, and perform real-time path planning according to the location of the grain transport vehicle to be operated and the grain unloading location, so as to control the grain transport vehicle to be operated to unload grain for transportation; The method of determining the harvesting posture data of the harvester to be operated by means of a position sensor and a posture sensor installed on the harvester to be operated, so as to predict the harvesting working area of ​​the harvester to be operated at the next moment based on the harvesting posture data, specifically includes: Based on the preset monitoring type of the attitude sensor, the attitude sensor is respectively installed at the preset position of the harvester to be operated; wherein the preset monitoring type can specify the corresponding attitude sensor to monitor at different positions; Monitoring the steering angle of the steering mechanism of the harvester to be operated according to a first posture sensor of the harvester to be operated at a first preset position; According to a second posture sensor of the harvester to be operated at a second preset position, monitoring the extension and contraction amount of the connecting oil cylinder corresponding to the harvester chassis of the harvester to be operated; According to the third posture sensor of the harvester to be operated at the third preset position, the posture angle of each component in the harvesting assembly of the harvester to be operated is monitored, so as to determine the posture data of the harvester to be operated at the current moment according to the steering angle of the steering mechanism, the telescopic amount of the connecting cylinder and the posture angle of each component; According to the position sensor on the harvester to be operated, the operating position of the harvester to be operated is obtained in real time, so as to mark the posture data at the current moment based on the operating position and obtain the harvesting posture data of the harvester to be operated; Based on the harvesting action characteristics of the harvester to be operated, the harvesting action at the next moment corresponding to the harvesting posture data is determined, and the harvesting action at the next moment, the harvesting posture data and the driving speed of the harvester to be operated are input into a preset prediction model to output the harvesting working area of ​​the harvester to be operated at the next moment.

2. A harvesting scheduling method for multiple agricultural machinery combined operations according to claim 1, characterized in that: Determining the harvester and the grain transport vehicle to be operated for the combine harvest based on the basic information of the current farm specifically includes: Acquire terrain data of a current farm and crop planting information of the current farm; wherein the crop planting information includes: crop type, crop planting time, and crop planting cycle; Dividing the current farm into a plurality of farmland operation areas based on the crop type, and determining a harvester type corresponding to each of the farmland operation areas; wherein the farmland operation areas correspond to the same crop type; Acquire harvesters of different models corresponding to the harvester type, and acquire the lifting and lowering range of the linkage harvesting system of each harvester of the different models; wherein the linkage harvesting system is composed of a lifting system and a linkage system connected to the harvester chassis and the harvesting assembly; Determine the harvester to be operated corresponding to the current farm based on the lifting range of the linked harvesting system of each harvester of different models and the terrain data corresponding to each farmland operation area; The corresponding grain transport vehicle type is determined based on the discharge port structure information of each harvester to be operated, and the grain transport vehicle type is scheduled based on the grain transport vehicle type and the equipment information of the current farm to obtain the grain transport vehicle to be operated with the minimum cost on the current farm.

3. A harvesting scheduling method for multiple agricultural machinery combined operations according to claim 2, characterized in that: Based on the grain transport vehicle type and the equipment information of the current farm, the grain transport vehicle of the grain transport vehicle type is dispatched to obtain the grain transport vehicle to be operated with the minimum cost of the current farm, specifically including: According to the type of grain transport vehicle and the equipment information of the current farm, the grain transport vehicle corresponding to each harvester to be operated is divided into a first grain transport vehicle and a second grain transport vehicle; wherein the first grain transport vehicle is an idle grain transport vehicle configured for the current farm, and the second grain transport vehicle is an unconfigured or non-idle grain transport vehicle for the current farm; If it is determined that the grain transport vehicle corresponding to the harvester to be operated is the second grain transport vehicle, then determining an initial second grain transport vehicle within a preset range based on the location of the current farm; Determine the distance cost of each of the initial second grain transport vehicles according to the distance between each of the initial second grain transport vehicles and the current farm within the preset range and the historical fuel consumption record of the initial second grain transport vehicles; Based on the distance cost, a preset number of initial second grain transport vehicles are obtained as the second grain transport vehicles to be selected, a rental price of each of the second grain transport vehicles to be selected is obtained, and based on the rental platform corresponding to each of the second grain transport vehicles to be selected, a rental evaluation of each of the second grain transport vehicles to be selected is extracted; Determine a first weighting coefficient of the distance cost based on the rental price, and determine a second weighting coefficient of the distance cost based on the rental evaluation, so as to perform weighted processing on the distance cost according to the first weighting coefficient and the second weighting coefficient, obtain the rental cost of each of the second grain transport vehicles to be selected, and obtain the second grain transport vehicle to be selected with the minimum cost; The first grain transport vehicle and the second grain transport vehicle with the lowest cost are selected as the grain transport vehicles with the lowest cost to be operated in the current farm.

4. The harvesting scheduling method for multiple agricultural machinery combined operations according to claim 2 is characterized in that: Before determining the harvester and the grain transport vehicle to be operated for the combine harvest based on the basic information of the current farm, the method further includes: Acquire multispectral images of the current farm based on a drone, and determine the chlorophyll content of crops in each farmland operation area of ​​the current farm based on destructive sampling; Performing continuous wavelet transform on the multispectral image data based on a preset wavelet basis function and a red edge wavelength range to obtain wavelet coefficients corresponding to the reflectivity of the red edge band image data; Inputting the wavelet coefficients into a random forest model trained based on multispectral images of historical harvesting processes to predict the predicted chlorophyll content corresponding to the wavelet coefficients; Based on the crop growth model corresponding to the farmland operation area, respectively determining the quantitative detection maturity corresponding to the chlorophyll content of the crop in the farmland operation area and the predicted maturity corresponding to the predicted chlorophyll content; Determine the maturity of crops in each farmland operation area in the current farm based on the average of the quantitatively detected maturity and the predicted maturity; If it is determined that the maturity of the crop reaches the maturity index value corresponding to the crop type, it is determined to harvest the farmland operation area.

5. The harvesting scheduling method for multiple agricultural machinery combined operations according to claim 1 is characterized in that: The method of monitoring the storage information of the built-in storage bin of the harvester to be operated based on the preset sensor, and predicting the grain unloading time of the harvester to be operated based on the storage information and the storage preset position of the harvester to be operated, specifically includes: Acquire storage bin structure data of the built-in storage bin of the harvester to be operated, and detect grain collection data of the harvester to be operated and remaining space data of the storage bin based on the preset sensor; The storage bin structure data, the grain collection data and the remaining space data are used as the storage information, so as to establish a geometric digital twin model corresponding to the storage bin of the harvester to be operated based on the storage information; Based on the geometric digital twin model, the grain collection position of the storage bin is acquired in real time to determine whether the grain collection position reaches the storage preset position of the harvester to be operated; If so, based on the grain collection position and the storage bin structure data, the remaining storage height of the storage bin is determined, and a grain collection simulation is performed in the geometric digital twin model according to the remaining storage height and the grain collection data to predict the grain unloading time of the harvester to be operated.

6. The method for harvesting and scheduling multiple agricultural machinery combined operations according to claim 1, characterized in that: According to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated, determining the grain unloading position corresponding to the harvesting work area at the next moment specifically includes: According to the positional relationship between the harvesting component and the grain unloading component in the harvester to be operated, the position of the grain unloading component relative to the harvesting working area at the next moment is determined to determine the grain unloading center point position of the grain unloading component; The grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting work area at the next moment; Wherein, after the grain unloading center point position of the grain unloading component is used as the grain unloading position corresponding to the harvesting working area at the next moment, the method further includes: Based on the built-in sensor of the grain transport vehicle to be operated, three-dimensional point cloud data of the storage area of ​​the grain transport vehicle to be operated is obtained; The crop stacking distribution of the grain transport vehicle to be operated is determined in real time based on the three-dimensional point cloud data of the storage area, and the position of the grain transport vehicle to be operated is adjusted according to the crop stacking distribution and the grain unloading position.

7. The method for harvesting and scheduling multiple agricultural machinery combined operations according to claim 1, characterized in that: The method further comprises: performing real-time path planning according to the position of the grain transport vehicle to be operated and the grain unloading position, and controlling the grain transport vehicle to be operated to unload grain for transportation. Specifically, the method comprises: Acquire the position of the grain transport vehicle to be operated as the starting position, and acquire the grain unloading position as the end position; Determine the road driving area and the farmland driving area between the grain transport vehicle to be operated and the grain unloading position based on the starting position and the end position; Based on the road turning points in the road driving area and the obstacle nodes in the farmland driving area, the driving nodes of the grain transport vehicle to be operated are determined, and based on the driving nodes, the driving directed graph nodes corresponding to the grain transport vehicle to be operated are determined; The optimal path corresponding to the node of the driving directed graph is determined by an ant colony algorithm, and the grain transport vehicle to be operated is controlled to reach the grain unloading location based on the optimal path for grain unloading and transportation.

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