Agricultural machinery group collaborative operation path planning system based on satellite navigation

Abstract

The invention relates to an agricultural machinery group collaborative operation path planning system based on satellite navigation, which relates to the technical field of agricultural planting and comprises a function division module, a preliminary planning module, a re-planning module and a feedback module. According to the application, the function of the unmanned aerial vehicle can be divided by using the function division module, the agricultural area is divided at the same time, and then the starting type, the starting time and the starting path of the unmanned aerial vehicle are designed according to the preliminary planning module and the re-planning module, so that a relatively accurate unmanned aerial vehicle starting scheme is obtained; therefore, the problem of path interference when a plurality of unmanned aerial vehicles with different functions are used in the prior art can be solved, the initial planning module and the re-planning module are utilized to carry out multiple times of refinement processing on the unmanned aerial vehicle starting scheme, a relatively accurate unmanned aerial vehicle starting scheme is obtained, and the unmanned aerial vehicle starting efficiency is improved. And the avoidance function of different unmanned aerial vehicles during operation at different time is ensured.

Description

Technical Field

[0001] The present invention relates to the field of agricultural planting technology, and in particular to a satellite navigation-based agricultural machinery collaborative operation path planning system. Background Art

[0002] The modernization of agriculture is an inevitable requirement for achieving high-quality development. As an important part of modern agricultural technology, agricultural drones are gradually changing the traditional agricultural production methods and making agriculture develop rapidly. During the busy farming season or the land contracting process, the existence of drones can greatly reduce the production costs, and can ensure the rapid identification of abnormalities in the agricultural planting process and reduce the impact of disasters on agriculture. Therefore, the existence of agricultural machinery groups can ensure high-quality agricultural planting.

[0003] For example, in the patent document with application number: 202311400547.6, a UAV path planning method is disclosed, and specifically a method is disclosed that can reduce the possibility of physical damage caused by various static or dynamic obstacles encountered by the UAV during operation.

[0004] Based on the above technical solution, the dynamic obstacles encountered by drones during agricultural planting are usually the impact of the search paths of each drone in the drone group. In existing equipment, drones are usually only equipped with multiple functions. When drones detect multiple functions one by one, the working efficiency of the drones and subsequent tracking require a longer response time. Summary of the invention

[0005] The purpose of the present invention is to provide a satellite navigation-based agricultural machinery collaborative operation path planning system.

[0006] The technical problem solved by the present invention is to solve the problem in the prior art that it is difficult to plan paths when multiple drones with different functions are used at the same time.

[0007] The present invention can be implemented by the following technical solutions: A satellite navigation-based agricultural machinery group collaborative operation path planning system, including a function division module, a preliminary planning module, and a re-planning module;

[0008] The function division module divides the drones based on the drones with different functions, and the function division module divides the agricultural areas into several regional blocks;

[0009] The preliminary planning module matches the regional blocks with the functions of the drones to determine the type, time and path of the drone launch;

[0010] The re-planning module re-plans the UAV's launch type, launch time and launch path based on the planning method in the preliminary planning module, the UAV's flight altitude and work area.

[0011] A further technical improvement of the present invention is that the function division module includes a UAV function division unit, which divides the UAVs into detection UAVs for agricultural detection and working UAVs for agricultural adjustment and processing based on their functions, and the function division module arranges and numbers the detection UAVs and the working UAVs.

[0012] A further technical improvement of the present invention is that the function division module includes a planting area division unit, which divides the planting area based on the planting state in the planting area to obtain a plurality of area blocks, and calculates the detection pressure of each area block. A and B are assigned parameters, where YAL is the parameter set of the planting area, YA is the overall value, ZWL is the importance of the planting type, and ZW is the standardized parameter of the importance of the planting type.

[0013] A further technical improvement of the present invention is that when the preliminary planning module is in use, the detection pressure YC of each area block is obtained, the area blocks are arranged according to the numerical value of the detection pressure YC, and then the detection drone group and the working drone group in the drone function division unit are obtained, and the number of detection drones and working drones required for each area block is determined according to the detection pressure.

[0014] A further technical improvement of the present invention is that after the number of detection drones and working drones is determined, a bow-shaped path planning is performed according to the shape of the area block, and the required detection time or working time is judged according to the overall length of the bow and the flight speed of the drone.

[0015] A further technical improvement of the present invention is that the re-planning module includes a start-up time simulation unit, a path simulation unit, a shortest distance judgment unit and an adjustment unit;

[0016] The startup time simulation unit obtains the UAV group running in the current area block, obtains its real-time path simulation through its flight path, obtains a path simulation model, simulates the startup time, and obtains a flight route for the UAVs that are expected to enter the area block to work;

[0017] The path simulation unit obtains a path line about the UAV according to the flight speed of the UAV and the moving path on the area block, and marks the line on the path simulation model;

[0018] The shortest distance judgment unit judges the shortest distance d between the UAV and the running UAV in the same simulation time. If the shortest distance d is less than the set safety threshold, it proves that the entry time and entry path of the UAV are not feasible;

[0019] The activation of the adjustment unit adjusts the entry time of the UAV or the entry starting point of the UAV, and adjusts the simulation path of the UAV.

[0020] A further technical improvement of the present invention is that the re-planning module includes a drone altitude adjustment module, which obtains the type and flight altitude of the drone group in the current area block, and at the same time obtains the type and flight altitude of the drone that is about to enter the area block, and marks the adjusted drone entry time and path with the original drone path line, and marks them on the same time-related path table, and conducts drills according to the type and flight altitude of each drone, determines whether there is an impact area on the path table, and determines the duration and range of the impact area, and performs feedback correction based on the duration and range of the area.

[0021] A further technical improvement of the present invention is that it also includes a summary unit, which obtains the coverage degree of the area involved in the above-mentioned area block and the time to complete the coverage, records it according to the time when the area block is completed as a whole, judges its overall completion speed, and obtains the work efficiency of the drone group based on the completion speed, and records the operating efficiency of the drone group.

[0022] Compared with the prior art, the present invention has the following beneficial effects:

[0023] 1. This application can divide the functions of drones and agricultural areas by using a function division module, and then design the startup type, startup time and startup path of the drone according to the preliminary planning module and the re-planning module to obtain a more accurate drone startup plan, thereby solving the path interference problem of multiple drones with different functions in the prior art when in use. At the same time, this application uses the preliminary planning module and the re-planning module to refine the drone startup plan multiple times to obtain a more accurate drone startup plan, thereby ensuring the avoidance function of different drones when operating at different times.

[0024] 2. When in use, the present application utilizes a re-planning module including a start time simulation unit, a path simulation unit, a closest distance judgment unit and an adjustment unit, so that new drones can be added according to the drone operation status of the current area block, and drones with different functions added can perform avoidance operations with the original drones to ensure the safety of drone flight.

[0025] 3. The re-planning module in this application includes a drone height adjustment module, through which the estimated entry time and entry starting point of the drone that is about to enter the area block can be further corrected, thereby reducing the impact caused by different heights, which includes but is not limited to the possibility that when the detection drone is lowered to a certain height, the working drone spraying pesticides is very likely to spray pesticides on the detection drone, causing problems with the detection accuracy of the detection drone. Or, when the detection drone is sampling, the fertilization drone is also lowered to a certain height and the fertilizer is directly spread on the detection drone, causing problems with the accuracy of the detection results, so the accuracy of the drone work can be guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0027] Figure 1 It is a system principle block diagram of the present invention. DETAILED DESCRIPTION

[0028] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0029] See also Figure 1 As shown, a satellite navigation-based agricultural machinery group collaborative operation path planning system includes a function division module, a preliminary planning module, a re-planning module and a feedback module, wherein the function division module is used to divide according to drones with different functions, and to divide the regional blocks according to agriculture, and preliminarily divide the agricultural area into several regional blocks; then the preliminary planning module matches the regional blocks and the functions of the drones to determine the time and path of the drone startup; the present application re-plans based on the time and path of the drone startup, that is, the re-planning module can re-plan the above operations, schedule them according to the working time of the drone group, and then perform path planning in a non-interference state; finally, the present application performs feedback adjustment on the re-planning module through the feedback module, that is, the drone that needs to work again is judged according to the feedback module, and according to the collaborative work of the above modules, the agriculture can be fully inspected and worked on to ensure the quality of agriculture.

[0030] Furthermore, the functional division module includes the following units:

[0031] The drone function division unit divides the drones into several drone groups based on their functions. For example, in this application, the drones are divided into detection drones and working drones. That is, the detection drones are used to continue to detect the state of the soil and the state of the planting. It also includes some environmental detections, such as detecting soil moisture, fertilizer concentration, air temperature and crop planting status, and can also include sampling and processing of the environment, transferring samples to the laboratory for further testing to ensure the accuracy of agricultural planting; and the working drones include fertilization drones and tillage drones, that is, drones used to adjust the planting status. The startup of the drone in this state depends on The detection result of the detection drone, and the state of the working drone after work depends on the detection of the detection drone, so the drone function division unit divides the drone into a detection drone group JW and a working drone group GW, and numbers the drones in the detection drone group JW respectively, and marks them as JW1, JW2, ... JWn in sequence, where n is a positive integer greater than 1, and numbers the drones in the working drone group GW, and marks them as GW1, GW2, ... GWm in sequence, where m is a positive integer greater than 1. At this time, n and m are not necessarily equal. Since the cost and demand of different types of drones are different, the number of drones of different categories is not necessarily the same;

[0032] The planting area division unit divides the planting area based on the planting status in the planting area. That is, in this application, the planting area is divided into regions according to the planting type, the height of the planting area, the actual scale of the planting area, the planting time and other conditional factors to obtain a number of different area blocks, and according to the above conditional factors of the area block, the detection pressure of the area block is obtained, that is, according to the formula The detection pressure YC of the regional block is obtained. In the present application, A and B are assigned parameters, wherein YAL is a parameter set of the planting area, that is, the height h of the planting area and the actual scale v of the planting area are digitized, that is, YAL=K*h+P*v, wherein K and P are assigned parameters, and YA is an overall value, that is, YA=K*HB+P*VB, wherein HB is a standardized value of the height of the planting area, and VB is a standardized value of the scale of the planting area, both of which are artificially summarized parameters, and ZWL is the importance of the planting type, and ZW is a standardized parameter of the importance of the planting type, so that the pressure parameter YC of the regional block can be obtained.

[0033] Furthermore, the preliminary planning module allocates drones based on the above technical solution and performs path planning for the drones. Specifically, the regional blocks in the planting area division module unit are first obtained, and the detection pressure YC of the corresponding regional blocks is obtained, the detection pressure YC is matched with the respective regional blocks, and the regional blocks are arranged according to the numerical value of the detection pressure YC, and then the detection drone group JW and the working drone group GW in the drone function division unit are obtained. In this embodiment, the detection time and working time required for each regional block are judged according to the detection pressure YC of the regional block, so the present application allocates the number of detection drones and working drones according to the detection time and working time required for each regional block. When allocating several detection drones and working drones, the detection time and working time required for the current regional block are used to obtain the most time-saving working route for the regional block. Therefore, when the neural algorithm performs verification simulation, it is based on the working routes of the detection drones and working drones.

[0034] Specifically, when planning the working paths of the inspection drone and the working drone, first determine them according to their working ranges, then perform bow-shaped path planning according to the shape of the area block, then plan according to the inspection drone and the working drone, and judge the total inspection time or working time required according to the overall length of the bow and the flight speed of the drone, and then when allocating several inspection drones and working drones, obtain the time required to allocate the inspection drones and working drones, sort the inspection time and working time required for all area blocks, and take the maximum value as the overall time required for the planting area of ​​this application, as the fastest working time, so that the work efficiency of the planting area of ​​this application can be obtained. In the above technical scheme, the time required to start the inspection drone or the working drone respectively at the same time can be preliminarily planned and calculated, and the fastest cycle of inspection and work can be judged according to the above time, so as to facilitate the correction of the re-planning module.

[0035] Furthermore, since the working ranges of the detection drone and the working drone are different, the distances between the bow-shaped paths of the area blocks are different. Therefore, if the detection drone and the working drone are started at the same time, a collision is very likely to occur, so this application needs to start the avoidance mode. That is, the re-planning module includes a start-up time simulation unit, a path simulation unit, a closest distance judgment unit and an adjustment unit. Since the start-up time of the detection drone and the working drone may be different, and the start-up route may be different, the present application obtains the drone group running in the current area block by using the start-up time simulation unit, obtains its real-time path simulation through its flight path, obtains a path simulation model, and then simulates the start-up time to obtain a flight route of the drone expected to enter the area block for work; therefore, the path simulation unit obtains a path line about the drone according to the flight speed of the drone and the moving path on the area block, and then marks the line on the path simulation model; the closest distance judgment unit is used to judge the shortest distance d between the drone and the running drone within the same simulation time. If the shortest distance d is less than the set safety threshold, it proves that the entry time and entry path of the drone are not feasible. Then, by starting the adjustment unit, the entry time of the drone or the entry starting point of the drone is adjusted, the simulation path of the drone is adjusted, and the above operation is continued to correct the path of the temporarily entered drone to avoid the possibility of collision and ensure that the entry time and starting point of the drone are safer.

[0036] As a further embodiment of the present application, in order to further ensure safe operation, the re-planning module includes a drone height adjustment module, that is, in the above technical solution, the type and flight altitude of the drone group in the current area block are obtained, and the type and flight altitude of the drone that is about to enter the area block are obtained at the same time, and the adjusted drone entry time and path are marked with the original drone path line, and marked on the same path table about time, and then drills are performed according to the type and flight altitude of each drone to determine whether there is an impact area on the path table, and the duration and range of the impact area are determined. Feedback correction is performed according to the duration and range of the area, that is, the estimated entry time and entry starting point of the drone that is about to enter the area block are further corrected, so as to reduce the impact caused by different heights, which includes but is not limited to when the detection drone is lowered to a certain height, the working drone spraying pesticides is very likely to spray pesticides on the detection drone, causing the possibility of problems with the detection accuracy of the detection drone. Or, when the detection drone is sampling, the fertilization working drone is also lowered to a certain height, and the fertilizer is directly sprayed on the detection drone, causing the possibility of problems with the accuracy of the detection result. In summary, by utilizing the marking of the impact area, the present application can not only take into account the possible collisions caused by path planning, but also target the range impact caused by the nature of the work, so that the path planning fits the actual work.

[0037] Furthermore, the re-planning module also includes a work partitioning module. That is, since the work of the working drone will cause a sudden change in the detection result of the detection drone, the partitioning module is used in this application to obtain a relatively accurate change in the detection result of the detection drone. That is, first obtain the same path table about time, and then mark the two routes corresponding to the shortest distance d between the drone and the running drone, and use the area between the two routes as a transition zone. When the detection drone arrives at the transition zone, the detection data in the area before the transition zone is used as the pre-change data, the detection data obtained between the transition zones is used as the change data, and the data obtained after the transition zone is used as the post-change data. In this way, the impact of the working drone on the agricultural parameters after work can be calculated according to the change in data, so that the modification of the agricultural parameters can be obtained.

[0038] As a further embodiment of the present application, the feedback module is based on the work partition module in the above technical solution, obtains the data before change, the data during change and the data after change in the work partition module, and especially judges whether the data after change meets the requirements based on the comparison between the data before change and the data after change. If not, the preliminary planning module and the re-planning module in the above technical solution are started, and the working drone is expected to be added according to the preliminary planning module and the re-planning module. The working drone can adjust the agricultural parameters again within an appropriate time. At the same time, if there is a detection drone on the area block, it is necessary to monitor the change status of the soil by the working drone according to the detection drone, and realize data feedback, and continuously feedback and adjust the agricultural parameters until it is detected that the agricultural parameters meet the requirements. All areas in the area block are covered by the working drone, and the possibility of omissions should be avoided. In summary, the present application can fully guarantee the status of agricultural planting data and ensure that agricultural planting can meet the requirements, such as pesticide concentration and fertilizer concentration, thereby ensuring the quality of agricultural planting.

[0039] The present application also includes a summary module, which is used to obtain the coverage degree of the area involved in the above-mentioned area block and the time to complete the coverage, record the time according to the overall completion of the area block, judge the overall completion speed, and obtain the working efficiency of the drone group according to the completion speed, and record the operating efficiency of the drone group. By recording the operating efficiency each time, the data is summarized as a database, which is more convenient for tracing back the subsequent data. That is, if a drone fails, it affects the detection and working speed of the area block. At this time, through the calculation of the operating efficiency, the working abnormality of the area block can be quickly obtained, and the abnormal drone can be quickly obtained based on the abnormality to ensure that the drone is quickly repaired.

[0040] In this application, all drones with different functions are equipped with satellite sensing systems and communication modules. Real-time positioning of the drone is achieved based on the satellite sensing system. At the same time, the communication module can send the location of the drone to the processing platform for information processing.

[0041] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A satellite navigation-based agricultural machinery collaborative operation path planning system, characterized by: It includes function division module, preliminary planning module and re-planning module; The function division module divides the drones based on the drones with different functions, and the function division module divides the agricultural areas into several regional blocks based on the agricultural areas; The preliminary planning module matches the regional blocks with the functions of the drone to determine the type, time and path of the drone launch; The re-planning module re-plans the start type, start time and start path of the UAV based on the planning method in the preliminary planning module, the flight altitude and the working area of ​​the UAV.

2. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 1, characterized in that: The function division module includes a UAV function division unit, which divides the UAVs into detection UAVs for agricultural detection and working UAVs for agricultural adjustment and processing based on their functions, and the function division module arranges and numbers the detection UAVs and the working UAVs.

3. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 2 is characterized in that: The functional division module includes a planting area division unit, which divides the planting area based on the planting state in the planting area to obtain a number of area blocks, and calculates the detection pressure of each area block. A and B are assigned parameters, where YAL is the parameter set of the planting area, YA is the overall value, ZWL is the importance of the planting type, and ZW is the standardized parameter of the importance of the planting type.

4. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 3 is characterized in that: When in use, the preliminary planning module obtains the detection pressure YC of each area block, arranges the area blocks according to the numerical value of the detection pressure YC, then obtains the detection drone group and the working drone group in the drone function division unit, and determines the number of detection drones and working drones required for each area block according to the detection pressure.

5. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 4 is characterized in that: After the number of inspection drones and working drones is determined, bow-shaped path planning is performed according to the shape of the area block, and the required inspection time or working time is determined based on the overall length of the bow and the flight speed of the drone.

6. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 5, characterized in that: The re-planning module includes a start-up time simulation unit, a path simulation unit, a shortest distance judgment unit and an adjustment unit; The startup time simulation unit obtains the drone group running in the current area block, obtains its real-time path simulation through its flight path, obtains a path simulation model, simulates the startup time, and obtains a flight route for the drones that are expected to enter the area block to work; The path simulation unit obtains a path line about the UAV according to the flight speed of the UAV and the moving path on the area block, and marks the line on the path simulation model; The shortest distance determination unit determines the shortest distance d between the UAV and the running UAV in the same simulation time. If the shortest distance d is less than the set safety threshold, it proves that the entry time and entry path of the UAV are not feasible; The adjustment unit is activated to adjust the entry time of the UAV or the entry starting point of the UAV, and adjust the simulation path of the UAV.

7. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 5, characterized in that: The re-planning module includes a drone altitude adjustment module, which obtains the type and flight altitude of the drone group in the current area block, and simultaneously obtains the type and flight altitude of the drone that is about to enter the area block, annotates the adjusted drone entry time and path with the original drone path line, and annotates them on the same time-related path table, conducts drills based on the type and flight altitude of each drone, determines whether there is an impact area on the path table, determines the duration of the impact area and the scope of the area, and performs feedback correction based on the duration and scope of the area.

8. The satellite navigation-based agricultural machinery collaborative operation path planning system according to claim 1, characterized in that: It also includes a summary unit, which obtains the coverage degree of the area involved in the above-mentioned area block and the time to complete the coverage, records it according to the time of overall completion of the area block, judges its overall completion speed, and obtains the work efficiency of the drone group based on the completion speed, and records the operating efficiency of the drone group.

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