CN109871029A - A kind of plant protection drone flight course planning optimization method based on image processing techniques - Google Patents
A kind of plant protection drone flight course planning optimization method based on image processing techniques Download PDFInfo
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- CN109871029A CN109871029A CN201910128838.1A CN201910128838A CN109871029A CN 109871029 A CN109871029 A CN 109871029A CN 201910128838 A CN201910128838 A CN 201910128838A CN 109871029 A CN109871029 A CN 109871029A
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Abstract
The invention discloses a kind of plant protection drone flight course planning optimization method based on image processing techniques, comprising steps of S1, using unmanned plane, acquire remote sensing images to generate the orthophotoquad of field；S2, the orthophotoquad that will have been spelled, divide small sized grid, extract its color and textural characteristics, are sent into classifier, determine the disease and insect information of each grid；S3, setting application threshold value, in each grid of S2, it is application region that pest and disease damage grade, which is higher than the threshold value, otherwise not to be administered region；S4, grid division, generate flight course planning, and planning includes a plurality of air strips；S5, the location point that every air strips need to be administered from beginning to end is found, forms new air strips；S6, by the implementation of S1 to S5, the case where can be derived that illness insect pest, then generate prescription map.The present invention can make plant protection drone provide a flight course planning most having to the application with pest and disease damage rice, improve the efficiency of application.
Description
Technical field
The present invention relates to the technical fields of plant protection drone agricultural application, refer in particular to a kind of based on image processing techniques
Plant protection drone flight course planning optimization method.
Background technique
As computer remote sensing technology constantly develops in recent years, gradually it is applied in agricultural production.Unmanned plane is distant
The area coverage of sense technology is wide, and high-efficient, can be observed simultaneously for the crops of large area.It is highly suitable for big face
Product agricultural production investigation, China possess 1,800,000,000 mu of basic farmlands, the support of a large amount of agricultural demand state-of-the-art technology, and unmanned plane is distant
Sense technology is made that very big effect.Secondly, unmanned aerial vehicle remote sensing technology by utilize state-of-the-art, can be largely
Upper reduction man power and material, and the cost of unmanned aerial vehicle remote sensing technology is low, in agricultural production process, utilizes unmanned aerial vehicle remote sensing skill
Art carries out spraying drug, it is possible to reduce the waste of drug has very high economic serviceability.It on the other hand can be accurately for agriculture
The case where field, is investigated, and for the accurate of farmland, accurate information monitoring is made in fertilising application and irrigation etc..
However, external is mostly that oil is dynamic since domestic plant protection drone is typically all to use battery power.Battery continues
Certainly and the dynamic no comparativity of continuation of the journey of oil, domestic why plant protection drone using battery power has various originals to boat ability
Cause is exactly the technology country of engine really and there are many external gap first, the engine technologies of the present dynamic unmanned planes of much oil
And in the foreign countries used, cost is naturally just very high, it is domestic general beyond affordability, so when unmanned plane is used for agriculture field,
For being administered to crops, pollination etc. just has in view of optimum efficiency, therefore just needs to have one to unmanned flight course line
A optimal planning, for not by pest and disease damage, or by pest and disease damage influenced smaller rice region, plant protection drone
It is just less without being administered or being administered dosage.For the rice more serious by pest and disease damage, the application dosage of plant protection drone
It accordingly will be more.
So accuracy pesticide applying both may be implemented to the rice with pest and disease damage, has administered the pest and disease damage of rice.Again may be used
To reduce the dosage of pesticide, improve the utilization rate of pesticide and meanwhile can also by be arranged unmanned plane optimization course line, can also
Effectively to solve the problems, such as plant protection drone on rice application because the reason of cruising ability deficiency influences spray pattern.So base
There is more advantage to rice application method in the unmanned plane course line of image procossing planning.It can solve and efficiently solve in agricultural
The problem of being encountered in actual production.
Summary of the invention
The purpose of the present invention is to overcome the shortcomings of the existing technology with it is insufficient, propose a kind of based on image processing techniques
Plant protection drone flight course planning optimization method obtains the flight optimization course line that plant protection drone is administered rice pest, this
The optimal plant protection drone line of flight is the prescription map generated based on image processing techniques, improves the utilization rate of pesticide, is reduced
The power consumption of equipment for plant protection operation, and reduce injury of the pesticide to pest and disease damage crop is not suffering from.
To achieve the above object, technical solution provided by the present invention are as follows: it is a kind of based on the plant protection of image processing techniques without
Man-machine flight course planning optimization method, comprising the following steps:
S1, splicing shape is used to field according to a certain specific overlapping rate acquisition remote sensing images using remote sensing unmanned plane
At the orthophotoquad of field；
S2, to the orthophotoquad being spliced in step S1, divide small sized grid, to each grid, extract
Its color and textural characteristics are sent into classifier, obtain the pest and disease damage grade of each grid, point there is normal, moderate, severe three etc.
Grade；Wherein, the color of grid and textural characteristics are sent into before classifier, great amount of samples need to be acquired in advance and mark and train point
Class device；
S3, the grade threshold for setting up application, for each grid in step S2, pest and disease damage grade is higher than the conduct of the threshold value
It is administered region, otherwise not to be administered region；
S4, the grid dividing according to orthophotoquad generate flight course planning based on sequence air strips method, the grid of formation are pressed
A plurality of flight air strips are cooked up according to the straight line path of unmanned plane during flying, the pest and disease damage that can be established according to grid in every air strips
The difference of grade decides whether to be administered, and chooses first on this air strips grid for needing to be administered with the last one, is labeled as
A, two dot position information of B；
S5, first and the last one need are found according to air strips defence line to each course line planned in course line in step S4
The location point to be administered forms new air strips；
S6, by the implementation of step S1 to S5, can be derived that field illness insect pest after marking off setting number region
The case where, prescription map is then generated, by the information of generated prescription map, the mainly seat of two points of head and the tail of each air strips
Mark, is input in the winged control program of plant protection drone, and plant protection drone is carried out according to the coordinate pair crop of these points
Accuracy pesticide applying.
Compared with prior art, the present invention have the following advantages that with the utility model has the advantages that
1, using present design, it so that plant protection drone is realized accuracy pesticide applying to the rice with pest and disease damage, subtract
Few injury of the pesticide to pest and disease damage rice is not suffering from, and the cruising ability of plant protection drone can be made to maximize the use.
2, it can be used for the accuracy pesticide applying of multiple types field crops, there is popularity and popularization.
3, image procossing, image processing techniques can be applied to and is provided in the accurate line of flight for plant protection drone, had
Conducive to realization Derived from Agricultural Modernization.
Detailed description of the invention
After Fig. 1 is it is contemplated by the invention that providing the farmland panorama sketch spliced through plurality of pictures and dividing panorama sketch
Farmland schematic diagram.
Fig. 2 is it is contemplated by the invention that the provided schematic diagram for carrying out image procossing to a certain piece of region.
The provided result figure carried out after image procossing to a certain piece of region is imagined in Fig. 3 invention.
Fig. 4 it is contemplated by the invention that provided plant protection drone flight prescription map, by the information input of prescription map to plant protection
In the winged control program of unmanned plane, so that the schematic diagram to the accuracy pesticide applying of crop may be implemented in unmanned plane.
Specific embodiment
In order to embody the novelty of this method, the imagination of this technology is preferably expressed, below in conjunction with attached drawing and specifically
Implement operation, pair it is contemplated by the invention that being further described.It illustrates, explanation and specific implementation operation herein is only explained
This imagination, but it is not limited solely to this imagination.Meanwhile to enjoy China in accordance with the law any about to intellectual property for imagination of the invention
The rights protection of imparting.On the contrary, the present invention cover it is any be defined by the claims on the essence and scope of the present invention do
Substitution, modification, equivalent method and scheme.
In order to enable the public is envisioned with a clearer understanding to this technology and understands, it can be to this in content below
The detail section that technology is imagined does a detailed description.But for those skilled in the art without these specific skills
Art illustrates to be also that well understood that this technological invention is imagined.
Plant protection drone flight course planning optimization method based on image processing techniques provided by the present embodiment, including it is following
Step:
S1, it is used using remote sensing unmanned plane to field according to a certain specific overlapping rate (such as 60%) acquisition remote sensing images
Splicing forms the orthophotoquad of field, as shown in Figure 1.
It should be noted that the camera type of the unmanned plane selected here is Visible Light Camera, the experimental field in test
Ground specification is 200m*200m (error in length ± 2cm), this is in order to facilitate the data analysis in following step, but test
The specification of middle blank should be selected according to the actual situation；Since the panorama sketch to be used here is to use multiple according to certain
The picture of Duplication (for example being 60%) be spliced.
S2, to the orthophotoquad being spliced in step S1, divide small sized grid (such as 10*10m, it is corresponding
In plant protection drone operation spraying swath), to each grid, its color and textural characteristics are extracted, be sent into classifier (can acquire big in advance
Amount sample is marked and trains classifier), the pest and disease damage grade (normal, moderate, severe) of each grid is obtained, such as Fig. 2
It is shown.
It comes out it should be noted that the present invention only states the method for the innovation of imagination in detail, can use for convenience of explanation
Some numbers for being easier to calculate and being easy to understand reader explain, specifically in practice should according to different features in kind,
Actual conditions make corresponding change numerically, to get a desired effect.
S3, according to plant protection expert advice, set up the grade threshold (such as moderate) of application, for each grid in step S2,
The conduct that pest and disease damage grade is higher than the threshold value is administered region, otherwise not to be administered region, as shown in Figure 3.
It should be noted that the probability for calculating rice illness insect pest here is by the sub-box region of each 10m*10m
On be divided into (20*20) a small grid again, obtain total small grid number N (N=400), be then applied to geographical coordinate pair
It the case where should arriving under the block field, calculating the corresponding rice illness insect pest under the next small grid region of panorama sketch, obtains
The number M of pest and disease damage rice is suffered under to each sub-box, the field regional water under then available each sub-box is corresponding
Probability P=M/N of rice illness insect pest.
S4, the grid dividing according to orthophotoquad generate flight course planning based on sequence air strips method, include multiple in planning
Air strips, every air strips are determined by A, B point position.
S5, first and the last one need are found according to air strips defence line to each course line planned in course line in step S4
The location point to be administered forms new air strips.
S6, by the implementation of step S1 to S5, substantially it can be concluded that field illness worm after dividing certain amount region
Harmful situation, then generates prescription map, as Fig. 4 shows.By the information of generated prescription map, the mainly head and the tail of each air strips
The coordinate of two points is input in the winged control program of plant protection drone, the coordinate that plant protection drone is put according to these
Accuracy pesticide applying is carried out to crop.
Embodiment described above is only the preferred embodiments of the invention, and but not intended to limit the scope of the present invention, therefore
All shapes according to the present invention change made by principle, should all be included within the scope of protection of the present invention.
Claims (1)
1. a kind of plant protection drone flight course planning optimization method based on image processing techniques, which is characterized in that including following step
It is rapid:
S1, splicing is used to form field to field according to a certain specific overlapping rate acquisition remote sensing images using remote sensing unmanned plane
The orthophotoquad of block；
S2, to the orthophotoquad being spliced in step S1, divide small sized grid, to each grid, extract its face
Color and textural characteristics are sent into classifier, obtain the pest and disease damage grade of each grid, and dividing has normal, moderate, severe three grades；
Wherein, before the color of grid and textural characteristics being sent into classifier, great amount of samples need to be acquired in advance and marks and trains classification
Device；
S3, the grade threshold for setting up application, for each grid in step S2, the conduct that pest and disease damage grade is higher than the threshold value is administered
Region, otherwise not to be administered region；
S4, the grid dividing according to orthophotoquad generate flight course planning based on sequence air strips method, by the grid of formation according to nothing
The straight line path of man-machine flight cooks up a plurality of flight air strips, the pest and disease damage grade that can be established according to grid in every air strips
Difference decide whether to be administered, choose first on this air strips and need the grid that is administered with the last one, be labeled as A, B two
Dot position information；
S5, is found by first and is applied with the last one needs according to air strips defence line for each course line planned in course line in step S4
The location point of medicine forms new air strips；
S6, by the implementation of step S1 to S5, can be derived that the feelings of field illness insect pest after marking off setting number region
Then condition generates prescription map, by the information of generated prescription map, the mainly coordinate of two points of head and the tail of each air strips,
It is input in the winged control program of plant protection drone, plant protection drone is carried out according to the coordinate pair crop of these points accurate
Application.
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| CN110456820A (en) * | 2019-08-22 | 2019-11-15 | 江苏农林职业技术学院 | Pesticide application system and control method based on ultra-wide band wireless location |
| CN110704556A (en) * | 2019-09-03 | 2020-01-17 | 镇江市勘察测绘研究院 | Geographic information acquisition method based on GIS technology |
| CN110825118A (en) * | 2019-12-23 | 2020-02-21 | 河南大学 | Multi-unmanned aerial vehicle cooperative farmland spraying method based on deep learning algorithm |
| CN110956132A (en) * | 2019-11-29 | 2020-04-03 | 苏州经贸职业技术学院 | Method for intelligently constructing weed control model based on unmanned aerial vehicle cooperation |
| CN111292439A (en) * | 2020-01-22 | 2020-06-16 | 上海杰狮信息技术有限公司 | Unmanned aerial vehicle inspection method and inspection system for urban pipe network |
| CN111488016A (en) * | 2020-04-17 | 2020-08-04 | 北京派得伟业科技发展有限公司 | Accurate quantitative operation method and device for plant protection unmanned aerial vehicle |
| CN111582055A (en) * | 2020-04-17 | 2020-08-25 | 清远市智慧农业研究院 | Aerial pesticide application route generation method and system for unmanned aerial vehicle |
| CN111670668A (en) * | 2020-06-05 | 2020-09-18 | 沈阳农业大学 | Accurate topdressing method for agricultural rice unmanned aerial vehicle based on hyperspectral remote sensing prescription chart |
| CN111753388A (en) * | 2019-12-30 | 2020-10-09 | 广州极飞科技有限公司 | Spraying control method, spraying control device, electronic equipment and computer-readable storage medium |
| CN112162566A (en) * | 2020-09-04 | 2021-01-01 | 深圳市创客火科技有限公司 | Route planning method, electronic device and computer-readable storage medium |
| CN113359855A (en) * | 2021-07-13 | 2021-09-07 | 华南农业大学 | Real-time control method for accurate pesticide application of plant protection unmanned aerial vehicle |
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| CN110282135A (en) * | 2019-06-14 | 2019-09-27 | 江苏农林职业技术学院 | A kind of accurate spraying system of plant protection drone pesticide and spraying method |
| CN110456820B (en) * | 2019-08-22 | 2021-07-27 | 江苏农林职业技术学院 | Pesticide spraying system based on ultra-bandwidth wireless positioning and control method |
| CN110456820A (en) * | 2019-08-22 | 2019-11-15 | 江苏农林职业技术学院 | Pesticide application system and control method based on ultra-wide band wireless location |
| CN110704556A (en) * | 2019-09-03 | 2020-01-17 | 镇江市勘察测绘研究院 | Geographic information acquisition method based on GIS technology |
| CN110956132A (en) * | 2019-11-29 | 2020-04-03 | 苏州经贸职业技术学院 | Method for intelligently constructing weed control model based on unmanned aerial vehicle cooperation |
| CN110956132B (en) * | 2019-11-29 | 2023-12-29 | 苏州经贸职业技术学院 | Method for constructing weed control model based on unmanned aerial vehicle cooperation intelligence |
| CN110825118A (en) * | 2019-12-23 | 2020-02-21 | 河南大学 | Multi-unmanned aerial vehicle cooperative farmland spraying method based on deep learning algorithm |
| CN111753388A (en) * | 2019-12-30 | 2020-10-09 | 广州极飞科技有限公司 | Spraying control method, spraying control device, electronic equipment and computer-readable storage medium |
| CN111292439A (en) * | 2020-01-22 | 2020-06-16 | 上海杰狮信息技术有限公司 | Unmanned aerial vehicle inspection method and inspection system for urban pipe network |
| CN111488016A (en) * | 2020-04-17 | 2020-08-04 | 北京派得伟业科技发展有限公司 | Accurate quantitative operation method and device for plant protection unmanned aerial vehicle |
| CN111582055A (en) * | 2020-04-17 | 2020-08-25 | 清远市智慧农业研究院 | Aerial pesticide application route generation method and system for unmanned aerial vehicle |
| CN111670668A (en) * | 2020-06-05 | 2020-09-18 | 沈阳农业大学 | Accurate topdressing method for agricultural rice unmanned aerial vehicle based on hyperspectral remote sensing prescription chart |
| CN112162566A (en) * | 2020-09-04 | 2021-01-01 | 深圳市创客火科技有限公司 | Route planning method, electronic device and computer-readable storage medium |
| CN112162566B (en) * | 2020-09-04 | 2024-01-16 | 深圳市创客火科技有限公司 | Route planning method, electronic device and computer readable storage medium |
| CN113359855A (en) * | 2021-07-13 | 2021-09-07 | 华南农业大学 | Real-time control method for accurate pesticide application of plant protection unmanned aerial vehicle |
| CN113359855B (en) * | 2021-07-13 | 2023-10-20 | 华南农业大学 | Accurate pesticide application real-time control method for plant protection unmanned plane |
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