CN113934232A - Virtual image control-based plant protection unmanned aerial vehicle air route planning system and method - Google Patents
Virtual image control-based plant protection unmanned aerial vehicle air route planning system and method Download PDFInfo
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Abstract
The invention relates to a virtual image control-based plant protection unmanned aerial vehicle route planning system and a virtual image control-based plant protection unmanned aerial vehicle route planning method, wherein the plant protection unmanned aerial vehicle route planning system comprises ground interaction equipment and an unmanned aerial vehicle; the unmanned aerial vehicle acquires image information and position information and sends the image information and the position information to the ground interaction equipment; the ground interaction equipment loads the constructed operation area model, receives image information and position information acquired by the unmanned aerial vehicle, and associates the position information acquired by the unmanned aerial vehicle into the constructed operation area model based on the same coordinate system; the ground interactive equipment takes one side of a set operation area as a reference boundary, an unmanned aerial vehicle flight line is formed by odd lines parallel to the reference boundary in the operation area, and even lines are boundary lines of the flight line. The position and the state of the plant protection unmanned aerial vehicle during farmland operation are displayed and controlled in real time by utilizing the virtual image in the ground interaction equipment, so that the operation efficiency of irrigation, fertilization and pesticide spraying is improved.
Description
Technical Field
The invention relates to the field of agriculture, in particular to a plant protection unmanned aerial vehicle route planning system and method based on virtual image control.
Background
The statements in this section merely provide background information related to the present disclosure and may not necessarily constitute prior art.
The existing plant protection unmanned aerial vehicle generally needs an operator to set two position points and plan a route of the unmanned aerial vehicle between the two points, the two-point route planning operation is complicated, each straight line operation is needed once, the operation efficiency is low, and the operation is manually completed; the planning of the air route is designed based on the coordinates of a two-dimensional plane, and different flight heights of the unmanned aerial vehicle cannot be planned in one operation aiming at different crop types; meanwhile, the unmanned aerial vehicle is limited by the limits of electric quantity and water carrying quantity (or weight of drugs and fertilizers), the plant protection task can be completed only by multiple flight operations, and the requirement of the plant protection task can be met only by depending on the operation of a complex remote controller in the multiple flight process.
Disclosure of Invention
In order to solve the technical problems in the background art, the invention provides a virtual image control-based flight path planning system and method for a plant protection unmanned aerial vehicle, wherein a working area (farmland) of the plant protection unmanned aerial vehicle is constructed into a virtual 3D model, the position information of the unmanned aerial vehicle is associated with the constructed 3D model and loaded in ground interaction equipment, a user only needs to select, calibrate or click a contour, a track or a specific position needing to be operated in the farmland by observing a dynamic live-action picture of the farmland model in a ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan a flight path in the framed area according to the selection of the user; simultaneously, the user is according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted, adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height, breaks away from present remote controller completely to the operation such as farmland fertilization, irrigation and medicine are accomplished to the efficient, utilize virtual image control's mode to promote plant protection unmanned aerial vehicle's operating efficiency.
In order to achieve the purpose, the invention adopts the following technical scheme:
the invention provides a plant protection unmanned aerial vehicle route planning method based on virtual image control, which comprises the following steps:
associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of the virtual unmanned aerial vehicle model in the constructed operation area model based on the same coordinate system;
acquiring a set operation area of the plant protection unmanned aerial vehicle based on the associated operation area model;
one side of the set operation area is used as a reference boundary, an odd line parallel to the reference boundary in the operation area is used as a flight line of the plant protection unmanned aerial vehicle, and an even line is used as a boundary line of the flight line.
The invention provides a plant protection unmanned aerial vehicle route planning method based on virtual image control, which comprises a ground interaction device and an unmanned aerial vehicle which are in communication connection;
a drone configured to: acquiring image information and position information, and sending the image information and the position information to ground interaction equipment;
a ground interaction device configured to: loading a constructed operation area model, receiving image information and position information acquired by an unmanned aerial vehicle, and associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of a virtual unmanned aerial vehicle model in the operation area model to form an interactive interface based on the same coordinate system, wherein the interactive interface is a virtual image;
the method for acquiring the flight route of the unmanned aerial vehicle by the ground interactive equipment executing the frame selection graphic path planning method specifically comprises the following steps: one side of the set operation area is used as a reference boundary, an unmanned aerial vehicle flight path is formed by odd lines parallel to the reference boundary in the operation area, and even lines are boundary lines of the flight path.
Further, the interval between two adjacent boundary lines is unmanned aerial vehicle's operation width.
Furthermore, two adjacent odd lines are connected end to form the flight line of the unmanned aerial vehicle.
Further, the ground interaction equipment acquires set target points of the unmanned aerial vehicle, and when the number of the set target points is less than 4, connecting lines are formed according to the sequence of the set target points to serve as a flight route of the unmanned aerial vehicle; and when the set number of the target points is more than or equal to 4, executing a frame selection graph path planning method.
Furthermore, the ground interaction equipment acquires the position information of the unmanned aerial vehicle, and the flight position and direction of the unmanned aerial vehicle are controlled based on the coordinate axis in the position information.
Furthermore, the ground interaction device divides the operation area in the operation model into n × n grid sub-areas by using the operation area terrain information contained in the image information acquired by the unmanned aerial vehicle, and acquires the flight path of the unmanned aerial vehicle based on each grid sub-area.
Furthermore, the ground interaction equipment is provided with a wireless communication module, and the image information and the position information acquired by the unmanned aerial vehicle are transmitted to the ground interaction equipment through the wireless communication module.
A third aspect of the invention provides a computer-readable storage medium.
A computer readable storage medium having stored thereon a computer program which, when executed by a processor, carries out the steps in the method for plant protection drone route planning based on virtual image control as described above.
A fourth aspect of the invention provides a computer apparatus.
A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps in the method for planning routes for plant protection unmanned aerial vehicle based on virtual image control as described above when executing the program.
Compared with the prior art, the above one or more technical schemes have the following beneficial effects:
1. the method comprises the steps of constructing a working area (farmland) of the plant protection unmanned aerial vehicle into a virtual 3D model, associating position information of the unmanned aerial vehicle with the constructed 3D model, and loading the model into ground interaction equipment, wherein a user only needs to select, calibrate or click a contour, a track or a specific position needing to be operated in the farmland by observing a dynamic live-action picture of the farmland model in a ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan a route in the selected area according to the selection of the user.
2. The user is according to among the ground interaction device, the dynamic image that plant protection unmanned aerial vehicle transmitted, and adjustment plant protection unmanned aerial vehicle's actual flight path, airspeed and flying height break away from present remote controller completely to the operation such as farmland fertilization, irrigation and medicine are accomplished to the high efficiency, utilize virtual image control's mode to promote plant protection unmanned aerial vehicle's operating efficiency.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to provide a further understanding of the invention, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the invention and together with the description serve to explain the invention and not to limit the invention.
FIG. 1 is a schematic diagram of an airline planning system architecture provided by one or more embodiments of the invention;
FIG. 2 is a schematic illustration of a back and forth working trajectory for cattle plowing provided by one or more embodiments of the present invention;
FIG. 3 is a schematic illustration of the principles of the back and forth plowing operation provided by one or more embodiments of the present invention;
FIG. 4 is a schematic illustration of a rectangular work area route acquisition provided by one or more embodiments of the present invention.
Detailed Description
The invention is further described with reference to the following figures and examples.
It is to be understood that the following detailed description is exemplary and is intended to provide further explanation of the invention as claimed. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the invention. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, and it should be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof, unless the context clearly indicates otherwise.
As described in the background art, the current plant protection unmanned aerial vehicle usually requires an operator to set two position points, and plan a flight path of the unmanned aerial vehicle between the two points, the unmanned aerial vehicle needs to perform multiple flight operations to complete a plant protection task for one area, multiple flights need multiple flight path planning processes, and multiple factors such as weather, wind direction, unmanned aerial vehicle coverage width, obstacle influence, and flight height caused by crop species need to be considered for each flight path planning, and meanwhile, the requirements of the plant protection task can be met by relying on complex remote controller operation in the multiple flight process, and the requirements on the experience and the operation level of the operator are high.
The AR technology is a technology for real-time computing the position and angle of a camera image and combining the corresponding image, video, and 3D model in augmented reality. Therefore, the following embodiments provide a virtual image control-based flight path planning system and method for a plant protection unmanned aerial vehicle, an operation area (farmland) of the plant protection unmanned aerial vehicle is constructed into a virtual 3D model, position information of the unmanned aerial vehicle is associated with the constructed 3D model and loaded in ground interaction equipment, an operation user only needs to select, calibrate or click a contour, a track or a specific position of the farm model in a field by observing a dynamic live-action picture of the farm model in a ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan a flight path in the framed area according to the selection of the user; simultaneously, the user is according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted, adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height, breaks away from present remote controller completely to operation such as self-adaptation, multitask, accurate, real-time, high-efficient ground completion farmland fertilization, irrigation and spout medicine utilize virtual image control's mode to promote plant protection unmanned aerial vehicle's operating efficiency.
The first embodiment is as follows:
a plant protection unmanned aerial vehicle air route planning method based on virtual image control comprises the following steps:
associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of the virtual unmanned aerial vehicle model in the operation area model based on the same coordinate system;
acquiring a set operation area of the unmanned aerial vehicle based on the associated operation area model;
one side of the set operation area is used as a reference boundary, an odd line parallel to the reference boundary in the operation area is used as a flight route of the unmanned aerial vehicle, and an even line is used as a boundary line of the flight route.
According to the method, the operation area (farmland) of the plant protection unmanned aerial vehicle is constructed into a virtual 3D model, the position information of the unmanned aerial vehicle is associated with the constructed 3D model and is loaded in the ground interaction equipment, an operation user only needs to select, calibrate or click the outline, track or specific position of the operation required in the farmland by observing the dynamic live-action picture of the farmland model in the ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan the route in the selected area according to the selection of the user; simultaneously, the user adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted to break away from present remote controller completely to promote plant protection unmanned aerial vehicle's operating efficiency with virtual image control's mode.
Example two:
as shown in fig. 1-4, the present embodiment provides a virtual image control-based plant protection unmanned aerial vehicle route planning system, which includes a ground interaction device and an unmanned aerial vehicle, which are in communication connection;
a drone configured to: acquiring image information and position information, and sending the image information and the position information to ground interaction equipment;
a ground interaction device configured to: loading a constructed operation area model, receiving image information and position information acquired by an unmanned aerial vehicle, and associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of a virtual unmanned aerial vehicle model in the operation area model to form an interactive interface based on the same coordinate system, wherein the interactive interface is a virtual image;
the ground interactive equipment takes one side of a set operation area as a reference boundary, takes an odd line parallel to the reference boundary in the operation area as an unmanned aerial vehicle flight line, and takes an even line as a boundary line of the flight line.
The method comprises the following specific steps:
the system utilizes the characteristics of AR technology augmented reality scene, combines the research on the operation of the plant protection unmanned aerial vehicle in the farmland, and based on Vufaria SDK plug-in, Unity3D and IMU-based 3D position tracking algorithm, realizes the intelligent control equipment program with interactive functions of augmented reality such as movement, rotation, zooming, action triggering and the like of the plant protection unmanned aerial vehicle, and the plant protection unmanned aerial vehicle carries out self-planning course and autonomous operation on the concave or convex polygon area of the actual farmland. In the flight process, the plant protection unmanned aerial vehicle adjusts the flight attitude in real time through a camera provided by the plant protection unmanned aerial vehicle according to the characteristics of the terrain, and can also be controlled by the forward, backward, hovering, speed, high and low positions and the like of an operator in real time.
The acquisition control center in the ground interaction equipment comprises an image receiving and processing module, a wireless image transmission module, a relay module and a wireless WiFi module. The image receiving and processing module receives the image data sent by the wireless image transmission module, and sends each data packet with the size of 512 bytes through the relay module and the wireless WiFi module. The wireless WiFi module establishes a communication handshake mechanism through the wireless image transmission module and the image receiving and processing module.
Can show a virtual unmanned aerial vehicle in ground interaction device's the interface, this virtual unmanned aerial vehicle utilizes AR technique, real-time calculation actual unmanned aerial vehicle carries image sensor's position and angle, carry out image acquisition and discernment to the position (the position apart from crops in the height) that the plant protection unmanned aerial vehicle is located, the growing environment of crops on every side etc. carries out image acquisition and discernment, image sensor carries out multi-angle look around to the reality scene of crops and shoots image and video, combine 3D MAX technique and OpenGL procedure to establish the 3D model, overlap virtual unmanned aerial vehicle model in real crops growth real scene on ground interaction device's interface, realize real-time tracking monitoring's effect. In the transmission process of the virtual image, image data is compressed by adopting a high-fidelity multi-resolution resampling image compression algorithm, and a WiFi signal is generated by using a relay module for image transmission.
Under same coordinate system, will be based on the operation area model that unmanned aerial vehicle acquireed image information and the positional information of unmanned aerial vehicle that founds is correlated, can demonstrate a virtual unmanned aerial vehicle in virtual operation area model, this virtual unmanned aerial vehicle corresponds with actual unmanned aerial vehicle position, controls virtual unmanned aerial vehicle's flight path, height and speed in virtual operation area model, has just also controlled actual unmanned aerial vehicle flight path, height and speed. The interface of the ground interaction equipment is a graphical control mode, the virtual image is displayed, and the image information acquired by the plant protection unmanned aerial vehicle can be displayed while the flight control of the plant protection unmanned aerial vehicle is completed in the virtual image.
In this embodiment, plant protection unmanned aerial vehicle's operation area (farmland) model can utilize unmanned aerial vehicle to carry the image information that image sensor acquireed and obtain after modeling, shows the boundary line in farmland in the model, the height of crops, the barrier in crops kind and the farmland, and the operation area model who obtains is the model at follow-up virtual unmanned aerial vehicle place.
The operation area model is constructed by image information acquired by the unmanned aerial vehicle, the image information comprises the flight height of the unmanned aerial vehicle, and the boundary length of the working area (farmland) is known and also included in the image information, after the coordinate system of the working area model is constructed, the position coordinates (set as the O point) of the unmanned aerial vehicle when the working area model is constructed can be obtained, after the virtual unmanned aerial vehicle model is introduced into the operation area model, the coordinates of the mass center point of the virtual unmanned aerial vehicle model are associated with the O point in the operation area model, the three-dimensional data (namely the movement capability of the plant protection unmanned aerial vehicle, such as the flying height, the pesticide spraying width and the like) of the virtual unmanned aerial vehicle model is also associated into the operation area model, changing the position of the O point in the work area model corresponds to changing the position of the virtual drone model, the position coordinates after the change of the plant protection unmanned aerial vehicle can be used for controlling the plant protection unmanned aerial vehicle to fly to the set position in the farmland range.
Meanwhile, the virtual unmanned aerial vehicle model can be set at any position in the operation area model by taking the O point as a reference, so that the plant protection unmanned aerial vehicle is controlled to fly to a set position in a farmland range.
The operation area model is displayed in the ground interaction equipment, the operation area model is a virtual model constructed by real images and corresponds to an actual farmland, and the ground interaction equipment changes the position of the virtual unmanned aerial vehicle model in a virtual image mode so as to control the plant protection unmanned aerial vehicle to fly to a set position in the farmland range.
In this embodiment, the ground interaction device establishes an unmanned aerial vehicle route planning database, performs three-dimensional real-time scanning on an unmanned aerial vehicle, an actual working area (farmland) and a crop growth real scene respectively, inputs a scanning image into the unmanned aerial vehicle route planning database, generates a virtual working area image corresponding to the scanning image information, and displays the virtual working area image on an interface of the ground intelligent interaction device.
In the embodiment, the data such as the high-precision position, the high-precision height, the flight speed, the direction angle and the pitch angle in the image information correspond to the relevant data information of the unmanned aerial vehicle in actual flight, a Kalman filtering algorithm is adopted for fusion and mutual correction of measurement data, and the remote wireless image transmission module transmits the fusion-corrected measurement data to the unmanned aerial vehicle route planning database.
In this embodiment, an unmanned aerial vehicle geometric model is established through 3DMAX software, and then the geometric model manufactured by 3DMAX is converted into a virtual unmanned aerial vehicle 3D model in OpenGL format by using View3ds conversion software. The size of the virtual unmanned aerial vehicle 3D model can be solved by directly adjusting the size of a geometric model in 3DMAX, and can also be solved by adjusting a program; the display list in the OpenG L library may control the real-time display speed of the 3D model. The virtual unmanned aerial vehicle 3D model is transmitted to the ground interaction equipment through the remote wireless image transmission module, and is displayed on a ground interaction equipment interface after being overlapped with the virtual operation area image.
DBF formation of image radar that plant protection unmanned aerial vehicle carried on can the 24 hours perception farmland environment, early warning adverse circumstances. The embedded AR technology realizes point cloud imaging of three-dimensional scales, effectively collects the real scenes of farmlands in operation, comprises terrain detection, a user only needs to select or calibrate or click the area outline or curve or position of the farmlands on an interface of ground interaction equipment, the plant protection unmanned aerial vehicle can independently plan the optimal path of fertilizer application and pesticide spraying, and detect obstacles in real time, so that independent obstacle-surrounding operation is realized, and a route is not necessarily a straight line. The unmanned aerial vehicle can also calculate the optimal operation navigation path according to the real-time requirements of the user (the drawing command of the figure outline or the curve track or the specific position sent by the user), and finally realize the efficient and accurate spraying operation of the plant protection unmanned aerial vehicle, thereby saving the amount of liquid medicine and fertilizer, and improving the operation efficiency of the farmland and the yield of products.
The ground interaction device interface can show the dynamic position of plant protection unmanned aerial vehicle when the farmland operation in real time, and the user observes and monitors plant protection unmanned aerial vehicle's dynamic operation sight at any time, drags the plant protection unmanned aerial vehicle who controls in the ground interaction device interface in real time, controls its flight attitude, including flying speed, flight direction, height position etc..
Autonomous route analysis
According to plant protection unmanned aerial vehicle's operation task and user's demand, ground interactive device sends the flight task request to plant protection unmanned aerial vehicle's action planner, the action planner makes reasonable action planning through central controller, central controller control plant protection unmanned aerial vehicle carries out flight and operation task, in flight process, the user observes the crops scene of being transmitted by vision sensor and picture transmission machine in real time through intelligent interactive device interface, the crops scene includes the growing situation of plant (the growing situation includes the height of plant, the blade quantity, the thickness of stem, leaf area size etc.), the pest condition and with plant interval sparse and dense condition etc. on every side. Corresponding data analysis is made while the vision sensor shoots the picture to with analysis result through picture transmission transmitter passback to ground interactive installation, the user can be according to received picture and data, real-time control unmanned aerial vehicle's flying speed, spray circumstances such as medicine volume or fertilization volume. The frame of the autonomous flight path of the system is shown in fig. 1.
(1) A frame selection graph path planning method:
the user can frame in advance in the interface of ground interaction device and elect unmanned aerial vehicle's flight area, and the frame selects the figure and can be rectangle, convex, spill or circular, and unmanned aerial vehicle flies and the operation in the figure area of user's frame selection. The central controller of the unmanned aerial vehicle performs image processing and feature extraction on the selected image, determines flight and operation tracks, and defaults to adopting a back-and-forth operation track for cattle cultivation to fly, as shown in fig. 2.
The principle of the back and forth tilling operation is shown in fig. 3, wherein L represents the longitudinal length of the working area, M represents the transverse length, and d represents the coverage width. Unmanned aerial vehicle traveles the bottom on work area border along the straight line, turns to next, then flies and the operation along another route parallel with the previous one, covers the width d of operation, and width between two adjacent air lines is promptly, and the work route is on a parallel with certain boundary line in coverage area to adjacent parallel operation route equidistance, the work amplitude of covering is d.
The rectangular work area route acquisition is shown in FIG. 4. If the operation area is rectangular, a parallel line is made every d/2 with a certain boundary of the area as a reference. The leftmost side of the flight area is a reference boundary, the dotted lines represent parallel lines, the distance between every two adjacent parallel lines is d/2, the parallel lines are sequentially ordered, the odd lines represent the operation route of the plant protection unmanned aerial vehicle, and the even lines represent the boundary line of the operation zone. w is a0As a starting waypoint, w1To terminate the waypoint, the arrow is in the same direction as the flight direction.
(2) The method for planning the path by the calibration points comprises the following steps:
the user can calibrate the flight destination of the unmanned aerial vehicle in the ground interaction equipment interface, at most four points can be calibrated, each calibration point displays one virtual unmanned aerial vehicle, the defined destinations are sp1, sp2, sp3 and sp4, the destinations sp1, sp2, sp3 and sp4 are numbered according to the default calibration sequence, and the user can redefine the calibration position by dragging the calibrated virtual unmanned aerial vehicle in the ground interaction equipment interface. If the number of the calibrated points is less than 4, the unmanned aerial vehicle flies and operates along the connecting line of the calibrated points; if the number of the index points is 4, the unmanned aerial vehicle plans the optimal path to carry out flight and operation according to a first method, namely a frame selection graph path planning method.
After the user marks 1 to 4 destinations, the ground interaction equipment performs optimal planning of the path according to the sequence of the destinations.
In the flight process of the unmanned aerial vehicle, a user can change the calibrated destination which the unmanned aerial vehicle does not reach at any time, and after the central control receives a new calibration point, the re-planning device of the autonomous air route system replans the path, so that the satisfied optimal operation path of the user is completed.
(3) Coordinate axis point control path planning method:
the user can default to use the projection position of the takeoff position of the unmanned aerial vehicle on the ground as the origin of coordinates (the origin of coordinates can also be dragged to a proper position by the user) according to the real-time picture of the scene where the unmanned aerial vehicle is located in the ground interaction device interface, sets three-dimensional coordinate axes which are respectively an x axis, a y axis and a z axis, and is respectively used for controlling the horizontal distance of flight, the height of flight and the flight direction in the picture. The user only needs to click a certain coordinate axis, corresponding parameters can be controlled, and therefore the flying position and direction of the unmanned aerial vehicle are controlled in real time.
The path planner is used for combining an OpenCV image algorithm and an A-algorithm, reading and storing a terrain image captured by the image sensor through an immead () function and an Imwrite () function, performing position arithmetic and logical operation on the terrain image, sequencing paths through a Manhattan method, establishing nodes and parent nodes, and searching for obstacles through a target tracking function CSR-DCF (), so as to find the optimal path. The optimal position and direction of flight are adjusted independently, and meanwhile, the position and direction of the unmanned aerial vehicle are sent to the ground interaction equipment in real time by the wireless graph transmitter.
(4) n × n grid division method:
for the situation that the terrain is complex or the situation that the user has special requirements on the operation, the terrain can be divided into n × n grid sub-areas for management.
After the plant protection unmanned aerial vehicle rises to suitable height, GPS sends geographical position information such as height to ground interactive equipment, plant protection unmanned aerial vehicle vision sensor carries out the topography to the operation area and shoots, later give intelligent interactive equipment with the geographic information picture passback that acquires, ground station computer handles the geographic information picture that plant protection unmanned aerial vehicle acquireed, show simultaneously on the intelligent interactive equipment screen, the user is according to the topographic features, and through the actual scene of analysis crops, decompose the picture into n mesh subregion, central controller then controls plant protection unmanned aerial vehicle and carries out the operation to each subregion order.
The quality assurance unmanned aerial vehicle autonomous air line system controlled by the virtual images can realize the function of photographing while flashing while the unmanned aerial line is autonomous, is flexible to control and accurate in operation, can know the growth condition and the disease and insect pest condition of crops in real time without going to a crop field, and really realizes low operation cost and high-precision agriculture.
The system constructs the operation area (farmland) of the plant protection unmanned aerial vehicle into a virtual 3D model, associates the position information of the unmanned aerial vehicle with the constructed 3D model and loads the model into the ground interaction equipment, an operation user only needs to select, calibrate or click the outline, track or specific position of the operation required in the farmland by observing the dynamic live-action picture of the farmland model in the ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan the route in the selected area according to the selection of the user.
Simultaneously, the user is according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted, adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height, breaks away from present remote controller completely to operation such as self-adaptation, multitask, accurate, real-time, high-efficient ground completion farmland fertilization, irrigation and spout medicine utilize virtual image control's mode to promote plant protection unmanned aerial vehicle's operating efficiency.
The mode of virtual image control, make operating personnel can follow the virtual model of ground interaction device loading and see unmanned aerial vehicle's current operation position and the image information that unmanned aerial vehicle acquireed under the current position directly, image information is that the actual picture in the farmland relies on existing wireless communication equipment to realize, and only need show unmanned aerial vehicle's positional information and control command window in the virtual model can, the picture information that unmanned aerial vehicle acquireed need not show, make the process of construction of virtual model simpler on the one hand, on the other hand does not need complicated farmland actual picture and virtual model matching process.
EXAMPLE III
The present embodiment provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps in the method for planning routes of plant protection unmanned aerial vehicles based on virtual image control as set forth in the first embodiment.
In the virtual image control-based flight path planning method for the plant protection unmanned aerial vehicle, the operation area (farmland) of the plant protection unmanned aerial vehicle is constructed into a virtual 3D model, the position information of the unmanned aerial vehicle is associated with the constructed 3D model and loaded in the ground interaction equipment, an operation user only needs to select, calibrate or click a contour, a track or a specific position of the operation needed in the farmland by observing a dynamic live-action picture of the farmland model in a ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan a flight path in the selected area according to the selection of the user; simultaneously, the user adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted to break away from present remote controller completely to promote plant protection unmanned aerial vehicle's operating efficiency with virtual image control's mode.
Example four
The embodiment provides a computer device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps in the virtual image control-based plant protection unmanned aerial vehicle route planning method provided in the embodiment.
In the virtual image control-based flight path planning method for the plant protection unmanned aerial vehicle executed by the processor, the operation area (farmland) of the plant protection unmanned aerial vehicle is constructed into a virtual 3D model, the position information of the unmanned aerial vehicle is associated with the constructed 3D model and loaded in the ground interaction equipment, an operation user only needs to select, calibrate or click a contour, a track or a specific position needing operation in the farmland by observing a dynamic live-action picture of the farmland model in a ground interaction equipment interface in real time, and the plant protection unmanned aerial vehicle can independently plan a flight path in the selected area according to the selection of the user; simultaneously, the user adjusts plant protection unmanned aerial vehicle's actual flight path, flying speed and flying height according to the dynamic image that the plant protection unmanned aerial vehicle among the ground interaction device transmitted to break away from present remote controller completely to promote plant protection unmanned aerial vehicle's operating efficiency with virtual image control's mode.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of a hardware embodiment, a software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a read-only memory or a random access memory.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A plant protection unmanned aerial vehicle route planning method based on virtual image control is characterized in that: the method comprises the following steps:
associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of the virtual unmanned aerial vehicle model in the constructed operation area model based on the same coordinate system;
acquiring a set operation area of the plant protection unmanned aerial vehicle based on the associated operation area model;
one side of the set operation area is used as a reference boundary, an odd line parallel to the reference boundary in the operation area is used as a flight line of the plant protection unmanned aerial vehicle, and an even line is used as a boundary line of the flight line.
2. Plant protection unmanned aerial vehicle air route planning system based on virtual image control, its characterized in that: the system comprises ground interaction equipment and an unmanned aerial vehicle which are in communication connection;
a drone configured to: acquiring image information and position information, and sending the image information and the position information to ground interaction equipment;
a ground interaction device configured to: loading a constructed operation area model, receiving image information and position information acquired by an unmanned aerial vehicle, and associating the position information acquired by the unmanned aerial vehicle with the coordinates of the centroid point of a virtual unmanned aerial vehicle model in the operation area model to form an interactive interface based on the same coordinate system, wherein the interactive interface is a virtual image;
the method for acquiring the flight route of the unmanned aerial vehicle by the ground interactive equipment executing the frame selection graphic path planning method specifically comprises the following steps: one side of the set operation area is used as a reference boundary, an unmanned aerial vehicle flight path is formed by odd lines parallel to the reference boundary in the operation area, and even lines are boundary lines of the flight path.
3. The plant protection unmanned aerial vehicle route planning system based on virtual image control of claim 2, wherein: the interval between two adjacent boundary lines is unmanned aerial vehicle's operation width.
4. The virtual image control-based plant protection unmanned aerial vehicle route planning system of claim 3, wherein: two adjacent odd lines are connected end to form the flight line of the unmanned aerial vehicle.
5. The plant protection unmanned aerial vehicle route planning system based on virtual image control of claim 2, wherein: the ground interaction equipment acquires set target points of the unmanned aerial vehicle, and when the number of the set target points is less than 4, connecting lines are formed according to the sequence of the set target points to serve as a flight route of the unmanned aerial vehicle; and when the set number of the target points is more than or equal to 4, executing a frame selection graph path planning method.
6. The plant protection unmanned aerial vehicle route planning system based on virtual image control of claim 2, wherein: the ground interaction equipment acquires the position information of the unmanned aerial vehicle, and the flight position and direction of the unmanned aerial vehicle are controlled based on the coordinate axis in the position information.
7. The plant protection unmanned aerial vehicle route planning system based on virtual image control of claim 2, wherein: the ground interaction equipment divides the operation area in the operation model into n multiplied by n grid subregions by using the operation area terrain information contained in the image information acquired by the unmanned aerial vehicle, and acquires the flight path of the unmanned aerial vehicle based on each grid subregion.
8. The plant protection unmanned aerial vehicle route planning system based on virtual image control of claim 2, wherein: the ground interaction equipment is provided with a wireless communication module, and the image information and the position information acquired by the unmanned aerial vehicle are transmitted to the ground interaction equipment through the wireless communication module.
9. A computer readable storage medium having stored thereon a computer program, wherein the program when executed by a processor implements the steps in the method for plant protection drone route planning based on virtual image control of claim 1.
10. A computer apparatus comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps in the method for virtual image control based plant protection drone route planning of claim 1.
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