CN113504792A - Unmanned aerial vehicle intelligent aerial broadcast path planning method, storage medium and unmanned aerial vehicle - Google Patents
Unmanned aerial vehicle intelligent aerial broadcast path planning method, storage medium and unmanned aerial vehicle Download PDFInfo
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Abstract
The invention discloses an intelligent air-borne broadcasting path planning method for an unmanned aerial vehicle, which comprises the following steps: acquiring position data of a target area and a target area boundary to obtain a target area graph; drawing an aerial broadcast pattern in a target area graph by adopting drawing software, and outputting the aerial broadcast pattern into a bitmap graph file consisting of a plurality of pixel points; calculating longitude and latitude data of each pixel point in the bitmap graphic file according to the position data of the graphic boundary of the target area; and planning the aerial broadcast path of the unmanned aerial vehicle by taking the pixel points as the waypoints on the flight path of the unmanned aerial vehicle. The method adopts the mode that the pixel points in the aerial seeding pattern are taken as the flight waypoints of the unmanned aerial vehicle, realizes the planning of the aerial seeding path of the unmanned aerial vehicle, has high control precision of the aerial seeding path of the unmanned aerial vehicle and simple control, and is suitable for the aerial seeding operation and the aerial seeding control of complex patterns, particularly multi-communication-domain graphs.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle control, in particular to an unmanned aerial vehicle intelligent air-seeding path planning method, a storage medium and an unmanned aerial vehicle.
Background
With the development of unmanned aerial vehicle technology, the unmanned aerial vehicle has been widely applied to various fields at present. In the field of agriculture and forestry plant protection, unmanned aerial vehicles are not only applied to the monitoring of forests and desertification lands, but also applied to agricultural planting and seeding and landscape plant planting.
Patent document CN107179776A discloses a landscape plant sowing method based on an unmanned aerial vehicle, which can make the unmanned aerial vehicle perform accurate operation in the area near the boundary by aiming at the sowing area with irregular edge shape, optimize the row scheduling order of the operation of the unmanned aerial vehicle through an algorithm, and reduce the flight distance and time of the non-effective operation time period, so as to improve the operation quality and make the shape of the sowing area more accurate and beautiful. However, the adopted aerial broadcast optimal path algorithm cannot be effectively applied to complex geometric combined graphs, and particularly, the complex geometric graphs with a plurality of non-connected domains exist in the same background are processed; moreover, for some graphs with complex boundaries and fine composition, the adopted image segmentation method has certain errors in control, and the control of the operation direction of the unmanned aerial vehicle needs to be combined in the control process, so that the whole control process is complex and tedious, and the air-seeding control requirement of complex geometric combined graphs cannot be met.
Disclosure of Invention
Aiming at the problems of low control precision and complex control process in the existing air-seeding control method, the invention provides an intelligent air-seeding path planning method for an unmanned aerial vehicle, a storage medium and the unmanned aerial vehicle, which can realize accurate air-seeding control on complex geometric combined graphs.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
the intelligent unmanned aerial vehicle aerial broadcast path planning method comprises the following steps:
acquiring position data of a target area and a target area boundary to obtain a target area graph;
drawing an aerial broadcast pattern in a target area graph by adopting drawing software, and outputting the aerial broadcast pattern into a bitmap graph file consisting of pixel points;
calculating longitude and latitude data of each pixel point in the bitmap graphic file according to the position data of the graphic boundary of the target area;
and planning the aerial broadcast path of the unmanned aerial vehicle by taking the pixel points as the waypoints on the flight path of the unmanned aerial vehicle.
In the above technical solution, further, the target area boundary includes an outer contour boundary of the target area and an outer contour boundary of an obstacle in the target area.
In the above technical solution, further, there is no intersection or coincidence between the contour boundary of the aerial seeding pattern and the outer contour boundary of the obstacle in the target area.
In the above technical solution, further, the position data of the target area boundary includes longitude and latitude data of the target area boundary.
In the above technical solution, further, the step of calculating the longitude and latitude data of each pixel point in the bitmap image file includes:
acquiring longitude and latitude coordinate information of any non-adjacent two points in a target area, and calculating the area of the target area according to position data of the boundary of the target area;
amplifying the aerial broadcast pattern according to the area of the target area to match the target area in proportion, and calculating the distance between adjacent pixel points in the bitmap graphic file of the aerial broadcast pattern;
and calculating according to the combination of the calibration points to obtain the longitude and latitude data of each pixel point in the bitmap graphic file.
In the technical scheme, further, the number of the interval pixel points between two adjacent waypoints on the aerial broadcast path is set according to the amplification proportion of the aerial broadcast pattern in the target area, and the waypoints on the flight path of the unmanned aerial vehicle are determined.
In the above technical solution, further, the step of planning the air-borne broadcast path of the unmanned aerial vehicle includes:
and acquiring parameters of the unmanned aerial vehicle, and generating an optimal flight path of the unmanned aerial vehicle by adopting an optimal path algorithm according to the parameters of the unmanned aerial vehicle and the pixel point data of the aerial broadcast pattern.
Among the above-mentioned technical scheme, furtherly, the unmanned aerial vehicle parameter includes that unmanned aerial vehicle minimum turns to angle, unmanned aerial vehicle consumption, unmanned aerial vehicle carry seed quantity, unmanned aerial vehicle seeding speed, unmanned aerial vehicle duration.
The invention also provides a storage medium, wherein the storage medium stores one or more execution programs, and the execution programs can be executed by a processor to realize the steps of the unmanned aerial vehicle intelligent air-seeding path planning method.
The invention also provides an unmanned aerial vehicle, which comprises a processor and a storage medium connected with the processor, wherein the storage medium stores an executive program, and the processor calls the executive program in the storage medium to execute the steps of realizing the unmanned aerial vehicle intelligent air-borne route planning method.
The invention adopts a mode of taking the pixel points in the aerial seeding pattern as the flight waypoints of the unmanned aerial vehicle to plan the aerial seeding path of the unmanned aerial vehicle, has high control precision of the aerial seeding path of the unmanned aerial vehicle and simple realization process, and well solves the problems of low control precision, complex control process, suitability for executing aerial seeding tasks of simple patterns and the like existing in the path planning of the existing aerial seeding operation of the unmanned aerial vehicle depending on boundary information, so that the method is applicable to the aerial seeding operation of complex patterns, particularly multi-communication-domain patterns.
The path planning method can also solve the problem that the existing unmanned aerial vehicle depends on the control of the ground station in the air-seeding operation, but the ground station only supports the limited path planning and is difficult to realize the complex graphic operation.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present invention, and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained according to the drawings without inventive efforts.
Fig. 1 is a flowchart of an intelligent air-seeding path planning method for an unmanned aerial vehicle according to an embodiment of the present invention.
Fig. 2 is a schematic diagram of an on-the-fly pattern according to an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention.
The unmanned aerial vehicle intelligent aerial broadcast path planning method adopts the pixel points in the aerial broadcast pattern as the reference for the unmanned aerial vehicle aerial broadcast path planning, and plans the flight path of the unmanned aerial vehicle on the basis of the longitude and latitude data of the pixel points as the mapping basis, so that the unmanned aerial vehicle is accurately controlled.
Example one
Referring to fig. 1, which is a flowchart of a method for planning an intelligent air-borne broadcast path of an unmanned aerial vehicle according to an embodiment of the present invention, the method for planning an intelligent air-borne broadcast path of an unmanned aerial vehicle includes:
s101, acquiring position data of a target area and a target area boundary to obtain a target area graph; the target area boundary comprises an outer contour boundary of the target area and an outer contour boundary of an obstacle in the target area; the barriers comprise ridges, telegraph poles and the like in the target area;
s102, drawing an aerial broadcast pattern in a target area graph by adopting drawing software, and outputting the aerial broadcast pattern into a bitmap graph file consisting of a plurality of pixel points, such as a graph file in a bmp format; the drawing software can adopt the existing general drawing software, and can draw and generate any complex and fine graph as required, as shown in FIG. 2;
s103, calculating longitude and latitude data of each pixel point in the bitmap graphic file according to the position data of the graphic boundary of the target area;
s104, taking the pixel points in the bitmap graphic file as flight points on the flight path of the unmanned aerial vehicle, and planning the flight path of the unmanned aerial vehicle; the pixel points are used as the basis for planning the flight path of the unmanned aerial vehicle, and the flight of the unmanned aerial vehicle is controlled.
As an alternative implementation, the target area and the target area boundary in the present embodiment may be based on the prior art to obtain relevant data and information from the satellite map and the existing mapping data. The position data of the target area boundary can be acquired by aerial photography of the target area by an unmanned aerial vehicle, or by adopting RTK dotter circling technology, or related data can be acquired according to existing surveying and mapping data and a satellite map.
In one embodiment, there is no intersection or coincidence between the contour boundary of the airborne pattern and the outer contour boundary of the obstacle within the target area. Therefore, the aerial seeding pattern avoids the area where the obstacle is located, the aerial seeding pattern can be suitable for aerial seeding operation of various different target areas, and a more free design space is provided for arrangement of the aerial seeding pattern in the target area.
In an embodiment, the location data of the target area boundary specifically includes longitude and latitude data of the target area boundary, that is, longitude and latitude data of the target area outer boundary and longitude and latitude data of the outer contour boundary of the obstacle in the target area.
In an embodiment, the step of calculating the longitude and latitude data of each pixel point in the bitmap image file in step S103 includes:
acquiring longitude and latitude coordinate information of any non-adjacent two points in a target area, and calculating the area of the target area according to position data of the boundary of the target area;
amplifying the aerial broadcast pattern according to the area of the target area to match the target area, and calculating the distance between each adjacent pixel point in the bitmap graphic file of the aerial broadcast pattern to obtain the effective resolution of the graphic file;
and calculating according to the combination of the calibration points to obtain the longitude and latitude data of each pixel point in the bitmap graphic file. Specifically, the calculation process of the longitude and latitude data of each pixel point is as follows: setting the plane of the pixel points of the graphic file as a Cartesian coordinate system, selecting a pixel point at the upper left corner of the graphic file as a calibration origin (or selecting any point as the calibration origin), selecting a pixel point at the lower right corner of the graphic file as a calibration reference point, wherein the calibration reference point and the calibration origin can also be two different pixel points with a certain distance interval, and performing geometric conversion on each pixel point in the graphic according to the effective resolution of the graphic file to obtain longitude and latitude data of each pixel point in the bitmap graphic file.
In an embodiment, the number of spaced pixel points between two adjacent waypoints on the air-borne broadcast path is set according to the amplification ratio of the air-borne broadcast pattern in the target area and the performance parameters of the unmanned aerial vehicle, and the waypoints on the unmanned aerial vehicle flight path for planning the air-borne broadcast path are determined.
In an embodiment, the step of planning the air-borne route of the drone in step S104 includes:
and acquiring parameters of the unmanned aerial vehicle, and generating an optimal flight path of the unmanned aerial vehicle by adopting an optimal path algorithm according to the parameters of the unmanned aerial vehicle and the pixel point data of the aerial broadcast pattern. Here unmanned aerial vehicle parameter includes that unmanned aerial vehicle minimum turns to angle, unmanned aerial vehicle consumption, unmanned aerial vehicle carry seed quantity, unmanned aerial vehicle seeding speed, unmanned aerial vehicle duration isoperformance parameter.
Example two
The embodiment of the present invention further provides a storage medium, where the storage medium stores one or more programs, and the one or more programs are executable by one or more processors to implement the steps of the method for planning an intelligent air-borne broadcast path of a drone in the foregoing embodiments.
EXAMPLE III
Based on the above embodiment, the present invention further provides an unmanned aerial vehicle, including a processor and a storage medium connected to the processor, where the storage medium stores an execution program, and the processor invokes the execution program in the storage medium to execute the steps of implementing the intelligent air-borne broadcast path planning method for an unmanned aerial vehicle described in the above embodiment.
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. An unmanned aerial vehicle intelligent air-seeding path planning method is characterized by comprising the following steps:
acquiring position data of a target area and a target area boundary to obtain a target area graph;
drawing an aerial broadcast pattern in a target area graph by adopting drawing software, and outputting the aerial broadcast pattern into a bitmap graph file consisting of pixel points;
calculating longitude and latitude data of each pixel point in the bitmap graphic file according to the position data of the graphic boundary of the target area;
and planning the aerial broadcast path of the unmanned aerial vehicle by taking the pixel points as the waypoints on the flight path of the unmanned aerial vehicle.
2. The unmanned aerial vehicle intelligent air-seeding path planning method according to claim 1, wherein the target area boundary comprises an outer contour boundary of a target area and an outer contour boundary of an obstacle in the target area.
3. The unmanned aerial vehicle intelligent aerial vehicle path planning method of claim 2, wherein there is no intersection or coincidence between contour boundaries of the aerial vehicle pattern and outer contour boundaries of obstacles within a target area.
4. The unmanned aerial vehicle intelligent air-seeding path planning method according to claim 1 or 2, wherein the position data of the target area boundary comprises longitude and latitude data of the target area boundary.
5. The unmanned aerial vehicle intelligent air-seeding path planning method according to claim 1, wherein the step of calculating longitude and latitude data of each pixel point in the bitmap image file comprises:
acquiring longitude and latitude coordinate information of any non-adjacent two points in a target area, and calculating the area of the target area according to position data of the boundary of the target area;
amplifying the aerial broadcast pattern according to the area of the target area to match the target area in proportion, and calculating the distance between adjacent pixel points in the bitmap graphic file of the aerial broadcast pattern;
and calculating according to the combination of the calibration points to obtain the longitude and latitude data of each pixel point in the bitmap graphic file.
6. The intelligent unmanned aerial vehicle aerial broadcast path planning method of claim 5, wherein the number of spaced pixel points between two adjacent waypoints on the aerial broadcast path is set according to the amplification ratio of the aerial broadcast pattern in the target area, and the waypoint on the unmanned aerial vehicle flight path is determined.
7. The intelligent unmanned aerial vehicle aerial broadcast path planning method of claim 1, wherein the step of planning the aerial broadcast path of the unmanned aerial vehicle comprises:
and acquiring parameters of the unmanned aerial vehicle, and generating an optimal flight path of the unmanned aerial vehicle by adopting an optimal path algorithm according to the parameters of the unmanned aerial vehicle and the pixel point data of the aerial broadcast pattern.
8. The method according to claim 7, wherein the parameters of the drone include a minimum steering angle of the drone, a power consumption of the drone, a number of seeds carried by the drone, a seeding speed of the drone, and a duration of the drone.
9. Storage medium, characterized in that it stores one or more executable programs, which can be executed by a processor to implement the steps of the intelligent unmanned aerial vehicle air-borne route planning method according to any one of claims 1-8.
10. Unmanned aerial vehicle, characterized in that, the unmanned aerial vehicle includes a processor and a storage medium connected with the processor, the storage medium stores an executive program, and the processor calls the executive program in the storage medium to execute the steps of implementing the unmanned aerial vehicle intelligent air-borne route planning method according to any one of claims 1-8.
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