CN118092479B - Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment - Google Patents
Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment Download PDFInfo
- Publication number
- CN118092479B CN118092479B CN202410524044.8A CN202410524044A CN118092479B CN 118092479 B CN118092479 B CN 118092479B CN 202410524044 A CN202410524044 A CN 202410524044A CN 118092479 B CN118092479 B CN 118092479B
- Authority
- CN
- China
- Prior art keywords
- preset
- range
- geofence
- unmanned aerial
- aerial vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000000034 method Methods 0.000 title claims abstract description 37
- 230000000007 visual effect Effects 0.000 description 11
- 238000004590 computer program Methods 0.000 description 6
- 238000010586 diagram Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 239000011159 matrix material Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
Landscapes
- Navigation (AREA)
Abstract
The invention provides an unmanned aerial vehicle flight task intelligent planning method, a system and electronic equipment, which comprise the steps of re-planning waypoint coordinates which are not located in any preset geofence range into each preset geofence range according to a nearby rule according to the position relation of each waypoint coordinate, each preset geofence range and the maximum visible range corresponding to each preset geofence range; splitting the first flight tasks according to the preset geofence ranges, and respectively distributing the second flight tasks formed by all waypoint coordinates in the preset geofence ranges to unmanned aerial vehicles equipped with the preset geofences. The method and the system can solve the problem that when the unmanned aerial vehicle executes the flight tasks crossing a plurality of geofences, the unmanned aerial vehicle is difficult to dispatch, greatly reduce the cost of the flight route planning of the unmanned aerial vehicle, and greatly improve the efficiency and the safety of the unmanned aerial vehicle for executing the flight tasks.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicle flight mission intelligent planning, in particular to an unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment.
Background
In recent years, along with development of unmanned aerial vehicle industry, unmanned aerial vehicle technology receives more and more attention, and is widely applied to each field gradually, at present, unmanned aerial vehicle flight task often passes through a plurality of geofences, and probably overlap each other between the geofences, and such task may need many unmanned aerial vehicles to cooperate to be carried out, if carry out the task dispatch of each unmanned aerial vehicle through the manual work, inefficiency, the error is great, be difficult to realize each unmanned aerial vehicle's high efficiency, high cooperation degree work, easily arouse the emergence of mutual collision or break away from monitoring area scheduling problem between unmanned aerial vehicles, in the prior art, there is the scheduling simultaneously many unmanned aerial vehicles difficulty, carry out the problem that flight task inefficiency, lack the intelligent scheme that can carry out effective planning to such flight task.
Thus, the prior art is still to be further developed.
Disclosure of Invention
The invention aims to overcome the technical defects and provide an unmanned aerial vehicle flight mission intelligent planning method, an unmanned aerial vehicle flight mission intelligent planning system and electronic equipment, so as to solve the problems in the prior art.
To achieve the above technical object, according to a first aspect of the present invention, there is provided an intelligent planning method for a flight mission of an unmanned aerial vehicle, including:
S100, acquiring each preset geofence range and a maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence;
s200, acquiring each waypoint coordinate in a first flight task of the unmanned aerial vehicle, and re-planning the waypoint coordinates which are not located in any one preset geofence range into each preset geofence range according to a nearby rule according to the position relation of each waypoint coordinate, each preset geofence range and the maximum visible range corresponding to each preset geofence range;
S300, splitting the first flight tasks according to the preset geofence ranges, and respectively distributing the second flight tasks formed by all waypoint coordinates in the preset geofence ranges to unmanned aerial vehicles equipped with the preset geofences.
Specifically, the re-planning the waypoint coordinates not located in any preset geofence range according to the vicinity rule to each preset geofence range includes:
and sequentially judging whether the waypoint coordinates in the range of two preset geofences exist or not, judging whether the waypoint coordinates which are not in any preset geofences are not in the range of any preset geofences according to the nearby rule according to the judging result, and re-planning the waypoint coordinates to the range of the preset geofences closest to the nearby rule according to the nearby rule.
Specifically, the determining, according to the determination result, whether the waypoint coordinates that are not located in any one of the preset geofences according to the vicinity rule are re-planned to be located in the preset geofences closest to the vicinity rule, includes:
if the waypoint coordinates in the two preset geofence ranges do not exist, the waypoint coordinates which are not in any preset geofence range are re-planned to be in the preset geofence range closest to the waypoint coordinates according to the nearby rule;
If the waypoint coordinates exist in the two preset geofences, respectively classifying the waypoint coordinates into the two preset geofences, respectively calculating the distance of a second flight mission formed by all the waypoints in the two preset geofences, and re-planning the waypoint coordinates into the preset geofences corresponding to the shorter distance.
Specifically, the re-planning the waypoint coordinates not located in any one preset geofence range to each preset geofence range according to the location relation between each waypoint coordinate and each preset geofence range, and the maximum visible range corresponding to each preset geofence range, including:
And marking the waypoint coordinates which are positioned in any maximum visible range but are not positioned in a preset geofence range corresponding to the maximum visible range as target waypoint coordinates, making a vertical line to the edge of the preset geofence closest to the target waypoint coordinates by the target waypoint coordinates, and moving the target waypoint coordinates along the vertical line to the inside of the preset geofence by a first preset distance to finish the re-planning.
Specifically, splitting the first flight task according to a preset geofence range, and respectively distributing the second flight task formed by all waypoint coordinates in each preset geofence range to unmanned aerial vehicles equipped with each preset geofence, wherein the method comprises the following steps:
Judging whether all the waypoint coordinates after the re-planning are positioned in the same preset geofence range, judging whether to acquire a selection signal of a flight task dispatch mode input by a user according to a judgment result, judging whether to allocate a second flight task formed by all the waypoint coordinates in each preset geofence range to an unmanned aerial vehicle equipped with each preset geofence according to the selection signal of the flight task dispatch mode input by the user.
Specifically, the determining whether all the re-planned waypoint coordinates are within the same preset geofence range, and determining whether to obtain a selection signal of a flight task dispatch mode input by a user according to a determination result, further includes:
If all the re-planned waypoint coordinates are not in the same preset geofence range, acquiring a selection signal of a flight task dispatch mode input by a user;
If all the waypoint coordinates after the re-planning are located in the same preset geofence range, a selection signal of a flight task dispatch mode input by a user is not acquired, and a second flight task formed by all the waypoint coordinates in the preset geofence range is directly dispatched to the unmanned aerial vehicle equipped with the preset geofence.
Specifically, the flight task dispatch modes include a first preset flight task dispatch mode and a second preset flight task dispatch mode, and the method for judging whether to dispatch the second flight task formed by all waypoint coordinates in each preset geofence range according to a selection signal of the flight task dispatch mode input by a user, and meanwhile, the method for distributing the second flight task to unmanned aerial vehicles equipped with each preset geofence includes:
And if the selection signal of the flight task dispatch mode input by the user is the selection signal of the first preset flight task dispatch mode, distributing the second flight task formed by all the waypoint coordinates in the range of each preset geofence to the unmanned aerial vehicle equipped with each preset geofence.
Specifically, the determining, according to a selection signal of a flight task dispatch mode input by a user, whether to allocate a second flight task formed by all waypoint coordinates within each preset geofence range to an unmanned aerial vehicle equipped with each preset geofence, further includes:
if the selection signal of the flight task dispatch mode input by the user is the selection signal of a second preset flight task dispatch mode, the second flight tasks formed by all the waypoint coordinates in the range of each preset geofence are sequentially distributed to the unmanned aerial vehicle equipped with each preset geofence according to the sequence of each preset geofence according to the route flight route corresponding to the first flight task by the unmanned aerial vehicle and the preset rules, wherein the preset rules comprise:
After the unmanned aerial vehicle corresponding to the last preset geofence range completes the second flight task, the next second flight task is distributed to the unmanned aerial vehicle equipped with the next preset geofence.
According to a second aspect of the present invention, there is provided an unmanned aerial vehicle flight mission intelligent planning system, comprising:
the acquisition module is used for acquiring the maximum visible range of each preset geofence range and the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the first flight task of the unmanned aerial vehicle;
The control module is used for re-planning the waypoint coordinates which are not positioned in any one preset geofence range into each preset geofence range according to the position relation between the waypoint coordinates and each preset geofence range and the maximum visible range corresponding to each preset geofence range, splitting the first flight tasks according to the preset geofence range, and respectively distributing the second flight tasks formed by all the waypoint coordinates in each preset geofence range to the unmanned aerial vehicle equipped with each preset geofence.
According to a third aspect of the present invention, there is provided an electronic device comprising: a memory; and the processor is used for storing computer readable instructions on the memory, and the computer readable instructions realize the unmanned aerial vehicle flight task intelligent planning method when being executed by the processor.
The beneficial effects are that:
According to the invention, the maximum visible range of each preset geofence range and the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the flight task are obtained, the unmanned aerial vehicle is re-planned into the preset geofence according to the space relation between each preset geofence and each waypoint coordinate in the flight task and the nearby principle, the first flight task is re-split according to the preset geofence range to form the second flight task, and the re-planned second flight task is distributed to the unmanned aerial vehicle equipped in each preset geofence range according to the designated flight mode to execute the flight task.
Drawings
Fig. 1 is a flowchart of an intelligent planning method for a flight mission of an unmanned aerial vehicle according to an embodiment of the present invention;
Fig. 2 is a schematic diagram of system components of an intelligent planning system for unmanned aerial vehicle flight tasks according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a secure geofence for a drone and a visual geofence for a drone provided in an embodiment of the present invention;
fig. 4 is a schematic diagram of a flight path of a unmanned aerial vehicle according to an embodiment of the present invention;
FIG. 5 is a schematic illustration of a scenario in which an airline is provided in only one geofence in an embodiment of the present invention;
FIG. 6 is a schematic illustration of a re-planning of waypoints when the route provided in an embodiment of the invention is within only one geofence;
FIG. 7 is a schematic illustration of a waypoint provided in an embodiment of the invention that is not within a geofence overlap region;
FIG. 8 is a schematic illustration of splitting a route when waypoints provided in embodiments of the invention are all located within independent geofences;
FIG. 9 is a schematic diagram of a waypoint provided in an embodiment of the invention having a geofence overlap region;
FIG. 10 is a schematic diagram of the grouping of airlines into groups provided in an embodiment of the invention;
FIG. 11 is a schematic diagram of the division of a route into two combinations provided in an embodiment of the present invention.
Detailed Description
In order to make the technical solution of the present application better understood by those skilled in the art, the technical solution of the present application will be clearly and completely described in the following with reference to the accompanying drawings, and based on the embodiments of the present application, other similar embodiments obtained by those skilled in the art without making any inventive effort should be included in the scope of protection of the present application. In addition, directional words such as "upper", "lower", "left", "right", and the like, as used in the following embodiments are merely directions with reference to the drawings, and thus, the directional words used are intended to illustrate, not to limit, the application.
The invention will be further described with reference to the drawings and preferred embodiments.
Referring to fig. 1, the invention provides an intelligent planning method for unmanned aerial vehicle flight tasks, comprising the following steps:
S100, acquiring each preset geofence range and a maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence;
It should be noted that, before step S100, setting a preset geofence range in the control module, a maximum visible range when the unmanned aerial vehicle flies along a boundary of each preset geofence, a first flight mission, a second flight mission, a first preset distance, and a flight mission dispatch mode.
Before step S100, a current video frame image corresponding to a maximum visible range shot by the unmanned aerial vehicle when flying along the boundary of each preset geofence is obtained, pixel coordinates of each pixel point on the boundary corresponding to the far end of the field of view of the unmanned aerial vehicle in the video frame image are calculated, the pixel coordinates of each pixel point are converted into geographic coordinates of each pixel point through a homography matrix, a set of the geographic coordinates of each pixel point is recorded as a visible geographic boundary of the current video frame image, a union set of all visible geographic boundaries corresponding to all video frame images corresponding to the maximum visible range shot by the unmanned aerial vehicle when flying along the boundary of each preset geofence is calculated, and the union set is used as the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence.
It can be understood that the preset geofence range, the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence, the first flight task, the second flight task, the first preset distance and the flight task dispatch mode can be specifically set according to the actual needs of the user, and the invention does not limit the specific name description and specific numerical values of the preset geofence range, the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence, the first flight task, the second flight task, the first preset distance and the flight task dispatch mode, so long as the unmanned aerial vehicle flight task intelligent planning method provided by the invention can be applied.
S200, acquiring coordinates of all waypoints in a first flight task of the unmanned aerial vehicle, and re-planning the coordinates of the waypoints which are not located in any one preset geofence range into all preset geofence ranges according to a nearby rule according to the position relation of the coordinates of all the waypoints, all the preset geofence ranges and the maximum visible range corresponding to all the preset geofence ranges.
Preferably, the preset geofence range is set as a safe geofence range, the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence is set as a visible geofence range, the first flight task is set as the flight task of the unmanned aerial vehicle when the route is not split, the second flight task is set as the sub-flight task after being split again in the preset geofence range, the flight task dispatch mode is set as the first preset flight task dispatch mode and the second preset flight task dispatch mode, preferably, the first preset distance is set so that the target waypoint coordinate after moving is located inside the preset geofence, and the nearest distance between the target waypoint coordinate and the edge of the nearest preset geofence is kept to be 10 meters.
Specifically, the re-planning the waypoint coordinates not located in any preset geofence range according to the vicinity rule to each preset geofence range includes:
and sequentially judging whether the waypoint coordinates in the range of two preset geofences exist or not, judging whether the waypoint coordinates which are not in any preset geofences are not in the range of any preset geofences according to the nearby rule according to the judging result, and re-planning the waypoint coordinates to the range of the preset geofences closest to the nearby rule according to the nearby rule.
Specifically, the determining, according to the determination result, whether the waypoint coordinates that are not located in any one of the preset geofences according to the vicinity rule are re-planned to be located in the preset geofences closest to the vicinity rule, includes:
if the waypoint coordinates in the two preset geofence ranges do not exist, the waypoint coordinates which are not in any preset geofence range are re-planned to be in the preset geofence range closest to the waypoint coordinates according to the nearby rule;
If the waypoint coordinates exist in the two preset geofences, respectively classifying the waypoint coordinates into the two preset geofences, respectively calculating the distance of a second flight mission formed by all the waypoints in the two preset geofences, and re-planning the waypoint coordinates into the preset geofences corresponding to the shorter distance.
Specifically, the re-planning the waypoint coordinates not located in any one preset geofence range to each preset geofence range according to the location relation between each waypoint coordinate and each preset geofence range, and the maximum visible range corresponding to each preset geofence range, including:
And marking the waypoint coordinates which are positioned in any maximum visible range but are not positioned in a preset geofence range corresponding to the maximum visible range as target waypoint coordinates, making a vertical line to the edge of the preset geofence closest to the target waypoint coordinates by the target waypoint coordinates, and moving the target waypoint coordinates along the vertical line to the inside of the preset geofence by a first preset distance to finish the re-planning.
It should be noted that if any waypoint exists and is not located in any maximum visible range, the waypoint is perpendicular to the edge of the preset geofence closest to the target waypoint coordinate, and the target waypoint coordinate is moved a first preset distance along the perpendicular to the inside of the preset geofence, so that re-planning is completed.
S300, splitting the first flight tasks according to the preset geofence ranges, and respectively distributing the second flight tasks formed by all waypoint coordinates in the preset geofence ranges to unmanned aerial vehicles equipped with the preset geofences.
Specifically, splitting the first flight task according to a preset geofence range, and respectively distributing the second flight task formed by all waypoint coordinates in each preset geofence range to unmanned aerial vehicles equipped with each preset geofence, wherein the method comprises the following steps:
Judging whether all the waypoint coordinates after the re-planning are positioned in the same preset geofence range, judging whether to acquire a selection signal of a flight task dispatch mode input by a user according to a judgment result, judging whether to allocate a second flight task formed by all the waypoint coordinates in each preset geofence range to an unmanned aerial vehicle equipped with each preset geofence according to the selection signal of the flight task dispatch mode input by the user.
Specifically, the determining whether all the re-planned waypoint coordinates are within the same preset geofence range, and determining whether to obtain a selection signal of a flight task dispatch mode input by a user according to a determination result, further includes:
If all the re-planned waypoint coordinates are not in the same preset geofence range, acquiring a selection signal of a flight task dispatch mode input by a user;
If all the waypoint coordinates after the re-planning are located in the same preset geofence range, a selection signal of a flight task dispatch mode input by a user is not acquired, and a second flight task formed by all the waypoint coordinates in the preset geofence range is directly dispatched to the unmanned aerial vehicle equipped with the preset geofence.
Specifically, the flight task dispatch modes include a first preset flight task dispatch mode and a second preset flight task dispatch mode, and the method for judging whether to dispatch the second flight task formed by all waypoint coordinates in each preset geofence range according to a selection signal of the flight task dispatch mode input by a user, and meanwhile, the method for distributing the second flight task to unmanned aerial vehicles equipped with each preset geofence includes:
And if the selection signal of the flight task dispatch mode input by the user is the selection signal of the first preset flight task dispatch mode, distributing the second flight task formed by all the waypoint coordinates in the range of each preset geofence to the unmanned aerial vehicle equipped with each preset geofence.
Specifically, the determining, according to a selection signal of a flight task dispatch mode input by a user, whether to allocate a second flight task formed by all waypoint coordinates within each preset geofence range to an unmanned aerial vehicle equipped with each preset geofence, further includes:
if the selection signal of the flight task dispatch mode input by the user is the selection signal of a second preset flight task dispatch mode, the second flight tasks formed by all the waypoint coordinates in the range of each preset geofence are sequentially distributed to the unmanned aerial vehicle equipped with each preset geofence according to the sequence of each preset geofence according to the route flight route corresponding to the first flight task by the unmanned aerial vehicle and the preset rules, wherein the preset rules comprise:
After the unmanned aerial vehicle corresponding to the last preset geofence range completes the second flight task, the next second flight task is distributed to the unmanned aerial vehicle equipped with the next preset geofence.
Preferably, the unmanned aerial vehicle completing the second flight task means that the unmanned aerial vehicle completes the return journey.
The working principle of the invention is illustrated by a specific example:
And acquiring unmanned aerial vehicle security geofence data and unmanned aerial vehicle visual geofence data. The visual geofence is that the drone flies to the security geofence boundary, and the furthest actual geoboundary can be observed by camera zooming, so the visual geofence must be larger than the security geofence. As shown in fig. 3, the blue polygon represents a security geofence, that is, a preset geofence proposed by the present invention, the green line box represents a visual geofence, that is, a maximum visual range corresponding to the preset geofence proposed by the present invention, and the symbol H represents an unmanned airport corresponding to each security geofence.
Acquiring the route and route point coordinates of the unmanned aerial vehicle flight mission, wherein the unmanned aerial vehicle flight route is shown in fig. 4:
Splitting and planning the route according to the safety geofence and the visual geofence, and distributing the planned route data to a specified unmanned aerial vehicle to execute the flight task.
The basic principle of splitting is as follows: the flight sequence of the waypoints cannot be changed; scheduling unmanned aerial vehicle of minimum frequency; shortest flight route mileage.
The specific example specifically includes the following steps:
(1) If the route is only within the same visual geofence, there is no need to split the route, only it is necessary to determine if there is a waypoint within the visual geofence but outside the security geofence, if so, as shown in fig. 5 and 6, the route is only within one geofence, waypoint 5 (waypoint 5 marked orange in fig. 6) is within the visual geofence while outside the security geofence, it is necessary to re-plan waypoint 5 (waypoint 5 marked orange in fig. 6) and display the waypoint coordinates of waypoint 5 (waypoint 5 marked orange in fig. 6) as target waypoint coordinates, and other waypoint coordinates located inside the security geofence as blue. If the situation does not exist, the existing waypoints are directly distributed to the unmanned aerial vehicle to which the safety geofence belongs without re-planning.
Specifically, the re-planning waypoint 5 (waypoint 5 labeled orange in fig. 6) includes: the waypoint 5 (waypoint 5 labeled orange in fig. 6) is plumbed to its nearest edge to the secure geofence and extends 10 meters inboard to re-plan the waypoint 5, and the planned waypoint 5 (waypoint 5 labeled blue in fig. 6) is labeled blue, and finally the re-planned route is distributed to the unmanned aerial vehicle to which the geofence belongs.
It can be appreciated that the technical characteristics can be conveniently checked by staff, and the intelligent degree, the visual degree and the usability of the invention are further improved.
(2) If the route runs through multiple geofences, the route needs to be split into multiple segments of routes based on the geofences and then assigned to multiple drones.
Where waypoints are not within the geofence overlap region, as in fig. 7, i.e., where waypoints are all located within separate geofences, the route is split, as in fig. 8.
For example: the first and second points are within fence number 1 and the third and fourth points are within fence number 2. The route is split into two sections, one section is the route formed by the first point and the second point and is executed by the unmanned aerial vehicle to which the No. 1 fence belongs, and the other section is the route formed by the third point and the fourth point and is executed by the unmanned aerial vehicle to which the No. 2 fence belongs. The split route also requires the step of (1) to determine if there are waypoints within the visible geofence but outside the secure geofence.
Waypoints are in the case of being located within the geofence overlap region, as in fig. 9. When the route is split, a certain navigation point is encountered in an overlapping area of a plurality of geofences, the serial number of the navigation point is recorded, after the route data of one pass is traversed to generate a group of split routes, the route is traversed again until all split route combinations are generated.
For example: the first point and the second point are positioned in one security geofence, the fourth point and the fifth point are positioned in the other security geofence, the third point is positioned in the overlapping area of the two security geofences, firstly, according to the principle of scheduling unmanned aerial vehicles with the least frequency, the route can be divided into two combinations, as shown in figure 10, the first point, the second point and the third point form a section of route, and the fourth point and the fifth point form a section of route; the second combination is shown in fig. 11, wherein the first point and the second point form a section of the route, and the third point, the fourth point and the fifth point form a section of the route. The two combinations only need to dispatch two unmanned aerial vehicles, then consider the shortest flight route mileage principle, calculate the route length of these two combinations respectively, which combination flight route mileage is shortest then adopt the route split of this kind of combination to issue to corresponding unmanned aerial vehicle to carry out the flight mission. Meanwhile, the split route is also the condition that whether the waypoint exists in the visible geofence but is outside the safe geofence or not is judged, and the step (1) is the same.
According to the user, whether a plurality of unmanned aerial vehicles are needed to execute the task is judged, two flight modes can be selected, and if the two flight modes are selected to fly simultaneously, the split airlines are issued to the plurality of unmanned aerial vehicles simultaneously to execute the corresponding flight tasks. If the first route task is selected to fly in sequence, after the first route task is issued to the corresponding unmanned aerial vehicle, the unmanned aerial vehicle waits for the completion of the flight, and when the unmanned aerial vehicle returns, the second route is issued to the corresponding unmanned aerial vehicle, and all the route tasks are issued in sequence in the same manner.
It can be appreciated that by acquiring the maximum visible range of each preset geofence range and the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the flight task, the invention re-plans the space relationship between each preset geofence and each waypoint coordinate in the flight task into the preset geofence according to the nearby principle, re-splits the first flight task according to the preset geofence range to form the second flight task, and distributes the re-planned second flight task to the unmanned aerial vehicle equipped in each preset geofence range according to the designated flight mode to execute the flight task.
Referring to fig. 2, another embodiment of the present invention provides an intelligent unmanned aerial vehicle flight mission planning system, which includes:
The acquiring module 100 is configured to acquire each preset geofence range, a maximum visible range when the unmanned aerial vehicle flies along a boundary of each preset geofence, and each waypoint coordinate in a first flight task of the unmanned aerial vehicle;
The control module 200 is configured to reprogram, according to a proximity rule, the waypoint coordinates that are not located in any one of the preset geofence ranges to the preset geofence ranges according to a positional relationship between the waypoint coordinates and the preset geofence ranges, and a maximum visible range corresponding to the preset geofence ranges, split a first flight task according to the preset geofence ranges, and respectively allocate a second flight task formed by all the waypoint coordinates in the preset geofence ranges to the unmanned aerial vehicle equipped with the preset geofences.
The method and the device have the advantages that the maximum visible range of each preset geofence range and the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the flight task are obtained, the first flight task is re-planned into the preset geofences according to the space relation between each preset geofence and each waypoint coordinate in the flight task according to the nearby principle, the first flight task is re-split according to the preset geofence range to form the second flight task, and the re-planned second flight task is distributed to the unmanned aerial vehicle equipped in each preset geofence range according to the designated flight mode to execute the flight task.
In a preferred embodiment, the present application also provides an electronic device, including:
A memory; and the processor is used for storing computer readable instructions on the memory, and the intelligent planning method for the unmanned aerial vehicle flight task is realized when the computer readable instructions are executed by the processor. The computer device may be broadly a server, a terminal, or any other electronic device having the necessary computing and/or processing capabilities. In one embodiment, the computer device may include a processor, memory, network interface, communication interface, etc. connected by a system bus. The processor of the computer device may be used to provide the necessary computing, processing and/or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. The non-volatile storage medium may have an operating system, computer programs, etc. stored therein or thereon. The internal memory may provide an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface and communication interface of the computer device may be used to connect and communicate with external devices via a network. Which when executed by a processor performs the steps of the method of the invention.
The present invention may be implemented as a computer readable storage medium having stored thereon a computer program which, when executed by a processor, causes steps of a method of an embodiment of the present invention to be performed. In one embodiment, the computer program is distributed over a plurality of computer devices or processors coupled by a network such that the computer program is stored, accessed, and executed by one or more computer devices or processors in a distributed fashion. A single method step/operation, or two or more method steps/operations, may be performed by a single computer device or processor, or by two or more computer devices or processors. One or more method steps/operations may be performed by one or more computer devices or processors, and one or more other method steps/operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step/operation or two or more method steps/operations.
Those of ordinary skill in the art will appreciate that the method steps of the present invention may be implemented by a computer program, which may be stored on a non-transitory computer readable storage medium, to instruct related hardware such as a computer device or a processor, which when executed causes the steps of the present invention to be performed. Any reference herein to memory, storage, database, or other medium may include non-volatile and/or volatile memory, as the case may be. Examples of nonvolatile memory include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), flash memory, magnetic tape, floppy disk, magneto-optical data storage, hard disk, solid state disk, and the like. Examples of volatile memory include Random Access Memory (RAM), external cache memory, and the like.
The method and the device have the advantages that the maximum visible range of each preset geofence range and the maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the flight task are obtained, the first flight task is re-planned into the preset geofences according to the space relation between each preset geofence and each waypoint coordinate in the flight task according to the nearby principle, the first flight task is re-split according to the preset geofence range to form the second flight task, and the re-planned second flight task is distributed to the unmanned aerial vehicle equipped in each preset geofence range according to the designated flight mode to execute the flight task.
The technical features described above may be arbitrarily combined. Although not all possible combinations of features are described, any combination of features should be considered to be covered by the description provided that such combinations are not inconsistent.
The above-described embodiments of the present invention do not limit the scope of the present invention. Any other corresponding changes and modifications made in accordance with the technical idea of the present invention shall be included in the scope of the claims of the present invention.
Claims (7)
1. An unmanned aerial vehicle flight mission intelligent planning method is characterized by comprising the following steps:
S100, acquiring each preset geofence range and a maximum visible range of the unmanned aerial vehicle when flying along the boundary of each preset geofence;
s200, acquiring each waypoint coordinate in a first flight task of the unmanned aerial vehicle, and re-planning the waypoint coordinates which are not located in any one preset geofence range into each preset geofence range according to a nearby rule according to the position relation of each waypoint coordinate, each preset geofence range and the maximum visible range corresponding to each preset geofence range;
S300, splitting a first flight task according to a preset geofence range, and respectively distributing a second flight task formed by all waypoint coordinates in each preset geofence range to unmanned aerial vehicles equipped with each preset geofence;
The re-planning the waypoint coordinates which are not in any preset geofence range to each preset geofence range according to the nearby rule comprises the following steps:
sequentially judging whether the waypoint coordinates in the range of two preset geofences exist or not, judging whether the waypoint coordinates which are not in any preset geofences are not in the range of any preset geofences according to the nearby rule according to the judging result, and re-planning the waypoint coordinates to the range of the preset geofences which are closest to the nearby rule;
And judging whether the waypoint coordinates which are not located in any preset geofence range according to the nearby rule are re-planned to be in the preset geofence range closest to the nearby rule according to the judging result, wherein the method comprises the following steps of:
if the waypoint coordinates in the two preset geofence ranges do not exist, the waypoint coordinates which are not in any preset geofence range are re-planned to be in the preset geofence range closest to the waypoint coordinates according to the nearby rule;
If the waypoint coordinates exist in the two preset geofences, respectively classifying the waypoint coordinates into the two preset geofences, respectively calculating the distance of a second flight task formed by all the waypoints in the two preset geofences, and re-planning the waypoint coordinates into the preset geofences corresponding to the shorter distance;
Re-planning the waypoint coordinates which are not positioned in any one preset geofence range into each preset geofence range according to the nearby rule according to the position relation of the waypoint coordinates and each preset geofence range and the maximum visible range corresponding to each preset geofence range, wherein the re-planning comprises the following steps:
And marking the waypoint coordinates which are positioned in any maximum visible range but are not positioned in a preset geofence range corresponding to the maximum visible range as target waypoint coordinates, making a vertical line to the edge of the preset geofence closest to the target waypoint coordinates by the target waypoint coordinates, and moving the target waypoint coordinates along the vertical line to the inside of the preset geofence by a first preset distance to finish the re-planning.
2. The method for intelligent planning of unmanned aerial vehicle flight mission according to claim 1, wherein the splitting the first flight mission according to the preset geofence range, and allocating the second flight mission formed by all waypoint coordinates in each preset geofence range to the unmanned aerial vehicle equipped with each preset geofence respectively comprises:
Judging whether all the waypoint coordinates after the re-planning are positioned in the same preset geofence range, judging whether to acquire a selection signal of a flight task dispatch mode input by a user according to a judgment result, judging whether to allocate a second flight task formed by all the waypoint coordinates in each preset geofence range to an unmanned aerial vehicle equipped with each preset geofence according to the selection signal of the flight task dispatch mode input by the user.
3. The method for intelligent planning of unmanned aerial vehicle flight mission according to claim 2, wherein the step of determining whether all the re-planned waypoint coordinates are within the same preset geofence range, and determining whether to obtain the selection signal of the flight mission dispatch mode input by the user according to the determination result, further comprises:
If all the re-planned waypoint coordinates are not in the same preset geofence range, acquiring a selection signal of a flight task dispatch mode input by a user;
If all the waypoint coordinates after the re-planning are located in the same preset geofence range, a selection signal of a flight task dispatch mode input by a user is not acquired, and a second flight task formed by all the waypoint coordinates in the preset geofence range is directly dispatched to the unmanned aerial vehicle equipped with the preset geofence.
4. The intelligent planning method for unmanned aerial vehicle flight mission according to claim 2, wherein the flight mission dispatch modes include a first preset flight mission dispatch mode and a second preset flight mission dispatch mode, the determining whether to allocate the second flight mission formed by all waypoint coordinates within each preset geofence range to the unmanned aerial vehicle equipped with each preset geofence according to the selection signal of the flight mission dispatch mode input by the user comprises:
And if the selection signal of the flight task dispatch mode input by the user is the selection signal of the first preset flight task dispatch mode, distributing the second flight task formed by all the waypoint coordinates in the range of each preset geofence to the unmanned aerial vehicle equipped with each preset geofence.
5. The intelligent planning method for unmanned aerial vehicle flight mission according to claim 4, wherein the determining whether to assign the second flight mission formed by all waypoint coordinates within the range of each preset geofence to the unmanned aerial vehicle equipped with each preset geofence according to the selection signal of the flight mission dispatch mode input by the user, further comprises:
if the selection signal of the flight task dispatch mode input by the user is the selection signal of a second preset flight task dispatch mode, the second flight tasks formed by all the waypoint coordinates in the range of each preset geofence are sequentially distributed to the unmanned aerial vehicle equipped with each preset geofence according to the sequence of each preset geofence according to the route flight route corresponding to the first flight task by the unmanned aerial vehicle and the preset rules, wherein the preset rules comprise:
After the unmanned aerial vehicle corresponding to the last preset geofence range completes the second flight task, the next second flight task is distributed to the unmanned aerial vehicle equipped with the next preset geofence.
6. An intelligent unmanned aerial vehicle flight mission planning system, characterized in that an intelligent unmanned aerial vehicle flight mission planning method according to any one of claims 1 to 5 is adopted, and the system comprises:
the acquisition module is used for acquiring the maximum visible range of each preset geofence range and the unmanned aerial vehicle when flying along the boundary of each preset geofence and each waypoint coordinate in the first flight task of the unmanned aerial vehicle;
The control module is used for re-planning the waypoint coordinates which are not positioned in any one preset geofence range into each preset geofence range according to the position relation between the waypoint coordinates and each preset geofence range and the maximum visible range corresponding to each preset geofence range, splitting the first flight tasks according to the preset geofence range, and respectively distributing the second flight tasks formed by all the waypoint coordinates in each preset geofence range to the unmanned aerial vehicle equipped with each preset geofence.
7. An electronic device, comprising:
A memory; and a processor having stored thereon computer readable instructions which when executed by the processor implement the unmanned aerial vehicle flight mission intelligent planning method of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410524044.8A CN118092479B (en) | 2024-04-29 | 2024-04-29 | Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202410524044.8A CN118092479B (en) | 2024-04-29 | 2024-04-29 | Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN118092479A CN118092479A (en) | 2024-05-28 |
| CN118092479B true CN118092479B (en) | 2024-07-23 |
Family
ID=91151029
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202410524044.8A Active CN118092479B (en) | 2024-04-29 | 2024-04-29 | Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN118092479B (en) |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117519250A (en) * | 2023-12-07 | 2024-02-06 | 青岛云世纪信息科技有限公司 | Unmanned aerial vehicle automatic obstacle avoidance method and system and electronic equipment |
| CN117707191A (en) * | 2023-10-10 | 2024-03-15 | 雷达新能源汽车(浙江)有限公司 | Unmanned aerial vehicle wheel flight control method, device, equipment and storage medium |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108287558A (en) * | 2017-12-29 | 2018-07-17 | 易瓦特科技股份公司 | The method and device that unmanned plane is controlled based on target area |
| JP7415881B2 (en) * | 2020-11-11 | 2024-01-17 | トヨタ自動車株式会社 | Control device, unmanned aerial vehicle, and method |
-
2024
- 2024-04-29 CN CN202410524044.8A patent/CN118092479B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117707191A (en) * | 2023-10-10 | 2024-03-15 | 雷达新能源汽车(浙江)有限公司 | Unmanned aerial vehicle wheel flight control method, device, equipment and storage medium |
| CN117519250A (en) * | 2023-12-07 | 2024-02-06 | 青岛云世纪信息科技有限公司 | Unmanned aerial vehicle automatic obstacle avoidance method and system and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN118092479A (en) | 2024-05-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111656424B (en) | Automatic flying unmanned aerial vehicle system based on big data and automatic flying method thereof | |
| CN111006671B (en) | Intelligent route planning method for refined routing inspection of power transmission line | |
| EP2749984B1 (en) | System and method for collaboratively controlling at least two aircraft | |
| US11393347B2 (en) | Cellular aerial vehicle traffic control system and method | |
| EP3657474B1 (en) | Aerial vehicle terrain awareness display | |
| US9245449B1 (en) | Constraint processing as an alternative to flight management systems | |
| EP3470786B1 (en) | A computer-implemented method and a system for generating a 3d path to a landing location for an aerial vehicle | |
| CN110606071A (en) | Parking method, parking device, vehicle and storage medium | |
| CN106774421B (en) | Unmanned aerial vehicle trajectory planning system | |
| CN104537895A (en) | Method and device for achieving 4D track flight | |
| CN105825719A (en) | Generation method and apparatus of unmanned plane inspection route | |
| CN110244765B (en) | Aircraft route track generation method and device, unmanned aerial vehicle and storage medium | |
| US20200174503A1 (en) | Database of drone flight plans for aircraft inspection using relative mapping | |
| US20190287412A1 (en) | Pairing aircraft during flight | |
| CN112148009A (en) | AGV cluster scheduling method and device, electronic equipment and computer readable storage medium | |
| CN118092479B (en) | Unmanned aerial vehicle flight mission intelligent planning method and system and electronic equipment | |
| KR102529949B1 (en) | Method and system for visualizing changable 3D flight paths | |
| US20080154491A1 (en) | Method for selective filtering of an aircraft flight plan according to the operational needs | |
| KR20190004983A (en) | Method and apparatus for providing digital moving map service for safe navigation of unmanned aerial vehicle | |
| JP2020184316A (en) | Navigation performance in urban air vehicle | |
| JP7239744B2 (en) | Information processing system | |
| CN117608302A (en) | Automatic routing inspection path planning method, device, equipment and storage medium | |
| CN116594426A (en) | Substation unmanned aerial vehicle routing planning method and system | |
| CN112631338B (en) | Air route planning method and device, computer equipment and storage medium | |
| CN116520871A (en) | Automatic route planning method based on man-machine cooperation |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |