CN115793716A - Automatic optimization method and system for unmanned aerial vehicle air route - Google Patents
Automatic optimization method and system for unmanned aerial vehicle air route Download PDFInfo
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Abstract
The invention provides an automatic optimization method and system for a flight path of an unmanned aerial vehicle, and relates to the technical field of flight path optimization. Firstly, acquiring a flight route and related information, converting a photographing point which is not interested in the flight route into a transition point according to a preset rule, and updating the flight route. And then, respectively calculating the distance between each transition point and the surrounding obstacles to obtain the safety threshold corresponding to the transition point. And finally, combining information of two adjacent waypoints before and after the transition point, calculating an optimized distance corresponding to the transition point, comparing the optimized distance with a safety threshold value, obtaining and deleting part of the transition point according to an optimized result, and optimizing the flight route. On one hand, unnecessary photographing points in the original route are converted into transition points, and the operation time of photographing and the like is shortened; on the other hand, by means of a threshold optimization algorithm, waypoints deviating from a straight line in the space are deleted intelligently and safely, so that the flight route is optimized automatically, and the automatic flight efficiency of the unmanned aerial vehicle is improved.
Description
Technical Field
The invention relates to the technical field of route optimization, in particular to a method and a system for automatically optimizing routes of an unmanned aerial vehicle.
Background
Along with the automatic flight of large-scale unmanned aerial vehicle, the unmanned aerial vehicle operation mode has been flown by traditional manual teaching manually operation unmanned aerial vehicle, and after the transition had planned the airline in advance, the unmanned aerial vehicle was flown, let its automatic execution airline. In the process of automatically executing the air route, no one can stop and take a picture at a preset air route point. Through the series of actions, the aim of automatically flying and acquiring data by the unmanned aerial vehicle is finally achieved. Unmanned aerial vehicle automatic flight can solve the problem in the aspect of operating personnel experience is not enough, accurate orbit flight, accurate position are shot etc, is the key process of following robot operation of realizing through unmanned aerial vehicle.
Although unmanned aerial vehicle automated flight can solve many problems, the efficiency of unmanned aerial vehicle automated flight can be greatly reduced if the route design is not reasonable in the process of executing automated route re-flight. The main problems are as follows: during the automatic re-flight route, the unmanned aerial vehicle can stop at each waypoint mechanically to execute corresponding tasks. And if the current waypoints are too many, the unmanned aerial vehicle can not fly a complete route before the electricity is exhausted. In addition, in the flight process, the photographing data of a plurality of invalid waypoints are recorded, and the operator may only be interested in part of key waypoints of the current airline and then obtain the photographing data from the interested waypoints. Therefore, how to automatically optimize the flight route of the unmanned aerial vehicle and enable the unmanned aerial vehicle to quickly execute the shooting task of the interest point is an urgent problem to be solved.
Disclosure of Invention
The invention aims to provide an automatic optimization method and system for a flight line of an unmanned aerial vehicle, which can intelligently delete waypoints deviating from a straight line in a space according to an actual threshold value, automatically optimize a flight line and improve the automatic flight efficiency of the unmanned aerial vehicle.
The embodiment of the invention is realized by the following steps:
in a first aspect, an embodiment of the present application provides a method for automatic route optimization of an unmanned aerial vehicle, including:
acquiring a loaded flight route, and extracting waypoint information and corresponding obstacle information; the navigation points comprise transition points and photographing points;
converting the uninteresting photographing points into transition points according to a preset rule, and updating the flight route;
respectively calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain a safety threshold corresponding to the transition point;
and calculating the optimized distance corresponding to the transition point by combining the information of the two adjacent waypoints before and after the transition point, comparing the optimized distance with the safety threshold value to obtain and optimize the flight path according to the optimized result.
Based on the first aspect, in some embodiments of the present invention, the step of converting the photo points that are not interested into the transition points according to the preset rule and updating the flight path includes:
acquiring and marking the interested photographing points in the waypoint set according to preset photographing point information which is interested by the operating personnel;
and converting the remaining unmarked photographing points in the waypoint set into transition points, and updating the flight route.
Based on the first aspect, in some embodiments of the present invention, the step of calculating the optimized distance corresponding to the transition point by combining information of two waypoints adjacent to the transition point includes:
and calculating the distance of a straight line formed by the transition point and the front and rear adjacent navigation points according to the space coordinates of the transition point and the front and rear adjacent navigation points of the transition point, and obtaining the optimized distance corresponding to the transition point.
Based on the first aspect, in some embodiments of the present invention, the step of comparing the optimized distance with the safety threshold to obtain and optimize the flight path according to the optimization result includes:
if the optimized distance corresponding to the transition point is smaller than the safety threshold, marking the transition point; if the optimized distance corresponding to the transition point is not smaller than the safety threshold, the transition point is not marked;
and deleting the marked transition points to obtain the optimized airplane route.
In a second aspect, an embodiment of the present application provides a system for automatic optimization of routes for unmanned aerial vehicles, which includes:
the information extraction module is used for acquiring the loaded flight route and extracting waypoint information and corresponding obstacle information; the navigation points comprise transition points and photographing points;
the first round of optimization module is used for converting the uninteresting photographing points into transition points according to a preset rule and updating the flight route;
the distance calculation module is used for calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain a safety threshold value corresponding to the transition point;
and the second round optimization module is used for calculating the optimized distance corresponding to the transition point by combining the information of two adjacent waypoints in front of and behind the transition point, comparing the optimized distance with the safety threshold value, and optimizing the flight path according to the optimized result.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory for storing one or more programs; a processor. The one or more programs, when executed by the processor, implement the method as described in any of the first aspects above.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as described in any one of the above first aspects.
Compared with the prior art, the embodiment of the invention has at least the following advantages or beneficial effects:
the embodiment of the application provides a method and a system for automatically optimizing an unmanned aerial vehicle flight path. Wherein the waypoints comprise transition points and photograph points. And then, converting the uninterested photographing points into transition points according to a preset rule, and updating the flight route. Thereby reduce the unnecessary task of shooing, shorten unmanned aerial vehicle and carry out the time of task. And then, respectively calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain the safety threshold corresponding to the transition point. And finally, calculating the optimized distance corresponding to the transition point by combining the information of the two adjacent waypoints in front of and behind the transition point, comparing the optimized distance with the safety threshold value to obtain and delete part of the transition points according to the optimized result, thereby optimizing the flight path and improving the operation efficiency. Overall, the present application optimizes flight paths primarily from two aspects. On one hand, unnecessary shooting tasks are reduced and the time for the unmanned aerial vehicle to execute the tasks is shortened by converting the shooting points which are not interested by operators in the original flight route into transition points; on the other hand, the waypoints deviating from the straight line in the space are deleted intelligently and safely through a threshold optimization algorithm, so that the flight route is optimized automatically, and the automatic flight efficiency of the unmanned aerial vehicle is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used 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 block diagram of steps of an embodiment of a method for automatic optimization of routes for unmanned aerial vehicles according to the present invention;
FIG. 2 is a schematic view of a flight path in an embodiment of a method for automatic optimization of a flight path of an unmanned aerial vehicle according to the present invention;
FIG. 3 is a schematic diagram of route optimization in an embodiment of the method for automatic optimization of routes for unmanned aerial vehicles according to the present invention;
FIG. 4 is a block diagram of the present invention for an automatic optimization system for routes of unmanned aerial vehicles;
fig. 5 is a block diagram of an electronic device according to an embodiment of the present invention.
Icon: 1. a memory; 2. a processor; 3. a communication interface; 11. an information extraction module; 12. a first round optimization module; 13. a distance calculation module; 14. and a second round optimization module.
Detailed description of the preferred embodiments
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, as presented in the figures, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
Examples
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the individual features of the embodiments can be combined with one another without conflict.
Generally, during the execution of an automatic route flight, an unmanned aerial vehicle mainly comprises the following steps:
1. and starting the unmanned aerial vehicle and automatically loading the air route to be executed. The flight path is planned in advance by an operator, and each section of flight path has a certain distance from a barrier so as to ensure the smooth execution of a flight task;
2. and after the unmanned aerial vehicle successfully loads the air route, executing blade action and flying to the first flying point. After the first flying point is executed, flying to the next flying point;
3. and flying to the next waypoint and executing related actions. Wherein, each navigation point which needs to execute corresponding action is divided into a transition point and a photographing point. At the transition point, no one can execute pause and body rotation actions; at the point of shooing, unmanned aerial vehicle then can carry out several actions such as pause, fuselage rotation, cloud platform rotation, shoot to the relevant picture and the data that the storage obtained. After the unmanned aerial vehicle flies to the current waypoint and executes related actions, repeating the steps 2 and 3;
4. and the unmanned aerial vehicle flies to each navigation point and is considered to finish the execution of the current air route after the corresponding action task is executed. And then, the unmanned aerial vehicle automatically executes a return flight command. After the return voyage is finished, the unmanned aerial vehicle stops the blades, so that the whole automatic air route flight and operation are finished.
Afterwards, the operation personnel can read relevant pictures and data from the storage card of unmanned aerial vehicle.
However, sometimes the operator is interested in only part of the key waypoints of the current route, and only needs the photographed data obtained on the part of the key waypoints. Therefore, how to automatically optimize the flight route of the unmanned aerial vehicle and enable the unmanned aerial vehicle to quickly execute the shooting task of the interest point is an urgent problem to be solved.
In view of the above problems, an embodiment of the present application provides a method for automatic route optimization of an unmanned aerial vehicle, and specifically, with reference to fig. 1, the method includes the following steps:
step S1: acquiring a loaded flight route, and extracting waypoint information and corresponding obstacle information; the waypoints include transition points and photograph points.
In the above steps, a schematic view of a flight path of the unmanned aerial vehicle is shown in fig. 2. Because the flight path track of the unmanned aerial vehicle is formed on the three-dimensional space, in order to improve the efficiency of the unmanned aerial vehicle for automatically executing flight path operation, the flight points cannot be deleted at will, so that the problem that the unmanned aerial vehicle touches obstacles in the air flight process to cause explosion is avoided.
Step S2: and converting the uninteresting photographing points into transition points according to a preset rule, and updating the flight path.
In the steps, firstly, the photographing points of interest in the waypoint set are marked according to the preset photographing point information of interest of the operating personnel. And then, converting the remaining unmarked photographing points in the waypoint set into transition points, so as to update the flight route, reduce unnecessary photographing tasks and shorten the time for the unmanned aerial vehicle to execute the tasks.
Specifically, assume that the waypoint set of the original flight path is: [ A1, A2^ A3^ A4^ A5, A6^ A7, A8^ A. Wherein, A2^ A3^ A4^ A6^ A8^ A with the symbol is the original fixed shot point, and the other points are transition points. According to the preset information, the photographing points which are interested by the operator only have A3^ A6^ A8^ A, so that the three points are marked, and the unmarked points A2^ A and A4^ A are converted into transition points, so that the flight route is updated, and a new waypoint set is obtained: [ A1, A2, A3^ A4, A5, A6^ A7, A8^ A. And finishing the first round optimization of the flight route.
And step S3: and respectively calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain the safety threshold corresponding to the transition point.
Illustratively, as shown in fig. 3, assume that the current transition point is A2, around which there are three obstacles, obstacle 1, obstacle 2, and obstacle 3. And calculating the distances from the transition point A2 to the three obstacles according to the space coordinates of each point, wherein the distances from the transition point A2 to the three obstacles are respectively D1, D2 and D3. In order to ensure the safe execution of the navigation task, the shortest distance among the distances of the three obstacles is selected as a safety threshold corresponding to the transition point. Therefore, within the range of the safety threshold value, the unmanned aerial vehicle can not touch the obstacle when executing the route. Equivalently, a spherical safety region which takes the transition point as the circle center and takes the safety threshold value as the radius is obtained, the unmanned aerial vehicle can not touch the barrier when flying within the spherical range, and the flying safety is ensured. Therefore, if the transition point is not on the straight line formed by the two adjacent waypoints before and after the transition point, that is, deviates from the straight line, the transition point can be optimally judged according to the safety threshold corresponding to the transition point so as to judge whether the transition point can be deleted or not. If the deletion can be carried out, the unmanned aerial vehicle can directly fly in a straight line, so that the flying distance is shortened.
And step S4: and calculating the optimized distance corresponding to the transition point by combining the information of the two adjacent waypoints before and after the transition point, comparing the optimized distance with the safety threshold value to obtain and optimize the flight path according to the optimized result.
In the above steps, firstly, according to the spatial coordinates of the transition point and the two waypoints adjacent to the front and the rear of the transition point, the distance between the transition point and a straight line formed by the two waypoints adjacent to the front and the rear is calculated, and the optimized distance corresponding to the transition point is obtained. If the optimized distance corresponding to the transition point is smaller than the safety threshold, marking the transition point; and if the optimized distance corresponding to the transition point is not less than the safety threshold, not marking. And then deleting the marked transition points to complete the second round of optimization to obtain the optimized aircraft route.
For example, referring to fig. 3, assume that the spatial coordinates of the current transition point A2 are (x 2, y2, z 2), the spatial coordinates of the previous waypoint A1 are (x 1, y1, z 1), and the spatial coordinates of the subsequent waypoint A3 are (x 3, y3, z 3). First, the spatial distances between the three points are calculated, respectively. Wherein, the space distance s1 from the current transition point A2 to the waypoint A1 is:
the spatial distance s2 from the current transition point A2 to the waypoint A3 is:
the spatial distance s3 from waypoint A1 to waypoint A3 is:
then, according to the obtained distances s1, s2 and s3, an included angle α between the straight line A1A2 and the straight line A1A3 can be obtained by the cosine law:
then, according to the included angle α, the distance D from the current transition point A2 to the straight line A1A3 can be obtained by the sine theorem, that is, the optimized distance corresponding to the current transition point A2 is:
and finally, judging whether the point can be deleted or not according to the optimized distance and the safety threshold value corresponding to the transition point. If the optimized distance D is smaller than the safety threshold value, the point can be deleted, and the point is marked as B1; if the optimized distance D is not less than the safety threshold, the point cannot be deleted. And then, sequentially carrying out the calculation and judgment on each transition point to obtain points B2, B3.
Based on the same inventive concept, the invention further provides an automatic optimization system for the unmanned aerial vehicle air route, and please refer to fig. 4, wherein fig. 4 is a structural block diagram of the automatic optimization system for the unmanned aerial vehicle air route provided by the embodiment of the application. The system comprises:
the information extraction module 11 is used for acquiring a loaded flight route and extracting waypoint information and corresponding obstacle information; the navigation points comprise transition points and photographing points;
the first round optimization module 12 is used for converting the uninteresting photographing points into transition points according to a preset rule and updating the flight path;
the distance calculation module 13 is used for calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain the safety threshold corresponding to the transition point;
and the second-round optimization module 14 is configured to calculate an optimized distance corresponding to the transition point by combining information of two adjacent waypoints before and after the transition point, compare the optimized distance with the safety threshold, and optimize the flight path according to an optimized result.
Referring to fig. 5, fig. 5 is a block diagram of an electronic device according to an embodiment of the present disclosure. The electronic device comprises a memory 1, a processor 2 and a communication interface 3, wherein the memory 1, the processor 2 and the communication interface 3 are electrically connected with each other directly or indirectly to realize the transmission or interaction of data. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 1 can be used for storing software programs and modules, such as program instructions/modules corresponding to the unmanned aerial vehicle airline automatic optimization system provided in the embodiments of the present application, and the processor 2 executes various functional applications and data processing by executing the software programs and modules stored in the memory 1. The communication interface 3 may be used for communication of signaling or data with other node devices.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made to the present application by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (7)
1. A method for unmanned aerial vehicle course automatic optimization is characterized by comprising the following steps:
acquiring a loaded flight route, and extracting waypoint information and corresponding obstacle information; the waypoints comprise transition points and photographing points;
converting the uninteresting photographing points into transition points according to a preset rule, and updating the flight path;
respectively calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain a safety threshold corresponding to the transition point;
and calculating the optimized distance corresponding to the transition point by combining the information of the two adjacent waypoints before and after the transition point, comparing the optimized distance with the safety threshold value to obtain and optimize the flight path according to the optimized result.
2. The method as claimed in claim 1, wherein the step of converting the uninteresting photographed points to transition points according to a predetermined rule and updating the flight path comprises:
acquiring and marking the interested photographing points in the waypoint set according to preset photographing point information which is interested by the operating personnel;
and converting the remaining unmarked photographing points in the waypoint set into transition points, and updating the flight route.
3. The method as claimed in claim 1, wherein the step of calculating the optimized distance corresponding to the transition point in combination with the information of two waypoints adjacent to each other before and after the transition point comprises:
and calculating the distance of a straight line formed by the transition point and the front and rear adjacent navigation points according to the space coordinates of the transition point and the front and rear adjacent navigation points of the transition point, and obtaining the optimized distance corresponding to the transition point.
4. The method of claim 1, wherein the step of comparing the optimized distance to the safety threshold to obtain and optimize the flight path based on the optimization comprises:
if the optimized distance corresponding to the transition point is smaller than the safety threshold, marking the transition point; if the optimized distance corresponding to the transition point is not smaller than the safety threshold, no mark is made;
and deleting the marked transition points to obtain the optimized airplane route.
5. A be used for unmanned aerial vehicle airline automatic optimization system, its characterized in that includes:
the information extraction module is used for acquiring the loaded flight route and extracting waypoint information and corresponding obstacle information; the waypoints comprise transition points and photographing points;
the first round of optimization module is used for converting the uninteresting photographing points into transition points according to a preset rule and updating the flight route;
the distance calculation module is used for calculating the distance between each transition point and the surrounding obstacles according to the obstacle information based on the updated flight path to obtain a safety threshold value corresponding to the transition point;
and the second round optimization module is used for calculating the optimized distance corresponding to the transition point by combining the information of two adjacent waypoints in front of and behind the transition point, comparing the optimized distance with the safety threshold value, and optimizing the flight path according to the optimized result.
6. An electronic device, comprising:
a memory for storing one or more programs;
a processor;
the one or more programs, when executed by the processor, implement the method for unmanned aerial vehicle route automatic optimization of any of claims 1-4.
7. A computer-readable storage medium, on which a computer program is stored, which computer program, when being executed by a processor, carries out a method for automatic optimization of a course of a drone according to any one of claims 1 to 4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117593916A (en) * | 2023-10-25 | 2024-02-23 | 数字鲸鱼(山东)能源科技有限公司 | Unmanned aerial vehicle route recording and application method with high safety |
| CN117593916B (en) * | 2023-10-25 | 2024-04-12 | 数字鲸鱼(山东)能源科技有限公司 | Unmanned aerial vehicle route recording and application method with high safety |
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| CN115793716B (en) | 2023-05-09 |
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