CN113625770B - Autonomous navigation planning method and device for carrying out inspection on photovoltaic power station based on flying unmanned aerial vehicle - Google Patents
Autonomous navigation planning method and device for carrying out inspection on photovoltaic power station based on flying unmanned aerial vehicle Download PDFInfo
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Abstract
The embodiment of the application discloses an autonomous navigation planning method, device, equipment and storage medium for carrying out inspection on a photovoltaic power station based on a flying unmanned aerial vehicle, and belongs to the technical field of unmanned aerial vehicle navigation planning.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicle navigation planning, in particular to an autonomous navigation planning method, an autonomous navigation planning device, autonomous navigation planning equipment and a storage medium for carrying out inspection on a photovoltaic power station based on a flying unmanned aerial vehicle.
Background
The unmanned aerial vehicle finds the optimal path in the process of reaching the target point, and the traditional unmanned aerial vehicle path planning is to consider the unmanned aerial vehicle as a particle for analysis; the route planning of the unmanned aerial vehicle usually only selects the route with fewer obstacles as the final route, but the limitation of electric quantity and flight time is ignored, so that the unmanned aerial vehicle is subjected to autonomous route planning in the prior art, and the problem that an autonomous route planning method is not scientific enough is solved due to the lack of condition factors.
Disclosure of Invention
The embodiment of the application aims to provide an autonomous navigation planning method, an autonomous navigation planning device, autonomous navigation planning equipment and a storage medium for carrying out inspection on a photovoltaic power station based on a flying unmanned aerial vehicle so as to solve the technical problems.
In order to solve the technical problems, the embodiment of the application provides an autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle, which adopts the following technical scheme:
The invention provides an autonomous navigation planning method for carrying out inspection on a photovoltaic power station based on a flying unmanned aerial vehicle, which is characterized by comprising the following steps:
constructing a three-dimensional map library based on a multi-target photovoltaic power station to be patrolled and examined, and acquiring a three-dimensional environment global map from the three-dimensional map library to serve as a first three-dimensional map;
The first three-dimensional map is sent to a preset analysis model to carry out three-dimensional environment analysis, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies;
Determining the distinguishing numbers of the unit bodies respectively corresponding to the multi-target photovoltaic power stations to be inspected, and using the distinguishing number information to represent the photovoltaic power stations to be inspected corresponding to the multi-target photovoltaic power stations to be inspected;
Determining flight starting position information of the inspection flying unmanned aerial vehicle, expressing the flight starting position information by A 0,0,0, respectively taking the multi-target photovoltaic power stations to be inspected as flight terminals, constructing an artificial potential field algorithm, and carrying out autonomous route planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, wherein the attractive force potential force from the inspection flying unmanned aerial vehicle to the flight terminals is as follows: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number of the obstacles, L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ], L has a distinguishing identification function on each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance between the inspection flying unmanned aerial vehicle and each obstacle is p rl when the inspection flying unmanned aerial vehicle flies, the distance between the inspection flying unmanned aerial vehicle and the flying end point is p rw, the Euclidean distance between the inspection flying unmanned aerial vehicle and each obstacle is p rl, and the Euclidean distance between the inspection flying unmanned aerial vehicle and the end point is p rw||,k3, which is the approaching minimum distance between the inspection flying unmanned aerial vehicle and each obstacle; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, k 1 and k 2 are both greater than 0;
and constructing an electric quantity screening mathematical model, after the inspection flying unmanned aerial vehicle performs autonomous route planning, performing electric quantity suitable screening on the planned autonomous route, and screening out the planned autonomous route as a final inspection autonomous route of the inspection flying vehicle under a preset electric quantity suitable condition.
Further, the sending the first stereo map to a preset analysis model for stereo environment analysis, where the preset analysis model includes at least:
Analyzing mountain lands, trees, buildings and multi-target photovoltaic power stations to be inspected in the first three-dimensional map, determining spatial position information of the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected in the first three-dimensional map, and respectively performing fixed-point marking by using four different color point values, wherein the four different color point values are respectively used for representing the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected.
Further, the three-dimensional grid planning is performed on the first three-dimensional map based on the grid method, the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grid with a preset size as the unit body, and the three-dimensional grid planning method further comprises:
after the three-dimensional grid map is divided, carrying out three-dimensional modeling and distinguishing numbering on a plurality of divided unit bodies;
the three-dimensional modeling of the plurality of divided unit bodies comprises the following operations:
Constructing a three-dimensional coordinate system by taking the length, the width and the height of the regular hexagonal grid as coordinate units of the three-dimensional coordinate system respectively, and determining three-dimensional coordinate (x, y, z) information of each unit body in the three-dimensional coordinate system;
the distinguishing numbering of the plurality of divided unit bodies comprises the following operations:
Carrying out first numbering on the plurality of unit bodies along the positive direction of the x axis of the three-dimensional coordinate system, and using I for representing, wherein I is a positive integer, the value range of I is [1, I ], and I represents the number of the unit bodies on the x axis under the condition of the same y value and the same z value;
Carrying out second numbering on the plurality of unit bodies along the positive direction of the y axis of the three-dimensional coordinate system, and using J to represent the unit bodies, wherein J is a positive integer, the value range of J is [1, J ], and J represents the number of the unit bodies on the y axis under the condition of the same x value and the same z value;
carrying out third numbering on the plurality of unit bodies along the positive direction of the z axis of the three-dimensional coordinate system, and using K for representing, wherein K is a positive integer, the value range of K is [1, K ], and K represents the number of the unit bodies on the z axis under the condition of the same x value and the same y value;
after the first number, the second number and the third number are finished, using A i,j,k as a distinguishing number among the unit bodies, and distinguishing and identifying the unit bodies.
Further, the autonomous route planning is performed on the inspection flying unmanned aerial vehicle based on the manual potential field algorithm, and the method specifically comprises the following operations:
determining the number L of the passed obstacles from a flight starting position to the flight ending position of the inspection flying unmanned aerial vehicle based on the manual potential field algorithm, marking the unit bodies where the passed obstacles are positioned respectively, and obtaining the distinguishing number information of the unit bodies corresponding to the passed obstacles respectively;
based on a preset screening model, when the number L of the passing obstacles is selected to be the minimum value, determining a planned path of the inspection flying unmanned aerial vehicle from a flight starting position to the flight ending point, and taking the planned path as a first standby selected main route of the flying unmanned aerial vehicle;
if the number L of the passing obstacles in the primary standby selected main route is the same, acquiring the number of passing obstacle-free unit bodies based on the distinguishing number information of the unit bodies corresponding to the passing obstacles respectively, and selecting a path when the number of passing obstacle-free unit bodies is the minimum value as a secondary standby selected main route of the flying unmanned aerial vehicle;
And if a plurality of secondary standby selected main routes exist, acquiring paths corresponding to the fact that the artificial combined force from the inspection flying unmanned aerial vehicle to the flying end point is the minimum value, and taking the paths as the tertiary standby selected main routes.
Further, the obstacle includes:
the multi-target photovoltaic power station for the inspection flying unmanned aerial vehicle passes through mountainous regions, trees, buildings and to be inspected in the flying process.
Further, the electric quantity screening mathematical model includes:
calculating a first reference time T 1 according to a preset flight time algorithm; presetting a flight time algorithm formula: wherein S represents the actual flight distance of the patrol flight unmanned aerial vehicle from the flight starting position to the flight end point,/> The average speed of the patrol flight unmanned aerial vehicle from the flight starting position to the flight ending point is represented, T 0 represents the time consumption of the patrol flight unmanned aerial vehicle when the patrol flight unmanned aerial vehicle works, and T 0 is more than or equal to 0;
Calculating a second reference time T 2 according to a power supply discharge time algorithm of a preset flying unmanned aerial vehicle; presetting a power supply discharge time algorithm formula of the flying unmanned aerial vehicle: Wherein Q 1 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the flying process, ζ 1 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the flying process in unit time, Q 2 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the operating process, ζ 2 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the operating process in unit time, and q=q 1+q2, Q represents the total electric energy storage capacity of the inspection flying unmanned aerial vehicle;
and comparing the calculated result of the power supply discharge time algorithm of the preset flying unmanned aerial vehicle with the calculated result of the power supply discharge time algorithm of the preset flying unmanned aerial vehicle, and taking the screened autonomous route as the final inspection autonomous route of the inspection aircraft if T 2≥T1.
Further, if T 2≥T1, the step of taking the screened autonomous route as the final inspection autonomous route of the inspection aircraft includes the following steps:
Screening the three-time standby selected main route based on the electric quantity screening mathematical model, and taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft if the three-time standby selected main route has an autonomous route meeting the screening conditions;
If the three-standby selected main route does not have an autonomous route meeting the screening conditions, screening the secondary standby selected main route based on the electric quantity screening mathematical model, and if the secondary standby selected main route has an autonomous route meeting the screening conditions, taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft;
and if the autonomous air line meeting the screening conditions exists in the primary air line, the primary air line is screened based on the electric quantity screening mathematical model, and if the autonomous air line meeting the screening conditions exists in the primary air line, the screened autonomous air line is used as the final inspection autonomous air line of the inspection aircraft.
Furthermore, the invention also provides an autonomous navigation planning device for inspecting the photovoltaic power station based on the flying unmanned aerial vehicle, which comprises the following steps:
The three-dimensional map construction module is used for constructing a three-dimensional map library based on the multi-target photovoltaic power station to be inspected, and acquiring a three-dimensional environment global map from the three-dimensional map library to serve as a first three-dimensional map; the first three-dimensional map is sent to a preset analysis model to carry out three-dimensional environment analysis, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies;
The photovoltaic power station position determining module is used for determining the distinguishing numbers of the unit bodies corresponding to the multi-target photovoltaic power stations to be inspected respectively, and representing the photovoltaic power stations to be inspected corresponding to the multi-target photovoltaic power stations to be inspected one by using the distinguishing number information;
the autonomous course simulation planning module is used for determining flight starting position information of the inspection flying unmanned aerial vehicle, representing the flight starting position information by A 0,0,0, respectively taking the multi-target photovoltaic power stations to be inspected as flight terminals, constructing an artificial potential field algorithm, and carrying out autonomous course planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, wherein the gravitation and potential force from the inspection flying unmanned aerial vehicle to the flight terminals are as follows: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ] and plays a role in distinguishing and identifying each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance of the inspection flying unmanned aerial vehicle relative to each obstacle in the flying process is p rl, the distance of the inspection flying unmanned aerial vehicle relative to the flying end point is p rw, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to each obstacle is p rl, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to the end point is p rw||,k3, and the size of the inspection flying unmanned aerial vehicle is determined by the shape and size of the mountain, the tree, the building and the multi-target photovoltaic power station to be inspected, which are analyzed by the environment; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, k 1 and k 2 are both greater than 0;
And the constraint model construction module is used for constructing an electric quantity screening mathematical model, carrying out electric quantity suitable screening on the planned autonomous route after the inspection flying unmanned aerial vehicle completes autonomous route planning, and screening out the planned autonomous route as a final inspection autonomous route of the inspection flying vehicle under the preset electric quantity suitable condition.
In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical schemes:
The computer equipment comprises a memory and a processor, wherein the memory stores a computer program, and the processor realizes the steps of the autonomous navigation planning method for inspecting the photovoltaic power station based on the unmanned aerial vehicle when executing the computer program.
In order to solve the above technical problems, an embodiment of the present application further provides a non-volatile computer readable storage medium, which adopts the following technical scheme:
A non-volatile computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of an autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to an embodiment of the present application.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
The embodiment of the application discloses an autonomous navigation planning method, device, equipment and storage medium for carrying out inspection on a photovoltaic power station based on a flying unmanned aerial vehicle.
Drawings
In order to more clearly illustrate the solution of the present application, a brief description will be given below of the drawings required for the description of the embodiments of the present application, it being apparent that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without the exercise of inventive effort for a person of ordinary skill in the art.
FIG. 1 is a diagram of an exemplary system architecture in which embodiments of the present application may be applied;
FIG. 2 is a flow chart of one embodiment of an autonomous navigational planning method for routing inspection of a photovoltaic power plant based on a flying drone in accordance with embodiments of the present application;
FIG. 3 is a logic flow diagram of an autonomous navigation planning method for inspecting a photovoltaic power plant based on a flying unmanned aerial vehicle according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an embodiment of an autonomous navigation planning device for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to the embodiment of the present application;
FIG. 5 is a schematic structural diagram of a constraint model building module according to an embodiment of the present application;
Fig. 6 is a schematic structural view of an embodiment of a computer device in an embodiment of the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
In order to make the person skilled in the art better understand the solution of the present application, the technical solution of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.
It should be noted that, the autonomous navigation planning method based on the unmanned aerial vehicle for inspecting the photovoltaic power station provided by the embodiment of the application is generally executed by a server/terminal device, and correspondingly, the autonomous navigation planning device based on the unmanned aerial vehicle for inspecting the photovoltaic power station is generally arranged in the server/terminal device.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to fig. 2, a flowchart of an embodiment of an autonomous navigation planning method for inspecting a photovoltaic power station based on a flying drone of the present application is shown, where the autonomous navigation planning method for inspecting a photovoltaic power station based on a flying drone includes the following steps:
Step 201, a three-dimensional map library is built based on a multi-target photovoltaic power station to be patrolled and examined, and a three-dimensional environment global map is obtained from the three-dimensional map library and is used as a first three-dimensional map.
Step 202, the first three-dimensional map is sent to a preset analysis model, three-dimensional environment analysis is carried out, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies.
In an embodiment of the present application, the sending the first stereo map to a preset analysis model to perform stereo environment analysis, where the preset analysis model includes at least:
Analyzing mountain lands, trees, buildings and multi-target photovoltaic power stations to be inspected in the first three-dimensional map, determining spatial position information of the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected in the first three-dimensional map, and respectively performing fixed-point marking by using four different color point values, wherein the four different color point values are respectively used for representing the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected.
In the embodiment of the present application, the grid planning is performed on the first stereoscopic map based on the grid method, and the first stereoscopic map is divided into stereoscopic grid maps composed of a plurality of unit bodies by taking a regular hexagonal grid with a preset size as a unit body, and the method further includes: after the three-dimensional grid map is divided, three-dimensional modeling and distinguishing numbering are carried out on a plurality of divided unit bodies, and the three-dimensional modeling is carried out on the plurality of divided unit bodies, and the three-dimensional modeling method specifically comprises the following operations: constructing a three-dimensional coordinate system by taking the length, the width and the height of the regular hexagonal grid as coordinate units of the three-dimensional coordinate system respectively, and determining three-dimensional coordinate (x, y, z) information of each unit body in the three-dimensional coordinate system;
The distinguishing numbering of the plurality of divided unit bodies comprises the following operations: carrying out first numbering on the plurality of unit bodies along the positive direction of the x axis of the three-dimensional coordinate system, and using I for representing, wherein I is a positive integer, the value range of I is [1, I ], and I represents the number of the unit bodies on the x axis under the condition of the same y value and the same z value; carrying out second numbering on the plurality of unit bodies along the positive direction of the y axis of the three-dimensional coordinate system, and using J to represent the unit bodies, wherein J is a positive integer, the value range of J is [1, J ], and J represents the number of the unit bodies on the y axis under the condition of the same x value and the same z value; carrying out third numbering on the plurality of unit bodies along the positive direction of the z axis of the three-dimensional coordinate system, and using K for representing, wherein K is a positive integer, the value range of K is [1, K ], and K represents the number of the unit bodies on the z axis under the condition of the same x value and the same y value; after the first number, the second number and the third number are finished, using A i,j,k as a distinguishing number among the unit bodies, and distinguishing and identifying the unit bodies.
And 203, determining the distinguishing numbers of the unit bodies respectively corresponding to the multi-target photovoltaic power stations to be inspected, and representing the photovoltaic power stations to be inspected corresponding to the distinguishing numbers by using the distinguishing number information.
Step 204, determining flight starting position information of the inspection flying unmanned aerial vehicle, and representing the flight starting position information by using an A 0,0,0, respectively using the multi-target photovoltaic power stations to be inspected as flight terminals, constructing an artificial potential field algorithm, and carrying out autonomous route planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, wherein the gravitation potential force from the inspection flying unmanned aerial vehicle to the flight terminals is as follows: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ] and plays a role in distinguishing and identifying each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance of the inspection flying unmanned aerial vehicle relative to each obstacle in the flying process is p rl, the distance of the inspection flying unmanned aerial vehicle relative to the flying end point is p rw, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to each obstacle is p rl, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to the end point is p rw||,k3, and the size of the inspection flying unmanned aerial vehicle is determined by the shape and size of the mountain, the tree, the building and the multi-target photovoltaic power station to be inspected, which are analyzed by the environment; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, and k 1 and k 2 are both greater than 0.
In the embodiment of the application, the autonomous route planning is performed on the inspection flying unmanned aerial vehicle based on the manual potential field algorithm, and the method specifically comprises the following operations:
determining the number L of the passed obstacles from a flight starting position to the flight ending position of the inspection flying unmanned aerial vehicle based on the manual potential field algorithm, marking the unit bodies where the passed obstacles are positioned respectively, and obtaining the distinguishing number information of the unit bodies corresponding to the passed obstacles respectively;
selecting a planned path of the patrol flight unmanned aerial vehicle from a flight starting position to the flight ending point when the number L of the passing obstacles is the minimum value based on a preset screening model, and taking the planned path as a first standby selected main route of the flight unmanned aerial vehicle; if the number L of the passing obstacles in the primary standby selected main route is the same, acquiring the number of passing obstacle-free unit bodies based on the distinguishing number information of the unit bodies corresponding to the passing obstacles respectively, and selecting a path when the number of passing obstacle-free unit bodies is the minimum value as a secondary standby selected main route of the flying unmanned aerial vehicle; and if a plurality of secondary standby selected main routes exist, acquiring paths corresponding to the fact that the artificial combined force from the inspection flying unmanned aerial vehicle to the flying end point is the minimum value, and taking the paths as the tertiary standby selected main routes.
In an embodiment of the present application, the obstacle includes: the multi-target photovoltaic power station for the inspection flying unmanned aerial vehicle passes through mountainous regions, trees, buildings and to be inspected in the flying process.
And 205, constructing an electric quantity screening mathematical model, and after the autonomous route planning of the inspection flying unmanned aerial vehicle is completed, carrying out electric quantity suitable screening on the planned autonomous route, wherein the planned autonomous route screened under the preset electric quantity suitable condition is used as the final inspection autonomous route of the inspection flying vehicle.
In the embodiment of the application, the electric quantity screening mathematical model comprises the steps of calculating a first reference time T 1 according to a preset flight time algorithm; presetting a flight time algorithm formula: wherein S represents the actual flight distance of the patrol flight unmanned aerial vehicle from the flight starting position to the flight end point,/> The average speed of the patrol flight unmanned aerial vehicle from the flight starting position to the flight ending point is represented, T 0 represents the time consumption of the patrol flight unmanned aerial vehicle when the patrol flight unmanned aerial vehicle works, and T 0 is more than or equal to 0;
Calculating a second reference time T 2 according to a power supply discharge time algorithm of a preset flying unmanned aerial vehicle; presetting a power supply discharge time algorithm formula of the flying unmanned aerial vehicle: Wherein Q 1 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the flying process, ζ 1 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the flying process in unit time, Q 2 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the operating process, ζ 2 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the operating process in unit time, and q=q 1+q2, Q represents the total electric energy storage capacity of the inspection flying unmanned aerial vehicle; and comparing the calculated result of the power supply discharge time algorithm of the preset flight unmanned aerial vehicle with the calculated result of the power supply discharge time algorithm of the preset flight unmanned aerial vehicle, if T 2≥T1 is carried out, taking the screened autonomous route as the final inspection autonomous route of the inspection unmanned aerial vehicle, otherwise, re-executing the steps 201 to 205 to carry out autonomous route planning on the inspection unmanned aerial vehicle.
In the embodiment of the present application, if T 2≥T1, the step of taking the screened autonomous route as the final routing inspection autonomous route of the routing inspection aircraft includes the following steps: screening the three-time standby selected main route based on the electric quantity screening mathematical model, and taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft if the three-time standby selected main route has an autonomous route meeting the screening conditions; if the three-standby selected main route does not have an autonomous route meeting the screening conditions, screening the secondary standby selected main route based on the electric quantity screening mathematical model, and if the secondary standby selected main route has an autonomous route meeting the screening conditions, taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft; and if the autonomous air line meeting the screening conditions exists in the primary air line, the primary air line is screened based on the electric quantity screening mathematical model, and if the autonomous air line meeting the screening conditions exists in the primary air line, the screened autonomous air line is used as the final inspection autonomous air line of the inspection aircraft.
According to the autonomous navigation planning method for carrying out inspection on the photovoltaic power station based on the flying unmanned aerial vehicle, disclosed by the embodiment of the application, the positions of the multi-target photovoltaic power station can be obtained by constructing the three-dimensional map library and the constraint model, the autonomous route planning is carried out on the flying unmanned aerial vehicle, the number of the flying unmanned aerial vehicle passing through the obstacle, the number of the barrier-free unit bodies, the minimum value of the artificial potential field force, the flight time constraint and the power supply constraint are adopted, the autonomous route planning is carried out on the flying unmanned aerial vehicle based on a circulating mode, and the scientificity and the applicability of the autonomous planning are ensured.
For easy understanding, the following will further describe and exemplify with reference to specific application scenarios, and referring specifically to fig. 3, fig. 3 is a logic flow diagram of an execution of an autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to an embodiment of the present application, specifically as follows:
Constructing a three-dimensional map library based on a multi-target photovoltaic power station to be patrolled and examined, and acquiring a first three-dimensional map; analyzing mountainous regions, trees, buildings and multi-target photovoltaic power stations to be inspected in a first three-dimensional map, respectively marking fixed points by using four different color point values, carrying out three-dimensional grid planning on the first three-dimensional map based on a grid method, carrying out three-dimensional modeling and distinguishing numbering on a plurality of divided unit bodies, determining distinguishing numbers of the unit bodies corresponding to the multi-target photovoltaic power stations to be inspected respectively, and representing the photovoltaic power stations to be inspected corresponding to the multi-target photovoltaic power stations to be inspected one by using distinguishing number information; determining flight starting position information of the inspection flying unmanned aerial vehicle, respectively taking a multi-target photovoltaic power station to be inspected as a flight end point, constructing an artificial potential field algorithm, determining the number of the passing obstacles from the flight starting position to the flight end point, respectively marking the unit bodies where the passing obstacles are located, and obtaining distinguishing number information of the unit bodies corresponding to the passing obstacles respectively; based on a preset screening model, when the number L of the passing obstacles is selected as the minimum value, acquiring a first standby selected main route; if the number L of the passing obstacles in the primary alternative main route is the same, acquiring a secondary alternative main route; if a plurality of secondary backup selected main routes exist, a path corresponding to the condition that the artificial combined force from the inspection flying unmanned aerial vehicle to the flying end point is the minimum is obtained, the path is taken as a tertiary backup selected main route, an electric quantity screening mathematical model is constructed, after the inspection flying unmanned aerial vehicle performs autonomous route planning, electric quantity suitable screening is performed on the planned autonomous route, the planned autonomous route screened under the preset electric quantity suitable condition is taken as a final inspection autonomous route of the inspection flying machine, wherein the screening step comprises the following steps:
Firstly, screening the three-time standby selected main route, and taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft if the three-time standby selected main route has an autonomous route meeting the screening conditions; if the three-standby selected main route does not have an autonomous route meeting the screening conditions, screening the secondary standby selected main route based on the electric quantity screening mathematical model, and if the secondary standby selected main route has an autonomous route meeting the screening conditions, taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft; and if the secondary standby selected main route does not have an autonomous route meeting the screening conditions, screening the primary standby selected main route based on the electric quantity screening mathematical model, and if the primary standby selected main route has an autonomous route meeting the screening conditions, taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft, otherwise, re-executing the inspection flying unmanned aerial vehicle autonomous route planning method.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored in a computer-readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
With further reference to fig. 4, as an implementation of the method shown in fig. 2, the present application provides an embodiment of an autonomous navigation planning apparatus for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 2, and the apparatus may be specifically applied to various electronic devices.
As shown in fig. 4, the autonomous navigation planning device 4 for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to the present embodiment includes: the system comprises a three-dimensional map construction module 401, a photovoltaic power station position determination module 402, an autonomous airline simulation planning module 403 and a constraint model construction module 404. Wherein:
The three-dimensional map construction module 401 is configured to construct a three-dimensional map library based on a multi-target photovoltaic power station to be patrolled and examined, and acquire a three-dimensional environment global map from the three-dimensional map library as a first three-dimensional map; the first three-dimensional map is sent to a preset analysis model to carry out three-dimensional environment analysis, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies;
The photovoltaic power station position determining module 402 is configured to determine a distinguishing number of unit bodies corresponding to the multiple target photovoltaic power stations to be inspected respectively, and characterize the photovoltaic power stations to be inspected corresponding to the distinguishing number information one by one;
The autonomous course simulation planning module 403 is configured to determine flight start position information of the inspection flying unmanned aerial vehicle, and represent the flight start position information with a 0,0,0, construct an artificial potential field algorithm by using the multi-target photovoltaic power stations to be inspected as flight terminals respectively, and perform autonomous course planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, where an attractive force potential from the inspection flying unmanned aerial vehicle to the flight terminals is: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ] and plays a role in distinguishing and identifying each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance of the inspection flying unmanned aerial vehicle relative to each obstacle in the flying process is p rl, the distance of the inspection flying unmanned aerial vehicle relative to the flying end point is p rw, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to each obstacle is p rl, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to the end point is p rw||,k3, and the size of the inspection flying unmanned aerial vehicle is determined by the shape and size of the mountain, the tree, the building and the multi-target photovoltaic power station to be inspected, which are analyzed by the environment; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, k 1 and k 2 are both greater than 0;
and the constraint model construction module 404 is configured to construct an electric quantity screening mathematical model, perform electric quantity suitable screening on the planned autonomous course after the inspection flying unmanned aerial vehicle performs autonomous course planning, and screen the planned autonomous course as a final inspection autonomous course of the inspection flying machine under a preset electric quantity suitable condition.
Referring specifically to fig. 5, fig. 5 is a schematic structural diagram of a constraint model building module according to an embodiment of the present application, where the constraint model building module 404 includes: a time-of-flight constraint unit 404a and a discharge time constraint unit 404b, wherein:
in the embodiment of the present application, the flight time constraint unit 404a in the constraint model building module presets a flight time algorithm formula: S represents the actual flight distance from the flight starting position to the flight ending point of the inspection flight unmanned aerial vehicle, v represents the average flight speed of the inspection flight unmanned aerial vehicle from the flight starting position to the flight ending point, T 0 represents the time consumption of the inspection flight unmanned aerial vehicle when working, and T 0 is more than or equal to 0.
In the embodiment of the present application, the discharging time constraint unit 404b in the constraint model building module presets a power discharging time algorithm formula of the flying unmanned aerial vehicle: Wherein Q 1 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the flying process, ζ 1 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the flying process in unit time, Q 2 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the operating process, ζ 2 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the operating process in unit time, and q=q 1+q2, Q represents the total electric storage capacity of the inspection flying unmanned aerial vehicle.
According to the autonomous navigation planning device for carrying out inspection on the photovoltaic power station based on the flying unmanned aerial vehicle, disclosed by the embodiment of the application, the positions of the multi-target photovoltaic power station are obtained by constructing the three-dimensional map library and the constraint model, the autonomous route planning is carried out on the flying unmanned aerial vehicle, the number of the flying unmanned aerial vehicle passing through the obstacle, the number of the barrier-free unit bodies, the minimum value of the artificial potential field force, the flight time constraint and the power supply constraint are adopted, the autonomous route planning is carried out on the flying unmanned aerial vehicle based on a circulating mode, and the scientificity and the applicability of the autonomous planning are ensured.
In order to solve the above technical problems, the embodiment of the present application further provides a computer device, and referring to fig. 6, fig. 6 is a basic structural block diagram of the computer device according to the present embodiment.
The computer device 6 comprises a memory 6a, a processor 6b, a network interface 6c communicatively connected to each other via a system bus. It should be noted that only a computer device 6 having components 6a-6c is shown in the figures, but it should be understood that not all of the illustrated components need be implemented, and that more or fewer components may alternatively be implemented. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and its hardware includes, but is not limited to, a microprocessor, an Application SPECIFIC INTEGRATED Circuit (ASIC), a Programmable gate array (Field-Programmable GATE ARRAY, FPGA), a digital Processor (DIGITAL SIGNAL Processor, DSP), an embedded device, and the like.
The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The memory 6a includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 6a may be an internal storage unit of the computer device 6, such as a hard disk or a memory of the computer device 6. In other embodiments, the memory 6a may also be an external storage device of the computer device 6, such as a plug-in hard disk, a smart memory card (SMART MEDIA CARD, SMC), a Secure Digital (SD) card, a flash memory card (FLASH CARD) or the like, which are provided on the computer device 6. Of course, the memory 6a may also comprise both an internal memory unit of the computer device 6 and an external memory device. In this embodiment, the memory 6a is generally used for storing an operating system and various application software installed on the computer device 6, for example, a program code of an autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle. Further, the memory 6a may also be used to temporarily store various types of data that have been output or are to be output.
The processor 6b may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 6b is typically used to control the overall operation of the computer device 6. In this embodiment, the processor 6b is configured to execute a program code stored in the memory 6a or process data, for example, a program code of the autonomous navigation planning method based on the inspection of the photovoltaic power plant by the flying unmanned aerial vehicle.
The network interface 6c may comprise a wireless network interface or a wired network interface, which network interface 6c is typically used to establish a communication connection between the computer device 6 and other electronic devices.
The application further provides another embodiment, namely a non-volatile computer readable storage medium, wherein the non-volatile computer readable storage medium stores an autonomous navigation planning program for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle, and the autonomous navigation planning program for inspecting the photovoltaic power station based on the flying unmanned aerial vehicle can be executed by at least one processor, so that the at least one processor executes the steps of the autonomous navigation planning method for inspecting the photovoltaic power station based on the flying unmanned aerial vehicle.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
It is apparent that the above-described embodiments are only some embodiments of the present application, but not all embodiments, and the preferred embodiments of the present application are shown in the drawings, which do not limit the scope of the patent claims. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a thorough and complete understanding of the present disclosure. Although the application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing description, or equivalents may be substituted for elements thereof. All equivalent structures made by the content of the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the scope of the application.
Claims (10)
1. An autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle is characterized by comprising the following steps:
constructing a three-dimensional map library based on a multi-target photovoltaic power station to be patrolled and examined, and acquiring a three-dimensional environment global map from the three-dimensional map library to serve as a first three-dimensional map;
The first three-dimensional map is sent to a preset analysis model to carry out three-dimensional environment analysis, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies;
Determining the distinguishing numbers of the unit bodies respectively corresponding to the multi-target photovoltaic power stations to be inspected, and using the distinguishing number information to represent the photovoltaic power stations to be inspected corresponding to the multi-target photovoltaic power stations to be inspected;
Determining flight starting position information of the inspection flying unmanned aerial vehicle, expressing the flight starting position information by A 0,0,0, respectively taking the multi-target photovoltaic power stations to be inspected as flight terminals, constructing an artificial potential field algorithm, and carrying out autonomous route planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, wherein the attractive force potential force from the inspection flying unmanned aerial vehicle to the flight terminals is as follows: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number of the obstacles, L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ], L has a distinguishing identification function on each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance between the inspection flying unmanned aerial vehicle and each obstacle is p rl when the inspection flying unmanned aerial vehicle flies, the distance between the inspection flying unmanned aerial vehicle and the flying end point is p rw, the Euclidean distance between the inspection flying unmanned aerial vehicle and each obstacle is prl, and the Euclidean distance between the inspection flying unmanned aerial vehicle and the end point is p rw||,k3 which is the accessible minimum distance between the inspection flying unmanned aerial vehicle and each obstacle; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, k 1 and k 2 are both greater than 0;
and constructing an electric quantity screening mathematical model, after the inspection flying unmanned aerial vehicle performs autonomous route planning, performing electric quantity suitable screening on the planned autonomous route, and screening out the planned autonomous route as a final inspection autonomous route of the inspection flying vehicle under a preset electric quantity suitable condition.
2. The autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to claim 1, wherein the sending the first stereoscopic map to a preset analysis model for stereoscopic environment analysis, specifically, the preset analysis model at least comprises:
Analyzing mountain lands, trees, buildings and multi-target photovoltaic power stations to be inspected in the first three-dimensional map, determining spatial position information of the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected in the first three-dimensional map, and respectively performing fixed-point marking by using four different color point values, wherein the four different color point values are respectively used for representing the mountain lands, the trees, the buildings and the multi-target photovoltaic power stations to be inspected.
3. The autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to claim 2, wherein the three-dimensional grid planning is performed on the first three-dimensional map based on a grid method, the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking a regular hexagonal grid with a preset size as a unit body, and the autonomous navigation planning method further comprises:
after the three-dimensional grid map is divided, carrying out three-dimensional modeling and distinguishing numbering on a plurality of divided unit bodies;
the three-dimensional modeling of the plurality of divided unit bodies comprises the following operations:
Constructing a three-dimensional coordinate system by taking the length, the width and the height of the regular hexagonal grid as coordinate units of the three-dimensional coordinate system respectively, and determining three-dimensional coordinate (x, y, z) information of each unit body in the three-dimensional coordinate system;
the distinguishing numbering of the plurality of divided unit bodies comprises the following operations:
Carrying out first numbering on the plurality of unit bodies along the positive direction of the x axis of the three-dimensional coordinate system, and using I for representing, wherein I is a positive integer, the value range of I is [1, I ], and I represents the number of the unit bodies on the x axis under the condition of the same y value and the same z value;
Carrying out second numbering on the plurality of unit bodies along the positive direction of the y axis of the three-dimensional coordinate system, and using J to represent the unit bodies, wherein J is a positive integer, the value range of J is [1, J ], and J represents the number of the unit bodies on the y axis under the condition of the same x value and the same z value;
carrying out third numbering on the plurality of unit bodies along the positive direction of the z axis of the three-dimensional coordinate system, and using K for representing, wherein K is a positive integer, the value range of K is [1, K ], and K represents the number of the unit bodies on the z axis under the condition of the same x value and the same y value;
after the first number, the second number and the third number are finished, using A i,j,k as a distinguishing number among the unit bodies, and distinguishing and identifying the unit bodies.
4. The autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to claim 3, wherein the autonomous route planning for the inspecting flying unmanned aerial vehicle based on the manual potential field algorithm specifically comprises the following operations:
determining the number L of the passed obstacles from a flight starting position to the flight ending position of the inspection flying unmanned aerial vehicle based on the manual potential field algorithm, marking the unit bodies where the passed obstacles are positioned respectively, and obtaining the distinguishing number information of the unit bodies corresponding to the passed obstacles respectively;
based on a preset screening model, when the number L of the passing obstacles is selected to be the minimum value, determining a planned path of the inspection flying unmanned aerial vehicle from a flight starting position to the flight ending point, and taking the planned path as a first standby selected main route of the flying unmanned aerial vehicle;
if the number L of the passing obstacles in the primary standby selected main route is the same, acquiring the number of passing obstacle-free unit bodies based on the distinguishing number information of the unit bodies corresponding to the passing obstacles respectively, and selecting a path when the number of passing obstacle-free unit bodies is the minimum value as a secondary standby selected main route of the flying unmanned aerial vehicle;
And if a plurality of secondary standby selected main routes exist, acquiring paths corresponding to the fact that the artificial combined force from the inspection flying unmanned aerial vehicle to the flying end point is the minimum value, and taking the paths as the tertiary standby selected main routes.
5. The autonomous navigational planning method for routing inspection of a photovoltaic power plant based on a flying drone of any of claims 1 to 4, wherein the obstacle comprises:
the multi-target photovoltaic power station for the inspection flying unmanned aerial vehicle passes through mountainous regions, trees, buildings and to be inspected in the flying process.
6. The autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to claim 5, wherein the electric quantity screening mathematical model comprises:
calculating a first reference time T 1 according to a preset flight time algorithm; presetting a flight time algorithm formula: wherein S represents the actual flight distance of the patrol flight unmanned aerial vehicle from the flight starting position to the flight end point,/> The average speed of the patrol flight unmanned aerial vehicle from the flight starting position to the flight ending point is represented, T 0 represents the time consumption of the patrol flight unmanned aerial vehicle when the patrol flight unmanned aerial vehicle works, and T 0 is more than or equal to 0;
Calculating a second reference time T 2 according to a power supply discharge time algorithm of a preset flying unmanned aerial vehicle; presetting a power supply discharge time algorithm formula of the flying unmanned aerial vehicle: Wherein Q 1 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the flying process, ζ 1 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the flying process in unit time, Q 2 represents the total discharge amount of the power supply of the inspection flying unmanned aerial vehicle in the operating process, ζ 2 represents the discharge coefficient of the power supply of the inspection flying unmanned aerial vehicle in the operating process in unit time, and q=q 1+q2, Q represents the total electric energy storage capacity of the inspection flying unmanned aerial vehicle;
and comparing the calculated result of the power supply discharge time algorithm of the preset flying unmanned aerial vehicle with the calculated result of the power supply discharge time algorithm of the preset flying unmanned aerial vehicle, and taking the screened autonomous route as the final inspection autonomous route of the inspection aircraft if T 2≥T1.
7. The autonomous navigation planning method for inspecting a photovoltaic power station based on a flying unmanned aerial vehicle according to claim 6, wherein if T 2≥T1, the selected autonomous course is used as the final inspection autonomous course of the inspection aircraft, comprising the steps of:
Screening the three-time standby selected main route based on the electric quantity screening mathematical model, and taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft if the three-time standby selected main route has an autonomous route meeting the screening conditions;
If the three-standby selected main route does not have an autonomous route meeting the screening conditions, screening the secondary standby selected main route based on the electric quantity screening mathematical model, and if the secondary standby selected main route has an autonomous route meeting the screening conditions, taking the screened autonomous route as a final inspection autonomous route of the inspection aircraft;
and if the autonomous air line meeting the screening conditions exists in the primary air line, the primary air line is screened based on the electric quantity screening mathematical model, and if the autonomous air line meeting the screening conditions exists in the primary air line, the screened autonomous air line is used as the final inspection autonomous air line of the inspection aircraft.
8. Autonomous navigation planning device based on unmanned aerial vehicle patrols and examines to photovoltaic power plant, its characterized in that includes:
The three-dimensional map construction module is used for constructing a three-dimensional map library based on the multi-target photovoltaic power station to be inspected, and acquiring a three-dimensional environment global map from the three-dimensional map library to serve as a first three-dimensional map; the first three-dimensional map is sent to a preset analysis model to carry out three-dimensional environment analysis, three-dimensional grid planning is carried out on the first three-dimensional map based on a grid method, and the first three-dimensional map is divided into three-dimensional grid maps composed of a plurality of unit bodies by taking regular hexagonal grids with preset sizes as unit bodies;
The photovoltaic power station position determining module is used for determining the distinguishing numbers of the unit bodies corresponding to the multi-target photovoltaic power stations to be inspected respectively, and representing the photovoltaic power stations to be inspected corresponding to the multi-target photovoltaic power stations to be inspected one by using the distinguishing number information;
the autonomous course simulation planning module is used for determining flight starting position information of the inspection flying unmanned aerial vehicle, representing the flight starting position information by A 0,0,0, respectively taking the multi-target photovoltaic power stations to be inspected as flight terminals, constructing an artificial potential field algorithm, and carrying out autonomous course planning on the inspection flying unmanned aerial vehicle based on the artificial potential field algorithm, wherein the gravitation and potential force from the inspection flying unmanned aerial vehicle to the flight terminals are as follows: the repulsive potential when the patrol flying unmanned aerial vehicle passes through each obstacle in the flying end process is as follows: /(I) The manual combined force from the inspection flying unmanned aerial vehicle to the flying end point is as follows: /(I)L is the number information of each obstacle, L is a positive integer, the value range of L is [1, L ] and plays a role in distinguishing and identifying each obstacle passing through in the process from the inspection flying unmanned aerial vehicle to the flying end point, the distance of the inspection flying unmanned aerial vehicle relative to each obstacle in the flying process is p rl, the distance of the inspection flying unmanned aerial vehicle relative to the flying end point is p rw, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to each obstacle is p rl, the Euclidean distance of the inspection flying unmanned aerial vehicle relative to the end point is p rw||,k3, and the size of the inspection flying unmanned aerial vehicle is determined by the shape and size of the mountain, the tree, the building and the multi-target photovoltaic power station to be inspected, which are analyzed by the environment; k 1 is the scaling factor of the attraction potential; k 2 is the scaling factor of the repulsive potential, k 1 and k 2 are both greater than 0;
And the constraint model construction module is used for constructing an electric quantity screening mathematical model, carrying out electric quantity suitable screening on the planned autonomous route after the inspection flying unmanned aerial vehicle completes autonomous route planning, and screening out the planned autonomous route as a final inspection autonomous route of the inspection flying vehicle under the preset electric quantity suitable condition.
9. A computer device comprising a memory and a processor, the memory having stored therein a computer program, the processor, when executing the computer program, implementing the steps of the autonomous navigational planning method for inspection of a photovoltaic power plant based on a flying drone as claimed in any one of claims 1 to 7.
10. A non-transitory computer readable storage medium, characterized in that the non-transitory computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the autonomous navigational planning method for inspection of a photovoltaic power plant based on a flying drone according to any one of claims 1 to 7.
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