CN112241182B

CN112241182B - Unmanned aerial vehicle route planning control method and system based on intelligent lamp pole and parking apron

Info

Publication number: CN112241182B
Application number: CN202011512868.1A
Authority: CN
Inventors: 杨海; 吴万兴
Original assignee: Shenzhen Lianhe Intelligent Technology Co ltd
Current assignee: Shenzhen Lianhe Intelligent Technology Co ltd
Priority date: 2020-12-20
Filing date: 2020-12-20
Publication date: 2021-03-16
Anticipated expiration: 2040-12-20
Also published as: CN112241182A

Abstract

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle route planning control method and system based on an intelligent lamp post and an air park. The method and the system can analyze the unmanned aerial vehicle shutdown reservation records so as to determine flight route information of different target unmanned aerial vehicles, so that the power change trend information of the target unmanned aerial vehicles can be analyzed by combining route planning priority sequences and intelligent lamp post monitoring information, and intelligent lamp posts, power monitoring and route planning can be combined. According to the invention, the global scheduling of the unmanned aerial vehicle is realized by combining intelligent lamp post monitoring data, unmanned aerial vehicle electric quantity monitoring and unmanned aerial vehicle route planning, and by analyzing electric quantity monitoring track information, the corresponding shutdown reservation adjustment information of the unmanned aerial vehicle parking apron can be ensured after the safe flight condition is met, and route planning change data can be distributed to the unmanned aerial vehicle to be adjusted according to the shutdown reservation adjustment information, so that the unmanned aerial vehicle to be adjusted is controlled to carry out route change and planning.

Description

Unmanned aerial vehicle route planning control method and system based on intelligent lamp pole and parking apron

Technical Field

The invention relates to the technical field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle route planning control method and system based on an intelligent lamp post and an air park.

Background

Along with the development of unmanned aerial vehicle technique, unmanned aerial vehicle's application is more and more extensive. Nowadays, smart logistics and smart distribution based on unmanned planes are becoming mature. More and more unmanned aerial vehicles shuttle between the urban building, provide a great deal of convenience for people's daily production life.

Along with the development of city wisdom lamp pole, wisdom lamp pole presents multi-functionalization development trend. Be provided with unmanned aerial vehicle air park and corresponding unmanned aerial vehicle charging device on the top of wisdom lamp pole, can park, descend to charge or change the battery for unmanned aerial vehicle so that unmanned aerial vehicle lasts the flight automatically for unmanned aerial vehicle.

However, with the increase of the number of unmanned aerial vehicles, how to realize the takeoff and landing planning of the unmanned aerial vehicle on the smart lamp post is very important. In the correlation technique, can set up the unmanned aerial vehicle air park for unmanned aerial vehicle on the wisdom lamp pole in different areas to supply unmanned aerial vehicle to take off and land. However, it is still difficult to plan the route of the drone, so that it is difficult to globally schedule the drone, and a shutdown takeoff process of the drone apron may be disordered.

Disclosure of Invention

The specification provides an unmanned aerial vehicle route planning control method and system based on an intelligent lamp post and an air park, and aims to solve or partially solve the technical problems.

The specification discloses an unmanned aerial vehicle route planning control method based on a smart lamp post and an air park, which is applied to an unmanned aerial vehicle route planning control center, and the method comprises the following steps:

extracting unmanned aerial vehicle parking reservation records of the unmanned aerial vehicle parking apron; acquiring flight route information of each target unmanned aerial vehicle corresponding to the unmanned aerial vehicle parking apron according to the unmanned aerial vehicle parking reservation record;

acquiring at least two pieces of target flight path information according to the flight path planning priority sequence of each target unmanned aerial vehicle and intelligent lamp post monitoring information corresponding to the unmanned aerial vehicle parking apron to obtain at least two flight path combinations; for any flight route combination, acquiring the electric quantity change trend information of each target unmanned aerial vehicle according to the real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combination;

acquiring an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination to obtain electric quantity monitoring track information of the flight path combination; when the electric quantity monitoring track information of at least two flight route combinations meets the safe flight condition, determining shutdown reservation adjustment information corresponding to the unmanned aerial vehicle parking apron; allocating air route planning change data for the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle parking apron according to the parking reservation adjustment information; wherein the unmanned aerial vehicle to be adjusted is at least one of the target unmanned aerial vehicles.

Optionally, the extracting the unmanned aerial vehicle parking reservation record of the unmanned aerial vehicle parking apron includes:

dividing reservation logs corresponding to the unmanned aerial vehicle apron into at least two first aviation flight log lists, wherein each first aviation flight log list has the same aviation flight time list;

extracting aviation flight characteristic information from each first aviation flight log list by adopting a preset log text analysis thread;

and screening the flight characteristic information of the at least two first flight log lists to obtain the unmanned aerial vehicle shutdown reservation record.

Optionally, the obtaining, according to the unmanned aerial vehicle stop reservation record, flight route information of each target unmanned aerial vehicle corresponding to the unmanned aerial vehicle apron includes:

inputting the unmanned aerial vehicle stop reservation records into a preset stop record splitting model, and outputting flight path information of the take-off and landing tracks corresponding to each target unmanned aerial vehicle in the unmanned aerial vehicle parking apron; the preset shutdown record splitting model is used for an unmanned aerial vehicle shutdown reservation record based on a takeoff and landing track, time-staggered flight information matched with the takeoff and landing time sequence difference information of the takeoff and landing track is detected from shutdown configuration information corresponding to an unmanned aerial vehicle parking apron, and flight route information of the takeoff and landing track corresponding to the time-staggered flight information matched with the takeoff and landing time sequence difference information of the takeoff and landing track in an idle state of the unmanned aerial vehicle parking apron is acquired.

Optionally, the method further comprises:

taking a flight time table for determining that the electric quantity monitoring track information of the at least two flight route combinations meets safe flight conditions as a reference time table, and acquiring a second flight log list of a preset flight time list from a dynamic flight log corresponding to the unmanned aerial vehicle apron;

acquiring aviation journal replacement information of the second aviation journal list;

when the aviation flight log replacement information of the second aviation flight log list triggers aviation flight scheduling information, determining shutdown reservation adjustment information corresponding to the unmanned aerial vehicle parking apron;

wherein the obtaining of the aviation flight log replacement information of the second aviation flight log list includes: dividing the second aviation flight log list into at least two aviation flight text sets, wherein each aviation flight text set has the same aviation flight time list; acquiring event attributes of the aviation flight transmission events corresponding to each aviation flight text set; acquiring a maximum event attribute and a minimum event attribute from the event attributes corresponding to the at least two aviation flight text sets; determining aviation journal replacement information of the second aviation journal list based on the attribute description values of the maximum event attribute and the minimum event attribute;

the second aviation flight log list comprises at least one of a third aviation flight log list and a fourth aviation flight log list, the third aviation flight log list is an aviation flight log list which takes the aviation flight time table as a reference time table, and a preset aviation flight time list behind the aviation flight time table is located in a dynamic aviation flight log corresponding to the unmanned aerial vehicle apron, and the fourth aviation flight log list is an aviation flight log list which takes the aviation flight time table as a reference time table and is located in a preset aviation flight time list in front of the aviation flight time table in the dynamic aviation flight log corresponding to the unmanned aerial vehicle apron.

Optionally, the method includes the steps of obtaining at least two pieces of target flight route information according to the route planning priority order of each target unmanned aerial vehicle and the smart lamp post monitoring information corresponding to the unmanned aerial vehicle parking apron, and obtaining at least two flight route combinations, including:

obtaining each first index weight distribution based on the air route planning index information of each target unmanned aerial vehicle;

obtaining first flight route data respectively corresponding to the first index weight distribution based on a preset first monitoring dimension index list, wherein the first flight route data comprise flight route data of each combination type of a preset flight route combination respectively corresponding to the first index weight distribution;

obtaining each second index weight distribution based on the route planning index information of each target unmanned aerial vehicle, and generating a first weight correlation degree of each second index weight distribution, wherein the first weight correlation degree is generated based on first flight route data corresponding to each first index weight distribution corresponding to the second index weight distribution;

adding each first weight correlation degree to a preset second monitoring dimension index list to obtain each second flight path data corresponding to each second index weight distribution, wherein the second flight path data comprise flight path data of the second index weight distribution corresponding to the preset flight path combination and/or flight path data of the non-corresponding preset flight path combination;

and determining whether the preset flight route combination exists in the route planning index information of each target unmanned aerial vehicle based on the second flight route data, and acquiring at least two pieces of target flight route information of the preset flight route combination to obtain at least two flight route combinations.

Optionally, for any flight route combination, acquiring the electric quantity change trend information of each target unmanned aerial vehicle according to the real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combination, including:

extracting flight attitude dynamic data of each target unmanned aerial vehicle in the flight route combination through a route planning path node corresponding to real-time route planning information of each target unmanned aerial vehicle in the current flight state, identifying current attitude data under each flight attitude dynamic data from flight control equipment running records corresponding to each target unmanned aerial vehicle in the flight route combination through a planning evaluation thread corresponding to the real-time route planning information of each target unmanned aerial vehicle in the current flight state, screening the current attitude data under each flight attitude dynamic data in the flight control equipment running records corresponding to each target unmanned aerial vehicle into a first attitude data packet, and screening attitude data except the first attitude data packet in the flight control equipment running records corresponding to each target unmanned aerial vehicle into a second attitude data packet;

on the premise that an interactive attitude data identifier and a non-interactive attitude data identifier exist in a flight control device operation record corresponding to each target unmanned aerial vehicle based on flight attitude dynamic data, determining an attitude difference coefficient between each second target current attitude data of the second attitude data packet under the non-interactive attitude data identifier and each first target current attitude data of the second attitude data packet under the interactive attitude data identifier according to first target current attitude data under the interactive attitude data identifier in the second attitude data packet and an attitude feature matrix of the first target current attitude data;

distributing second target current attitude data of the second attitude data packet under the non-interactive attitude data identification and the first target current attitude data under the interactive attitude data identification with similarity in attitude difference coefficient to the interactive attitude data identification based on the attitude difference coefficient; wherein, when the non-interactive attitude data identifier corresponding to the second attitude data packet contains a plurality of current attitude data missing from the flight attitude continuity index, determining attitude difference coefficients between the current attitude data of the second attitude data packet which are missing on flight attitude continuity indexes under the non-interactive attitude data identification according to the first target current attitude data of the second attitude data packet under the interactive attitude data identification and the attitude feature matrix of the first target current attitude data, screening the current attitude data with the missing on the flight attitude continuity indexes under the non-interactive attitude data identification according to the attitude difference coefficient between the current attitude data with the missing on the flight attitude continuity indexes; setting an attitude evaluation factor for the screened third target current attitude data according to the first target current attitude data of the second attitude data packet under the interactive attitude data identifier and the attitude feature matrix of the first target current attitude data, and sequentially distributing part of the third target current attitude data under the interactive attitude data identifier based on the magnitude sequence of the attitude evaluation factors;

determining a first ratio value for characterizing a first data volume of current pose data in the first pose data packet, a second ratio value for characterizing a second data volume of current pose data of the second pose data packet under the interactive pose data identification, and a third ratio value for characterizing a third data volume of current pose data of the second pose data packet under the non-interactive pose data identification; calculating a difference value between the first proportion value and the second proportion value, and judging whether the proportion of the third proportion value to the difference value exceeds a target proportion value or not;

when the ratio of the third ratio value to the difference value does not exceed the target ratio value, determining the current attitude data under the non-interactive attitude data identification as static attitude data, and determining the electric quantity change trend information of each target unmanned aerial vehicle according to the static attitude data, the current attitude data in the first attitude data packet and the current attitude data under the interactive attitude data identification.

Optionally, the obtaining an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight route combination to obtain electric quantity monitoring trajectory information of the flight route combination includes:

determining the electric quantity change association list according to trend correlation among electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination;

and extracting list element characteristics in the electric quantity change association list, and obtaining electric quantity monitoring track information of the flight route combination based on the list element characteristics.

Optionally, when the electric quantity monitoring trajectory information of at least two flight route combinations all meets the safe flight condition, determining the stop reservation adjustment information corresponding to the unmanned aerial vehicle air park, including: and when the track fluctuation coefficients corresponding to the electric quantity monitoring track information of at least two flight route combinations are smaller than the set fluctuation coefficient, determining the stop reservation adjustment information according to the stop reservation queue characteristics corresponding to the unmanned aerial vehicle parking apron.

Optionally, the allocating, according to the stop reservation adjustment information, route planning change data for the to-be-adjusted unmanned aerial vehicle corresponding to the unmanned aerial vehicle apron includes:

determining a plurality of adjustment strategies from the halt reservation adjustment information;

determining a route planning influence index corresponding to each adjustment strategy;

selecting a target unmanned aerial vehicle corresponding to the adjustment strategy corresponding to the minimum air route planning influence index as the unmanned aerial vehicle to be adjusted;

and distributing the air route planning change data for the unmanned aerial vehicle to be adjusted according to the air route adjustment instruction and the electric quantity adjustment instruction corresponding to the adjustment strategy.

The specification discloses an unmanned aerial vehicle route planning control system based on a smart lamp post and an air park, which comprises an unmanned aerial vehicle route planning control center and an unmanned aerial vehicle communicated with the unmanned aerial vehicle route planning control center; wherein, unmanned aerial vehicle airline planning control center is used for:

Through one or more technical schemes of this description, this description has following beneficial effect or advantage: the method comprises the steps of obtaining flight route information of each target unmanned aerial vehicle according to an unmanned aerial vehicle parking reservation record of an unmanned aerial vehicle parking apron, obtaining at least two pieces of target flight route information based on a route planning priority sequence of each target unmanned aerial vehicle and smart lamp pole monitoring information corresponding to the unmanned aerial vehicle parking apron to obtain at least two flight route combinations, and obtaining electric quantity change trend information of each target unmanned aerial vehicle according to real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combinations. Further, an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination is obtained to obtain electric quantity monitoring track information of the flight path combination. And determining the corresponding shutdown reservation adjustment information of the unmanned aerial vehicle parking apron when the electric quantity monitoring track information of at least two flight route combinations conforms to the safe flight condition. Therefore, the air route planning change data can be distributed to the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle parking apron according to the parking reservation adjustment information.

In the practical application process, the unmanned aerial vehicle parking reservation record of the unmanned aerial vehicle parking apron can be analyzed, so that flight route information of different target unmanned aerial vehicles is determined, and the electric quantity change trend information of the target unmanned aerial vehicles can be analyzed by combining the route planning priority sequence and the intelligent lamp post monitoring information. So design, can combine together wisdom lamp pole, electric quantity control and air route planning. Further, by analyzing the electric quantity monitoring track information, the corresponding shutdown reservation adjustment information of the unmanned aerial vehicle parking apron can be ensured to be determined after the safe flight condition is met. Therefore, the air route planning and changing data can be distributed to the unmanned aerial vehicle to be adjusted according to the stop reservation adjusting information, and the unmanned aerial vehicle to be adjusted is controlled to change and plan the air route. So design, can combine wisdom lamp pole monitoring data, unmanned aerial vehicle electric quantity control and unmanned aerial vehicle air route planning to realize the global scheduling to unmanned aerial vehicle, avoid the shutdown of unmanned aerial vehicle air park to take off the flow and appear the confusion.

The above description is only an outline of the technical solution of the present specification, and the embodiments of the present specification are described below in order to make the technical means of the present specification more clearly understood, and the present specification and other objects, features, and advantages of the present specification can be more clearly understood.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the specification. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

fig. 1 shows a schematic flow diagram of a method for controlling route planning of an unmanned aerial vehicle based on a smart light pole and an apron according to an embodiment of the present description;

FIG. 2 shows a schematic diagram of an unmanned aerial vehicle route planning control center according to one embodiment of the present description;

fig. 3 shows a schematic architecture diagram of an unmanned aerial vehicle route planning control system based on smart lamp posts and an apron according to an embodiment of the present disclosure.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

The embodiment of the specification provides an unmanned aerial vehicle route planning control method and system based on an intelligent lamp pole and an air park, and aims to solve the technical problems in the background art.

As an alternative embodiment, please refer to fig. 1, which shows a flowchart of a smart lamp post and apron-based unmanned aerial vehicle route planning control method, which can be applied to an unmanned aerial vehicle route planning control center, and which can include the following steps S21-S23.

Step S21, extracting unmanned aerial vehicle parking reservation records of the unmanned aerial vehicle parking apron; and acquiring flight route information of each target unmanned aerial vehicle corresponding to the unmanned aerial vehicle parking apron according to the unmanned aerial vehicle parking reservation record.

In some embodiments, the unmanned aerial vehicle stop reservation record is pre-stored in a database corresponding to the unmanned aerial vehicle route planning control center. The target unmanned aerial vehicle is an unmanned aerial vehicle corresponding to the unmanned aerial vehicle stop reservation record. The flight route information comprises takeoff period information, flight period information, return period information, landing period information and flight path information of the target unmanned aerial vehicle.

Step S22, acquiring at least two pieces of target flight path information according to the path planning priority sequence of each target unmanned aerial vehicle and the intelligent lamp post monitoring information corresponding to the unmanned aerial vehicle parking apron to obtain at least two flight path combinations; and for any flight path combination, acquiring the electric quantity change trend information of each target unmanned aerial vehicle according to the real-time flight path planning information of each target unmanned aerial vehicle in the current flight state in the flight path combination.

In some embodiments, the route planning priority is determined according to a category of the preset flight mission of each target drone. Wisdom lamp pole monitoring information can be environmental monitoring information. Flight path combinations may include overlaps and companion flights between different flight paths. And the real-time air route planning information is determined according to the real-time flight state of the target unmanned aerial vehicle. The electric quantity variation trend information is used for representing the power consumption state of the target unmanned aerial vehicle in flight.

Step S23, acquiring an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination, and acquiring electric quantity monitoring track information of the flight path combination; when the electric quantity monitoring track information of at least two flight route combinations meets the safe flight condition, determining shutdown reservation adjustment information corresponding to the unmanned aerial vehicle parking apron; and distributing air route planning change data for the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle parking apron according to the parking reservation adjustment information.

In some embodiments, the power change association list is used to represent a comparison list of power change trend information between different target drones, and is used to globally monitor the power change trend information of different target drones. The electric quantity monitoring track information is used for representing track information of electric quantity change of the target unmanned aerial vehicle corresponding to the flight line combination, and the track information can reflect a power consumption comparison result and a flight distance comparison result between the target unmanned aerial vehicles corresponding to the flight line combination. The safe flight condition is used for representing that the target unmanned aerial vehicle corresponding to the flight route combination does not have flight accidents when the flight route is switched. And the stop reservation adjustment information is used for carrying out air route adjustment on the unmanned aerial vehicle corresponding to the unmanned aerial vehicle parking apron. The air route planning change data is used for indicating the unmanned aerial vehicle to be adjusted to carry out air route adjustment, and the unmanned aerial vehicle to be adjusted is at least one of the target unmanned aerial vehicles.

It can be understood that, by executing the contents described in the above steps S21-S23, the flight route information of each target unmanned aerial vehicle can be obtained according to the unmanned aerial vehicle parking reservation record of the unmanned aerial vehicle parking apron, and then at least two pieces of target flight route information are obtained based on the route planning priority order of each target unmanned aerial vehicle and the smart light pole monitoring information corresponding to the unmanned aerial vehicle parking apron to obtain at least two flight route combinations, so that the electric quantity change trend information of each target unmanned aerial vehicle can be obtained according to the real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combinations. Further, an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination is obtained to obtain electric quantity monitoring track information of the flight path combination. And determining the corresponding shutdown reservation adjustment information of the unmanned aerial vehicle parking apron when the electric quantity monitoring track information of at least two flight route combinations conforms to the safe flight condition. Therefore, the air route planning change data can be distributed to the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle parking apron according to the parking reservation adjustment information.

In some embodiments, the extracting the unmanned airplane stop reservation recording of the unmanned airplane apron described in step S21 may include the following steps: dividing reservation logs corresponding to the unmanned aerial vehicle apron into at least two first aviation flight log lists, wherein each first aviation flight log list has the same aviation flight time list; extracting aviation flight characteristic information from each first aviation flight log list by adopting a preset log text analysis thread; and screening the flight characteristic information of the at least two first flight log lists to obtain the unmanned aerial vehicle shutdown reservation record. So, can ensure unmanned aerial vehicle and shut down the continuity of reservation record in the chronogenesis.

In some embodiments, in step S21, acquiring flight path information of each target drone corresponding to the drone apron according to the drone parking reservation record, which may exemplarily include the following steps: and inputting the unmanned aerial vehicle parking reservation records into a preset parking record splitting model, and outputting flight route information of the takeoff and landing tracks corresponding to all target unmanned aerial vehicles in the unmanned aerial vehicle parking apron. The preset shutdown record splitting model is used for an unmanned aerial vehicle shutdown reservation record based on a takeoff and landing track, time-staggered flight information matched with the takeoff and landing time sequence difference information of the takeoff and landing track is detected from shutdown configuration information corresponding to an unmanned aerial vehicle parking apron, and flight route information of the takeoff and landing track corresponding to the time-staggered flight information matched with the takeoff and landing time sequence difference information of the takeoff and landing track in an idle state of the unmanned aerial vehicle parking apron is acquired. By the design, the integrity of flight route information can be ensured, so that global scheduling is realized during subsequent route change, and conflict of the route change is avoided.

On the basis of the contents described in the above-described steps S21 to S23, the contents described in the following steps S24 to S26 may be further included.

And step S24, taking the flight time schedule which determines that the electric quantity monitoring track information of the at least two flight route combinations all accord with safe flight conditions as a reference time schedule, and acquiring a second flight log list of a preset flight time list from the dynamic flight log corresponding to the unmanned aerial vehicle apron.

And step S25, acquiring aviation flight log replacement information of the second aviation flight log list.

Step S26, when the aviation flight log replacement information of the second aviation flight log list triggers aviation flight scheduling information, determining shutdown reservation adjustment information corresponding to the unmanned aerial vehicle parking apron.

Therefore, when the aviation flight scheduling information is triggered by the aviation flight log replacement information of the second aviation flight log list, the shutdown reservation adjustment information corresponding to the unmanned aerial vehicle parking apron can be determined, and the shutdown reservation adjustment information can be rapidly determined.

Further, the obtaining of the aviation journal replacement information of the second aviation journal list described in step S25 includes: dividing the second aviation flight log list into at least two aviation flight text sets, wherein each aviation flight text set has the same aviation flight time list; acquiring event attributes of the aviation flight transmission events corresponding to each aviation flight text set; acquiring a maximum event attribute and a minimum event attribute from the event attributes corresponding to the at least two aviation flight text sets; and determining aviation journal replacement information of the second aviation journal list based on the attribute description values of the maximum event attribute and the minimum event attribute.

In the content described in the above step S24 to step S26, the second aviation flight log list includes at least one of a third aviation flight log list and a fourth aviation flight log list, the third aviation flight log list is an aviation flight log list that uses the aviation flight schedule as a reference schedule and is located in a preset aviation flight time list after the aviation flight schedule in the dynamic aviation flight log corresponding to the unmanned aerial vehicle apron, and the fourth aviation flight log list is an aviation flight log list that uses the aviation flight schedule as a reference schedule and is located in a preset aviation flight time list before the aviation flight schedule in the dynamic aviation flight log corresponding to the unmanned aerial vehicle apron.

In one possible example, in order to ensure that no route conflict occurs between flight route combinations, and thus avoid the occurrence of flight accidents, the method described in step S22 obtains at least two pieces of target flight route information according to the route planning priority order of each target unmanned aerial vehicle and the smart lamp post monitoring information corresponding to the unmanned aerial vehicle apron, and obtains at least two flight route combinations, which further includes the contents described in the following steps S221 to S225.

Step S221, obtaining each first index weight distribution based on the air route planning index information of each target unmanned aerial vehicle.

Step S222, obtaining, based on a preset first monitoring dimension index list, first flight path data corresponding to each first index weight distribution, where the first flight path data includes flight path data of each combination category of a preset flight path combination corresponding to the first index weight distribution.

Step S223, obtaining each second index weight distribution based on the route planning index information of each target unmanned aerial vehicle, and generating a first weight correlation degree of each second index weight distribution, where the first weight correlation degree is generated based on first flight route data corresponding to each first index weight distribution corresponding to the second index weight distribution.

Step S224, adding each of the first weight correlations to a preset second monitoring dimension index list, and obtaining each of second flight route data corresponding to each of the second index weight distributions, where the second flight route data includes flight route data corresponding to the preset flight route combination and/or flight route data not corresponding to the preset flight route combination for the second index weight distribution.

Step S225, determining whether the preset flight path combination exists in the path planning index information of each target unmanned aerial vehicle based on the second flight path data, and acquiring at least two pieces of target flight path information of the preset flight path combination to obtain at least two flight path combinations.

When the contents described in the above steps S221 to S225 are applied, analysis of the index weight distribution can be performed based on the route planning index information, so as to determine different flight route data, which can ensure that no flight route conflict occurs between the flight route combinations obtained based on the flight route data, thereby avoiding the occurrence of flight accidents.

In one possible embodiment, the inventor finds that in determining the electric quantity change trend information, the flight attitude data of the unmanned aerial vehicle needs to be considered, so that the influence of different flight attitudes on electric quantity loss is weakened. To achieve this, for any flight route combination, as described in step S22, obtaining the power variation trend information of each target drone according to the real-time route planning information of each target drone in the flight route combination in the current flight state, which may further be implemented as described in the following steps a to e.

Step a, extracting dynamic flight attitude data of each target unmanned aerial vehicle through an air route planning path node corresponding to real-time air route planning information of each target unmanned aerial vehicle in the current flight state in the flight air route combination, identifying current attitude data under the dynamic flight attitude data from flight control equipment running records corresponding to each target unmanned aerial vehicle through a planning evaluation thread corresponding to the real-time air route planning information of each target unmanned aerial vehicle in the current flight state in the flight air route combination, screening the current attitude data under the dynamic flight attitude data in the flight control equipment running records corresponding to each target unmanned aerial vehicle into a first attitude data packet, and screening attitude data except the first attitude data packet in the flight control equipment running records corresponding to each target unmanned aerial vehicle into a second attitude data packet.

And b, on the premise that the interactive attitude data identification and the non-interactive attitude data identification exist in the flight control equipment operation record corresponding to each target unmanned aerial vehicle based on the flight attitude dynamic data, determining attitude difference coefficients between each second target current attitude data of the second attitude data packet under the non-interactive attitude data identification and each first target current attitude data of the second attitude data packet under the interactive attitude data identification according to first target current attitude data under the interactive attitude data identification in the second attitude data packet and an attitude feature matrix of the first target current attitude data.

C, distributing second target current attitude data of the second attitude data packet under the non-interactive attitude data identification and the first target current attitude data under the interactive attitude data identification, which have similarity on the attitude difference coefficient, to the interactive attitude data identification based on the attitude difference coefficient; wherein, when the non-interactive attitude data identifier corresponding to the second attitude data packet contains a plurality of current attitude data missing from the flight attitude continuity index, determining attitude difference coefficients between the current attitude data of the second attitude data packet which are missing on flight attitude continuity indexes under the non-interactive attitude data identification according to the first target current attitude data of the second attitude data packet under the interactive attitude data identification and the attitude feature matrix of the first target current attitude data, screening the current attitude data with the missing on the flight attitude continuity indexes under the non-interactive attitude data identification according to the attitude difference coefficient between the current attitude data with the missing on the flight attitude continuity indexes; setting an attitude evaluation factor for the screened third target current attitude data according to the first target current attitude data of the second attitude data packet under the interactive attitude data identifier and the attitude feature matrix of the first target current attitude data, and sequentially distributing part of the third target current attitude data under the interactive attitude data identifier based on the magnitude sequence of the attitude evaluation factors.

Determining a first proportional value for characterizing a first data capacity of current attitude data in the first attitude data packet, a second proportional value for characterizing a second data capacity of current attitude data of the second attitude data packet under the interactive attitude data identifier, and a third proportional value for characterizing a third data capacity of current attitude data of the second attitude data packet under the non-interactive attitude data identifier; and calculating a difference value between the first proportion value and the second proportion value, and judging whether the proportion of the third proportion value to the difference value exceeds a target proportion value or not.

And e, when the ratio of the third ratio value to the difference value does not exceed the target ratio value, determining the current attitude data under the non-interactive attitude data identification as static attitude data, and determining the electric quantity change trend information of each target unmanned aerial vehicle according to the static attitude data, the current attitude data in the first attitude data packet and the current attitude data under the interactive attitude data identification.

It can be understood that, when the content described in the above steps a to e is implemented, the flight attitude dynamic data of each target unmanned aerial vehicle can be extracted and the current attitude data under each flight attitude dynamic data can be identified, so that the secondary distribution can be performed on the current attitude data, thereby realizing the simulation correction of the flight attitude of the target unmanned aerial vehicle, so that the determined electric quantity change trend information is not influenced by the flight attitude, thereby weakening the influence of different flight attitudes on electric quantity loss, and further ensuring that the electric quantity change trend information is stable with the actual flight state of the target unmanned aerial vehicle.

In some embodiments, the obtaining the power change correlation list of the power change trend information of each target drone included in the flight route combination to obtain the power monitoring trajectory information of the flight route combination in step S23 may include: determining the electric quantity change association list according to trend correlation among electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination; and extracting list element characteristics in the electric quantity change association list, and obtaining electric quantity monitoring track information of the flight route combination based on the list element characteristics. Therefore, the stability of the electric quantity monitoring track information on the time sequence can be ensured, and misjudgment caused by sudden change of the electric quantity monitoring track in a short time is avoided.

In some embodiments, the determining the corresponding stopping reservation adjustment information of the unmanned aerial vehicle apron when the power monitoring trajectory information of at least two flight route combinations meets the safe flight condition, which is described in step S23, includes: and when the track fluctuation coefficients corresponding to the electric quantity monitoring track information of at least two flight route combinations are smaller than the set fluctuation coefficient, determining the stop reservation adjustment information according to the stop reservation queue characteristics corresponding to the unmanned aerial vehicle parking apron. Therefore, the safety of the unmanned aerial vehicle in flight can be ensured while the stop reservation adjustment information is determined, and the generation of flight accidents is avoided.

In some embodiments, in step S23, allocating route planning change data to the to-be-adjusted unmanned aerial vehicle corresponding to the unmanned aerial vehicle apron according to the stop schedule adjustment information, further includes: determining a plurality of adjustment strategies from the halt reservation adjustment information; determining a route planning influence index corresponding to each adjustment strategy; selecting a target unmanned aerial vehicle corresponding to the adjustment strategy corresponding to the minimum air route planning influence index as the unmanned aerial vehicle to be adjusted; and distributing the air route planning change data for the unmanned aerial vehicle to be adjusted according to the air route adjustment instruction and the electric quantity adjustment instruction corresponding to the adjustment strategy. By the design, the minimization of the flight influence of the air route planning change data on the unmanned aerial vehicle can be ensured, so that the global stability of the whole unmanned aerial vehicle cluster is ensured.

Based on the same inventive concept as in the previous embodiments, the present specification further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the steps of any of the methods described above.

Based on the same inventive concept as the previous embodiment, an embodiment of the present specification further provides an unmanned aerial vehicle route planning control center 200, as shown in fig. 2, including a memory 204, a processor 202, and a computer program stored on the memory 204 and executable on the processor 202, wherein the processor 202 implements the steps of any one of the methods described above when executing the program.

Based on the same inventive concept as the previous embodiment, please refer to fig. 3 in combination, which shows an unmanned aerial vehicle route planning control system 100 based on smart lamp posts and an air park, comprising an unmanned aerial vehicle route planning control center 200 and a plurality of unmanned aerial vehicles 300 communicating with the unmanned aerial vehicle route planning control center 200; wherein the unmanned aerial vehicle route planning control center 200 is configured to:

For a functional description of the unmanned aircraft route planning control center 200, reference is made to the description of the method shown in fig. 1, which is not further described here.

Through one or more embodiments of the present description, the present description has the following advantages or advantages: the method comprises the steps of obtaining flight route information of each target unmanned aerial vehicle according to an unmanned aerial vehicle parking reservation record of an unmanned aerial vehicle parking apron, obtaining at least two pieces of target flight route information based on a route planning priority sequence of each target unmanned aerial vehicle and smart lamp pole monitoring information corresponding to the unmanned aerial vehicle parking apron to obtain at least two flight route combinations, and obtaining electric quantity change trend information of each target unmanned aerial vehicle according to real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combinations. Further, an electric quantity change association list of electric quantity change trend information of each target unmanned aerial vehicle included in the flight path combination is obtained to obtain electric quantity monitoring track information of the flight path combination. And determining the corresponding shutdown reservation adjustment information of the unmanned aerial vehicle parking apron when the electric quantity monitoring track information of at least two flight route combinations conforms to the safe flight condition. Therefore, the air route planning change data can be distributed to the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle parking apron according to the parking reservation adjustment information.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, this description is not intended for any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the present specification and that specific languages are described above to disclose the best modes of the specification.

In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the present description may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the specification, various features of the specification are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that is, the present specification as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this specification.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the description and form different embodiments. For example, in the following claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of this description may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components of a gateway, proxy server, system in accordance with embodiments of the present description. The present description may also be embodied as an apparatus or device program (e.g., computer program and computer program product) for performing a portion or all of the methods described herein. Such programs implementing the description may be stored on a computer-readable medium or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the specification, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The description may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Claims

1. An unmanned aerial vehicle route planning control method based on a smart lamp post and an air park is characterized by being applied to an unmanned aerial vehicle route planning control center, and the method comprises the following steps:

2. The method of claim 1, wherein extracting the drone aircraft stopping reservation record for the drone aircraft apron comprises:

3. The method according to claim 1, wherein the obtaining flight path information of each target drone corresponding to the drone apron according to the drone stop reservation record includes:

4. The method according to any one of claims 1 to 3, further comprising:

5. The method of claim 4, wherein the obtaining at least two pieces of target flight route information according to the route planning priority order of each target unmanned aerial vehicle and the smart lamp post monitoring information corresponding to the unmanned aerial vehicle apron to obtain at least two flight route combinations comprises:

obtaining each second index weight distribution based on the air route planning index information of each target unmanned aerial vehicle, and generating a first weight correlation degree of each second index weight distribution;

6. The method according to claim 5, wherein for any flight route combination, acquiring the power variation trend information of each target unmanned aerial vehicle according to the real-time route planning information of each target unmanned aerial vehicle in the current flight state in the flight route combination comprises:

7. The method according to claim 1, wherein the obtaining of the power change correlation list of the power change trend information of each target unmanned aerial vehicle included in the flight route combination to obtain the power monitoring trajectory information of the flight route combination comprises:

8. The method of claim 7, wherein when the power monitoring trajectory information of at least two flight route combinations meets the safe flight condition, determining the corresponding stop schedule adjustment information of the unmanned aerial vehicle apron comprises: and when the track fluctuation coefficients corresponding to the electric quantity monitoring track information of at least two flight route combinations are smaller than the set fluctuation coefficient, determining the stop reservation adjustment information according to the stop reservation queue characteristics corresponding to the unmanned aerial vehicle parking apron.

9. The method of claim 8, wherein the allocating route planning change data to the unmanned aerial vehicle to be adjusted corresponding to the unmanned aerial vehicle apron according to the stop reservation adjustment information comprises:

10. An unmanned aerial vehicle route planning control system based on a smart lamp post and an air park is characterized by comprising an unmanned aerial vehicle route planning control center and an unmanned aerial vehicle communicated with the unmanned aerial vehicle route planning control center; wherein, unmanned aerial vehicle airline planning control center is used for: