CN117130987B - Flight control management method for large-scale unmanned aerial vehicle cluster - Google Patents
Flight control management method for large-scale unmanned aerial vehicle cluster Download PDFInfo
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Abstract
The invention provides a flight control management method of a large-scale unmanned aerial vehicle cluster, which relates to the technical field of unmanned aerial vehicle algorithm management control, and comprises the steps of acquiring unmanned aerial vehicle algorithm management information, creating or inquiring a model name folder, loading an algorithm model file into a memory or releasing a corresponding algorithm memory, and outputting algorithm quantity modification information; the model name folder is backed up, the algorithm names and the algorithm model names are compared and executed, the model name folder is updated, and update completion information is output; inquiring the model name of the algorithm, and outputting the existence detail information; inquiring the update version number, outputting confirmation update information or performing update rollback; the method is used for solving the problems that the existing flight control management method of the large-scale unmanned aerial vehicle cluster lacks analysis on the change of the unmanned aerial vehicle execution algorithm, so that the unmanned aerial vehicle needs to be restarted when the algorithm is updated, and the actual experience of a user is poor.
Description
Technical Field
The invention relates to the technical field of unmanned aerial vehicle algorithm management control, in particular to a flight control management method of a large-scale unmanned aerial vehicle cluster.
Background
The unmanned aerial vehicle algorithm management control technology is a method for simulating unmanned aerial vehicle clusters on a computer by using a simulation technology so as to verify the correctness of design and development and reduce development cost and risk; however, in practical application, the flight control of the unmanned aerial vehicle still has certain challenges; the traditional unmanned aerial vehicle control method relies on priori knowledge and manual feature extraction, and has the problems of poor adaptability, insufficient robustness and the like; the deep learning algorithm can automatically extract the characteristics and has strong adaptability and robustness, so that the method is widely applied to the field of unmanned aerial vehicle control.
The existing unmanned aerial vehicle cluster flight control management method generally analyzes unmanned aerial vehicle traffic in an operating state, and lacks detailed analysis when an unmanned aerial vehicle execution algorithm is changed or updated, for example, the method is disclosed in application publication No.: in the Chinese patent of CN114779813A, a 'multi-unmanned aerial vehicle dynamic task allocation method based on an improved contract net algorithm' is disclosed, wherein the scheme is to acquire task information of an unmanned aerial vehicle, analyze the task information and set bid information and sign up based on analysis results; the scheme lacks analysis of the change of the unmanned aerial vehicle execution algorithm when executing the task; when a new algorithm is generated, the unmanned aerial vehicle execution algorithm needs to be restarted, so that the actual experience of a user is reduced, and in view of the fact, the existing flight control management method of the large-scale unmanned aerial vehicle cluster needs to be optimized.
Disclosure of Invention
Aiming at the defects existing in the prior art, the invention provides a flight control management method of a large-scale unmanned aerial vehicle cluster, which can acquire unmanned aerial vehicle algorithm management information, create or inquire a model name folder, load an algorithm model file into a memory or release a corresponding algorithm memory; backing up the model name folder to obtain a backup folder; the model name folder is updated, updated information is output to confirm or updated rollback is carried out based on the backup folder, so that the problem that the existing flight control management method of the large-scale unmanned aerial vehicle cluster lacks analysis on the change of an unmanned aerial vehicle execution algorithm, so that the unmanned aerial vehicle needs to be restarted when the algorithm is updated, and the actual experience of a user is poor is solved.
In order to achieve the above object, in a first aspect, the present invention provides a flight control management method for a large-scale unmanned aerial vehicle cluster, including the steps of:
step S1, acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
step S2, when algorithm adding information or algorithm deleting information is obtained, creating or inquiring a model name folder corresponding to an algorithm model name, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file; loading the algorithm model file into a memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion;
step S3, when the algorithm updating information is obtained, the model name folder is backed up based on the algorithm model name to obtain a backup folder; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name;
s4, receiving algorithm quantity modification information and updating completion information, inquiring algorithm model names based on the algorithm quantity modification information, and outputting presence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
Further, the step S2 includes the following sub-steps:
step S201, acquiring algorithm adding information or algorithm deleting information;
step S202011, creating a folder based on the algorithm model name when the algorithm adding information is acquired, and marking the folder as a new folder;
step S202012, storing the algorithm version number, the algorithm model file and the model configuration file into a new folder, and marking the new folder as a modified folder;
and step S202013, loading the algorithm model file into a memory based on the model configuration file, and outputting algorithm quantity modification information.
Further, the step S2 further includes the following sub-steps:
step S202021, when algorithm deleting information is received, inquiring a model name folder based on the algorithm model name, and marking the model name folder as a modified folder;
step S202022, marking the algorithm model file in the modification folder as a file to be deleted, and deleting the model file in the memory based on the file to be deleted;
and step S202023, deleting the modified folder and outputting algorithm quantity modification information.
Further, the algorithm comparison information includes different algorithm information and the same algorithm information, and the step S3 includes the following sub-steps:
step S3011, receiving algorithm updating information, when the algorithm updating information is received, carrying out backup processing on a model name folder named as an algorithm model name, and marking the backed-up folder as a backup folder;
step S3012, obtaining the name of an execution algorithm of the current unmanned aerial vehicle cluster;
step S3013, comparing the execution algorithm name with the algorithm model name, and outputting the same algorithm information when the execution algorithm name is the same as the algorithm model name; outputting different algorithm information when the executing algorithm name is different from the algorithm model name;
and step S3014, when different algorithm information is received, updating the algorithm model files and the algorithm version numbers in the model name folder based on the algorithm model names, and outputting update completion information, wherein the update completion information comprises the update version numbers.
Further, the step S3 further includes the following sub-steps:
step S3021, when receiving the same algorithm information, querying a folder named hover algorithm, and marking the folder as hover; dynamically loading an algorithm model file in a hovering folder;
step S3022, updating the algorithm model file and the algorithm version number in the model name folder based on the algorithm model name; marking the updated algorithm model file as an updating algorithm;
step S3023, controlling the unmanned aerial vehicle cluster to dynamically load the update algorithm, and outputting update completion information.
Further, the step S4 includes the following sub-steps:
step S401, receiving algorithm quantity modification information and updating completion information;
step S402011, inquiring the folder based on the algorithm model name when the algorithm number modification information is received, and outputting the folder information when the folder with the name of the algorithm model name is inquired; when the folder named as the algorithm model name is not queried, outputting the information of the folder without existence; the presence detail information comprises presence files and information and non-presence folder information;
step S402012, obtaining a modification mode, and outputting modification completion information when the modification mode is adding and the existence detail information is the existence folder information or when the modification mode is deleting and the existence detail information is the nonexistence folder information;
step S402013, outputting modification failure information when the modification manner and the presence detail information are not the combination in step S402012;
further, the step S4 further includes the following sub-steps:
step S402021, inquiring an algorithm version number in a model name folder with an algorithm model name when receiving update completion information, and marking the algorithm version number as a version number to be analyzed;
step S402022, comparing the version number to be analyzed with the update version number, and outputting confirmation update information when the version number to be analyzed is the same as the update version number;
and step S402023, when the version number to be analyzed is different from the update version number, performing update rollback processing, and updating the model name folder corresponding to the version number to be analyzed into a backup folder.
In a second aspect, the invention provides a flight control management system of a large-scale unmanned aerial vehicle cluster, which comprises a file system management module, an algorithm management module and a management confirmation module; the file system management module comprises an instruction receiving unit, an algorithm updating unit and an algorithm processing unit; the instruction receiving unit is used for acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
the algorithm updating unit is used for creating or inquiring a model name folder corresponding to the algorithm model name when the algorithm adding information or the algorithm deleting information is acquired, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file;
the algorithm processing unit is used for loading the algorithm model file into the memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion;
the algorithm management module is used for backing up the model name folder based on the algorithm model name to obtain a backup folder when the algorithm updating information is acquired; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name;
the management confirmation module is used for receiving the algorithm quantity modification information and the updating completion information, inquiring the algorithm model name based on the algorithm quantity modification information and outputting the existence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
In a third aspect, the present application provides a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method as described above.
The invention has the beneficial effects that: according to the invention, the unmanned aerial vehicle algorithm management information is acquired, the model name folder corresponding to the algorithm model name is newly built or queried, and the algorithm model file is loaded into the memory or the corresponding algorithm memory is released, so that the subsequent unmanned aerial vehicle can conveniently and directly load or reduce the memory pressure from the memory when executing a new algorithm; the intelligent and high-efficiency performance of the flight control management of the unmanned aerial vehicle cluster are improved;
the invention carries out backup on the model name folder, compares the execution algorithm name with the algorithm model name, carries out update processing on the model name folder, outputs update completion information, inquires the update version number based on the algorithm model name in the update completion information, and outputs confirmation update information or carries out update rollback based on the backup folder; the unmanned aerial vehicle can update the algorithm executed by the unmanned aerial vehicle cluster without restarting related components, so that the actual experience of a user is improved; and whether the updating is successful can be judged after the hot updating, and if the updating is unsuccessful, the updating rollback can be carried out, so that the intelligence of the method and the accuracy of judging the hot updating result are further improved.
Additional aspects of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of the steps of the method of the present invention;
FIG. 2 is a control level schematic of the system of the present invention;
fig. 3 is a functional block diagram of the system of the present invention.
Detailed Description
The invention is further described in connection with the following detailed description, in order to make the technical means, the creation characteristics, the achievement of the purpose and the effect of the invention easy to understand.
Example 1
Referring to fig. 1, the invention provides a flight control management method of a large-scale unmanned aerial vehicle cluster, which can acquire unmanned aerial vehicle algorithm management information; creating or inquiring a folder, loading an algorithm model file into a memory or releasing a corresponding algorithm memory; backing up the file folder, and updating the original file folder; inquiring the model name of the algorithm, and outputting modification completion information or modification failure information; querying the update version number, outputting confirmation update information or updating rollback based on the backup folder.
Specifically, the method comprises the following steps:
step S1, acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
referring to fig. 2, service in fig. 2 is an interface layer, and an RPC interface is defined by protobuf, where the definition includes an algorithm name, an algorithm version, algorithm input data, and the like; the File system is a File system management layer, and version management of an algorithm model is realized through monitoring operations such as adding, deleting, changing and the like of files under the catalogue; the Model manager is an algorithm Model management layer, and after the Model is triggered, the Model manager can load a corresponding algorithm Model according to the information transmitted by the file system management module to a corresponding version directory and the Model configuration file under the directory; after loading is completed, follow-up actions are carried out according to the change type of the file; the Request handler is a Request processing module, can call an actual algorithm model to infer according to the loaded input and output information in the model configuration, and returns a result to a service layer;
step S2, when algorithm adding information or algorithm deleting information is obtained, creating or inquiring a model name folder corresponding to an algorithm model name, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file; loading the algorithm model file into a memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion; step S2 further comprises the following sub-steps:
step S201, acquiring algorithm adding information or algorithm deleting information;
step S202011, creating a folder based on the algorithm model name when the algorithm adding information is acquired, and marking the folder as a new folder;
in specific implementation, creating a folder based on the algorithm model name refers to creating a folder with the name of the algorithm model name; for example, an exemplary directory structure is as follows
Work directory
Model name 1 of ___ algorithm
I ___ algorithm version number 101
Model file of the ___ model
Model ___ model config # model Profile
I ___ algorithm version number 102
Model file of the ___ model
Model ___ model config # model Profile
I ___ if desired, more sub-version numbers can be added
Model name 2 of ___ algorithm
The sub-directories of each level of the I ___ are the same as the algorithm model name 1;
for example, when the algorithm model name in the algorithm adding information is "pattern 1 model", a folder with a directory structure as follows is created:
model ___ pattern 1
I ___ algorithm version number 101
Model file of the ___ model
A | ___ model. Config# model profile;
step S202012, storing the algorithm version number, the algorithm model file and the model configuration file into a new folder, and marking the new folder as a modified folder;
step S202013, loading an algorithm model file into a memory based on the model configuration file, and outputting algorithm quantity modification information;
when the method is implemented, after the files under the working directory are changed, a corresponding algorithm model is loaded according to the model configuration file under the newly built directory; after the algorithm model is loaded, a handler is correspondingly constructed, and a corresponding route is established in a service layer; when the service layer receives the request, the service layer routes the request to the corresponding handler according to the information such as the model name, the model version and the like in the request; the handler calls an actual algorithm model to infer according to the loaded input and output information in the model configuration, and returns a result to the service layer;
step S202021, when algorithm deleting information is received, inquiring a model name folder based on the algorithm model name, and marking the model name folder as a modified folder;
step S202022, marking the algorithm model file in the modification folder as a file to be deleted, and deleting the model file in the memory based on the file to be deleted;
when an existing version number folder under a 'model name' directory is deleted (for example, the subdirectory 01 is directly deleted), releasing an algorithm memory corresponding to a pointer of a handler, and deleting a route corresponding to the handler from a service layer; for example, when the algorithm model name in the algorithm deletion information is "algorithm model name 2", the algorithm memory is released by loading the model configuration file under the catalog, and then the algorithm model name 2 folder is deleted;
it should be noted that, when only a certain algorithm version number corresponding to the algorithm model name needs to be deleted, the algorithm model name in the algorithm deletion information may be changed into the algorithm model name and the algorithm version number, so as to implement deletion processing of the algorithm version;
step S202023, deleting the modified folder and outputting algorithm quantity modification information;
step S3, when the algorithm updating information is obtained, the model name folder is backed up based on the algorithm model name to obtain a backup folder; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name; step S3 further comprises the following sub-steps:
step S3011, receiving algorithm updating information, when the algorithm updating information is received, carrying out backup processing on a model name folder named as an algorithm model name, and marking the backed-up folder as a backup folder;
in specific implementation, if the algorithm model name in the algorithm updating information is the algorithm model name 1, the folder is:
model name 1 of ___ algorithm
I ___ algorithm version number 101
Model file of the ___ model
Model ___ model config # model Profile
Performing backup processing to obtain a backup folder;
step S3012, obtaining the name of an execution algorithm of the current unmanned aerial vehicle cluster;
step S3013, comparing the execution algorithm name with the algorithm model name, and outputting the same algorithm information when the execution algorithm name is the same as the algorithm model name; outputting different algorithm information when the executing algorithm name is different from the algorithm model name;
step S3014, when receiving different algorithm information, updating the algorithm model files and the algorithm version numbers in the model name folder based on the algorithm model names, and outputting update completion information, wherein the update completion information comprises update version numbers;
when a model file under a certain existing version number folder under a 'model name' directory changes (for example, in an algorithm version number 101 directory under an algorithm model name 1 directory, the md5 value of a model. Pt changes), loading a new algorithm model into a memory, switching a pointer of a handler from the memory of an old version algorithm to a new version after verification, releasing the memory of the old version algorithm, and simultaneously providing services for the new version algorithm, and changing the algorithm version number 101 into an algorithm version number 101.N, wherein n represents algebra of the version and can be a positive integer or 2.3, for example;
step S3021, when receiving the same algorithm information, querying a folder named hover algorithm, and marking the folder as hover; dynamically loading an algorithm model file in a hovering folder;
when the name of the executed algorithm is the same as the name of the algorithm model, if the algorithm is updated directly at the moment, the model configuration file needs to be loaded into the memory, the unmanned aerial vehicle executes the algorithm again, the unmanned aerial vehicle has a short-time non-algorithm execution state in the process, and if the unmanned aerial vehicle keeps a motion state before updating, uncontrollable motion of the unmanned aerial vehicle can occur in the updating process; therefore, the hovering algorithm is loaded in the unmanned aerial vehicle memory in advance, and when the executing algorithm needs to be updated, the method comprises the following steps of: executing algorithm-loading hovering algorithm-updating executing algorithm-loading updated executing algorithm, which can avoid the occurrence of uncontrollable movement in the updating process;
in practice, the Dynamic Link Library (DLL) may be used: compiling the algorithm module into a dynamic link library, and loading the dynamic link library into an application program by loading a library file during running; or using a configuration file or database: storing information of the algorithm module in a configuration file or database, and reading the information at run-time; dynamically loading and using corresponding algorithm modules according to the configuration information; thus realizing the dynamic loading of the algorithm;
step S3022, updating the algorithm model file and the algorithm version number in the model name folder based on the algorithm model name; marking the updated algorithm model file as an updating algorithm;
step S3023, controlling the unmanned aerial vehicle cluster to dynamically load an update algorithm, and outputting update completion information;
s4, receiving algorithm quantity modification information and updating completion information, inquiring algorithm model names based on the algorithm quantity modification information, and outputting presence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; inquiring the update version number based on the algorithm model name in the update completion information, outputting confirmation update information or updating rollback based on the backup folder; step S4 further comprises the sub-steps of:
step S401, receiving algorithm quantity modification information and updating completion information;
step S402011, inquiring the folder based on the algorithm model name when the algorithm number modification information is received, and outputting the folder information when the folder with the name of the algorithm model name is inquired; when the folder named as the algorithm model name is not queried, outputting the information of the folder without existence; the presence detail information comprises presence files and information and non-presence folder information;
step S402012, obtaining a modification mode, and outputting modification completion information when the modification mode is adding and the existence detail information is the existence folder information or when the modification mode is deleting and the existence detail information is the nonexistence folder information;
in step S402013, when the modification and the presence detail information are not the combination in step S402012, modification failure information is output.
Step S402021, inquiring an algorithm version number in a model name folder with an algorithm model name when receiving update completion information, and marking the algorithm version number as a version number to be analyzed;
step S402022, comparing the version number to be analyzed with the update version number, and outputting confirmation update information when the version number to be analyzed is the same as the update version number;
and step S402023, when the version number to be analyzed is different from the update version number, performing update rollback processing, and updating the model name folder corresponding to the version number to be analyzed into a backup folder.
Example two
Referring to fig. 3, in a second aspect, the present invention provides a flight control management system for a large-scale unmanned aerial vehicle cluster, including a file system management module, an algorithm management module, and a management confirmation module; the file system management module comprises an instruction receiving unit, an algorithm updating unit and an algorithm processing unit; the instruction receiving unit is used for acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
the algorithm updating unit is used for creating or inquiring a model name folder corresponding to the algorithm model name when the algorithm adding information or the algorithm deleting information is acquired, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file;
the algorithm processing unit is used for loading the algorithm model file into the memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion;
the algorithm management module is used for backing up the model name folder based on the algorithm model name to obtain a backup folder when the algorithm updating information is acquired; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name;
the management confirmation module is used for receiving the algorithm quantity modification information and the updating completion information, inquiring the algorithm model name based on the algorithm quantity modification information and outputting the existence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
Example III
In a third aspect, the present invention provides a storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods described above. By the above technical solution, the computer program, when executed by the processor, performs the method in any of the alternative implementations of the above embodiments to implement the following functions: acquiring unmanned aerial vehicle algorithm management information, creating or inquiring a model name folder corresponding to an algorithm model name, loading an algorithm model file into a memory or releasing the corresponding algorithm memory, and backing up the model name folder based on the algorithm model name to obtain a backup folder; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, outputting update completion information, wherein the update completion information comprises an update version number and an algorithm model name, receiving algorithm quantity modification information and update completion information, inquiring the algorithm model name based on the algorithm quantity modification information, and outputting the existence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media having computer-usable program code embodied therein. The storage medium may be implemented by any type or combination of volatile or nonvolatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM), electrically erasable Programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory, EEPROM), erasable Programmable Read-Only Memory (Erasable Programmable Red Only Memory, EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
The above examples are only specific embodiments of the present invention, and are not intended to limit the scope of the present invention, but it should be understood by those skilled in the art that the present invention is not limited thereto, and that the present invention is described in detail with reference to the foregoing examples: any person skilled in the art may modify or easily conceive of the technical solution described in the foregoing embodiments, or perform equivalent substitution of some of the technical features, while remaining within the technical scope of the present disclosure; such modifications, changes or substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (9)
1. A flight control management method of a large-scale unmanned aerial vehicle cluster is characterized by comprising the following steps:
step S1, acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
step S2, when algorithm adding information or algorithm deleting information is obtained, creating or inquiring a model name folder corresponding to an algorithm model name, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file; loading the algorithm model file into a memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion;
step S3, when the algorithm updating information is obtained, the model name folder is backed up based on the algorithm model name to obtain a backup folder; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name;
s4, receiving algorithm quantity modification information and updating completion information, inquiring algorithm model names based on the algorithm quantity modification information, and outputting presence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
2. The method for flight control management of a large-scale unmanned aerial vehicle cluster according to claim 1, wherein the step S2 comprises the following sub-steps:
step S201, acquiring algorithm adding information or algorithm deleting information;
step S202011, creating a folder based on the algorithm model name when the algorithm adding information is acquired, and marking the folder as a new folder;
step S202012, storing the algorithm version number, the algorithm model file and the model configuration file into a new folder, and marking the new folder as a modified folder;
and step S202013, loading the algorithm model file into a memory based on the model configuration file, and outputting algorithm quantity modification information.
3. The method for flight control management of a large-scale unmanned aerial vehicle cluster according to claim 2, wherein the step S2 further comprises the sub-steps of:
step S202021, when algorithm deleting information is received, inquiring a model name folder based on the algorithm model name, and marking the model name folder as a modified folder;
step S202022, marking the algorithm model file in the modification folder as a file to be deleted, and deleting the model file in the memory based on the file to be deleted;
and step S202023, deleting the modified folder and outputting algorithm quantity modification information.
4. The method for controlling and managing the flight of a large-scale unmanned aerial vehicle cluster according to claim 3, wherein the algorithm comparison information comprises different algorithm information and the same algorithm information, and the step S3 comprises the following sub-steps:
step S3011, receiving algorithm updating information, when the algorithm updating information is received, carrying out backup processing on a model name folder named as an algorithm model name, and marking the backed-up folder as a backup folder;
step S3012, obtaining the name of an execution algorithm of the current unmanned aerial vehicle cluster;
step S3013, comparing the execution algorithm name with the algorithm model name, and outputting the same algorithm information when the execution algorithm name is the same as the algorithm model name; outputting different algorithm information when the executing algorithm name is different from the algorithm model name;
and step S3014, when different algorithm information is received, updating the algorithm model files and the algorithm version numbers in the model name folder based on the algorithm model names, and outputting update completion information, wherein the update completion information comprises the update version numbers.
5. The method for flight control management of a large-scale unmanned aerial vehicle cluster according to claim 4, wherein the step S3 further comprises the sub-steps of:
step S3021, when receiving the same algorithm information, querying a folder named hover algorithm, and marking the folder as hover; dynamically loading an algorithm model file in a hovering folder;
step S3022, updating the algorithm model file and the algorithm version number in the model name folder based on the algorithm model name; marking the updated algorithm model file as an updating algorithm;
step S3023, controlling the unmanned aerial vehicle cluster to dynamically load the update algorithm, and outputting update completion information.
6. The method for flight control management of a large-scale unmanned aerial vehicle cluster according to claim 5, wherein the step S4 comprises the following sub-steps:
step S401, receiving algorithm quantity modification information and updating completion information;
step S402011, inquiring the folder based on the algorithm model name when the algorithm number modification information is received, and outputting the folder information when the folder with the name of the algorithm model name is inquired; when the folder named as the algorithm model name is not queried, outputting the information of the folder without existence; the presence detail information comprises presence files and information and non-presence folder information;
step S402012, obtaining a modification mode, and outputting modification completion information when the modification mode is adding and the existence detail information is the existence folder information or when the modification mode is deleting and the existence detail information is the nonexistence folder information;
in step S402013, when the modification and the presence detail information are not the combination in step S402012, modification failure information is output.
7. The method for flight control management of a large-scale unmanned aerial vehicle cluster according to claim 6, wherein the step S4 further comprises the sub-steps of:
step S402021, inquiring an algorithm version number in a model name folder with an algorithm model name when receiving update completion information, and marking the algorithm version number as a version number to be analyzed;
step S402022, comparing the version number to be analyzed with the update version number, and outputting confirmation update information when the version number to be analyzed is the same as the update version number;
and step S402023, when the version number to be analyzed is different from the update version number, performing update rollback processing, and updating the model name folder corresponding to the version number to be analyzed into a backup folder.
8. A system suitable for a flight control management method of a large-scale unmanned aerial vehicle cluster according to any one of claims 1 to 7, comprising a file system management module, an algorithm management module, and a management confirmation module; the file system management module comprises an instruction receiving unit, an algorithm updating unit and an algorithm processing unit; the instruction receiving unit is used for acquiring unmanned aerial vehicle algorithm management information, wherein the unmanned aerial vehicle algorithm management information comprises algorithm updating information, algorithm adding information and algorithm deleting information; the unmanned aerial vehicle algorithm management information also comprises an algorithm model name;
the algorithm updating unit is used for creating or inquiring a model name folder corresponding to the algorithm model name when the algorithm adding information or the algorithm deleting information is acquired, wherein the model name folder comprises an algorithm version number, an algorithm model file and a model configuration file;
the algorithm processing unit is used for loading the algorithm model file into the memory or releasing the corresponding algorithm memory; outputting algorithm quantity modification information, wherein the algorithm quantity modification information comprises a modification mode and a modification folder, and the modification mode comprises addition and deletion;
the algorithm management module is used for backing up the model name folder based on the algorithm model name to obtain a backup folder when the algorithm updating information is acquired; acquiring the current unmanned aerial vehicle execution algorithm name, the comparison execution algorithm name and the algorithm model name, and outputting algorithm comparison information; updating the model name folder based on the algorithm comparison information, and outputting updating completion information, wherein the updating completion information comprises an updating version number and an algorithm model name;
the management confirmation module is used for receiving the algorithm quantity modification information and the updating completion information, inquiring the algorithm model name based on the algorithm quantity modification information and outputting the existence detail information; outputting modification completion information or modification failure information based on the modification manner and the presence detail information; and inquiring the update version number based on the algorithm model name in the update completion information, and outputting confirmation update information or performing update rollback based on the backup folder.
9. A storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method according to any of claims 1-7.
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