CN114967720A - Method and device for generating standby strategy during intelligent flight of unmanned aerial vehicle - Google Patents
Method and device for generating standby strategy during intelligent flight of unmanned aerial vehicle Download PDFInfo
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- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/08—Control of attitude, i.e. control of roll, pitch, or yaw
- G05D1/0808—Control of attitude, i.e. control of roll, pitch, or yaw specially adapted for aircraft
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
Abstract
The invention discloses a method and a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle, wherein the method comprises the following steps: acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database; acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in the flight strategy database, and calling an implementable flight strategy; obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy; and recording an application strategy of the unmanned aerial vehicle when the unmanned aerial vehicle deals with abnormal flight generating the obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicles, in particular to a method and a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle.
Background
At present, the unmanned aerial vehicle mainly depends on manual control or the preset flight route strictly flies according to the flight route, flexible flexibility is lacked, once the master control system loses connection in the face of emergency, the unmanned aerial vehicle is extremely easy to lose control in the absence of guidance, and therefore, the fact that the unmanned aerial vehicle flying intelligently is provided with a necessary standby flight strategy is extremely critical.
Disclosure of Invention
In order to solve the above problems, the embodiment of the application provides a method and a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle, the standby flight strategy is generated based on actual flight parameters, the standby flight strategy and an actual execution strategy are in double-line parallel, and when the method and the device are applied to the unmanned aerial vehicle, the unmanned aerial vehicle can be prevented from being out of control, and bidirectional verification can be performed with the execution strategy.
In a first aspect, an embodiment of the present application provides a method for generating a standby policy during intelligent flight of an unmanned aerial vehicle, where the method includes:
acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in the flight strategy database, and calling an implementable flight strategy;
obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy;
recording an application strategy of the unmanned aerial vehicle in response to abnormal flight generating the obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
Preferably, the acquiring of historical flight data, the screening of abnormal conditions and the correlation of corresponding flight strategies, and the establishing of the flight strategy database specifically include:
acquiring flight records including manually controlled and automatically controlled flight data, and uniformly generating historical flight data;
screening abnormal conditions in the uniformly generated historical flight data, correspondingly restoring a flight strategy corresponding to the abnormal conditions, and associating the abnormal conditions with the flight strategy;
establishing a flight strategy database by taking the type of the abnormal condition as a retrieval header file and taking the abnormal parameter of the abnormal condition as a matching object;
the abnormal parameters comprise a repairable offset parameter and a non-self-repairable fault parameter; the flight strategy at least comprises a flight route, a flight speed, a flight attitude and an external influence parameter record.
Preferably, the obtaining of the obstacle data in the flight process and the matching of the abnormal situation in the flight strategy database and the calling of the implementable flight strategy specifically include:
acquiring flight data based on the unmanned aerial vehicle in the flight state, and marking the flight data as barrier data when parameters influencing the normal execution of the current task exist;
feeding back a generation factor of the obstacle data, namely the type of the abnormal condition;
preliminarily matching the generated factors obtained by feedback with a retrieval header file in the flight strategy database;
carrying out concept object matching on the successfully matched barrier data and the abnormal parameters governed by the retrieval head file;
the flight strategies corresponding to the abnormal parameters matched with the concept objects are all classified into an implementable strategy group to wait for calling;
and marking the obstacle data matched with the incomplete concept object as new anomalies, recording an original path generated by the obstacle data, generating an obstacle log, and sending the obstacle log to a manual operation platform.
Preferably, the concept object matching specifically includes:
according to the type of the abnormal parameter, expanding the amplitude of the abnormal parameter, predefining an expansion threshold for each type of the abnormal parameter, and forming an object coverage area;
dividing the object coverage area into a plurality of orders of magnitude based on abnormal parameters of abnormal conditions to distinguish the emergency degree of the abnormal conditions of the same type, wherein the abnormal parameters corresponding to the abnormal conditions sequentially fall into different orders of magnitude;
and acquiring fault data, matching the magnitude of the fault data based on the magnitude concept, and defining all the abnormal parameters in the magnitude as concept object matching.
Preferably, obtaining the internal parameters and the external influence parameters of the current unmanned aerial vehicle, screening the optimal strategy in the flight strategies, optimizing the execution parameters of the optimal strategy, and generating a standby strategy, includes:
acquiring internal parameters of the current unmanned aerial vehicle, wherein the internal parameters at least comprise a flight line, a flight speed and a flight attitude;
acquiring external influence parameters of the current unmanned aerial vehicle, wherein the external influence parameters at least comprise air pressure, wind speed and wind direction;
predefining relevance threshold values for all parameters in the internal parameters, and carrying out domain expansion on all parameters based on the relevance threshold values to form a screening domain;
calling the flight strategies in the implementable strategy group, extracting various parameters in the flight strategies to be matched with the screening domains of the corresponding items, and marking the successfully matched parameter items;
defining the flight strategies with high matching degree of the internal parameters as reference strategies, selecting the strategy with the lowest flight influence rate on the unmanned aerial vehicle from the external influence parameters in the reference strategies, and defining the strategy as an optimal strategy;
optimizing parameters of the optimal strategy during execution based on the deviation between the external influence parameters of the optimal strategy and the external influence parameters of the current unmanned aerial vehicle, and reducing the influence of external environmental factors on the flight of the unmanned aerial vehicle;
and fitting the optimized execution parameters with the optimal strategy to generate the standby strategy.
Preferably, the recording an application strategy of the unmanned aerial vehicle in response to an abnormal flight that generates the obstacle data, and outputting the standby strategy and the actually executed application strategy as a flight record in synchronization includes:
generating an actual execution strategy of the unmanned aerial vehicle in response to abnormal flight generating barrier data based on an execution parameter of the current unmanned aerial vehicle in response to the barrier data in flight, and recording the actual execution strategy as an application strategy;
and synchronously outputting the standby strategy and the application strategy as a flight record, wherein the flight record comprises two comparable flight strategies, the standby strategy is a standby reference, and the application strategy is actual execution.
In a second aspect, an embodiment of the present application provides a generation device of a standby strategy during intelligent flight of an unmanned aerial vehicle, the device includes:
a data processing module: acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
a policy matching module: acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in a flight strategy database, and calling an implementable flight strategy;
a policy generation module: obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy;
a policy output module: and recording an application strategy of the unmanned aerial vehicle when the unmanned aerial vehicle deals with abnormal flight generating barrier data, and synchronously outputting a standby strategy and an actually executed application strategy as a flight record.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the computer program to implement the steps of the method as provided in the first aspect or any one of the possible implementation manners of the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method as provided in the first aspect or any one of the possible implementations of the first aspect.
The invention has the beneficial effects that:
the invention provides a method and a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle.
The generation of the standby strategy in the invention can be gradually optimized based on a large number of actual strategies for normal flight, and the flight strategy database is enriched, so that the standby strategy is more effective and real.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flow diagram of a method for generating a standby strategy during intelligent flight of an unmanned aerial vehicle according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application.
In the following description, the terms "first" and "second" are used for descriptive purposes only and are not intended to indicate or imply relative importance. The following description provides embodiments of the present application, where different embodiments may be substituted or combined, and thus the present application is intended to include all possible combinations of the same and/or different embodiments described. Thus, if one embodiment includes feature A, B, C and another embodiment includes feature B, D, then this application should also be construed to include embodiments that include one or more of all other possible combinations of A, B, C, D, even though such embodiments may not be explicitly recited in the following text.
The following description provides examples, and does not limit the scope, applicability, or examples set forth in the claims. Changes may be made in the function and arrangement of elements described without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Furthermore, features described with respect to some examples may be combined into other examples.
Referring to fig. 1, fig. 1 is a schematic flowchart of a method for generating a standby policy during intelligent flight of an unmanned aerial vehicle according to an embodiment of the present application. In an embodiment of the present application, the method includes:
s101, obtaining historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database.
The execution subject of this application can be unmanned aerial vehicle.
In the embodiment of the application, historical flight data is used as basic reference data, and a necessary data association structure is defined to generate a flight strategy database.
In one possible implementation, step S101 includes:
acquiring flight records including manually controlled and automatically controlled flight data, and uniformly generating historical flight data;
screening abnormal conditions in the uniformly generated historical flight data, correspondingly restoring a flight strategy corresponding to the abnormal conditions, and associating the abnormal conditions with the flight strategy;
and establishing a flight strategy database by taking the type of the abnormal condition as a retrieval header file and taking the abnormal parameter of the abnormal condition as a matching object.
In the embodiment of the application, the exception type is defined according to the source of the exception parameter, the source of the exception can be unified, but the exception parameter is not unified, and fluctuation in a certain range may exist; the abnormal condition caused by the abnormal parameter also has a certain change, such as fluctuation of the current parameter, which causes the rotation speed of the propeller to change.
It is understood that the exception parameters include a recoverable offset parameter and a non-self-recoverable fault parameter; the flight strategy at least comprises flight routes, flight speeds, flight attitudes and external influence parameter records.
In the embodiment of the application, the flight data corresponding to the means control has more effective reference value, and the flight data of the automatic control is closer to the situation when the standby strategy is executed, so that both flight data are necessary, and the proportion of the two data can be adjusted if necessary.
S102, acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in the flight strategy database, and calling an implementable flight strategy.
In the embodiment of the application, in the normal flight process of the unmanned aerial vehicle, the current task can be perfectly executed, and if a fault exists, the current task is interfered, so that the fault information can be extracted and marked to serve as barrier data, and the barrier data is repaired or reported by a main control strategy.
It can be understood that the barrier data corresponds to the abnormal parameter, and for the recoverable offset parameter, the master control strategy or the standby strategy can be automatically repaired; for the fault parameters which cannot be repaired by self, the main control strategy or the standby strategy cannot be repaired by self, and can be fed back to the manual operation platform in time to be repaired by workers.
In one possible embodiment, step S102 includes:
acquiring flight data based on the unmanned aerial vehicle in the flight state, and marking the flight data as barrier data when parameters influencing the normal execution of the current task exist;
feeding back a generation factor of the obstacle data, namely the type of the abnormal condition;
preliminarily matching the generated factors obtained by feedback with a retrieval header file in the flight strategy database;
carrying out concept object matching on the successfully matched barrier data and the abnormal parameters governed by the retrieval head file;
the flight strategies corresponding to the abnormal parameters matched with the concept objects are all classified into an implementable strategy group to wait for calling;
and marking the obstacle data matched with the incomplete concept object as new anomalies, recording an original path generated by the obstacle data, generating an obstacle log, and sending the obstacle log to a manual operation platform.
In the application, the mapping relation covered in the flight strategy data comprises primary matching and concept object matching, wherein the primary matching is only to correspondingly screen and remove a search header file; and the concept object is matched, the division is carried out according to the emergency degree of the fault data, the similar strategies are matched in a conceptual mode so as to screen out the better and matched flight strategies, and the flight strategies with overlarge difference of influence factors are eliminated.
In the embodiment of the application, the concrete steps of matching the concept object comprise:
according to the type of the abnormal parameter, expanding the amplitude of the abnormal parameter, predefining an expansion threshold for each type of the abnormal parameter, and forming an object coverage area;
dividing the object coverage area into a plurality of orders of magnitude based on abnormal parameters of abnormal conditions to distinguish the emergency degree of the abnormal conditions of the same type, wherein the abnormal parameters corresponding to the abnormal conditions sequentially fall into different orders of magnitude;
and acquiring fault data, matching the magnitude of the fault data based on the magnitude concept, and defining all the abnormal parameters in the magnitude as concept object matching.
In the embodiment of the present application, the abnormal condition includes a plurality of abnormal parameters, and the abnormal parameters are different, such as on/off of current and fluctuation of voltage. Therefore, the actual meaning of the data corresponding to the abnormal parameter can be used for defining the change rule or change mode of the data, so that the types of the abnormal parameters formed by the change of the abnormal parameter are various, the change range of the abnormal parameters can be expanded according to the types of the abnormal parameters, the expansion threshold value is predefined for each type of the abnormal parameters, and the expansion threshold value can be zero, namely, the expansion is not performed.
The expanded abnormal parameters have abnormal parameter values in a larger range, wherein part of the abnormal parameter values may be normal, and part of the abnormal parameter values are real abnormal parameters. At this time, the object coverage area may be divided into multiple magnitudes, where a normal magnitude and an abnormal magnitude exist in the multiple magnitudes.
In the embodiment of the application, the flight strategies in the magnitude levels which are successfully matched are all used as implementable strategies to expand the selectable range of the standby strategies.
S103, obtaining the internal parameters and the external influence parameters of the current unmanned aerial vehicle, screening the optimal strategy in the flight strategies, optimizing the execution parameters of the optimal strategy, and generating a standby strategy.
In this application embodiment, when unmanned aerial vehicle carries out the master control strategy, unmanned aerial vehicle's internal parameter, external influence parameter all can obtain, and standby strategy can directly borrow when generating. Wherein, unmanned aerial vehicle's internal parameter includes flight line, airspeed, flight gesture at least, and unmanned aerial vehicle's external influence parameter includes atmospheric pressure, wind speed, wind direction at least.
It will be appreciated that the internal parameters facilitate matching a more appropriate flight strategy, and the external influencing parameters facilitate optimizing the implementation parameters of the selected flight strategy to suit the current external environment.
In one possible embodiment, step S103 includes:
acquiring internal parameters of the current unmanned aerial vehicle, wherein the internal parameters at least comprise a flight line, a flight speed and a flight attitude;
acquiring external influence parameters of the current unmanned aerial vehicle, wherein the external influence parameters at least comprise air pressure, wind speed and wind direction;
predefining relevance threshold values for all parameters in the internal parameters, and performing domain expansion on all parameters based on the relevance threshold values to form a screening domain;
calling the flight strategies in the implementable strategy group, extracting various parameters in the flight strategies to match with the screening domain of the corresponding item, and marking the successfully matched parameter item;
defining the flight strategies with high matching degree of the internal parameters as reference strategies, selecting the strategy with the lowest flight influence rate on the unmanned aerial vehicle from the external influence parameters in the reference strategies, and defining the strategy as an optimal strategy;
optimizing parameters of the optimal strategy during execution based on the deviation between the external influence parameters of the optimal strategy and the external influence parameters of the current unmanned aerial vehicle, and reducing the influence of external environmental factors on the flight of the unmanned aerial vehicle;
and fitting the optimized execution parameters with the optimal strategy to generate the standby strategy.
In the embodiment of the present application, the relevance threshold is a standard value for enlarging the screening range, and is intended to expand based on the attributes of each parameter, so as to increase the matching success rate of the optimal strategy.
The degree of matching can be defined according to the deviation value. In the embodiment of the application, the influence of external environmental factors on the unmanned aerial vehicle is preferably reduced to the lowest, namely, the flight of the unmanned aerial vehicle is not influenced by the wind speed, the wind direction and the like, and when the standby strategy is generated, difference compensation on the wind speed and the wind direction can be carried out on the basis of the historical parameters of automatic control to optimize the execution parameters.
It can be understood that, in the manual control process, the influence of external environmental factors on the flight is greatly reduced and shielded by the manual control; however, in the automatic control process, the change of external environmental factors can cause the automatic change of the execution parameters of the unmanned aerial vehicle, and on the basis, the history parameters of the automatic control have more effective reference meanings.
S104, recording an application strategy of the unmanned aerial vehicle in response to abnormal flight generating the obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
In the embodiment of the application, the backup strategy is in parallel with the main control strategy, under normal conditions, the backup strategy is in a backup state and does not participate in the control of the unmanned aerial vehicle, at the moment, bidirectional verification can be performed between the backup strategy and the main control strategy, on one hand, a generation mechanism of the backup strategy can be adjusted, and on the other hand, the validity of the backup strategy and the historical correctness of the main control strategy can be verified in the matching degree of the backup strategy and the main control strategy. Further, the parameters of the master control strategy can be included in the flight strategy database as historical flight data.
In one possible embodiment, step S104 includes:
generating an actual execution strategy of the unmanned aerial vehicle when the unmanned aerial vehicle deals with abnormal flight generating barrier data based on the execution parameters of the current unmanned aerial vehicle when the unmanned aerial vehicle deals with the barrier data during flight, and recording the actual execution strategy as an application strategy;
and synchronously outputting the standby strategy and the application strategy as a flight record, wherein the flight record comprises two comparable flight strategies, the standby strategy is a standby reference, and the application strategy is actual execution.
The execution process of the backup strategy after generation in the normal flight process is parallel to the main control strategy (application strategy) without mutual interference. After the flight is finished, the synchronous output is a flight record which can be used for data analysis by workers.
If the main control strategy of the unmanned aerial vehicle fails in the flight process and cannot be continuously executed, the backup strategy can take over the follow-up flight of the unmanned aerial vehicle to control the unmanned aerial vehicle so as to complete the follow-up flight task or emergency landing.
The device for generating the standby strategy during intelligent flight of the unmanned aerial vehicle provided by the embodiment of the application is described in detail below with reference to fig. 2. It should be noted that, the device for generating the standby strategy during the intelligent flight of the unmanned aerial vehicle shown in fig. 2 is used for executing the method of the embodiment shown in fig. 1 of the present application, for convenience of description, only the part related to the embodiment of the present application is shown, and details of the specific technology are not disclosed, please refer to the embodiment shown in fig. 1 of the present application.
Please refer to fig. 2, fig. 2 is a schematic structural diagram of a device for generating a standby strategy during intelligent flight of an unmanned aerial vehicle according to an embodiment of the present application. As shown in fig. 2, the apparatus includes:
the data processing module 201: acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
the policy matching module 202: acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in a flight strategy database, and calling an implementable flight strategy;
the policy generation module 203: obtaining the internal parameters and the external influence parameters of the current unmanned aerial vehicle, screening the optimal strategy in the flight strategies, optimizing the execution parameters of the optimal strategy, and generating a standby strategy.
The policy output module 204: and the system is used for receiving result information fed back by the risk challenge management group and controlling the production work to be supervised based on the result information.
It is clear to a person skilled in the art that the solution according to the embodiments of the present application can be implemented by means of software and/or hardware. The term "unit" and "module" in this specification refers to software and/or hardware capable of performing a specific function independently or in cooperation with other components, wherein the hardware may be, for example, a Field-Programmable Gate Array (FPGA), an Integrated Circuit (IC), or the like.
Each processing unit and/or module in the embodiments of the present application may be implemented by an analog circuit that implements the functions described in the embodiments of the present application, or may be implemented by software that executes the functions described in the embodiments of the present application.
Referring to fig. 3, a schematic structural diagram of an electronic device according to an embodiment of the present application is shown, where the electronic device may be used to implement the method in the embodiment shown in fig. 1. As shown in fig. 3, the electronic device 300 may include: at least one central processor 301, at least one network interface 304, a user interface 303, a memory 305, at least one communication bus 302.
Wherein a communication bus 302 is used to enable the connection communication between these components.
The user interface 303 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 303 may further include a standard wired interface and a wireless interface.
The network interface 304 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
The central processor 301 may include one or more processing cores. The central processor 301 connects various parts within the entire electronic device 300 using various interfaces and lines, and performs various functions of the terminal 300 and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 305 and calling data stored in the memory 305. Alternatively, the central Processing unit 301 may be implemented in at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The CPU 301 may integrate one or a combination of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), a modem, and the like. Wherein, the CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It is understood that the modem may not be integrated into the cpu 301, but may be implemented by a single chip.
The Memory 305 may include a Random Access Memory (RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable medium. The memory 305 may be used to store instructions, programs, code sets, or instruction sets. The memory 305 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the various method embodiments described above, and the like; the storage data area may store data and the like referred to in the above respective method embodiments. The memory 305 may alternatively be at least one storage device located remotely from the central processor 301. As shown in fig. 3, memory 305, which is a type of computer storage medium, may include an operating system, a network communication module, a user interface module, and program instructions.
In the electronic device 300 shown in fig. 3, the user interface 303 is mainly used for providing an input interface for a user to obtain data input by the user; the central processor 301 may be configured to invoke the generation application of the standby policy during intelligent flight of the unmanned aerial vehicle stored in the memory 305, and specifically perform the following operations:
acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in the flight strategy database, and calling an implementable flight strategy;
obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy;
recording an application strategy of the unmanned aerial vehicle in response to abnormal flight generating the obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the above-described method. The computer-readable storage medium may include, but is not limited to, any type of disk including floppy disks, optical disks, DVD, CD-ROMs, microdrive, and magneto-optical disks, ROMs, RAMs, EPROMs, EEPROMs, DRAMs, VRAMs, flash memory devices, magnetic or optical cards, nanosystems (including molecular memory ICs), or any type of media or device suitable for storing instructions and/or data.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implementing, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some service interfaces, devices or units, and may be an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned memory comprises: various media capable of storing program codes, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by a program, which is stored in a computer-readable memory, and the memory may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above description is only an exemplary embodiment of the present disclosure, and the scope of the present disclosure should not be limited thereby. That is, all equivalent changes and modifications made in accordance with the teachings of the present disclosure are intended to be included within the scope of the present disclosure. Embodiments of the present disclosure will be readily apparent to those skilled in the art from consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (9)
1. A method for generating a standby strategy during intelligent flight of an unmanned aerial vehicle is characterized by comprising the following steps:
acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in the flight strategy database, and calling an implementable flight strategy;
obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy;
recording an application strategy of the unmanned aerial vehicle in response to abnormal flight generating the obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
2. The method according to claim 1, wherein obtaining historical flight data, screening abnormal situations and corresponding flight strategies for association, and establishing a flight strategy database specifically comprises:
acquiring flight records including manually controlled and automatically controlled flight data, and uniformly generating historical flight data;
screening abnormal conditions in the uniformly generated historical flight data, correspondingly restoring a flight strategy corresponding to the abnormal conditions, and associating the abnormal conditions with the flight strategy;
establishing a flight strategy database by taking the type of the abnormal condition as a retrieval header file and taking the abnormal parameter of the abnormal condition as a matching object;
the abnormal parameters comprise a repairable offset parameter and a non-self-repairable fault parameter; the flight strategy at least comprises a flight route, a flight speed, a flight attitude and an external influence parameter record.
3. The method according to claim 2, wherein obtaining obstacle data during flight to match with abnormal conditions in the flight strategy database and invoking an enforceable flight strategy specifically comprises:
acquiring flight data based on the unmanned aerial vehicle in the flight state, and marking the flight data as barrier data when parameters influencing the normal execution of the current task exist;
feeding back a generation factor of the obstacle data, namely the type of the abnormal condition;
preliminarily matching the generated factors obtained by feedback with a retrieval header file in the flight strategy database;
carrying out concept object matching on the successfully matched barrier data and the abnormal parameters governed by the retrieval head file;
the flight strategies corresponding to the abnormal parameters matched with the concept objects are all classified into an implementable strategy group to wait for calling;
and marking the obstacle data matched with the incomplete concept object as new anomalies, recording an original path generated by the obstacle data, generating an obstacle log, and sending the obstacle log to a manual operation platform.
4. The method of claim 3, wherein the conceptual object matching specifically comprises:
according to the type of the abnormal parameter, expanding the amplitude of the abnormal parameter, predefining an expansion threshold for each type of the abnormal parameter, and forming an object coverage area;
dividing the object coverage area into a plurality of orders of magnitude based on abnormal parameters of abnormal conditions to distinguish the emergency degree of the abnormal conditions of the same type, wherein the abnormal parameters corresponding to the abnormal conditions sequentially fall into different orders of magnitude;
and acquiring fault data, matching the magnitude of the fault data based on the magnitude concept, and defining all the abnormal parameters in the magnitude as concept object matching.
5. The method of claim 4, wherein obtaining internal parameters and external influence parameters of the current UAV, screening an optimal strategy among the flight strategies, and performing parameter optimization on the optimal strategy to generate a standby strategy, comprises:
acquiring internal parameters of the current unmanned aerial vehicle, wherein the internal parameters at least comprise a flight line, a flight speed and a flight attitude;
acquiring external influence parameters of the current unmanned aerial vehicle, wherein the external influence parameters at least comprise air pressure, wind speed and wind direction;
predefining relevance threshold values for all parameters in the internal parameters, and carrying out domain expansion on all parameters based on the relevance threshold values to form a screening domain;
calling the flight strategies in the implementable strategy group, extracting various parameters in the flight strategies to match with the screening domain of the corresponding item, and marking the successfully matched parameter item;
defining the flight strategies with high matching degree of the internal parameters as reference strategies, selecting the strategy with the lowest flight influence rate on the unmanned aerial vehicle from the external influence parameters in the reference strategies, and defining the strategy as an optimal strategy;
optimizing parameters of the optimal strategy during execution based on the deviation between the external influence parameters of the optimal strategy and the external influence parameters of the current unmanned aerial vehicle, and reducing the influence of external environmental factors on the flight of the unmanned aerial vehicle;
and fitting the optimized execution parameters with the optimal strategy to generate the standby strategy.
6. The method of claim 5, wherein recording an application strategy of the drone in response to an abnormal flight that generated the obstacle data, outputting the backup strategy as a flight record in synchronization with the application strategy actually executed, comprises:
generating an actual execution strategy of the unmanned aerial vehicle in response to abnormal flight generating barrier data based on an execution parameter of the current unmanned aerial vehicle in response to the barrier data in flight, and recording the actual execution strategy as an application strategy;
and synchronously outputting the standby strategy and the application strategy as a flight record, wherein the flight record comprises two comparable flight strategies, the standby strategy is a standby reference, and the application strategy is actual execution.
7. The utility model provides a generating device of reserve strategy when unmanned aerial vehicle intelligence flies which characterized in that includes:
a data processing module: acquiring historical flight data, screening abnormal conditions and corresponding flight strategies for association, and establishing a flight strategy database;
a policy matching module: acquiring obstacle data in the flight process, matching the obstacle data with abnormal conditions in a flight strategy database, and calling an implementable flight strategy;
a policy generation module: obtaining internal parameters and external influence parameters of the current unmanned aerial vehicle, screening an optimal strategy in the flight strategies, optimizing execution parameters of the optimal strategy, and generating a standby strategy;
a policy output module: and recording an application strategy of the unmanned aerial vehicle in response to abnormal flight generating obstacle data, and synchronously outputting the standby strategy and the actually executed application strategy as a flight record.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method according to any of claims 1-6 are implemented when the computer program is executed by the processor.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 6.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117111639A (en) * | 2023-10-19 | 2023-11-24 | 浙江容祺科技有限公司 | Unmanned aerial vehicle flight optimal route optimizing method in complex environment |
| CN117170394A (en) * | 2023-09-01 | 2023-12-05 | 中国南方电网有限责任公司超高压输电公司广州局 | Unmanned aerial vehicle emergency control method, device and equipment for converter station inspection |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117170394A (en) * | 2023-09-01 | 2023-12-05 | 中国南方电网有限责任公司超高压输电公司广州局 | Unmanned aerial vehicle emergency control method, device and equipment for converter station inspection |
| CN117170394B (en) * | 2023-09-01 | 2024-04-30 | 中国南方电网有限责任公司超高压输电公司广州局 | Unmanned aerial vehicle emergency control method, device and equipment for converter station inspection |
| CN117111639A (en) * | 2023-10-19 | 2023-11-24 | 浙江容祺科技有限公司 | Unmanned aerial vehicle flight optimal route optimizing method in complex environment |
| CN117111639B (en) * | 2023-10-19 | 2024-01-26 | 浙江容祺科技有限公司 | Unmanned aerial vehicle flight optimal route optimizing method in complex environment |
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