Unmanned aerial vehicle scheduling method and system

Abstract

The invention provides an unmanned aerial vehicle scheduling method and system, and the method comprises the steps: detecting a target execution task corresponding to a target unmanned aerial vehicle in real time when the starting of the target unmanned aerial vehicle is detected in real time, and the target execution task comprises a corresponding starting place and a terminal place; simulating a simulated flight path matched with the target unmanned aerial vehicle in real time according to the starting place and the ending place based on a preset rule, and judging whether a target influence factor influencing the flight of the target unmanned aerial vehicle exists in the simulated flight path or not in real time; and if it is judged in real time that there is a target influence factor influencing the flight of the target unmanned aerial vehicle in the flight path, performing corresponding optimization processing on the simulated flight path to generate a corresponding target flight path in real time, and correspondingly completing the scheduling of the target unmanned aerial vehicle according to the target flight path. According to the invention, flight hidden dangers occurring in the task execution process of the unmanned aerial vehicle can be effectively eliminated, and the working efficiency is correspondingly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicles, and particularly to a method and system for dispatching unmanned aerial vehicles. Background Art

[0002] With the progress of technology and the rapid development of the times, unmanned aerial vehicle technology has also developed rapidly, and unmanned aerial vehicle technology has been deeply applied in many fields, correspondingly improving work efficiency.

[0003] Among them, with the continuous development of unmanned aerial vehicle technology, the prior art can remotely control unmanned aerial vehicles and can make unmanned aerial vehicles fly automatically during the process of dispatching unmanned aerial vehicles to perform corresponding tasks.

[0004] Furthermore, during the process of dispatching unmanned aerial vehicles in the prior art, most of them directly generate corresponding flight paths according to dispatching tasks and make unmanned aerial vehicles execute corresponding tasks according to the flight paths. However, this dispatching method does not consider the actual flight conditions of unmanned aerial vehicles and does not consider the influencing factors on the flight paths of unmanned aerial vehicles, resulting in certain flight hazards during the flight of unmanned aerial vehicles and correspondingly reducing the work efficiency of unmanned aerial vehicles. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for dispatching unmanned aerial vehicles to solve the problem that in the process of dispatching unmanned aerial vehicles in the prior art, the influencing factors on the flight paths of unmanned aerial vehicles are not considered, resulting in flight hazards during the flight of unmanned aerial vehicles.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for dispatching unmanned aerial vehicles, wherein the method includes:

[0008] When it is detected in real time that a target unmanned aerial vehicle is started, a target execution task corresponding to the target unmanned aerial vehicle is detected in real time, and the target execution task includes a corresponding starting location and a termination location;

[0009] Based on a preset rule, a simulated flight path adapted to the target unmanned aerial vehicle is simulated in real time according to the starting location and the termination location, and it is judged in real time whether there are target influencing factors affecting the flight of the target unmanned aerial vehicle in the simulated flight path;

[0010] If it is judged in real time that there are target influencing factors affecting the flight of the target unmanned aerial vehicle in the simulated flight path, corresponding optimization processing is performed on the simulated flight path to generate a corresponding target flight path in real time, and the dispatching of the target unmanned aerial vehicle is completed according to the target flight path.

[0011] The beneficial effects of the present invention are as follows: After detecting the startup of the target UAV in real time, corresponding scheduling processing will be immediately carried out. Specifically, the target execution task corresponding to the current target UAV will be detected in real time. At the same time, a simulated flight path adapted to the current target UAV can be immediately simulated in real time according to the pre-set rules. Based on this, it will be determined in real time whether there are target influencing factors in the current simulated flight path that affect the flight of the target UAV, that is, it will be determined in real time whether the current UAV can execute the corresponding target execution task according to the simulated flight path. Specifically, if so, the current simulated flight path can be immediately optimized and subsequent scheduling can be completed, thereby being able to eliminate the flight hazards of the UAV correspondingly and improving the work efficiency correspondingly.

[0012] Further, the step of simulating a simulated flight path adapted to the target UAV in real time according to the starting point and the ending point based on the preset rules includes:

[0013] When the starting point and the ending point are obtained in real time, real-time parsing processing is performed on the target execution task to detect several task nodes correspondingly included in the target execution task in real time;

[0014] According to the starting point and the ending point, a real-scene map corresponding to the target UAV is matched in real time in the preset map database;

[0015] A simulated flight path adapted to the target UAV is simulated correspondingly according to the real-scene map and several task nodes through a preset program.

[0016] Further, the step of simulating a simulated flight path adapted to the target UAV correspondingly according to the real-scene map and several task nodes through a preset program includes:

[0017] When the real-scene map is obtained in real time, the task location corresponding to each task node is detected in real time, and the task locations corresponding to each task node are different;

[0018] A corresponding target identifier is added to each task location, and each task location is mapped to the real-scene map according to the target identifier;

[0019] A simulated flight path adapted to the target UAV is simulated according to the real-scene map.

[0020] Further, the step of simulating a simulated flight path adapted to the target UAV according to the real-scene map includes:

[0021] Inside the real - scene map, in the direction from the starting location to the ending location, each of the task locations is correspondingly set as a flight node adapted to the drone.

[0022] Inside the real - scene map, each of the flight nodes is connected in sequence to correspondingly form a simulated flight path adapted to the target drone.

[0023] Further, the step of real - time judging whether there are target influencing factors affecting the flight of the target drone in the simulated flight path includes:

[0024] When the simulated flight path is obtained in real time, it is judged in real time whether the endurance mileage of the target drone is greater than the simulated flight path;

[0025] If it is judged in real time that the endurance mileage of the target drone is greater than the simulated flight path, a secondary judgment is immediately executed, and the endurance mileage is a specific value.

[0026] Further, the step of immediately executing the secondary judgment includes:

[0027] If it is judged in real time that the endurance mileage of the target drone is greater than the simulated flight path, it is judged in real time whether the maximum flight height of the target drone is greater than the height of all obstacles in the simulated flight path;

[0028] If it is judged in real time that the maximum flight height of the target drone is greater than the height of all obstacles in the simulated flight path, a tertiary judgment is immediately executed.

[0029] Further, the step of immediately executing the tertiary judgment includes:

[0030] If it is judged in real time that the maximum flight height of the target drone is greater than the height of all obstacles in the simulated flight path, it is judged in real time whether the positioning device of the target drone is in a normal working state;

[0031] If it is judged in real time that the positioning device of the target drone is in a normal working state, it is determined in real time that there are no target influencing factors affecting the flight of the target drone in the simulated flight path, and the simulated flight path is correspondingly set as the target flight path of the target drone.

[0032] The second aspect of the embodiments of the present invention proposes:

[0033] A drone scheduling system, wherein the system includes:

[0034] A detection module, configured to, when detecting in real time that a target unmanned aerial vehicle (UAV) is started, detect in real time a target execution task corresponding to the target UAV, where the target execution task includes a corresponding starting location and an ending location;

[0035] A simulation module, configured to, based on a preset rule, simulate in real time a simulated flight path adapted to the target UAV according to the starting location and the ending location, and determine in real time whether there is a target influencing factor affecting the flight of the target UAV within the simulated flight path;

[0036] A processing module, configured to, if it is determined in real time that there is a target influencing factor affecting the flight of the target UAV within the simulated flight path, perform corresponding optimization processing on the simulated flight path to generate in real time a corresponding target flight path, and complete the scheduling of the target UAV according to the target flight path.

[0037] Further, the simulation module is specifically configured to:

[0038] When obtaining the starting location and the ending location in real time, perform real-time parsing processing on the target execution task to detect in real time a number of task nodes included in the target execution task;

[0039] Match in real time a real-scene map corresponding to the target UAV in a preset map database according to the starting location and the ending location;

[0040] Simulate in real time a simulated flight path adapted to the target UAV according to the real-scene map and the number of task nodes through a preset program.

[0041] Further, the simulation module is specifically configured to:

[0042] When obtaining the real-scene map in real time, detect in real time a task location corresponding to each task node, and the task locations corresponding to each task node are different from each other;

[0043] Add a corresponding target identifier to each task location, and map each task location to the real-scene map according to the target identifier;

[0044] Simulate in real time a simulated flight path adapted to the target UAV according to the real-scene map.

[0045] Further, the simulation module is specifically configured to:

[0046] Inside the real-scene map, set each task location as a flight node adapted to the UAV in the direction from the starting location to the ending location;

[0047] Inside the real - scene map, each of the flight nodes is connected in sequence to correspondingly form a simulated flight path adapted to the target UAV.

[0048] Furthermore, the simulation module is specifically configured to:

[0049] When the simulated flight path is obtained in real - time, it is determined in real - time whether the endurance mileage of the target UAV is greater than the simulated flight path;

[0050] If it is determined in real - time that the endurance mileage of the target UAV is greater than the simulated flight path, a secondary judgment is immediately executed, and the endurance mileage is a specific value.

[0051] Furthermore, the simulation module is specifically configured to:

[0052] If it is determined in real - time that the endurance mileage of the target UAV is greater than the simulated flight path, it is determined in real - time whether the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path;

[0053] If it is determined in real - time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, a third judgment is immediately executed.

[0054] Furthermore, the simulation module is specifically configured to:

[0055] If it is determined in real - time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, it is determined in real - time whether the positioning device of the target UAV is in a normal working state;

[0056] If it is determined in real - time that the positioning device of the target UAV is in a normal working state, it is determined in real - time that there are no target influencing factors affecting the flight of the target UAV within the simulated flight path, and the simulated flight path is correspondingly set as the target flight path of the target UAV.

[0057] The third aspect of the embodiments of the present invention proposes:

[0058] A computer includes a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the UAV scheduling method as described above is implemented.

[0059] The fourth aspect of the embodiments of the present invention proposes:

[0060] A readable storage medium stores a computer program thereon. Wherein, when the program is executed by a processor, the UAV scheduling method as described above is implemented.

[0061] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flowchart of the UAV scheduling method provided for the first embodiment of the present invention;

[0063] Figure 2 A structural block diagram of the UAV scheduling system provided for the third embodiment of the present invention.

[0064] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0065] For the convenience of understanding the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are given in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0066] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0068] Please refer to Figure 1 , which shows the UAV scheduling method provided for the first embodiment of the present invention. The UAV scheduling method provided in this embodiment can accurately simulate the flight hazards faced by the UAV before the UAV actually executes the task, so as to ensure the smooth execution of the UAV task and correspondingly improve the work efficiency.

[0069] Specifically, this embodiment provides:

[0070] A UAV scheduling method, specifically including the following steps:

[0071] Step S10, when it is detected in real time that the target UAV starts, the target execution task corresponding to the target UAV is detected in real time, and the target execution task includes the corresponding starting location and ending location;

[0072] Step S20, based on a preset rule, a simulated flight path adapted to the target UAV is simulated in real time according to the starting location and the ending location, and it is judged in real time whether there are target influencing factors affecting the flight of the target UAV in the simulated flight path;

[0073] Step S30, if it is judged in real time that there are target influencing factors affecting the flight of the target UAV in the simulated flight path, corresponding optimization processing is performed on the simulated flight path to generate a corresponding target flight path in real time, and the scheduling of the target UAV is completed according to the target flight path.

[0074] Specifically, in this embodiment, it should be noted first that in order to accurately simulate the flight process of the UAV before the UAV executes an actual task, it is necessary to simulate the flight scene corresponding to the UAV and the real-time working state of the UAV in real time. Based on this, in order to accurately restore the flight process of the UAV, specifically, in the actual application process, the server set in the background can detect the working state of the UAV in real time. Among them, when the server detects in real time that a certain UAV needs to go out to execute a task, the current UAV is set as the target UAV to be simulated at this time. At the same time, the target execution task required by the current target UAV is detected synchronously. It can be understood that the target execution task will include the corresponding starting location and ending location for subsequent processing.

[0075] Further, after the starting location and the ending location required are detected in real time through the above steps, corresponding simulation processing can be performed at this time. Preferably, corresponding simulation rules are preset inside the server. Based on this, the server can first simulate a simulated flight path adapted to the current target drone in the existing ug three-dimensional program in real time, that is, a path suitable for the current drone to perform tasks. At the same time, it is necessary to further determine in real time whether there are target influencing factors affecting the flight of the current target drone in the current simulated flight path. Specifically, if so, it can correspondingly indicate that there are certain flight hazards in the current simulated flight path, that is, the current simulated flight path will affect the current target drone to perform corresponding tasks. Therefore, it is necessary to optimize the current simulated flight path in real time and be able to output the target flight path correspondingly. Based on this, the current target drone can finally smoothly perform corresponding tasks according to the target flight path. Correspondingly, if not, it can directly indicate that the current simulated flight path is the best flight path and enable the current target drone to fly correspondingly according to the simulated flight path, thereby ensuring the smooth execution of tasks by the drone and improving work efficiency.

[0076] Second Embodiment

[0077] Further, the step of simulating a simulated flight path adapted to the target drone in real time according to the preset rules based on the starting location and the ending location includes:

[0078] When the starting location and the ending location are obtained in real time, perform real-time parsing processing on the target task to detect several task nodes correspondingly included in the target task in real time;

[0079] Match a real-scene map corresponding to the target drone in the preset map database according to the starting location and the ending location in real time;

[0080] Simulate a simulated flight path adapted to the target drone according to the real-scene map and several task nodes through a preset program.

[0081] Further, the step of simulating a simulated flight path adapted to the target drone according to the real-scene map and several task nodes through a preset program includes:

[0082] When the real-scene map is obtained in real time, detect the task location corresponding to each task node in real time, and the task locations corresponding to each task node are different;

[0083] Add a corresponding target identifier to each of the task locations, and map each of the task locations to the real - scene map according to the target identifier;

[0084] Simulate a simulated flight path adapted to the target UAV according to the real - scene map.

[0085] Further, the step of simulating a simulated flight path adapted to the target UAV according to the real - scene map includes:

[0086] Inside the real - scene map, in the direction from the starting location to the ending location, set each of the task locations as a flight node adapted to the UAV;

[0087] Inside the real - scene map, connect each of the flight nodes in sequence to correspondingly form a simulated flight path adapted to the target UAV.

[0088] Further, the step of real - time judging whether there is a target influencing factor affecting the flight of the target UAV in the simulated flight path includes:

[0089] When the simulated flight path is obtained in real time, real - time judge whether the endurance mileage of the target UAV is greater than the simulated flight path;

[0090] If it is real - time judged that the endurance mileage of the target UAV is greater than the simulated flight path, immediately perform a secondary judgment, and the endurance mileage is a specific value.

[0091] Further, the step of immediately performing a secondary judgment includes:

[0092] If it is real - time judged that the endurance mileage of the target UAV is greater than the simulated flight path, real - time judge whether the maximum flight height of the target UAV is greater than the height of all obstacles in the simulated flight path;

[0093] If it is real - time judged that the maximum flight height of the target UAV is greater than the height of all obstacles in the simulated flight path, immediately perform a third judgment.

[0094] Further, the step of immediately performing a third judgment includes:

[0095] If it is real - time judged that the maximum flight height of the target UAV is greater than the height of all obstacles in the simulated flight path, real - time judge whether the positioning device of the target UAV is in a normal working state;

[0096] If it is determined in real time that the positioning device of the target UAV is in a normal working state, it is determined in real time that there are no target influencing factors affecting the flight of the target UAV within the simulated flight path, and the simulated flight path is correspondingly set as the target flight path of the target UAV.

[0097] In addition, in this embodiment, it should also be noted that after the required starting point and ending point are obtained in real time through the above steps, it is necessary to parse and process the target execution task of the current target UAV at this time to generate a simulated flight path adapted to the current target UAV in real time. Specifically, the present invention will detect in real time a number of task nodes included in the current target execution task. At the same time, in order to be able to simulate the real flight environment correspondingly, at this time, a real-scene map corresponding to the current target UAV will be matched in real time in the preset map database according to the above starting point and ending point. Based on this, in order to accurately generate a corresponding simulated flight path in this real-scene map, at this time, the task locations respectively included in each current task node will be further detected. It should be noted that the real-scene map provided by the present invention is a three-dimensional real-scene map. In addition, since the UAV may need to pass through multiple locations during the execution of the task, multiple task locations need to be correspondingly obtained. Based on this, corresponding target identifiers will be immediately added to each current task location. At the same time, according to the order of the current target identifiers, each current task location can be mapped into the current real-scene map one by one, so that each task location can be prominently displayed inside the current real-scene map. Based on this, inside the current real-scene map, through the above three-dimensional program, each current task location can be correspondingly set as a flight node adapted to the current target UAV in the direction from the current starting point to the ending point. Based on this, each current flight node can be connected one by one inside the current real-scene map to form a simulated flight path adapted to the current target UAV in real time for subsequent processing.

[0098] Further, after obtaining the required simulated flight path in real time through the above steps, it is necessary to objectively and accurately determine whether there are flight hazards that will affect the flight of the current target UAV in the current simulated flight path. Specifically, after obtaining the simulated flight path in real time through the above steps, the length of the current simulated flight path will be calculated first. Correspondingly, the present invention will synchronously detect the maximum cruising range of the current target UAV and determine in real time whether the maximum cruising range of the current target UAV is greater than the length of the current simulated flight path. Specifically, if so, a secondary judgment can be made again. Correspondingly, if not, the simulated flight path needs to be shortened accordingly. Based on this, after determining in real time that the endurance mileage of the target UAV is greater than the simulated flight path, it will be further determined whether the maximum flight altitude of the current target UAV is greater than the height of all obstacles in the current simulated flight path, that is, it is determined in real time whether the current target UAV can fly smoothly along the current simulated flight path, that is, whether it will be blocked. Specifically, if so, it is correspondingly determined that the current target UAV can fly normally and the final third judgment is immediately executed. Correspondingly, if not, the current simulated flight path needs to be changed accordingly, that is, the current target UAV needs to bypass the current obstacle affecting flight, so as to complete the optimization of the current simulated flight path. Based on this, after determining in real time through the above steps that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, it will finally be determined whether the positioning device of the current target UAV is in a normal working state. Specifically, if so, the current target UAV will execute the corresponding task according to the above target flight path. Correspondingly, if not, the current target UAV needs to be repaired, and after the repair is completed, the current target UAV will execute the corresponding task according to the above target flight path, so that possible flight hazards can be accurately simulated before the target UAV actually executes the task, and thus the scheduling of the UAV can be successfully completed, improving the work efficiency.

[0099] Please refer to Figure 2 , the third embodiment of the present invention provides:

[0100] An unmanned aerial vehicle scheduling system, wherein the system includes:

[0101] A detection module, configured to, when detecting in real time that the target UAV is started, detect in real time the target execution task corresponding to the target UAV, and the target execution task includes a corresponding starting point and an ending point;

[0102] A simulation module, configured to, based on a preset rule, simulate in real time a simulated flight path adapted to the target UAV according to the starting point and the ending point, and determine in real time whether there are target influencing factors in the simulated flight path that affect the flight of the target UAV;

[0103] A processing module, which is configured to, if it is determined in real time that there is a target influencing factor in the simulated flight path that affects the flight of the target unmanned aerial vehicle (UAV), perform corresponding optimization processing on the simulated flight path to generate a corresponding target flight path in real time, and complete the scheduling of the target UAV according to the target flight path.

[0104] Further, the simulation module is specifically configured to:

[0105] When the starting location and the ending location are obtained in real time, perform real-time parsing processing on the target execution task to detect in real time a number of task nodes included in the target execution task;

[0106] In a preset map database, match in real time a real-world map corresponding to the target UAV according to the starting location and the ending location;

[0107] Through a preset program, simulate a simulated flight path adapted to the target UAV according to the real-world map and the number of task nodes.

[0108] Further, the simulation module is specifically configured to:

[0109] When the real-world map is obtained in real time, detect in real time a task location corresponding to each task node, and the task locations corresponding to each task node are different;

[0110] Add a corresponding target identifier to each task location, and map each task location to the real-world map according to the target identifier;

[0111] Simulate a simulated flight path adapted to the target UAV according to the real-world map.

[0112] Further, the simulation module is specifically configured to:

[0113] Inside the real-world map, in the direction from the starting location to the ending location, set each task location as a flight node adapted to the UAV;

[0114] Inside the real-world map, connect each flight node in sequence to form a simulated flight path adapted to the target UAV.

[0115] Further, the simulation module is specifically configured to:

[0116] When the simulated flight path is obtained in real time, determine in real time whether the endurance of the target UAV is greater than the simulated flight path;

[0117] If it is determined in real time that the endurance mileage of the target UAV is greater than the simulated flight path, a secondary judgment is immediately executed, and the endurance mileage is a specific value.

[0118] Further, the simulation module is specifically configured to:

[0119] If it is determined in real time that the endurance mileage of the target UAV is greater than the simulated flight path, it is determined in real time whether the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path;

[0120] If it is determined in real time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, a third judgment is immediately executed.

[0121] Further, the simulation module is specifically configured to:

[0122] If it is determined in real time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, it is determined in real time whether the positioning device of the target UAV is in a normal working state;

[0123] If it is determined in real time that the positioning device of the target UAV is in a normal working state, it is determined in real time that there are no target influencing factors affecting the flight of the target UAV within the simulated flight path, and the simulated flight path is correspondingly set as the target flight path of the target UAV.

[0124] The fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the UAV scheduling method described above is implemented.

[0125] The fifth embodiment of the present invention provides a readable storage medium, on which a computer program is stored. Wherein, when the program is executed by a processor, the UAV scheduling method described above is implemented.

[0126] In summary, the UAV scheduling method and system provided by the above embodiments of the present invention can accurately simulate the flight hazards faced by the UAV before the UAV executes an actual task, correspondingly improving the working efficiency of the UAV.

[0127] It should be noted that the above-mentioned various modules can be functional modules or program modules, and can be implemented either by software or by hardware. For the modules implemented by hardware, the above-mentioned various modules can be located in the same processor; or the above-mentioned various modules can also be located in different processors in any combined form.

[0128] The logic and / or steps represented in the flowchart or otherwise described herein can, for example, be considered as a definitional sequence of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device. As used in this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

[0129] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, as the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0130] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0131] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0132] The above-described embodiments merely represent several implementation manners of the present invention. The description thereof is relatively specific and detailed, but it should not be construed as a limitation on the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all fall within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the appended claims.

Claims

1. A method for unmanned aerial vehicle scheduling, characterized in that, The method includes: When it is detected in real time that the target UAV starts, the target execution task corresponding to the target UAV is detected in real time, and the target execution task includes the corresponding starting location and ending location; Based on a preset rule, a simulated flight path adapted to the target UAV is simulated in real time according to the starting location and the ending location, and it is judged in real time whether there are target influencing factors affecting the flight of the target UAV in the simulated flight path; If it is judged in real time that there are target influencing factors affecting the flight of the target UAV in the simulated flight path, corresponding optimization processing is performed on the simulated flight path to generate a corresponding target flight path in real time, and the scheduling of the target UAV is completed according to the target flight path.

2. The drone scheduling method according to claim 1, wherein: The step of simulating in real time a simulated flight path adapted to the target UAV based on a preset rule according to the starting location and the ending location includes: When the starting location and the ending location are obtained in real time, real-time parsing processing is performed on the target execution task to detect in real time a number of task nodes included in the target execution task; A real-scene map corresponding to the target UAV is matched in real time in a preset map database according to the starting location and the ending location; A simulated flight path adapted to the target UAV is simulated through a preset program according to the real-scene map and a number of the task nodes.

3. The drone scheduling method according to claim 2, characterized in that: The step of simulating through a preset program a simulated flight path adapted to the target UAV according to the real-scene map and a number of the task nodes includes: When the real-scene map is obtained in real time, the task locations respectively corresponding to each of the task nodes are detected in real time, and the task locations corresponding to each of the task nodes are different; A corresponding target identifier is added to each of the task locations, and each of the task locations is mapped into the real-scene map according to the target identifier; A simulated flight path adapted to the target UAV is simulated according to the real-scene map.

4. The drone scheduling method according to claim 3, wherein: The step of simulating a simulated flight path adapted to the target UAV according to the real-scene map includes: Inside the real-scene map, in the direction from the starting location to the ending location, each of the task locations is set as a flight node adapted to the UAV; Inside the real-scene map, each of the flight nodes is connected in sequence to form a simulated flight path adapted to the target UAV.

5. The drone scheduling method according to claim 4, wherein: The step of judging in real time whether there are target influencing factors affecting the flight of the target UAV in the simulated flight path includes: When the simulated flight path is obtained in real time, it is judged in real time whether the endurance mileage of the target UAV is greater than the simulated flight path; If it is judged in real time that the endurance mileage of the target UAV is greater than the simulated flight path, a secondary judgment is immediately executed, and the endurance mileage is a specific value.

6. The drone scheduling method according to claim 5, wherein: The step of immediately executing the secondary judgment includes: If it is determined in real time that the endurance mileage of the target UAV is greater than the simulated flight path, it is determined in real time whether the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path; If it is determined in real time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, three judgments are immediately executed.

7. The drone scheduling method according to claim 6, wherein: The step of immediately executing three judgments includes: If it is determined in real time that the maximum flight altitude of the target UAV is greater than the height of all obstacles in the simulated flight path, it is determined in real time whether the positioning device of the target UAV is in a normal working state; If it is determined in real time that the positioning device of the target UAV is in a normal working state, it is determined in real time that there are no target influencing factors affecting the flight of the target UAV within the simulated flight path, and the simulated flight path is correspondingly set as the target flight path of the target UAV.

8. A drone scheduling system, characterized in that, The system includes: A detection module, configured to, when it is detected in real time that the target UAV is started, detect in real time a target execution task corresponding to the target UAV, where the target execution task includes a corresponding starting location and an ending location; A simulation module, configured to simulate in real time a simulated flight path adapted to the target UAV based on a preset rule according to the starting location and the ending location, and determine in real time whether there are target influencing factors affecting the flight of the target UAV within the simulated flight path; A processing module, configured to, if it is determined in real time that there are target influencing factors affecting the flight of the target UAV within the simulated flight path, perform corresponding optimization processing on the simulated flight path to generate a corresponding target flight path in real time, and complete the scheduling of the target UAV according to the target flight path.

9. A computer, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the UAV scheduling method according to any one of claims 1 to 7.

10. A readable storage medium, on which a computer program is stored, characterized in that, When the program is executed by the processor, it implements the UAV scheduling method according to any one of claims 1 to 7.

Images