A method, system and electronic device for unmanned vehicle piloting training

Abstract

The application relates to the technical field of unmanned aerial vehicle driving training, and discloses an unmanned aerial vehicle driving training method, system and electronic device, the method comprising the following steps: a trainee selects a simulated meteorological environment, generates a training view, utilizes the training view for training, generates operation information, and a trainer generates guidance information for training guidance. The system and the electronic device correspond to the method. According to the application, the simulation of the meteorological environment improves the real feeling and the simulation effect, the on-screen display of the trainee's view, the trainer's view and the channel view of the training view improves the trainee's control over the driving process, the communication connection of the VR display device realizes the real-time observation of the trainer on the training process of the trainee, the trainer is connected to the training environment of the trainee, which provides a technical basis for real-time guidance, the channel view realizes the real-time feeling of the channel change of the unmanned aerial vehicle, and the training link is supplemented. Finally, the unmanned aerial vehicle driving training is optimized.

Description

Technical Field

[0001] This application relates to the field of drone pilot training technology, specifically a drone pilot training method, system, and electronic equipment. Background Technology

[0002] With the development of the low-altitude economy and drone technology, the demand for drone pilots is increasing, making research on drone pilot training necessary.

[0003] VR technology can create virtual environments for drone pilot training, which is helpful for the development of drone pilot training. Therefore, it is necessary to study the application of VR technology in the field of drone pilot training.

[0004] However, when the inventors were researching the application of VR technology in the field of drone pilot training, they discovered the following problems with the existing technology:

[0005] 1. Virtual training environments built using VR technology have poor realism.

[0006] 2. When using VR technology to build a virtual training environment, only the trainee's first-person perspective is provided. Instructors cannot access the trainee's virtual training environment, and the single perspective makes the trainee's grasp of the driving process poor.

[0007] 3. Trainees cannot experience the changes in the drone's flight path in the virtual training environment, resulting in the absence of an important part of the training.

[0008] In summary, there is an urgent need for a technical solution to optimize drone pilot training. Summary of the Invention

[0009] The purpose of this application is to provide a method, system, and electronic device for training unmanned aerial vehicle (UAV) pilots, in order to solve the technical problems mentioned in the background section.

[0010] To achieve the above objectives, this application discloses the following technical solutions:

[0011] In a first aspect, this application discloses a method for training unmanned aerial vehicle (UAV) pilots, the method comprising:

[0012] S1: Students wear the first VR display device and select a simulated weather environment;

[0013] S2: The waterway simulation model generates a training view based on the simulated meteorological environment;

[0014] S3: Trainees use VR operating devices that are communicatively connected to the first VR display device and the training view to conduct training and generate corresponding operation information;

[0015] S4: The instructor wears the second VR display device, obtains the training view mentioned in step S3, and provides training guidance to the trainees to generate corresponding guidance information;

[0016] Wherein: the simulated meteorological environment is generated based on historical real meteorological environments; the waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments; the training views include student perspective, instructor perspective, and waterway perspective; the operation information specifically refers to the control commands issued by the student through the VR operation device during training;

[0017] The first VR display device is communicatively connected to the second VR display device.

[0018] Preferably, the method further includes:

[0019] A1: Construct the channel simulation model;

[0020] A2: Generate the training view using the aforementioned waterway simulation model;

[0021] Wherein: the training view also includes a corresponding simulated waterway and a simulated view background; the trainee's perspective is the trainee's primary perspective and the instructor's first secondary perspective during training; the instructor's perspective is the trainee's first secondary perspective and the instructor's primary perspective during training; the waterway perspective is the trainee's and instructor's second secondary perspective during training.

[0022] Preferably, the construction of the waterway simulation model specifically includes:

[0023] The historical real weather environment and the corresponding disturbances that occurred when the UAV flew in the real weather environment are obtained and the disturbances are captured.

[0024] A first correspondence is established between the historical real meteorological environment and the disturbance, and the first correspondence is used to match the corresponding disturbance using the historical real meteorological environment;

[0025] The simulated meteorological environment is obtained by performing feature identification on the historical real meteorological environment.

[0026] The first correspondence is updated using the simulated meteorological environment to obtain a second correspondence, which is used to match the corresponding disturbance using the simulated meteorological environment.

[0027] The simulated meteorological environment and the second correspondence are stored in a preset waterway simulation learning model;

[0028] The waterway simulation learning model is trained to obtain the waterway simulation model.

[0029] Preferably, training the waterway simulation learning model specifically includes:

[0030] The following steps are performed to train the waterway simulation learning model:

[0031] B1: Obtain the simulated meteorological environment;

[0032] B2: Fill the background of the simulated view using the simulated meteorological environment;

[0033] B3: Match the corresponding disturbance using the simulated meteorological environment and the second correspondence;

[0034] B4: Obtain the training channel and the trainee's operational information, and update the training channel using the disturbance and operational information obtained in step B3 to obtain the simulated channel;

[0035] B5: Generate the training view based on the simulated waterway and the simulated view background, and display it in the corresponding viewpoints of the trainee, the instructor, and the waterway;

[0036] B6: Repeat steps B1 to B5 until the accuracy of the training view output by the channel simulation learning model is greater than the preset model accuracy threshold, and output the channel simulation learning model as the channel simulation model.

[0037] Preferably, the process of generating the training view using the waterway simulation model specifically includes the following steps:

[0038] C1: The waterway simulation model receives the simulated meteorological environment selected by the trainee;

[0039] C2: Run the channel simulation model to generate the simulated channel and the simulated view background corresponding to the simulated meteorological environment obtained in step C1;

[0040] C3: Using the simulated waterway and the simulated view background obtained in step C2, generate the training view and display it on the first VR display device and the second VR display device;

[0041] C4: Obtain the operation information, repeat steps C2 and C3 to update the simulated waterway, and then update the training view displayed on the first VR display device and the second VR display device.

[0042] Preferably, the training conducted by the trainees using the training view specifically includes:

[0043] Trainees access the training view through a first VR display device;

[0044] The results of the simulated drone performing the operation under the simulated weather environment are obtained from the perspective of the trainees;

[0045] The guidance information is obtained from the instructor's perspective;

[0046] The operational information is obtained from the channel perspective in the simulated channel under the simulated weather environment.

[0047] Preferably, obtaining the training view in step S3 specifically includes:

[0048] The instructor's second VR display device communicates with the student's first VR display device to obtain the student's training view in real time, and switches between the main view and the secondary view to obtain the training view displayed on the instructor's second VR display device.

[0049] Preferably, the generation of the corresponding guidance information specifically includes:

[0050] The instructor obtains the training view through a second VR display device;

[0051] The system utilizes the trainee's perspective to acquire and observe the results of the trainee's simulated drone performing the operation information under the simulated weather environment, and generates corresponding guidance information when guidance is required.

[0052] The instructor inputs the guidance information from their perspective.

[0053] The trainee's operational information is acquired and observed from the channel perspective within the simulated channel under the simulated weather environment.

[0054] Secondly, this application discloses a drone pilot training system, which is applicable to the drone pilot training method described above, and the system includes:

[0055] A simulated meteorological environment acquisition module is configured to upload data after the student wears the first VR display device and selects a simulated meteorological environment.

[0056] The training view generation module is configured to generate a training view based on the simulated meteorological environment from the waterway simulation model and then upload it.

[0057] The training module is configured such that trainees use the training view to conduct training and upload the corresponding operation information after generating it.

[0058] The guidance module is configured such that: the instructor wears a second VR display device, the second VR display device acquires the training view in the training module, provides training guidance to the trainees, generates corresponding guidance information, and then uploads it;

[0059] Wherein: the simulated meteorological environment is generated based on historical real meteorological environments; the waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments; the training views include student perspective, instructor perspective, and waterway perspective; the operation information specifically refers to the control commands issued by the student through the VR operation device during training;

[0060] The first VR display device is communicatively connected to the second VR display device.

[0061] Thirdly, this application discloses an electronic device, including: at least one processor and at least one memory, the memory being communicatively connected to the processor; the memory storing a computer program executable by the processor, wherein when the computer program is executed by the processor, the unmanned aerial vehicle (UAV) pilot training method described above is implemented.

[0062] Beneficial effects: The UAV pilot training method, system, and electronic equipment of this application enhance the realism and simulation effect by simulating meteorological environments. By displaying the student's perspective, instructor's perspective, and flight path perspective on the same screen, the training view improves the student's grasp of the piloting process. The communication connection of the VR display device enables the instructor to observe the student's training process in real time. Integrating the instructor into the student's training environment provides a technical basis for real-time guidance. The flight path perspective allows for real-time perception of UAV flight path changes, supplementing the training process and optimizing UAV pilot training. Attached Figure Description

[0063] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0064] Figure 1 A flowchart illustrating the drone pilot training method provided in this application embodiment;

[0065] Figure 2 This is a structural block diagram of the unmanned aerial vehicle (UAV) pilot training system provided in an embodiment of this application. Detailed Implementation

[0066] The technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0067] In this document, the term "comprising" is intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0068] This embodiment discloses, in its first aspect, as follows: Figure 1 The method shown is a drone pilot training method that uses VR technology and corresponding display and operation devices. The method includes:

[0069] S1: Trainees wear the first VR display device and select a simulated weather environment.

[0070] S2: The waterway simulation model generates a training view based on the simulated meteorological environment.

[0071] S3: Trainees use the training view for training and generate corresponding operation information.

[0072] S4: The instructor wears the second VR display device, obtains the training view from step S3, and provides training guidance to the trainees, generating corresponding guidance information.

[0073] The simulated meteorological environment is generated based on historical real-world meteorological conditions. The waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments. The training views include the trainee's perspective, the instructor's perspective, and the waterway perspective. The operational information specifically refers to the control commands issued by the trainee during training through a VR operating device that communicates with the first VR display device.

[0074] The first VR display device and the second VR display device are connected in communication.

[0075] It should be noted that the generation process of training views and operation information in this embodiment adopts existing VR technology, specifically imaging and interaction technologies.

[0076] Specifically, the method also includes:

[0077] A1: Construct a waterway simulation model.

[0078] A2: Generate training views using a waterway simulation model.

[0079] The training view includes a corresponding simulated waterway and a simulated view background. The trainee's perspective is the trainee's primary view and the instructor's first secondary view during training. The instructor's perspective is the trainee's first secondary view and the instructor's primary view during training. The waterway perspective is the second secondary view for both trainees and instructors during training.

[0080] This embodiment achieves real-time updates of the simulated waterway for trainees based on simulated meteorological environment and operational information by constructing a waterway simulation model, thus providing a high degree of realism in training in a virtual environment.

[0081] Specifically, constructing a waterway simulation model includes:

[0082] Obtain historical real-time weather conditions and corresponding disturbances that occur when the drone flies in those conditions, and capture those disturbances.

[0083] A first correspondence is established between historical real-world meteorological environments and disturbances. This first correspondence is used to match the corresponding disturbances using historical real-world meteorological environments. In this embodiment, the disturbance specifically refers to the change in the flight state of the UAV caused by the meteorological environment. For example, the change in the flight state of the UAV under strong wind conditions is considered a disturbance. By capturing and recording disturbances, a data foundation is provided for optimizing the simulated flight path during trainee training.

[0084] By identifying features from historical real-world meteorological environments, a simulated meteorological environment is obtained. It should be noted that the feature identification technology used here is an existing technology, aiming to extract real-world meteorological conditions and map them into a virtual environment, providing a data foundation for improving the realism of training in a virtual environment.

[0085] The first correspondence is updated using simulated meteorological environment to obtain the second correspondence, which is then used to match the corresponding disturbance using simulated meteorological environment.

[0086] The simulated meteorological environment and the corresponding relationship between them are stored in the preset waterway simulation learning model.

[0087] The waterway simulation learning model is trained to obtain the waterway simulation model.

[0088] Specifically, training the waterway simulation learning model includes:

[0089] The training of the waterway simulation learning model involves the following steps:

[0090] B1: Obtain simulated meteorological environment.

[0091] B2: Filling the background of the simulated view using simulated weather conditions. In this embodiment, background images under different weather conditions are preset. The background of the simulated view, i.e., the background of the training view, is filled by matching the corresponding background image to the simulated weather environment. For example, if the simulated weather environment selected by the trainee is sunny, the background image of sunny weather will be adaptively filled.

[0092] B3: Match the corresponding disturbances using simulated meteorological environment and second correspondence.

[0093] B4: Obtain the training channel and trainee operational information. Update the training channel using the disturbance and operational information obtained in step B3 to obtain the simulated channel. It should be noted that the training channel here is a preset channel used for training, providing the data foundation for optimizing the simulated channel. The specific principle behind obtaining the simulated channel is as follows: trainees train based on the training channel. Under the influence of simulated weather conditions and operational information, the channel piloted by the trainee deviates from the training channel; this channel is the simulated channel. The deviation between the simulated channel and the training channel is displayed in the channel perspective, which helps trainees and instructors observe the driving results in real time, improving training quality.

[0094] B5: Generate a training view based on the simulated waterway and simulated view background, and display it in the corresponding perspectives of trainees, instructors, and waterway.

[0095] B6: Repeat steps B1 to B5 until the accuracy of the training view output by the channel simulation learning model is greater than the preset model accuracy threshold, and then output the channel simulation learning model as the channel simulation model.

[0096] Specifically, generating training views using a waterway simulation model includes the following steps:

[0097] C1: The waterway simulation model receives the simulated meteorological environment selected by the trainee.

[0098] C2: Run the channel simulation model to generate a simulated channel and simulated view background corresponding to the simulated meteorological environment obtained in step C1.

[0099] C3: Using the simulated waterway and the simulated view background obtained in step C2, generate the training view and display it on the first VR display device and the second VR display device.

[0100] C4: Obtain the operation information, repeat steps C2 and C3 to update the simulated waterway, and then update the training view displayed on the first VR display device and the second VR display device.

[0101] This embodiment uses a waterway simulation model to update the simulated waterway in real time, providing a data foundation for training trainees and guidance for instructors, thereby enhancing the realism and supplementing the training process.

[0102] Specifically, trainees utilize the training view for training, which includes:

[0103] Trainees access the training view through a first VR display device;

[0104] The results of the simulated drone performing the operation under the simulated weather environment are obtained from the perspective of the trainees;

[0105] The guidance information is obtained from the instructor's perspective;

[0106] The operational information is obtained from the channel perspective in the simulated channel under the simulated weather environment.

[0107] In this embodiment, the multi-view display provides a data foundation for trainees to improve their driving skills and provides technical support for improving training quality.

[0108] Specifically, obtaining the training view in step S3 includes:

[0109] The instructor's second VR display device communicates with the student's first VR display device to obtain the student's training view in real time, and switches between the main view and the secondary view to obtain the training view displayed on the instructor's second VR display device.

[0110] It should be noted that the training view in the VR display device worn by the instructor is the same as that in the VR display device worn by the trainee; only the content displayed in the primary and secondary viewpoints differs. By connecting the instructor to the trainee's virtual environment, the technical support for real-time guidance is provided. Furthermore, the communication connection between the VR display devices worn by the instructor and the trainee enables training in different spaces, allowing for remote training and significantly improving the flexibility of training for trainees.

[0111] Specifically, generate corresponding guidance information, including:

[0112] The instructor obtains the training view through a second VR display device;

[0113] By utilizing the trainees' perspective, we can acquire and observe the results of the trainees' simulated drones performing operations in simulated weather conditions, and generate corresponding guidance information when guidance is needed.

[0114] Instructional guidance is provided from the instructor's perspective. It should be noted that this guidance can take various forms, including but not limited to text and audio. Trainees receive real-time instruction from the instructor through this guidance, improving the quality of the training.

[0115] The trainees' operational information is obtained and observed from the perspective of the waterway in a simulated waterway under simulated weather conditions.

[0116] This embodiment discloses, in a second aspect, as follows: Figure 2 The system shown is a drone pilot training system applicable to the drone pilot training method described above. The system includes:

[0117] The simulated meteorological environment acquisition module is configured so that students can upload data after wearing the first VR display device and selecting the simulated meteorological environment.

[0118] The training view generation module is configured to generate training views based on the simulated meteorological environment of the waterway simulation model and then upload them.

[0119] The training module is configured so that trainees can use the training view to conduct training and then upload the corresponding operation information.

[0120] The guidance module is configured such that: the instructor wears a second VR display device, which acquires the training view from the training module, provides training guidance to the trainees, generates corresponding guidance information, and then uploads it.

[0121] The simulated meteorological environment is generated based on historical real-world meteorological conditions. The waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments. The training views include the trainee's perspective, the instructor's perspective, and the waterway perspective. The operational information specifically refers to the control commands issued by the trainee through the VR operating device during training.

[0122] The first VR display device and the second VR display device are connected in communication.

[0123] It should be noted that the drone pilot training system in this embodiment corresponds to the drone pilot training method described above. Therefore, the drone pilot training system in this embodiment that is not specifically described may have the same functional definition, working principle and technical effect as the drone pilot training method described above, but is not limited to these. This text will not elaborate on these details here.

[0124] This embodiment discloses an electronic device in a third aspect, comprising: at least one processor and at least one memory, the memory being communicatively connected to the processor. The memory stores a computer program executable by the processor, which, when executed by the processor, implements the drone pilot training method described above.

[0125] In summary, the UAV pilot training method, system, and electronic equipment of this embodiment enhance realism and simulation effects by simulating meteorological environments. The simultaneous display of the trainee's, instructor's, and flight path perspectives in the training view improves the trainee's grasp of the piloting process. The communication connection of the VR display device enables the instructor to observe the trainee's training process in real time. Integrating the instructor into the trainee's training environment provides a technical foundation for real-time guidance. The flight path perspective allows for real-time perception of UAV flight path changes, completing a training component and optimizing UAV pilot training.

[0126] In the embodiments provided in this application, it should be understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code, or any suitable combination thereof. For hardware implementation, the processor may be implemented in one or more of the following: application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, other electronic units designed to implement the functions described herein, or combinations thereof. For software implementation, some or all of the processes of the embodiments may be performed by a computer program instructing the associated hardware. During implementation, the program may be stored in a computer-readable storage medium or transmitted as one or more instructions or code on a computer-readable storage medium. Computer-readable storage media include computer storage media and communication media, wherein communication media include any medium that facilitates the transmission of a computer program from one place to another. Storage media may be any available medium accessible to a computer. Computer-readable storage media may include, but are not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code having the form of instructions or data structures and accessible to a computer.

[0127] Finally, it should be noted that the above description is only a preferred embodiment of this application and is not intended to limit this application. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for training unmanned aerial vehicle (UAV) pilots, characterized in that, The method includes: S1: Students wear the first VR display device and select a simulated weather environment; S2: The waterway simulation model generates a training view based on the simulated meteorological environment; S3: Trainees use VR operating devices that are communicatively connected to the first VR display device and the training view to conduct training and generate corresponding operation information; S4: The instructor wears the second VR display device, obtains the training view mentioned in step S3, and provides training guidance to the trainees to generate corresponding guidance information; Wherein: the simulated meteorological environment is generated based on historical real meteorological environments; the waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments; the training views include student perspective, instructor perspective, and waterway perspective; the operation information specifically refers to the control commands issued by the student through the VR operation device during training; The first VR display device is communicatively connected to the second VR display device; The method also includes: A1: Construct the channel simulation model; A2: Generate the training view using the aforementioned waterway simulation model; Wherein: the training view also includes a corresponding simulated waterway and simulated view background; the trainee's perspective is the trainee's primary perspective and the instructor's first secondary perspective during training; the instructor's perspective is the trainee's first secondary perspective and the instructor's primary perspective during training; the waterway perspective is the trainee's and instructor's second secondary perspective during training; The construction of the waterway simulation model specifically includes: The historical real weather environment and the corresponding disturbances that occurred when the UAV flew in the real weather environment are obtained and the disturbances are captured. A first correspondence is established between the historical real meteorological environment and the disturbance, and the first correspondence is used to match the corresponding disturbance using the historical real meteorological environment; The simulated meteorological environment is obtained by performing feature identification on the historical real meteorological environment. The first correspondence is updated using the simulated meteorological environment to obtain a second correspondence, which is used to match the corresponding disturbance using the simulated meteorological environment. The simulated meteorological environment and the second correspondence are stored in a preset waterway simulation learning model; The waterway simulation learning model is trained to obtain the waterway simulation model.

2. The drone pilot training method according to claim 1, characterized in that, The training of the waterway simulation learning model specifically includes: The following steps are performed to train the waterway simulation learning model: B1: Obtain the simulated meteorological environment; B2: Fill the background of the simulated view using the simulated meteorological environment; B3: Match the corresponding disturbance using the simulated meteorological environment and the second correspondence; B4: Obtain the training channel and the trainee's operational information, and update the training channel using the disturbance and operational information obtained in step B3 to obtain the simulated channel; B5: Generate the training view based on the simulated waterway and the simulated view background, and display it in the corresponding viewpoints of the trainee, the instructor, and the waterway; B6: Repeat steps B1 to B5 until the accuracy of the training view output by the channel simulation learning model is greater than the preset model accuracy threshold, and output the channel simulation learning model as the channel simulation model.

3. The unmanned aerial vehicle (UAV) pilot training method according to claim 1, characterized in that, The process of generating the training view using the waterway simulation model specifically includes the following steps: C1: The waterway simulation model receives the simulated meteorological environment selected by the trainee; C2: Run the channel simulation model to generate the simulated channel and the simulated view background corresponding to the simulated meteorological environment obtained in step C1; C3: Using the simulated waterway and the simulated view background obtained in step C2, generate the training view and display it on the first VR display device and the second VR display device; C4: Obtain the operation information, repeat steps C2 and C3 to update the simulated waterway, and then update the training view displayed on the first VR display device and the second VR display device.

4. The drone pilot training method according to claim 1, characterized in that, The training conducted by trainees using the training view specifically includes: Trainees access the training view through a first VR display device; The results of the simulated drone performing the operation under the simulated weather environment are obtained from the perspective of the trainees; The guidance information is obtained from the instructor's perspective; The operational information is obtained from the channel perspective in the simulated channel under the simulated weather environment.

5. The unmanned aerial vehicle (UAV) pilot training method according to claim 1, characterized in that, The acquisition of the training view in step S3 specifically includes: The instructor's second VR display device communicates with the student's first VR display device to obtain the student's training view in real time, and switches between the main view and the secondary view to obtain the training view displayed on the instructor's second VR display device.

6. The unmanned aerial vehicle (UAV) pilot training method according to claim 1, characterized in that, The generation of corresponding guidance information specifically includes: The instructor obtains the training view through a second VR display device; The system utilizes the trainee's perspective to acquire and observe the results of the trainee's simulated drone performing the operation information under the simulated weather environment, and generates corresponding guidance information when guidance is required. The instructor inputs the guidance information from their perspective. The trainee's operational information is acquired and observed using the channel perspective within the simulated channel under the simulated weather environment.

7. A drone pilot training system, wherein the system is applicable to the drone pilot training method as described in any one of claims 1-6, characterized in that, The system includes: A simulated meteorological environment acquisition module is configured to upload data after the student wears a first VR display device and selects a simulated meteorological environment. The training view generation module is configured to generate a training view based on the simulated meteorological environment from the waterway simulation model and then upload it. The training module is configured such that trainees use the training view to conduct training and then upload the corresponding operation information. The guidance module is configured such that: the instructor wears a second VR display device, the second VR display device acquires the training view in the training module, provides training guidance to the trainees, generates corresponding guidance information, and then uploads it; Wherein: the simulated meteorological environment is generated based on historical real meteorological environments; the waterway simulation model is used to generate corresponding training views based on different simulated meteorological environments; the training views include student perspective, instructor perspective, and waterway perspective; the operation information specifically refers to the control commands issued by the student through the VR operation device during training; The first VR display device is communicatively connected to the second VR display device.

8. An electronic device, characterized in that, include: At least one processor and at least one memory, the memory being communicatively connected to the processor; the memory storing a computer program executable by the processor, which, when executed by the processor, implements the UAV pilot training method as described in any one of claims 1-6.

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