CN107168346A - A kind of asynchronous system brain control UAS based on wearable display - Google Patents

Abstract

The invention discloses an asynchronous brain-controlled unmanned aerial vehicle system based on a wearable display. The wearable display is used to present a group of visual stimulation units flashing at different frequencies, corresponding to a set of different operating instructions of the unmanned aerial vehicle. The user looks at different visual stimulation units, and the resulting EEG signals are processed to identify the stimulation unit and the corresponding operation instructions that the user is looking at, and the recognition results are sent to the drone for execution. The scene picture is sent back to the ground, superimposed with the visual stimulation unit, and displayed on the wearable display. Providing the user with first-person perspective feedback can improve the portability of the steady-state visual evoked potential brain-computer interface system. The present invention also makes full use of the idle state decoding, which can greatly reduce the operation burden and fatigue feeling of using the brain-computer interface to control the flight, and give the user a more free flying experience.

Description

An asynchronous brain-controlled UAV system based on wearable display

technical field

The invention belongs to the technical fields of biomedical engineering and automatic control, in particular, it relates to a steady-state visual evoked potential presentation method and a brain-computer interface asynchronous control drone flight system based on it, especially a wearable display-based Asynchronous brain-controlled UAV system.

Background technique

Brain-computer interface is a technology that can realize the interaction between human and the outside world without relying on external muscles. It can help patients with limited mobility, paralysis, and stroke to re-establish contact with the outside world, express their wishes, and assist in daily life. The asynchronous brain-computer interface allows the system to follow the patient's wishes, rather than the patient following the system's orders, which has great potential use value and development prospects. Commonly used EEG patterns include motor imagery, steady-state visual evoked potentials, and P300.

Steady-state visual evoked potential is when the human eye receives a certain frequency of visual stimulation, the occipital lobe of the brain is induced to produce a response signal that is the same as the frequency of the stimulation or multiplied by the frequency, and the signal can be recognized and converted into a corresponding control command Used to control external devices. Brain-computer interface systems based on steady-state visual evoked potentials have been extensively studied due to their advantages of stability, minimal training, many control commands that can be provided, and high information transmission rates that can be achieved with simple data processing methods. Existing brain-computer interface systems based on steady-state visual evoked potentials usually use LED boards/LCD/CRT screens as visual stimulus presentation means, resulting in the overall system being very bloated, not easy to carry, and not immersive enough for users to operate , which adversely affects the practicability of the system.

As a current research hotspot, UAVs have been extensively studied for their huge potential in practicality, especially when UAVs are equipped with some external equipment such as robotic arms, cameras, various manipulation devices, etc. It brings a lot of help and meets the life needs of many remote operations of people with disabilities, such as going out to find the way, shopping for vegetables, and transporting things. However, existing drones generally use remote controls or flight ground software, which are not easy to use for people with handicapped hands and feet, and they often have more urgent needs than able-bodied people.

The "UAV control method based on steady-state visual evoked potential" of Southeast University and "an aircraft control device based on steady-state visual method and device, but the visual stimulation unit is still located at a certain distance directly in front of the user, which affects the user's sense of participation; in addition, the user needs to keep looking at the block when flying in a certain direction, due to the steady state The visual evoked stimulation unit itself will bring fatigue to the user, and long-term staring will bring a strong sense of flickering and fatigue to the user, which reduces the ease of use of the system and the user's recognition of the system. Over time, Users will become less and less willing to use the system.

Contents of the invention

In view of the above-mentioned deficiencies in the prior art, the present invention aims to provide an asynchronous steady-state visual evoked potential brain-controlled drone system based on a wearable display, so as to effectively improve the portability of the system and reduce user fatigue sense and operational burden to ultimately improve the usability of the system.

The present invention specifically adopts the following technical solutions to solve the above-mentioned technical problems.

An asynchronous brain-controlled unmanned aerial vehicle system based on a wearable display, including a wearable display and a steady-state visually evoked stimulation unit mounted on the wearable display, an EEG signal acquisition unit, and an EEG signal processing unit; wherein:

The steady-state visual evoking stimulation unit induces and generates EEG signals through visual stimulation;

The EEG signal acquisition unit is used to collect EEG signals and send them to the EEG signal processing unit for real-time processing and identification, and send the recognition results to the UAV.

Preferably, the steady state visual evoking stimulation unit includes a plurality of visual stimulation subunits with different flicker frequencies.

Preferably, the plurality of visual stimulation subunits are: forward subunit, upward subunit, downward subunit, left rotor unit and right rotor unit, correspondingly, each visual stimulation subunit corresponds to forward, Up, down, left turn, right turn control commands.

Preferably, the backward control command is realized by successive forward, upward, downward, left turn and/or right turn control commands.

Preferably, the flickering frequencies of the forward subunit, the left rotor unit, the right rotor unit, the up subunit and the down subunit are 10.7Hz, 9.37Hz, 8.33Hz, 12.5Hz and 7.5Hz respectively.

Preferably, the EEG signal acquisition unit includes a portable EEG acquisition device and a wireless transmission module; wherein:

The portable EEG acquisition device is an EEG acquisition device capable of collecting any number of channels of the EEG signals generated in the occipital region of the cerebral cortex, and is used to collect EEG signals;

The wireless transmission module is used to send the collected EEG signal to the EEG signal processing unit.

Preferably, the EEG signal processing unit includes a classification processing module and a classification recognition module; wherein:

The classification processing module is used for feature extraction and classification of the received EEG signals;

The classification and identification module is used to identify the classified EEG signals, and the obtained identification results are sent to the drone.

Preferably, the classification processing module uses a canonical correlation analysis method for feature extraction and classification.

Preferably, the classification processing module classifies the EEG signals into: idle state and working state; wherein:

When the user gazes at the steady-state visual evoking stimulation unit, the EEG signal is classified as a working state;

When the user looks away from the steady-state visual evoking stimulation unit, the EEG signal will be classified as an idle state.

Preferably, the classification and identification module adopts an idle state identification method based on threshold detection to identify the classified EEG signals, and when the ratio of the largest correlation coefficient to the next largest correlation coefficient is less than or equal to the set threshold, it is judged as an idle state, Otherwise, it is in the working state; the flight direction corresponding to the flicker frequency corresponding to the maximum correlation coefficient in the working state is output to the UAV as the recognition result, and the recognition result sent to the UAV in the idle state is still translated into the latest working state. flight direction.

Preferably, the wearable display-based asynchronous brain-controlled UAV system also includes a real-time scene acquisition and transmission unit, which is mounted on the UAV to collect real-time images of the UAV. The image frame is transmitted to the wearable display; the real-time image frame is superimposed with the steady-state visual evoking stimulation unit and displayed on the wearable display.

Preferably, the real-time scene collection and transmission unit includes a camera and a video capture card; wherein:

The camera is used for the acquisition of unmanned aerial vehicle flight video images;

The video capture card is used to wirelessly transmit the captured drone flight video images to the wearable display.

Compared with the prior art, the present invention has the following beneficial effects:

1. Traditional brain-computer interface systems based on steady-state visual evoked potentials usually use LED boards/LCD/CRT screens as visual stimulus presentation methods, resulting in a bloated overall system that is not easy to carry and does not give users enough operating experience Immersion, which adversely affects the usability of the system. The display means proposed by the present invention displays the stimulation unit and the visual feedback screen on a wearable display, and a group of visual stimulation units with different flickering frequencies surround the feedback screen without blocking the visual field of the feedback screen. Wearing the display, the user can control the drone immersively and understand the current flight environment.

2. In the traditional brain-computer interface control UAV system, the user needs to keep watching the box while controlling the flight in a certain direction. Since the steady-state visual evoked stimulation unit itself will bring fatigue to the user, it will take a long time Staring will bring a strong sense of flickering and fatigue to the user, reducing the ease of use of the system and the user's recognition of the system. As time passes, the user will become less and less willing to use the system. In the control paradigm proposed by the present invention, the user only needs to watch the visual stimulation unit when switching the flight direction, and can maintain the flying state of the drone without continuously watching the visual stimulation unit, which reduces the user's operating burden and fatigue, and the user It can also maintain a continuous grasp of the flight status of the drone, and will not have time to pay attention to the feedback of the flight scene because of the continuous gazing at the stimulation unit, and can also be more focused when gazing at the stimulation unit, without the need to continue to distract attention in the flight scene. It is beneficial to improve the overall performance of the system.

3. The traditional UAV control method requires the operation of both hands. The control method proposed by the present invention only requires the user to switch the spatial attention, and provides a method for the disabled to control the UAV, which can help them life and improve the quality of life.

Description of drawings

Other characteristics, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:

Fig. 1 is a system schematic diagram of a preferred embodiment of the present invention;

Fig. 2 is the display schematic diagram of the steady-state visual evoked stimulation unit and the real-time scene feedback screen on the wearable display;

Fig. 3 is the placement position figure of the electrode in the portable EEG acquisition device on the scalp;

Figure 4 is a flow chart of the principle of the asynchronous control paradigm.

detailed description

The following is a detailed description of the embodiments of the present invention: this embodiment is implemented on the premise of the technical solution of the present invention, and provides detailed implementation methods and specific operation processes. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention, and these all belong to the protection scope of the present invention.

Example

The asynchronous brain-controlled unmanned aerial vehicle system based on the wearable display provided in this embodiment adopts a steady-state visually evoked stimulation unit (potential), and uses a wearable display to present a group of visual stimulation subunits flashing at different frequencies, respectively corresponding to no A set of different operation instructions of the man-machine, the user looks at different visual stimulation sub-units, the resulting EEG signals are processed and the stimulation sub-units and their corresponding operation instructions that the user is looking at are identified, and the recognition results are Send it to the drone for execution, and the real-time scene of the drone is sent back to the ground, superimposed with the steady-state visual evoked stimulation unit, displayed on the wearable display, and provides the user with first-person perspective feedback; also by designing an asynchronous The paradigm of controlled flight is used to reduce the operational burden and fatigue of using brain-computer interface to control flight.

Further, the steady-state visual-evoking stimulation unit and the visual feedback picture are displayed on a wearable display, and the feedback picture is surrounded by a group of visual stimulation subunits with different flickering frequencies so as not to affect the user's understanding of the real-time flight scene. Wearing the display, the user can control the drone immersively and understand the current flight environment.

Further, in order to ensure a high recognition rate and stability, and to ensure that users can have a complete viewing experience on the visual feedback screen, in this embodiment, there are five types of visual stimulation subunits: forward subunit, upward subunit , down subunit, left rotor unit, and right rotor unit, corresponding to five commonly used control commands: forward control command, upward control command, downward control command, left turn control command, right turn control command, which can realize Control of UAV flight in 3D space. As backward, it can be realized through continuous five control command lines, such as turning left twice.

Further, in order to improve the portability of the UAV system, the EEG signal acquisition unit adopts a portable acquisition device (portable EEG acquisition device).

Preferably, when classifying, the EEG signal processing unit adopts a typical correlation analysis method for feature extraction and classification, and when identifying the idle state and the working state, adopts a very practical idle state identification method based on threshold detection. When the maximum correlation When the ratio of the coefficient to the next largest correlation coefficient is less than or equal to a certain threshold, it is judged as an idle state, otherwise it is a working state, and the flight direction corresponding to the stimulation frequency corresponding to the largest correlation coefficient in the working state is the classification result.

Further, in order to reduce the operating burden and fatigue experience of the user, in the UAV system, the user only needs to watch the visual stimulation unit when switching the flight direction, and can maintain the flying state of the UAV without continuously watching the visual stimulation unit. . (1) After the user looks at a certain stimulation unit and is recognized, the aircraft will fly in this direction; (2) The user can look away from the stimulation unit and turn to the visual feedback screen to grasp the flight status. Continue to fly in this direction; (3) Afterwards, the user can look at other stimulation units according to their wishes in combination with the flying state. After being recognized, the user can look away and repeat the above (1) (2) process. At the same time, the user is not limited to this process. When the user wants to quickly switch between directions, the process (2) can still be omitted. The implementation method of the asynchronous control paradigm is that the user looks at the stimulation unit, and its EEG signal is classified into the flight direction corresponding to the unit in the working state; Its EEG signals will be classified as idle, but the commands sent to the aircraft will still be translated into the flight direction in the last working state. Wait until the next time the EEG signal is resolved into other flight directions, and the instructions sent to the aircraft will change to other flight directions.

Furthermore, the drone flight video images are collected by the camera mounted on the drone, and wirelessly transmitted back to the wearable display via the video capture card.

The present invention will be described more fully hereinafter with reference to the accompanying drawings, in which various embodiments are shown.

Aiming at the various problems existing in the control of unmanned aerial vehicles with steady-state visual evoked potentials, as shown in Figure 1, the solution of the present invention is to use wearable displays and design new control paradigms to control the flight of unmanned aerial vehicles. It is: using a wearable display to present a group of visual stimulation sub-units that flash at different frequencies, corresponding to a set of different operating instructions of the drone, the user looks at different visual stimulation units, and the resulting EEG signals are processed And identify the stimulation unit that is watched by the user and its corresponding operation command, the recognition result is sent to the drone for execution, the real-time scene of the drone is sent back to the ground, superimposed with the visual stimulation sub-unit, and displayed on the The wearable display provides the user with first-person perspective feedback; at the same time, an asynchronous control flight paradigm is designed to make full use of idle state decoding to reduce the operational burden and fatigue of using the brain-computer interface to control flight.

Embodiments of the present invention and concrete processes thereof are as follows:

As shown in Figure 2, the wearable display used in this embodiment can be Fat Shark FSV1074 HD2, and its spectacle lenses are two 800×600 LCD screens, which allow the development of visual images in the glasses, and can also receive data from external devices. To the image, support to connect with the computer HDMI cable to project. The use method of this embodiment can be to use the OPEN GL library to draw the visual stimulation unit, and draw the pictures sent back by the drone together on the wearable display.

As shown in Figure 2, in this embodiment, five visual stimulation units surround the real-time scene interaction screen from the periphery, and the five visual stimulation frequencies (flicker frequencies) can be 10.7Hz, 9.37Hz, 8.33Hz, 12.5Hz, 7.5Hz respectively , corresponding to the five flight directions of forward, left, right, up, and down, and the operator can choose to look at the corresponding stimulation unit according to his own intention.

The present invention uses an EEG collection device capable of collecting signals generated in the occipital region of the cerebral cortex with any number of channels. This embodiment can use the portable acquisition device Emotiv Epoc, which is a wireless EEG acquisition device with 14 channels + 2 reference channels. It adopts wireless Bluetooth technology and has a battery life of up to 12 hours. conductive paste. As shown in Fig. 3, the electrodes in the embodiment mainly select the positions of P3, P4, 01, and 02.

In this embodiment, in terms of data transmission, the control command can be communicated to the aircraft by serial port + XBee wireless data transmission, and the real-time scene picture can be returned to the wearable display by wireless image transmission module + UVC video acquisition card.

In this embodiment, the EEG signal processing module can be a Win32 application program written in Visual C++, which has the functions of data receiving, saving, online processing, and instruction sending. When processing EEG signals, first perform 5-64Hz band-pass filtering, and then perform canonical correlation analysis on the EEG signals at a calculation speed of 1s window length and 0.125s sliding window length, so as to complete feature extraction, among which canonical correlation analysis In the algorithm, the reference signal is composed of the fundamental wave and harmonics corresponding to the stimulation frequency, and each stimulation frequency and the EEG signal will output the maximum correlation coefficient through correlation analysis. There are five stimulation frequencies (flicker frequencies) in this embodiment, so Produces the five largest correlation coefficients. As shown in Figure 4, first there is a discrimination between the idle state and the working state. Among the five largest correlation coefficients, if the ratio of the largest one to the second largest one is less than a certain threshold, it is regarded as the idle state. In the idle state, The output command is mapped to the command of the latest working state, so that the flight can be continued in the original direction. If it is judged to be in the working state, then output the flight command corresponding to the largest one of the five largest correlation coefficients.

In this embodiment, in order to ensure the flight stability of the UAV, when the EEG signal processing module detects that the working state instruction is switched, the UAV will fly along this direction at a slower speed within 1 second after the instruction has just been switched. , while ignoring other instructions transmitted within this 1s. After 1s, whether the user controls the UAV to continue to fly faster in this direction in an idle state or watches other stimuli to switch the flight direction, this 1s buffer time will help the drone The machine remains stable when switching between categories.

In this embodiment, the ARDrone unmanned aerial vehicle can be used, and the aircraft end receives the control command, and automatically adjusts the attitude according to the control command to realize the flight in the corresponding direction. At the same time, the camera equipped on the aircraft transmits the real-time images back to the wearable display through the wireless image transmission module, and the wearable display receives the images and draws them.

In this embodiment, the specific implementation process of using the system to control the drone is as follows:

(1) Select five healthy subjects, labeled S1 to S5.

(2) Pre-experiment: Each subject received a pre-experiment in total. In each experiment, the subject first wore the EEG acquisition device Emotiv Epoc and the wearable display Fat shark FSV1074 HD2, and then stared at different images in turn according to the prompts. The visual stimulation block is 5s, and each block is randomly prompted. In addition, it will be prompted to be idle. At this time, the subject should focus on the center of the screen. In this experiment, the feedback screen is replaced by a static image, and each experiment lasts 240s.

(3) During the pre-experiment, the EEG signal processing module, that is, the Win32 application program, records and saves the experimental data. After the experiment, the module filters and classifies the saved data offline, and automatically searches for each subject. The most appropriate idle state detection threshold.

(4) UAV control experiment: The subject controls the UAV to fly according to his own wishes. At this time, the EEG signal processing module processes and classifies the EEG signal of the subject online according to the optimal threshold obtained in (3), and Output control commands to the aircraft end, and the aircraft end sends back real-time feedback screens to the subjects. The subject can first stare at the forward square, and then the aircraft starts to fly forward slowly for 1 second. If the subject wants to: a. Continue to fly forward, he can not watch any stimulus and observe the feedback screen, and the drone will fly at a faster speed. Keep the speed forward; b. Change the flight direction, if you turn right, look at the right turn square, and the aircraft will turn right at a slower speed for 1 second; c. And so on.

In this example:

This embodiment provides an asynchronous steady-state visual evoked potential control drone system based on a wearable display, including: a set of steady-state visual evoked stimulation units and a first-person perspective feedback screen are presented on the wearable display, The user wears the display and chooses to look at the visual stimulation unit corresponding to a certain flight direction to induce the corresponding EEG signal, which is processed and recognized by the signal processing module, and the recognition result is sent to the drone, and the drone immediately It can fly in the corresponding flight direction according to the user's wishes, and the real-time scene of the drone is transmitted back to the ground, superimposed with the visual stimulation unit, and displayed on the wearable display. There is also an asynchronous control flight paradigm that takes advantage of idle state decoding.

The steady-state visual evoking stimulation unit and visual feedback images are displayed on the wearable display, and the user can control the drone immersively and understand the current flight environment by wearing the display.

The group of visual stimulation subunits with different flickering frequencies are surrounded by external feedback images, different visual stimulation subunits: arrows of forward subunit, upward subunit, downward subunit, left rotor unit and right rotor unit Corresponding to the flight directions of the UAV forward, upward, downward, left turn, and right turn respectively.

The EEG signal is acquired by a portable acquisition electrode (portable acquisition device) and wirelessly transmitted to the signal processing module for processing. The EEG signal processing process mainly includes: (1) band-pass filtering; (2) classification based on canonical correlation analysis method; and (3) an idle state identification method based on threshold detection, when the ratio of the maximum correlation coefficient to the next largest correlation coefficient is less than or equal to a certain threshold, it is judged as an idle state, otherwise it is a working state, and the maximum correlation coefficient corresponding to the working state The flight direction corresponding to the stimulus frequency is the classification result, which is wirelessly transmitted to the drone.

In the unmanned aerial vehicle system, the user only needs to watch the visual stimulation unit when switching the flight direction, and can maintain the flying state of the drone without continuously watching the visual stimulation unit. (1) After the user looks at a certain stimulation unit and is recognized, the aircraft will fly in this direction; (2) The user can look away from the stimulation unit and turn to the visual feedback screen to grasp the flight status. Continue to fly in this direction; (3) Afterwards, the user can look at other stimulation units according to their wishes in combination with the flying state. After being recognized, the user can look away and repeat the above (1) (2) process. At the same time, the user is not limited to this process. When the user wants to quickly switch between directions, the process (2) can still be omitted.

The implementation method of the asynchronous control paradigm is the above-mentioned idle state detection method, the user looks at the stimulation unit, and its EEG signal is classified as the flight direction corresponding to the unit in the working state; the user moves away from a certain visual stimulation unit After the eyes turn to the visual feedback screen, the EEG signal will be classified as an idle state, but the commands sent to the aircraft end will still be translated into the flight direction in the last working state. Wait until the next time the EEG signal is resolved into other flight directions, and the instructions sent to the aircraft will change to other flight directions.

The drone flight video picture is collected by a camera mounted on the drone, and wirelessly transmitted back to the wearable display via a video capture card.

This embodiment provides users with first-person perspective feedback, which can improve the portability of the steady-state visual evoked potential brain-computer interface system. It also makes full use of idle state decoding, which can greatly reduce the operational burden and fatigue of using the brain-computer interface to control flight. Feel and give users a more free flying experience.

Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention.

Claims (10)

1. An asynchronous brain-controlled unmanned aerial vehicle system based on a wearable display, characterized in that it includes a wearable display and a steady-state visually evoked stimulation unit, an EEG signal acquisition unit and an EEG signal mounted on the wearable display. processing unit; where: The steady-state visual evoking stimulation unit induces and generates EEG signals through visual stimulation; The EEG signal acquisition unit is used to collect EEG signals and send them to the EEG signal processing unit for real-time processing and identification, and send the recognition results to the UAV. 2. The asynchronous brain-controlled unmanned aerial vehicle system based on a wearable display according to claim 1, wherein the steady-state visually evoked stimulation unit includes a plurality of visually stimulating subunits with different flicker frequencies. 3. The asynchronous brain-controlled UAV system based on a wearable display according to claim 2, wherein a plurality of visual stimulation subunits are respectively: forward subunit, upward subunit, downward subunit, left The rotor unit and the right rotor unit, correspondingly, each visual stimulation subunit corresponds to the control commands of forward, upward, downward, left turn and right turn respectively; It also includes a backward control command, which is realized by successive forward, upward, downward, left turn and/or right turn control commands. 4. The asynchronous brain-controlled unmanned aerial vehicle system based on wearable display according to claim 2, is characterized in that, described forward subunit, left rotor unit, right rotor unit, upward subunit and downward subunit The flashing frequencies of the units are 10.7Hz, 9.37Hz, 8.33Hz, 12.5Hz and 7.5Hz respectively. 5. The asynchronous brain-controlled UAV system based on the wearable display according to claim 1, wherein the EEG signal acquisition unit includes a portable EEG acquisition device and a wireless transmission module; wherein: The portable EEG acquisition device is used to collect EEG signals; The wireless transmission module is used to send the collected EEG signal to the EEG signal processing unit. 6. The asynchronous brain-controlled UAV system based on the wearable display according to claim 1, wherein the EEG signal processing unit includes a classification processing module and a classification recognition module; wherein: The classification processing module is used for feature extraction and classification of the received EEG signals; The classification and identification module is used to identify the classified EEG signals, and the obtained identification results are sent to the drone. 7. the asynchronous brain-controlled unmanned aerial vehicle system based on wearable display according to claim 6, is characterized in that, described classification processing module adopts typical correlation analysis method to carry out feature extraction and classification; The classification processing module classifies the EEG signals into: idle state and working state; wherein: When the user gazes at the steady-state visual evoking stimulation unit, the EEG signal is classified as a working state; When the user looks away from the steady-state visual evoking stimulation unit, the EEG signal will be classified as an idle state. 8. The asynchronous brain-controlled unmanned aerial vehicle system based on wearable display according to claim 1, characterized in that, the classification recognition module adopts an idle state recognition method based on threshold detection to recognize the classified EEG signals , when the ratio of the largest correlation coefficient to the next largest correlation coefficient is less than or equal to the set threshold, it is judged to be in the idle state, otherwise it is in the working state; in the working state, the flight direction corresponding to the flickering frequency corresponding to the maximum correlation coefficient is output as the recognition result to none For man-machine, the recognition result sent to the UAV in the idle state is still translated into the flight direction in the latest working state. 9. The asynchronous brain-controlled unmanned aerial vehicle system based on a wearable display according to any one of claims 1 to 8, further comprising a real-time scene collection and transmission unit, and the real-time scene collection and transmission unit Mounted on the drone, it is used to collect the real-time image of the drone and transmit it to the wearable display; the real-time image is superimposed with the steady-state visual evoking stimulation unit and displayed on the wearable display. 10. The asynchronous brain-controlled UAV system based on the wearable display according to claim 9, wherein the real-time scene collection and transmission unit includes a camera and a video capture card; wherein: The camera is used for the acquisition of unmanned aerial vehicle flight video images; The video capture card is used to wirelessly transmit the captured drone flight video images to the wearable display.