UAV control method and system based on monocular camera

Abstract

The present invention discloses a monocular camera-based drone control method and system. The monocular camera-based drone control system includes an IMU unit and a monocular camera. The monocular camera includes an image sensor and a microprocessor. The image sensor outputs a light signal, and the microprocessor converts the light signal into an electrical signal. The electrical signal also carries IMU data. The monocular camera-based drone control method and system disclosed in the present invention have the beneficial effect that, within the allowable time delay range, the second-level control information is preferentially used to replace the first-level control information to control the controlled objects such as the engine and blades. Conversely, if the allowable time delay range is exceeded, the first-level control information immediately replaces the second-level control information. Among them, within the allowable time delay range, the second-level control information fully reflects the interactive characteristics between the drone's onboard equipment and the ground control station.

Description

Technical Field

[0001] The present invention belongs to the field of interaction between unmanned aerial vehicles (UAVs) and ground control stations, and in particular relates to a UAV control method and system based on a monocular camera. Background Art

[0002] The publication number is CN105138126A, the subject name is invention patent application for shooting control method and device of drone, and electronic device, and its IPC classification number is G06F3 / 01. Its technical solution discloses "determining whether a predefined mode activation condition is met; starting a preset shooting mode corresponding to the predefined mode activation condition to apply to the shooting operation. Optionally, the predefined mode activation condition includes at least one of the following: receiving a preset instruction issued by the user, detecting that the user is in a preset posture, and detecting that the drone or the user is in a preset environmental state."

[0003] It can be seen that the above invention patent application has disclosed one of the technical solutions for the drone photography control method. However, the above technical solution focuses on defining the corresponding mode activation conditions for each preset photography mode, so that the drone can accurately know the preset photography mode to be activated when a certain mode activation condition is met, ensuring that the user's actual photography needs are met; it does not further solve the problems such as the flexible selection of the drone's autonomous control mode (first-level control information) and the ground control station remote control mode (second-level control information), and needs further improvement. Summary of the Invention

[0004] In view of the status of the existing technology, the present invention overcomes the above-mentioned shortcomings and provides a drone control method and system based on a monocular camera.

[0005] The present invention adopts the following technical solution, which is a UAV control system based on a monocular camera, including an IMU unit and further comprising:

[0006] Monocular camera, which includes an image sensor and a microprocessor. The image sensor outputs a light signal, which is converted into an electrical signal by the microprocessor. The electrical signal also carries IMU data.

[0007] A flight control unit is electrically connected to the monocular camera and the IMU unit via an onboard circuit. The flight control unit is wirelessly connected to the ground control station via a data link. The flight control unit generates first-level control information containing imaging data, coordinate data, and IMU data in real time. The flight control unit transmits the first-level control information back to the ground control station via the data link. The ground control station optimizes the first-level control information into second-level control information according to a preset ground control station processing method. The ground control station uploads the second-level control information to the flight control unit via the data link. The flight control unit controls the controlled object according to a preset decision-making method.

[0008] The preset decision method is specifically implemented as follows:

[0009] The timing starts when the flight control unit generates the first-level control information. Within the specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise, the flight control unit controls the controlled object according to the first-level control information.

[0010] The present invention adopts the following technical solution, and the UAV control method based on a monocular camera includes the following steps:

[0011] The image sensor outputs a light signal, which is converted into an electrical signal by the microprocessor. The electrical signal also carries the IMU data.

[0012] The flight control unit generates first-level control information containing imaging data, coordinate data, and IMU data in real time. The flight control unit transmits the first-level control information back to the ground control station via a data link. The ground control station optimizes the first-level control information into second-level control information based on a preset ground control station processing method. The ground control station uploads the second-level control information to the flight control unit via a data link. The flight control unit controls the controlled object based on a preset decision-making method.

[0013] The preset decision method is specifically implemented as follows:

[0014] The timing starts when the flight control unit generates the first-level control information. Within the specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise, the flight control unit controls the controlled object according to the first-level control information.

[0015] As a preferred technical solution of the above technical solution, the microprocessor includes a pre-processing module and a data processing module, wherein:

[0016] The pre-processing module is electrically connected to the image sensor, and the pre-processing module adjusts the optical signal parameters of the image sensor autonomously or under control;

[0017] The data processing module is electrically connected to the flight control unit. The data processing module processes the optical signal autonomously or under control to output an electrical signal, and transmits real-time imaging data and coordinate data to the electrical signal.

[0018] As a preferred technical solution of the above technical solution, the pre-processing module is controlled to adjust the optical signal parameters of the image sensor, which is specifically implemented as follows:

[0019] The flight control unit autonomously controls the pre-processing module to adjust the optical signal parameters of the image sensor; or:

[0020] The ground control station remotely controls the pre-processing module via the flight control unit to adjust the optical signal parameters of the image sensor.

[0021] As a preferred technical solution of the above technical solution, the data processing module is controlled to process the optical signal, which is specifically implemented as follows:

[0022] The flight control unit autonomously controls the data processing module to process the optical signal; or:

[0023] The ground control station remotely controls the data processing module via the flight control unit to process the optical signal.

[0024] As the preferred technical solution of the above technical solutions, the preset ground control station processing method is specifically implemented as the following steps: one or more steps of the machine vision processing step, three-dimensional data conversion step, IMU data correction step and PID data control step are comprehensively applied according to actual conditions.

[0025] The monocular camera-based drone control method and system disclosed in the present invention have the following beneficial effects:

[0026] 1. Monocular camera-based drone control methods reduce reliance on other expensive sensors, lowering the overall cost of drones and facilitating large-scale deployment. Furthermore, monocular cameras can capture image data in real time, providing the drone with rich visual information that helps it perceive and understand its surroundings, thereby improving its autonomous control capabilities.

[0027] 2. Traditional drone control methods often rely on a variety of expensive sensors, such as GPS, LiDAR, and depth cameras. These sensors are not only costly, but also bulky and heavy, significantly impacting the drone's flight performance. In contrast, monocular cameras offer the advantages of small size, light weight, and low cost. Using a low-pixel monocular camera and an onboard drone flight control unit, they can identify obstacle locations in complex environments without requiring prior knowledge of obstacles, thus improving obstacle avoidance capabilities.

[0028] 3. The monocular camera-based drone control method offers advantages such as low cost, compact size, light weight, and strong real-time performance, making it adaptable to a wide range of application scenarios. Within the acceptable latency range, second-level control information is preferentially used to replace first-level control information to control controlled objects such as the engine and propellers. Otherwise, if the latency exceeds the acceptable range, first-level control information immediately replaces second-level control information. Within the acceptable latency range, second-level control information fully reflects the interaction characteristics between the drone's onboard equipment and the ground control station. DETAILED DESCRIPTION

[0029] The present invention discloses a monocular camera-based drone control method and system. The specific implementation of the present invention is further described below in conjunction with a preferred embodiment (Example 1).

[0030] Example 1.

[0031] Those skilled in the art should note that the “flight control unit”, “UAV flight control unit”, “airborne UAV flight control unit”, etc. that may be involved in various embodiments of the present invention are the same concept and are no longer distinguished.

[0032] Those skilled in the art should note that the “data link”, “data transmission link”, etc. that may be involved in various embodiments of the present invention are the same concept and are no longer distinguished.

[0033] Those skilled in the art should note that the “monocular camera”, “monocular camera head”, etc. that may be involved in various embodiments of the present invention are the same concept and are no longer distinguished.

[0034] Preferably, the monocular camera-based drone control system includes an IMU unit and further includes:

[0035] A monocular camera consists of an image sensor and a microprocessor. The image sensor outputs a light signal, which is converted into an electrical signal by the microprocessor. The microprocessor then outputs real-time imaging data and coordinate data on the electrical signal. The electrical signal also carries IMU data, thereby reflecting the three-dimensional spatial position of the drone. Monocular cameras have the advantages of small size, light weight, and low cost, making them easy to install on drones and providing them with rich visual information.

[0036] A flight control unit, wherein the flight control unit is electrically connected to the monocular camera (the microprocessor thereof) and the IMU unit via an onboard circuit, and is wirelessly connected to a ground control station via a data link. The flight control unit obtains real-time imaging data and coordinate data output by the monocular camera, obtains real-time IMU data output by the IMU unit, and generates first-level control information in real time including the imaging data, coordinate data, and IMU data. The flight control unit transmits the first-level control information back to the ground control station via the data link (for example, the data volume of the first-level control information is significantly smaller than the data volume of the real-time imaging data and coordinate data output by the monocular camera). The ground control station obtains the first-level control information, optimizes the first-level control information into second-level control information according to a preset ground control station processing method, and uploads the second-level control information to the flight control unit via the data link. The flight control unit obtains the second-level control information. The flight control unit controls the controlled object according to a preset decision-making method.

[0037] The preset decision method is specifically implemented as follows:

[0038] The timing starts when the flight control unit generates the first-level control information. Within a specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise (the second-level control information is not obtained within the specified delay interval), the flight control unit controls the controlled object according to the first-level control information. This ensures that the flight control unit preferentially uses the second-level control information instead of the first-level control information to control the engine, blades, and other controlled objects within the allowable delay range. Otherwise (exceeding the maximum value of the specified delay interval), the first-level control information immediately replaces the second-level control information to control the engine, blades, and other controlled objects.

[0039] The microprocessor includes a pre-processing module and a data processing module, wherein:

[0040] The preprocessing module is electrically connected to the image sensor. The preprocessing module autonomously or under control adjusts the optical signal parameters of the image sensor (for example, exposure time, frame rate, etc.), so that the image sensor outputs a finely tuned optical signal to the preprocessing module, thereby optimizing the imaging capability of the image sensor.

[0041] The data processing module is electrically connected to the flight control unit. The data processing module processes the optical signal autonomously or under control to output an electrical signal, and transmits real-time imaging data and coordinate data to the electrical signal.

[0042] Among them, as one of the parallel technical solutions of the pre-processing module, the pre-processing module is controlled to adjust the optical signal parameters of the image sensor, which is specifically implemented as follows:

[0043] The flight control unit autonomously controls the pre-processing module to adjust the optical signal parameters of the image sensor; or:

[0044] The ground control station remotely controls the pre-processing module via the flight control unit to adjust the optical signal parameters of the image sensor.

[0045] Among them, as one of the parallel technical solutions of the data processing module, the data processing module is controlled to process the optical signal, which is specifically implemented as follows;

[0046] The flight control unit autonomously controls the data processing module to process the optical signal; or:

[0047] The ground control station remotely controls the data processing module via the flight control unit to process the optical signal.

[0048] It is worth mentioning that, unlike existing small terminal devices such as handheld drone remote controls, ground control stations are larger in scale, have more equipment, and have stronger processing capabilities, and can realize functions that handheld drone remote controls cannot carry or achieve.

[0049] Among them, the preset ground control station processing method is specifically implemented as the following steps: according to the actual comprehensive application of one or more steps in the machine vision processing step, three-dimensional data conversion step, IMU data correction step and PID data control step, the first-level control information is optimized into the second-level control information.

[0050] The specific technical solutions of the machine vision processing steps of this embodiment are described below.

[0051] Image acquisition and preprocessing: Restore and archive the imaging data and coordinate data carried by the first-level control information. Perform denoising on the imaging data to remove noise interference caused by environmental factors or the camera itself, thereby improving image quality. For example, algorithms such as median filtering and Gaussian filtering can be used to remove salt and pepper noise and Gaussian noise in the image.

[0052] Image enhancement: By adjusting image parameters such as contrast and brightness, the features in the image are made more obvious, facilitating subsequent feature extraction and analysis.

[0053] Feature extraction: Use edge detection algorithms such as the Canny edge detection algorithm to extract edge information of objects in the image.

[0054] Extract feature points from the image, such as SIFT (Scale-Invariant Feature Transform) feature points or SURF (Speeded Up Robust Features) feature points. These feature points are scale-invariant and rotation-invariant, enabling stable object recognition under different viewing angles and lighting conditions.

[0055] Target recognition and tracking: Based on the extracted feature points, a specific target is identified (it can be a special target manually designated by the operator at the ground control station and not pre-entered into the UAV's flight control unit), the identified target is tracked, and the position and motion status of the specific target in the image are determined in real time.

[0056] Depth estimation: Combines archived imaging and coordinate data to estimate the depth information of specific targets in the image (in contrast, the limited onboard storage space of drones cannot archive long-term imaging and coordinate data, which can give full play to the scale advantages of ground control stations). This generates three-dimensional data of the drone's surrounding environment, which can serve as an effective input for the three-dimensional data conversion step.

[0057] The specific technical solution of the three-dimensional data conversion step of this embodiment is described below.

[0058] Establish the drone coordinate system: Take the drone's starting point or a specific midpoint as the origin, and extend to set up the X, Y, and Z coordinate axes.

[0059] Establish a ground coordinate system: Define the ground coordinate system according to the actual application scenario so that it can be converted to the drone coordinate system.

[0060] Set up a monocular camera imaging model: This describes the relationship between the target's position in 3D space and its projection onto the camera's image plane. This model typically uses a pinhole camera model, which involves the monocular camera's intrinsic and extrinsic parameter matrices. The intrinsic matrix describes the monocular camera's internal parameters, such as focal length and pixel size; the extrinsic matrix describes the monocular camera's position and pose in the world coordinate system.

[0061] 3D Coordinate Conversion: Based on the imaging and coordinate data output by the monocular camera and the monocular camera imaging model, the 2D coordinates on the image plane are converted to coordinates in 3D space. Using known camera parameters and the target's position in the image, the target's coordinates in 3D space are calculated through geometric calculations or mathematical models.

[0062] Coordinate conversion and alignment: Convert the three-dimensional coordinates in the drone coordinate system into the coordinates in the ground coordinate system to facilitate data interaction and fusion with other systems.

[0063] Output conversion results: The results of the three-dimensional data conversion are sorted and formatted, and output as data that can be used by the flight control unit and ground control station, which can serve as an effective input for the IMU data correction step.

[0064] The specific technical solution of the IMU data correction step of this embodiment is described below.

[0065] Data Acquisition and Fusion: Restore and archive the IMU data carried by the first-level control information, especially the accelerometer data and gyroscope data. The accelerometer measures the acceleration of the drone, and the gyroscope measures the angular velocity of the drone.

[0066] Data fusion: Fusing IMU data with coordinate data to improve the accuracy of drone position and attitude estimation. Kalman filtering, extended Kalman filtering, and other algorithms can be used for data fusion.

[0067] Error Analysis and Modeling: Analyze the sources of error in IMU data, including sensor noise, bias, and temperature drift. Build an error model to describe the characteristics and behavior of the error. For example, a statistical model can be used to model sensor noise, and a polynomial model can be used to model temperature drift.

[0068] Error correction algorithm: Based on the error model, a corresponding error correction algorithm is designed. Common error correction methods include zero-bias correction, scale factor correction, and temperature compensation. Zero-bias correction is used to eliminate the initial deviation of the sensor, scale factor correction is used to adjust the sensor's measurement scale, and temperature compensation is used to compensate for errors caused by temperature changes.

[0069] Dynamic Correction and Update: During flight, IMU data is monitored in real time and dynamically corrected using an error correction algorithm. Error models and correction parameters are continuously updated to adapt to varying flight states and environmental conditions. For example, adaptive filtering algorithms can be used to automatically adjust correction parameters based on real-time data.

[0070] Output corrected data: The corrected IMU data is sorted and formatted, and output as data that can be used by the flight control unit and ground control station, which can be used as an effective input for the PID data control step.

[0071] Preferably, the monocular camera-based drone control method comprises the following steps:

[0072] The image sensor outputs a light signal, which is converted into an electrical signal by a microprocessor. This signal then outputs real-time imaging data and coordinate data on the electrical signal. The electrical signal also carries IMU data, thereby reflecting the three-dimensional spatial position of the drone. Monocular cameras have the advantages of small size, light weight, and low cost, making them easy to install on drones and providing them with rich visual information.

[0073] The flight control unit obtains real-time imaging data and coordinate data output by the monocular camera, obtains real-time IMU data output by the IMU unit, generates first-level control information including the imaging data, coordinate data, and IMU data in real time, and transmits the first-level control information back to the ground control station via a data link (for example, the data volume of the first-level control information is significantly smaller than the data volume of the real-time imaging data and coordinate data output by the monocular camera). The ground control station obtains the first-level control information, optimizes the first-level control information into second-level control information according to a preset ground control station processing method, and uploads the second-level control information to the flight control unit via the data link. The flight control unit controls the controlled object according to a preset decision-making method.

[0074] The preset decision method is specifically implemented as follows:

[0075] The timing starts when the flight control unit generates the first-level control information. Within a specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise (the second-level control information is not obtained within the specified delay interval), the flight control unit controls the controlled object according to the first-level control information. This ensures that the flight control unit preferentially uses the second-level control information instead of the first-level control information to control the engine, blades, and other controlled objects within the allowable delay range. Otherwise (exceeding the maximum value of the specified delay interval), the first-level control information immediately replaces the second-level control information to control the engine, blades, and other controlled objects.

[0076] It is worth mentioning that the technical solution of the monocular camera-based drone control system disclosed in this embodiment is also applicable to the monocular camera-based drone control method. The technical solution of the monocular camera-based drone control method is not repeated here.

[0077] The following describes the overall concept of the monocular camera-based drone control method and system disclosed in this embodiment.

[0078] Specifically, a monocular camera-based drone control method and system uses the monocular camera to collect data and convert and output imaging data and coordinate data to reflect the drone's three-dimensional spatial position. The imaging data and coordinate data are transmitted in real time to the drone's flight control unit via an onboard line to output first-level control information. The first-level control information is then transmitted back to a ground control station via a data link. The ground control station optimizes the first-level control information into second-level control information using machine vision technology, three-dimensional data conversion technology, IMU data correction technology, and PID data control technology. The second-level control information is then uploaded to the drone's flight control unit via a data link. Within a preset time limit, the drone's flight control unit controls the engine and other controlled objects based on the uploaded second-level control information. If the preset time limit is exceeded, the drone's flight control unit directly controls the engine and other controlled objects based on the first-level control information. The first-level control information focuses on necessary and urgent information, with a small data volume and strong real-time performance, enabling rapid response in emergency situations. The second-level control information focuses on completeness and comprehensiveness, with a large data volume and complex calculations, providing more precise control instructions for the drone, improving the stability and accuracy of the drone's flight.

[0079] It is worth mentioning that the technical features such as the PID data control steps involved in the patent application of this invention should be regarded as prior art. The specific structure, working principle and possible control method and spatial layout method of these technical features can be selected by conventional choices in the field and should not be regarded as the inventive point of the patent of this invention. The patent of this invention will not be further elaborated.

[0080] For those skilled in the art, it is still possible to modify the technical solutions described in the aforementioned embodiments, or to make equivalent replacements for some of the technical features therein. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A UAV control system based on a monocular camera, characterized in that: Including the IMU unit, also includes: Monocular camera, which includes an image sensor and a microprocessor. The image sensor outputs a light signal, which is converted into an electrical signal by the microprocessor. The electrical signal also carries IMU data. A flight control unit is electrically connected to the monocular camera and the IMU unit via an onboard circuit. The flight control unit is wirelessly connected to the ground control station via a data link. The flight control unit generates first-level control information containing imaging data, coordinate data, and IMU data in real time. The flight control unit transmits the first-level control information back to the ground control station via the data link. The ground control station optimizes the first-level control information into second-level control information according to a preset ground control station processing method. The ground control station uploads the second-level control information to the flight control unit via the data link. The flight control unit controls the controlled object according to a preset decision-making method. The preset ground control station processing method is specifically implemented as follows: one or more steps of a machine vision processing step, a three-dimensional data conversion step, an IMU data correction step, and a PID data control step are comprehensively applied according to actual conditions; The specific implementation of the machine vision processing steps is as follows: Image acquisition and preprocessing: Restore and archive the imaging data and coordinate data carried by the first-level control information, and perform denoising on the imaging data; Image enhancement: adjust the contrast and brightness of the image; Feature extraction: Use the Canny edge detection algorithm to extract the edge information of objects in the image; Extract feature points from an image: Target recognition and tracking: Identify specific targets based on extracted feature points, track the identified targets, and determine the position and motion status of specific targets in the image in real time; Depth estimation: Combines archived imaging data and coordinate data to estimate the depth information of specific targets in the image and generate three-dimensional data of the drone's surrounding environment; The preset decision method is specifically implemented as follows: The timing starts when the flight control unit generates the first-level control information. Within the specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise, the flight control unit controls the controlled object according to the first-level control information.

2. The monocular camera-based drone control system according to claim 1, characterized in that: The microprocessor includes a pre-processing module and a data processing module, wherein: The pre-processing module is electrically connected to the image sensor, and the pre-processing module adjusts the optical signal parameters of the image sensor autonomously or under control; The data processing module is electrically connected to the flight control unit. The data processing module processes the optical signal autonomously or under control to output an electrical signal, and transmits real-time imaging data and coordinate data to the electrical signal.

3. The monocular camera-based drone control system according to claim 2, characterized in that: The pre-processing module is controlled to adjust the optical signal parameters of the image sensor, which is specifically implemented as follows: The flight control unit autonomously controls the pre-processing module to adjust the optical signal parameters of the image sensor; or: The ground control station remotely controls the pre-processing module via the flight control unit to adjust the optical signal parameters of the image sensor.

4. The monocular camera-based drone control system according to claim 2, characterized in that: The data processing module is controlled to process the optical signal, which is specifically implemented as follows: The flight control unit autonomously controls the data processing module to process the optical signal; or: The ground control station remotely controls the data processing module via the flight control unit to process the optical signal.

5. A UAV control method based on a monocular camera, characterized in that: The following steps are involved: The image sensor outputs a light signal, which is converted into an electrical signal by the microprocessor. The electrical signal also carries the IMU data. The flight control unit generates first-level control information containing imaging data, coordinate data, and IMU data in real time. The flight control unit transmits the first-level control information back to the ground control station via a data link. The ground control station optimizes the first-level control information into second-level control information based on a preset ground control station processing method. The ground control station uploads the second-level control information to the flight control unit via a data link. The flight control unit controls the controlled object based on a preset decision-making method. The preset ground control station processing method is specifically implemented as follows: one or more steps of a machine vision processing step, a three-dimensional data conversion step, an IMU data correction step, and a PID data control step are comprehensively applied according to actual conditions; The specific implementation of the machine vision processing steps is as follows: Image acquisition and preprocessing: Restore and archive the imaging data and coordinate data carried by the first-level control information, and perform denoising on the imaging data; Image enhancement: adjust the contrast and brightness of the image; Feature extraction: Use the Canny edge detection algorithm to extract the edge information of objects in the image; Extract feature points from an image: Target recognition and tracking: Identify specific targets based on extracted feature points, track the identified targets, and determine the position and motion status of specific targets in the image in real time; Depth estimation: Combines archived imaging data and coordinate data to estimate the depth information of specific targets in the image and generate three-dimensional data of the drone's surrounding environment; The preset decision method is specifically implemented as follows: The timing starts when the flight control unit generates the first-level control information. Within the specified delay interval, the flight control unit determines whether to obtain the second-level control information. If the second-level control information is obtained within the specified delay interval, the flight control unit controls the controlled object according to the second-level control information. Otherwise, the flight control unit controls the controlled object according to the first-level control information.

6. The monocular camera-based drone control method according to claim 5, characterized in that: The microprocessor includes a pre-processing module and a data processing module, wherein: The pre-processing module is electrically connected to the image sensor, and the pre-processing module adjusts the optical signal parameters of the image sensor autonomously or under control; The data processing module is electrically connected to the flight control unit. The data processing module processes the optical signal autonomously or under control to output an electrical signal, and transmits real-time imaging data and coordinate data to the electrical signal.

7. The monocular camera-based drone control method according to claim 6, characterized in that: The pre-processing module is controlled to adjust the optical signal parameters of the image sensor, which is specifically implemented as follows: The flight control unit autonomously controls the pre-processing module to adjust the optical signal parameters of the image sensor; or: The ground control station remotely controls the pre-processing module via the flight control unit to adjust the optical signal parameters of the image sensor.

8. The monocular camera-based drone control method according to claim 6, characterized in that: The data processing module is controlled to process the optical signal, which is specifically implemented as follows: The flight control unit autonomously controls the data processing module to process the optical signal; or: The ground control station remotely controls the data processing module via the flight control unit to process the optical signal.