Real-time electronic image stabilization system for flapping-wing flying robot

Abstract

The invention discloses a real-time electronic image stabilization system for a flapping-wing flying robot, which effectively solves the problems of image dithering and blurring of a flapping-wing flying robot in a complex flying environment by combining flying attitude monitoring and a real-time image stabilization algorithm. The system comprises an image acquisition module, an electronic image stabilization module, a flight attitude monitoring module and a control system, the image acquisition module acquires image data in real time, and the electronic image stabilization module performs real-time stabilization processing on an image based on attitude change of an aircraft. The flight attitude monitoring module collects attitude data of the aircraft through a three-axis gyroscope, an accelerometer and a magnetometer, and calculates an accurate flight attitude matrix through a sensor fusion algorithm. The control system dynamically adjusts parameters of the electronic image stabilization module according to the flight attitude data to ensure image stability. Compared with the prior art, the method has high real-time performance and response speed, image stability parameters can be adjusted in real time in the flight process, and the image quality is remarkably improved.

Description

Technical Field

[0001] The invention relates to the technical field of aerial video stabilization for flapping-wing flying robots, and in particular to a real-time electronic image stabilization system for flapping-wing flying robots. Background Art

[0002] With the rapid development of UAV technology, flapping-wing aircraft, as a new type of aircraft, has gradually attracted widespread attention due to its flexibility and low energy consumption. Compared with traditional fixed-wing or rotary-wing aircraft, flapping-wing aircraft have higher maneuverability and adaptability, and are particularly suitable for flying in narrow spaces and performing high-maneuverability tasks. However, the flexibility and flight characteristics of flapping-wing aircraft also bring challenges to its attitude control and image stabilization.

[0003] In flapping-wing aircraft applications, image acquisition is usually a key module for navigation, environmental perception, and mission execution. However, the aircraft will experience various external interferences during flight, such as wind speed changes, airflow fluctuations, aircraft vibrations, and attitude changes. These factors can cause dramatic changes in the pitch, roll, and heading angles of the aircraft, causing image jitter, blur, or even loss, affecting image quality and, in turn, affecting the aircraft's mission execution.

[0004] At present, in flapping-wing aircraft, image stabilization technology usually relies on traditional software algorithm-based image stabilization technology or hardware-controlled image stabilization technology. Traditional image stabilization technology performs image compensation by post-processing the image sequence and using the motion vector in the image, but this type of technology often has the following shortcomings:

[0005] Slow response speed: Traditional image stabilization technology mainly relies on image post-processing algorithms, which have long processing delays. This makes it difficult for fast-moving aircraft to respond to the impact of attitude changes on images in real time.

[0006] Lack of real-time performance: Existing image stabilization technology can usually only be processed offline during the flight of the aircraft and cannot handle the rapid attitude changes of the aircraft in real time.

[0007] Unstable image quality: Traditional image stabilization technology usually relies on algorithms to correct local areas of the image, but in a rapidly changing environment, it is still difficult to effectively eliminate the impact of rapid posture changes on image quality.

[0008] Unable to effectively deal with the problem of multi-sensor data fusion: In the application of flapping-wing aircraft, the aircraft needs to collect attitude data and image data at the same time, but traditional image stabilization technology fails to fully integrate sensor data (such as gyroscopes, accelerometers, magnetometers, etc.) for real-time image compensation, resulting in limited image stabilization effect.

[0009] Therefore, the existing technology cannot effectively meet the image stabilization requirements of flapping-wing aircraft in complex environments, especially when the flight attitude changes dramatically or the environmental conditions are complex, the image quality is often greatly affected. The shortcomings of the existing technology are mainly reflected in poor real-time performance, slow response and low stability of image quality.

[0010] Therefore, we urgently need to design a flapping-wing flying robot with a real-time electronic image stabilization system to solve the above-mentioned problems. Summary of the invention

[0011] The purpose of the present invention is to solve the technical problems raised in the above-mentioned background technology, and to provide a real-time electronic image stabilization system for a flapping-wing flying robot.

[0012] The above-mentioned purpose of the present invention is achieved like this:

[0013] The solution of the present invention is a real-time electronic image stabilization system for a flapping-wing flying robot, and the system includes the following modules:

[0014] Image acquisition module: used to obtain image data taken by the flapping-wing flying robot during flight in real time, wherein the image data includes a multi-frame image sequence;

[0015] Electronic image stabilization module: used to perform real-time stabilization processing on the image data, estimate the image motion vector field and compensate the image based on the motion vector field to eliminate the jitter and blur of the image during flight. The electronic image stabilization module includes image registration, motion estimation and motion compensation submodules. The core calculation formula of the image stabilization processing is:

[0016]

[0017] in, is the stabilized image, is the original image, For time The motion matrix of the moment, is the displacement vector of the image;

[0018] Flight attitude monitoring module: The three-axis gyroscope, three-axis accelerometer and three-axis magnetometer are used to monitor the attitude of the flapping-wing flying robot during flight, including the pitch angle. , Roll Angle , heading angle The flight attitude monitoring module collects the attitude data of the aircraft in real time, and transmits the data of the pitch angle, roll angle and heading angle to the control system to adjust the working state of the electronic image stabilization module;

[0019] Control system: According to the flight attitude data, real-time image data and historical data, the parameters of the electronic image stabilization module are adjusted in real time. The control system uses the following control algorithm for image stabilization:

[0020]

[0021] in, is the pixel value of the stabilized image, is the neighborhood pixel value of the original image, It is a weighted function that is adjusted in real time in combination with sensor output data;

[0022] As a preferred technical solution of the present invention, the electronic image stabilization module calculates the motion vector field of the image through a motion estimation algorithm, and estimates the displacement between image pixels using an optical flow method. The formula is:

[0023]

[0024] in, is the gradient of the image, is the pixel motion velocity vector, is the time variation of the image.

[0025] As a preferred technical solution of the present invention, the optical flow method further performs image registration by minimizing the error function, and the formula is:

[0026]

[0027] in, is the error function, is the offset between images, is the pixel value of the target image, is the source image pixel value.

[0028] As a preferred technical solution of the present invention, the flight attitude monitoring module adopts a three-axis gyroscope, a three-axis accelerometer and a three-axis magnetometer. The sensor calculates the flight attitude matrix ( ), where the flight attitude matrix ( ) is calculated as:

[0029]

[0030] in, , and The rotation matrices around the Z-axis, Y-axis, and X-axis respectively describe the heading, pitch, and roll angles of the aircraft;

[0031] The three-axis gyroscope is installed at the center of the flying robot body to accurately measure the angular velocity of the aircraft; the three-axis accelerometer is installed at the front of the aircraft, aligned with the flight direction, to ensure high accuracy of acceleration data; the three-axis magnetometer is installed at the tail of the aircraft to minimize the interference of the fuselage magnetic field, so as to ensure the accuracy of the heading angle measurement;

[0032] Flight Attitude Matrix With pitch angle , Roll Angle , heading angle The relationship between is given by the following formula:

[0033]

[0034] in, is the flight attitude matrix, is the pitch angle, is the roll angle, is the heading angle.

[0035] As a preferred technical solution of the present invention, the electronic image stabilization module smoothes the image using a weighted average algorithm, and the formula is:

[0036]

[0037] in, is the pixel value of the image after filtering, is the weighting function, is the pixel value in the neighborhood.

[0038] As a preferred technical solution of the present invention, the image acquisition module includes a high-definition camera with a resolution of 1920×1080 pixels and an image acquisition frequency of 30 frames per second. The image data is transmitted to the electronic image stabilization module for processing via real-time transmission.

[0039] As a preferred technical solution of the present invention, the electronic image stabilization module and the flight attitude monitoring module are integrated into the control system of the flying robot, with power consumption lower than 5W, and are suitable for long-term flight missions.

[0040] As a preferred technical solution of the present invention, the system can adjust the working parameters of the electronic image stabilization module in real time according to the attitude data and image processing results during the flight, so as to ensure image stability and flight stability.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] 1. The present invention combines flight attitude monitoring and real-time electronic image stabilization technology to quickly perform image stabilization processing when the aircraft's attitude changes. By calculating the aircraft's pitch angle, roll angle, and heading angle in real time, and using these data to adjust the image stabilization algorithm, the clarity and stability of the image during flight are ensured. Unlike traditional image stabilization technology, the present invention can respond to changes in the aircraft's attitude in real time, effectively eliminating image blur and jitter caused by factors such as external airflow, wind speed changes, or internal vibrations of the aircraft, significantly improving image stability;

[0043] 2. The existing technology usually relies on post-processing of images, which has the disadvantages of long processing delay and poor real-time performance. However, the present invention obtains the attitude data of the aircraft in real time through the flight attitude monitoring module, and processes it in combination with the real-time image stabilization algorithm, avoiding the delay problem of traditional technology and being able to adjust the image stabilization parameters in real time. In particular, when the aircraft makes a rapid turn, changes attitude sharply, or encounters sudden airflow, the system can respond quickly and adjust the image stabilization strategy to ensure stable image quality in a dynamic flight environment;

[0044] 3. The present invention uses a variety of sensors such as a three-axis gyroscope, a three-axis accelerometer, and a three-axis magnetometer, combined with a sensor fusion algorithm (such as a Kalman filter) to accurately estimate the flight attitude matrix of the aircraft. This multi-sensor data fusion technology can effectively improve the accuracy of the flight attitude, especially when the aircraft encounters wind speed changes or complex flight environments. The system can provide more accurate attitude estimation and adjust the image stabilization algorithm in real time, thereby minimizing the impact of aircraft attitude changes on image stability. This enables the system to better adapt to various flight conditions in complex flight environments and ensure stable image output. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction is given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 This is a system block diagram of a real-time electronic image stabilization system for a flapping-wing flying robot;

[0047] Figure 2 The present invention is a diagram showing the structure of a flight attitude monitoring module of a real-time electronic image stabilization system for a flapping-wing flying robot. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0049] The following is combined with Figure 1 and Figure 2 , the specific implementation methods of the present invention are described in detail.

[0050] 1. System structure;

[0051] The system of the present invention mainly includes the following modules:

[0052] Image acquisition module: used to obtain the image data taken by the flapping-wing flying robot during flight in real time. The image data is usually a multi-frame image sequence. The image acquisition module uses a high-definition camera with a resolution of 1920x1080 pixels and an image acquisition frequency of 30 frames per second. The image data is transmitted to the electronic image stabilization module for processing in real time.

[0053] Electronic image stabilization module: receives image data and eliminates image jitter and blur caused by flight attitude changes during flight through image stabilization algorithms. This module includes image registration, motion estimation, and motion compensation submodules.

[0054] The core calculation formula for image stabilization processing is:

[0055]

[0056] in, is the stabilized image, is the original image, For time The motion matrix of the moment, is the displacement vector of the image.

[0057] Flight attitude monitoring module: The three-axis gyroscope, three-axis accelerometer and three-axis magnetometer are used to monitor the attitude of the flapping-wing flying robot during flight, including the pitch angle. , Roll Angle , heading angle .

[0058] The flight attitude monitoring module collects the attitude data of the aircraft in real time, and transmits the data of the pitch angle, roll angle and heading angle to the control system to adjust the working state of the electronic image stabilization module.

[0059] The three-axis gyroscope is installed in the center of the flying robot body to accurately measure the angular velocity of the aircraft. The three-axis accelerometer is installed at the front of the aircraft to align its acceleration data with the flight direction to ensure high accuracy. The three-axis magnetometer is installed at the tail of the aircraft to ensure the accuracy of its heading angle measurement.

[0060] Control system: According to the flight attitude data, real-time image data and historical data, the parameters of the electronic image stabilization module are adjusted in real time. The control system uses the following control algorithm for image stabilization:

[0061]

[0062] in, is the pixel value of the stabilized image, is the neighborhood pixel value of the original image, is the weighting function.

[0063] The electronic image stabilization module smoothes the image using a weighted average algorithm, and the formula is:

[0064]

[0065] in, is the pixel value of the image after filtering, is the weighting function, is the pixel value in the neighborhood.

[0066] 2. Flight attitude matrix and Euler angles;

[0067] Flight Attitude Matrix Used to describe the three-dimensional spatial attitude of the aircraft. Flight attitude matrix and Euler angle (pitch angle , Roll Angle , heading angle ) can be represented by the rotation matrix:

[0068] Flight Attitude Matrix It is calculated by multiplying the rotation matrices around the Z, Y, and X axes.

[0069] The calculation formula of the rotation matrix is:

[0070]

[0071] in: is the matrix for rotation around the Z axis; is the matrix for rotation around the Y axis; The matrix for rotation around the X axis.

[0072] The calculation formula of the flight attitude matrix is:

[0073]

[0074] in, is the pitch angle, is the roll angle, is the heading angle.

[0075] The following is a specific description in conjunction with the embodiments;

[0076] Example 1: Real-time image stabilization control in a complex urban environment;

[0077] This embodiment is based on a real scenario: a flapping-wing flying robot performs a flight mission in a complex urban environment. When flying in such an environment, the aircraft is often disturbed by factors such as high-rise buildings, fast airflow, and wind speed changes. These factors may cause the aircraft's flight attitude to change dramatically, thereby affecting the quality of image acquisition. In order to maintain image stability in such a complex environment,

[0078] This embodiment proposes a system solution that combines flight attitude monitoring and electronic image stabilization technology.

[0079] System composition: This system is mainly composed of four parts: image acquisition module, electronic image stabilization module, flight attitude monitoring module and control system.

[0080] Image acquisition module: This module consists of a high-definition camera with a resolution of 1920×1080 pixels and an image acquisition frequency of 30 frames per second. During the flight, the camera continuously collects image sequences and transmits the image data in real time to the electronic image stabilization module for processing.

[0081] The image acquisition module can capture images of the aircraft in complex environments in real time and transmit them to the electronic image stabilization module.

[0082] Electronic image stabilization module:

[0083] After the image data is transmitted to the electronic image stabilization module, it is stabilized by a real-time image processing algorithm. The module first adjusts the image according to the flight attitude of the aircraft to eliminate the jitter and blur caused by the change in flight attitude. The core algorithm is as follows:

[0084]

[0085] in, is the stabilized image, is the original image, For time The motion matrix of the moment, is the image displacement vector. This formula indicates that by calculating the motion matrix of the aircraft, the displacement of the image is compensated to eliminate the dynamic blur in the image.

[0086] Flight attitude monitoring module: The flight attitude monitoring module monitors the attitude changes of the aircraft in real time through the three-axis gyroscope, three-axis accelerometer and three-axis magnetometer installed on the aircraft. The pitch angle collected by the sensor , Roll Angle and heading angle The data is processed by the sensor fusion algorithm to calculate the flight attitude matrix of the aircraft ( ).

[0087] The calculation formula of the posture matrix is:

[0088]

[0089] in, , and Represents the rotation matrices around the Z-axis, Y-axis, and X-axis respectively, and is used to describe the heading, pitch, and roll attitude of the aircraft.

[0090] Control system: The control system receives the real-time attitude data provided by the flight attitude monitoring module and adjusts the parameters of the electronic image stabilization module based on this data. Specifically, the control system uses the following algorithm to adjust image stabilization:

[0091]

[0092] in, is the pixel value of the stabilized image, is the neighborhood pixel value of the original image, is a weighted function. The weighted function is adjusted in real time according to the attitude changes of the aircraft to achieve the best image stabilization effect.

[0093] Implementation process: The aircraft takes off and enters the urban environment. The flight attitude monitoring module monitors the aircraft's attitude data in real time through sensors. The aircraft's pitch, roll and heading angles will change during flight.

[0094] At the same time, the image acquisition module captures the real-time image of the aircraft and transmits the image data to the electronic image stabilization module for processing.

[0095] The electronic image stabilization module eliminates jitter and blur in the image by adjusting the motion compensation of the image according to the flight attitude matrix (R) provided by the flight attitude monitoring module.

[0096] The control system dynamically adjusts the weighting function of the image stabilization algorithm according to the flight attitude data to improve the accuracy of image smoothing processing.

[0097] Application effect: By adjusting the image stabilization parameters in real time, the aircraft can effectively cope with complex flight environments. In complex situations such as strong winds and obstacles, the stability of the image is guaranteed, and the image blur and jitter caused by the change of the aircraft's attitude are successfully eliminated.

[0098] Example 2: Image stabilization in high wind speed environment;

[0099] This embodiment takes into account the flight application of an aircraft in a high wind speed environment. When an aircraft encounters strong winds, the flight attitude may change significantly, so it is necessary to adjust the electronic image stabilization module in real time to stabilize its image.

[0100] Working principle of the system: Flight attitude monitoring module: In a strong wind environment, the aircraft collects attitude data through a three-axis gyroscope, accelerometer, and magnetometer. Under high wind conditions, the pitch, roll, and heading angles of the aircraft may change significantly.

[0101] Sensor fusion: The flight attitude monitoring module uses the Kalman filter algorithm to fuse the data from different sensors to obtain the accurate attitude matrix of the aircraft ( ), the motion of the vehicle is described by the rotation matrix.

[0102] Electronic image stabilization module: The electronic image stabilization module smoothes the image using a weighted average algorithm based on the aircraft's attitude matrix (R) and real-time image data.

[0103] The algorithm formula is:

[0104]

[0105] in, It is a weighted function adjusted according to the real-time flight attitude to stabilize its image.

[0106] Implementation process: The aircraft flies in a high wind speed environment, and the flight attitude monitoring module collects the aircraft's attitude data in real time.

[0107] The control system adjusts the algorithm of the electronic image stabilization module according to the flight attitude data so that its image can remain stable when the wind speed changes greatly.

[0108] The image acquisition module continuously captures images and transmits the image data to the electronic image stabilization module for real-time image processing.

[0109] Application effect: In a high wind speed environment, the aircraft's attitude data is accurately estimated through the sensor fusion algorithm, and the electronic image stabilization module adjusts the image stabilization algorithm in real time, effectively eliminating image jitter caused by wind speed changes and ensuring image clarity and stability.

[0110] Example 3: Flight attitude and image stabilization in a variable airflow environment;

[0111] This embodiment involves a flapping-wing flying robot performing tasks in a complex and changeable airflow environment. Airflow changes can cause the aircraft's flight attitude to change rapidly, especially in areas with complex terrain such as mountains and canyons, where the aircraft's attitude changes can be very drastic. In order to ensure that the images taken by the aircraft in these environments are always stable, we combine real-time flight attitude monitoring and image stabilization algorithms.

[0112] How the system works:

[0113] Flight attitude monitoring module: This module obtains the aircraft's attitude data in real time through a three-axis gyroscope, a three-axis accelerometer and a three-axis magnetometer.

[0114] Specifically: Three-axis gyroscope: It estimates the roll, pitch and heading angles of the aircraft by measuring the angular velocity of the aircraft. The data collection is highly accurate, allowing it to accurately measure the attitude changes of the aircraft even when making rapid turns or encountering air flow fluctuations.

[0115] Three-axis accelerometer: used to measure the acceleration of the aircraft in different directions, and further correct the attitude changes, especially when the aircraft moves quickly, to ensure the accuracy of its attitude data.

[0116] Three-axis magnetometer: measures the direction of the Earth's magnetic field and provides heading angle data to correct the direction of the aircraft and reduce the impact of external interference on the heading.

[0117] The pitch angle of the aircraft ( )、Roll angle and heading angle The data is optimized through sensor fusion algorithms (such as Kalman filtering) to calculate the precise attitude matrix of the aircraft ( ).

[0118] Calculation of flight attitude matrix: Flight attitude matrix ( ) is calculated as follows:

[0119]

[0120] in: is the matrix for rotation around the Z axis (heading angle), is the matrix for rotation around the Y axis (pitch angle), is the matrix for rotation around the X-axis (roll angle). These rotation matrices are used to describe the attitude of the aircraft in three-dimensional space. By combining the product of the three rotation matrices, the flight attitude matrix ( ) can accurately reflect the attitude changes of the aircraft.

[0121] Image acquisition module: The aircraft is equipped with a high-definition camera with a resolution of 1920×1080 pixels and an image acquisition frequency of 30 frames per second. The image data collected by the camera is transmitted to the electronic image stabilization module in real time.

[0122] Electronic image stabilization module: After receiving the image data, the electronic image stabilization module first calculates the motion vector field of the image. The electronic image stabilization module performs real-time image processing. The attitude changes of the aircraft will affect the stability of the image, and the electronic image stabilization module eliminates these effects through motion estimation and compensation.

[0123] The specific algorithm is as follows: Motion estimation: Calculate the motion difference between each frame in the image and the previous frame.

[0124]

[0125] in, is the stabilized image, is the original image, For time The motion matrix of the moment, is the displacement vector of the image.

[0126] Image smoothing: The electronic image stabilization module uses a weighted average algorithm to smooth the image and eliminate image fluctuations caused by changes in flight attitude. The weighted average algorithm is as follows:

[0127]

[0128] in, is the weighting function, is the pixel value in the neighborhood.

[0129] Control system: The control system adjusts the image processing parameters of the electronic image stabilization module in real time based on flight attitude data, image data, and historical data. By optimizing the weighting function, the system can flexibly adjust the image stabilization parameters according to the changes in flight attitude. In particular, when the aircraft encounters rapid airflow changes or complex obstacles, the control system will increase the weight of the image smoothing algorithm to stabilize the image.

[0130] Implementation process: The aircraft starts and enters a complex airflow environment: The aircraft collects the pitch angle, roll angle and heading angle data of the aircraft in real time through the attitude monitoring module, and calculates the precise flight attitude matrix (R) through the sensor fusion algorithm.

[0131] Image acquisition and real-time processing: The image acquisition module continuously captures image data at a frequency of 30 frames per second and transmits it to the electronic image stabilization module. The electronic image stabilization module adjusts the image according to the flight attitude matrix (R) to eliminate image fluctuations caused by airflow changes.

[0132] Real-time control to adjust the image stabilization algorithm: The control system adjusts the weighting function of the image stabilization algorithm based on the flight attitude data and image data collected in real time to make the image smooth and stable.

[0133] Application effect: In a complex and changeable airflow environment, the aircraft can quickly adapt to changes in the aircraft's attitude through real-time attitude monitoring and image stabilization processing algorithms. Especially when encountering strong winds, airflow fluctuations and rapid turns, the image can remain stable, eliminating image blur and jitter, ensuring the efficient execution of the flight mission.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A real-time electronic image stabilization system for a flapping-wing flying robot, characterized in that: The system includes the following modules: Image acquisition module: used to obtain image data taken by the flapping-wing flying robot during flight in real time, wherein the image data includes a multi-frame image sequence; Electronic image stabilization module: used to perform real-time stabilization processing on the image data, estimate the image motion vector field and compensate the image based on the motion vector field to eliminate the jitter and blur of the image during flight. The electronic image stabilization module includes image registration, motion estimation and motion compensation submodules. The core calculation formula of the image stabilization processing is: ， in, is the stabilized image, is the original image, For time The motion matrix of the moment, is the displacement vector of the image; Flight attitude monitoring module: The three-axis gyroscope, three-axis accelerometer and three-axis magnetometer are used to monitor the attitude of the flapping-wing flying robot during flight, including the pitch angle. , Roll Angle , heading angle The flight attitude monitoring module collects the attitude data of the aircraft in real time, and transmits the data of the pitch angle, roll angle and heading angle to the control system to adjust the working state of the electronic image stabilization module; Control system: According to the flight attitude data, real-time image data and historical data, the parameters of the electronic image stabilization module are adjusted in real time. The control system uses the following control algorithm for image stabilization: ， in, is the pixel value of the stabilized image, is the neighborhood pixel value of the original image, It is a weighted function that is adjusted in real time based on the sensor output data.

2. A real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The electronic image stabilization module calculates the motion vector field of the image through a motion estimation algorithm and estimates the displacement between image pixels using an optical flow method. The formula is: ， in, is the gradient of the image, is the pixel motion velocity vector, is the time variation of the image.

3. A real-time electronic image stabilization system for a flapping-wing flying robot according to claim 2, characterized in that: The optical flow method further performs image registration by minimizing the error function, and the formula is: ， in, is the error function, is the offset between images, is the pixel value of the target image, is the source image pixel value.

4. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The flight attitude monitoring module uses a three-axis gyroscope, a three-axis accelerometer and a three-axis magnetometer. The sensor calculates the flight attitude matrix of the flapping-wing flying robot through a sensor fusion algorithm. .

5. A real-time electronic image stabilization system for a flapping-wing flying robot according to claim 4, characterized in that: The flight attitude matrix The calculation formula is: ， in, , and The rotation matrices around the Z-axis, Y-axis, and X-axis respectively describe the heading, pitch, and roll angles of the aircraft.

6. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 4, characterized in that: The three-axis gyroscope is installed at the center of the flying robot body to accurately measure the angular velocity of the aircraft; the three-axis accelerometer is installed at the front of the aircraft, aligned with the flight direction, to ensure high accuracy of acceleration data; the three-axis magnetometer is installed at the tail of the aircraft to minimize interference from the fuselage magnetic field; Flight Attitude Matrix With pitch angle , Roll Angle , heading angle The relationship between is given by the following formula: ， in, is the flight attitude matrix, is the pitch angle, is the roll angle, is the heading angle.

7. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The electronic image stabilization module smoothes the image using a weighted average algorithm, and the formula is: ， in, is the pixel value of the filtered image, is the weighting function, is the pixel value in the neighborhood.

8. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The image acquisition module includes a high-definition camera with a resolution of 1920×1080 pixels and an image acquisition frequency of 30 frames per second. The image data is transmitted to the electronic image stabilization module for processing in a real-time transmission manner.

9. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The electronic image stabilization module and the flight attitude monitoring module are integrated into the control system of the flying robot, with power consumption less than 5W, and are suitable for long-term flight missions.

10. The real-time electronic image stabilization system for a flapping-wing flying robot according to claim 1, characterized in that: The system adjusts the working parameters of the electronic image stabilization module in real time according to the attitude data and image processing results during the flight.

Images