An intelligent pan-tilt integrated photography tripod system and its precise control method

Abstract

The present invention discloses an intelligent pan-tilt integrated photography tripod system and a precise control method thereof, which relates to the technical field of intelligent pan-tilts, including a posture detection unit that collects pan-tilt posture data and outputs a compensation posture vector; an image acquisition unit that collects scene images and generates a result of judging illumination changes; a gravity compensation unit that calculates a gravity compensation angle value based on the compensation posture vector; a control parameter generation unit that generates initial pan-tilt control parameters according to preset shooting requirements; a servo control unit that dynamically adjusts the pan-tilt control parameters according to the result of judging illumination changes and the gravity compensation angle value; and a drive execution unit that controls a stepper motor to drive the pan-tilt to rotate according to the adjusted pan-tilt control parameters. The present invention realizes precise control of the pan-tilt through real-time posture detection and environmental illumination analysis, combined with gravity compensation and dynamic parameter adjustment, improves shooting stability and image quality, and adapts to complex and changeable shooting environments.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent pan-tilt platforms, and in particular to an intelligent pan-tilt platform integrated photographic tripod system and a precise control method thereof. Background Art

[0002] With the development of photography technology, the application of high-precision gimbal control in complex environments is becoming increasingly important. However, existing gimbal systems still have deficiencies in posture detection, light adaptation, and gravity compensation. Traditional posture detection units often lack temperature compensation mechanisms, resulting in poor working stability under different ambient temperatures. In terms of light processing, existing technologies usually only focus on basic image acquisition and simple preprocessing, which makes it difficult to effectively cope with complex and changing lighting environments, especially in scenes with rapidly changing light, where image quality and subsequent processing effects are unstable.

[0003] In addition, the existing gimbal gravity compensation technology mostly uses simplified models, which makes it difficult to accurately describe the gravitational characteristics of the gimbal under different postures and loads. These problems affect the control accuracy and shooting effect of the gimbal system in complex environments. Summary of the invention

[0004] In view of the fact that the existing pan-tilt system has problems such as insufficient posture detection accuracy, poor illumination adaptability, and inaccurate gravity compensation in complex environments, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to achieve high-precision pan / tilt control to adapt to complex lighting environments and provide a stable shooting effect.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides an intelligent gimbal integrated photography tripod system, which includes a posture detection unit, including a three-axis accelerometer, a three-axis gyroscope and a temperature sensor, for collecting posture data of the gimbal and outputting a compensation posture vector; an image acquisition unit, including a camera, the camera collects scene images, the image acquisition unit is used to extract brightness distribution characteristics of the scene image, and generate a lighting change judgment result; a gravity compensation unit, the gravity compensation unit is connected to the posture detection unit, the gravity compensation unit calculates the gravity compensation angle value of the gimbal based on the compensation posture vector; a control parameter generation unit, for generating initial gimbal control parameters according to preset shooting requirements; a servo control unit, the servo control unit is connected to the gravity compensation unit and the image acquisition unit, and dynamically adjusts the gimbal control parameters according to the lighting change judgment result and the gravity compensation angle value; a drive execution unit, the drive execution unit is connected to the servo control unit, the drive execution unit includes a stepper motor, and the stepper motor drives the gimbal to rotate according to the adjusted gimbal control parameters.

[0008] As a preferred solution of the intelligent gimbal integrated photography tripod system described in the present invention, the processing flow of the posture detection unit is as follows: a three-axis accelerometer and a three-axis gyroscope collect posture data of the gimbal, and the posture data includes three-axis acceleration data and three-axis angular velocity data; the posture data is low-pass filtered to obtain filtered posture data; an extended Kalman filter is used to estimate an initial posture vector based on the filtered posture data, wherein the initial posture vector includes a posture angle and a gyroscope deviation; based on the temperature data collected by the temperature sensor, the gyroscope deviation in the initial posture vector is compensated in real time to obtain a compensated posture vector; and the compensated posture vector is output to the gravity compensation unit.

[0009] As a preferred solution of the intelligent pan-tilt integrated photography tripod system described in the present invention, the processing flow of the image acquisition unit is as follows: the camera acquires the scene image; the brightness analysis of the scene image is performed to extract the brightness distribution characteristics; the timing analysis of the brightness distribution characteristics of multiple consecutive frames of scene images is performed to calculate the brightness change amount and the change rate; based on the brightness change amount and the change rate, the type of illumination change is judged, and the illumination change types include normal, instantaneous change and continuous change; the illumination change judgment result is generated, and the illumination change judgment result is output to the servo control unit.

[0010] As a preferred solution of the intelligent gimbal integrated photography tripod system described in the present invention, the processing flow of the gravity compensation unit is as follows: receiving the compensation posture vector output by the posture detection unit; according to the compensation posture vector, using the quaternion method to calculate the three-dimensional spatial posture of the gimbal, and obtaining the gravity component of each axis through trigonometric function decomposition; obtaining the gimbal load parameters, and combining with the pre-established gimbal gravity characteristic model, calculating the static gravity moment and dynamic inertia compensation moment; superimposing the static gravity moment and the dynamic inertia compensation moment to obtain a comprehensive compensation torque; based on the comprehensive compensation torque, calculating the gravity compensation torque of each axis; converting the gravity compensation torque into a gravity compensation angle value through the motor characteristic curve, and outputting it to the servo control unit.

[0011] As a preferred solution of the intelligent pan-tilt integrated photography tripod system described in the present invention, the processing flow of the servo control unit is as follows: obtaining the initial pan-tilt control parameters generated by the control parameter generation unit; receiving the illumination change judgment result output by the image acquisition unit and the gravity compensation angle value output by the gravity compensation unit; selecting the corresponding compensation strategy according to the illumination change type in the illumination change judgment result, and generating the pan-tilt angle compensation value; taking the three-axis angle value in the initial pan-tilt control parameter as a reference, superimposing the gravity compensation angle value and the pan-tilt angle compensation value, and generating the comprehensive compensation control parameter; performing range limitation processing on the comprehensive compensation control parameter, converting the comprehensive compensation control parameter after the range limitation processing into a drive signal, and outputting it to the drive execution unit.

[0012] As a preferred solution of the intelligent pan-tilt integrated photography tripod system described in the present invention, the initial attitude vector is estimated based on the filtered attitude data, including the following steps: initializing the estimated values ​​of the attitude angle and the gyroscope deviation; using the quaternion kinematic model to predict the attitude angle using the filtered angular velocity data; using the filtered acceleration data as the observation value to correct the predicted attitude angle; iteratively executing the prediction and correction steps to update the estimation of the attitude angle and the gyroscope deviation; determining the iteration termination condition by combining a fixed number of iterations with a convergence threshold; and outputting the initial attitude vector containing the updated attitude angle and the gyroscope deviation.

[0013] As a preferred solution of the intelligent pan-tilt integrated photography tripod system of the present invention, the calculation formula of the static gravity moment is as follows:

[0014]

[0015] in, is the static gravity moment of the ith joint, is the equivalent mass of the i-th joint, g is the gravitational acceleration, is the equivalent effective arm length of the ith joint, is the angle of the i-th joint relative to the vertical direction, is the bearing friction coefficient of the ith joint, is the angular velocity of the i-th joint, is the friction torque of the ith joint, is a symbolic function.

[0016] In the second aspect, an embodiment of the present invention provides a precise control method for an intelligent gimbal integrated with a photographic tripod system, which includes a control parameter generation unit generating initial gimbal control parameters according to preset shooting requirements; a posture detection unit collecting gimbal posture data and outputting a compensation posture vector; an image acquisition unit collecting scene images and generating a lighting change judgment result; a gravity compensation unit calculating a gravity compensation angle value according to the compensation posture vector; a servo control unit dynamically adjusting the gimbal control parameters based on the lighting change judgment result and the gravity compensation angle value; a drive execution unit controlling a stepper motor to drive the gimbal to a corresponding position according to the adjusted gimbal control parameters; the image acquisition unit executing scene shooting after the gimbal is stable, and the system performs a quality assessment on the shooting results; if the quality of the shooting results does not meet the preset threshold and the maximum number of adjustments is not reached, the servo control unit fine-tunes the gimbal control parameters based on the assessment results and returns to the drive execution unit step; if the quality of the shooting results meets the preset threshold or the maximum number of adjustments is reached, the current scene shooting task is completed.

[0017] The beneficial effects of the present invention are as follows: the present invention improves the accuracy and stability of the pan / tilt control to a certain extent by integrating functional modules such as posture detection, gravity compensation, image acquisition and servo control. The system can adapt to changes in illumination and help maintain the relative stability of image quality. The filtering, abnormal data elimination and temperature compensation technologies used are conducive to improving the reliability of posture data and reducing the impact of temperature changes. The present invention has a certain real-time response capability, and the control parameters can be adjusted according to shooting requirements, which helps to improve the shooting quality in different environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0019] Figure 1 System architecture diagram for the smart gimbal integrated with a photography tripod system.

[0020] Figure 2 Processing flow of the attitude detection unit of the intelligent gimbal integrated photography tripod system.

[0021] Figure 3 Processing flow for the gravity compensation unit of the intelligent gimbal integrated with the photography tripod system.

[0022] Figure 4 The process of generating the gimbal angle compensation value for the intelligent gimbal integrated with the photographic tripod system. DETAILED DESCRIPTION

[0023] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0024] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0025] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0026] Example 1, reference Figure 1~Figure 4 , which is the first embodiment of the present invention, and which provides an intelligent pan-tilt integrated photography tripod system, the system architecture diagram is as follows Figure 1 As shown, the system is designed to achieve high-precision gimbal control, adapt to complex lighting environments, and provide stable shooting effects, including,

[0027] The attitude detection unit includes a three-axis accelerometer, a three-axis gyroscope and a temperature sensor, which is used to collect the attitude data of the gimbal and output a compensation attitude vector.

[0028] The image acquisition unit includes a camera, which acquires scene images. The image acquisition unit is used to extract brightness distribution characteristics of the scene images and generate illumination change judgment results.

[0029] The gravity compensation unit is connected to the posture detection unit, and the gravity compensation unit calculates the gravity compensation angle value of the gimbal based on the compensation posture vector.

[0030] The control parameter generation unit is used to generate initial gimbal control parameters according to preset shooting requirements, including three-axis angle values ​​(pitch angle, yaw angle and roll angle), three-axis acceleration data, three-axis angular velocity data, etc.; among which, the three-axis angle values ​​can be calculated through the three-axis acceleration data and the three-axis angular velocity data.

[0031] The servo control unit is connected with the gravity compensation unit and the image acquisition unit, and dynamically adjusts the pan / tilt control parameters according to the illumination change judgment result and the gravity compensation angle value.

[0032] The driving execution unit is connected to the servo control unit. The driving execution unit includes a stepping motor. The stepping motor drives the pan-tilt head to rotate according to the adjusted pan-tilt head control parameters.

[0033] The processing flow of the posture detection unit is as follows: Figure 2As shown, it specifically includes: the three-axis accelerometer and the three-axis gyroscope collect the attitude data of the gimbal, including the three-axis acceleration data and the three-axis angular velocity data; the attitude data is low-pass filtered to obtain the filtered attitude data, wherein the low-pass filtering uses a Butterworth filter with a cutoff frequency of 50Hz; based on the statistical characteristics of the filtered attitude data, the Mahalanobis distance method is used to identify and remove abnormal data, and the identified abnormal data points are replaced with the average value of the adjacent data points; the extended Kalman filter is used to estimate the initial attitude vector based on the filtered attitude data, wherein the initial attitude vector includes the attitude angle and the gyroscope bias. First, the estimated values ​​of the attitude angle and the gyroscope bias are initialized. The attitude angle is usually expressed in Euler angles (roll angle, pitch angle, yaw angle), and the initial value can be set to (0,0, 0) or an approximate value can be given according to the installation position of the system. The initial estimate of the gyroscope bias is usually set to the zero vector, or a pre-calibrated value is used.

[0034] Next, the quaternion kinematic model is used to predict the attitude angle using the filtered angular velocity data. Compared with the Euler angle, the quaternion can avoid the universal joint lock problem and has higher computational efficiency. The quaternion kinematic equation is discretized using the fourth-order Runge-Kutta method to obtain the predicted quaternion, which is then converted into the Euler angle to update the attitude angle part of the state vector. Among them, the quaternion kinematic equation is:

[0035]

[0036] Among them, q is the attitude quaternion, is the angular velocity vector, is the antisymmetric matrix of angular velocity.

[0037] Subsequently, the filtered acceleration data is used as the observation value to correct the predicted attitude angle. Ideally, when stationary or in uniform motion, the accelerometer measures the component of gravity acceleration in the body coordinate system, so the attitude angle can be estimated by the accelerometer reading. At the same time, a threshold for the acceleration measurement is set to identify and handle possible external interference. When the difference between the measured acceleration and the gravity acceleration exceeds the preset threshold, it is considered that there is external interference. Next, the prediction and correction steps are iteratively performed to continuously update the estimation of the attitude angle and gyroscope bias. The iteration termination condition is determined by combining a fixed number of iterations with a convergence threshold. Finally, the initial attitude vector containing the updated attitude angle and gyroscope bias is output.

[0038] To further improve the accuracy, the gyroscope deviation in the initial attitude vector is compensated in real time based on the temperature data collected by the temperature sensor to obtain the compensated attitude vector, which is then output to the gravity compensation unit. The process of obtaining the compensated attitude vector is as follows: During the system calibration phase, the gyroscope deviation is measured at different temperatures, and the polynomial relationship model between the gyroscope deviation and temperature is obtained by fitting the least squares method; to reduce the computational complexity, it is recommended that the order of the polynomial fitting model does not exceed the second order to ensure real-time performance.

[0039] Furthermore, temperature data of the temperature sensor is obtained in real time, and the temperature data is substituted into a polynomial relationship model to calculate a gyroscope deviation compensation value at the current temperature; the gyroscope deviation compensation value is added to the gyroscope deviation in the initial attitude vector to obtain a temperature-compensated gyroscope deviation; the temperature-compensated gyroscope deviation is combined with the attitude angle in the initial attitude vector to form a compensated attitude vector.

[0040] It is worth noting that the attitude detection unit effectively reduces the impact of temperature changes on attitude detection by adding a temperature sensor and compensating for gyroscope deviation in real time, thereby improving the system's working stability under different ambient temperatures; at the same time, the attitude detection unit uses a method combining low-pass filtering and Mahalanobis distance to process abnormal data, which can not only filter out high-frequency noise, but also identify and eliminate abnormal values ​​caused by vibration, impact and other factors, thereby improving the reliability of attitude data.

[0041] In traditional technologies, image acquisition units usually only focus on basic image acquisition and simple preprocessing, such as denoising and color correction. These systems often cannot effectively cope with complex and changing lighting environments, resulting in unstable image quality and subsequent processing effects in scenes with rapidly changing light. In addition, traditional image processing systems usually treat lighting analysis as an independent module and lack effective real-time interaction with other control units. This design limits the system's ability to respond quickly to lighting changes, especially in scenes that require precise control, such as professional photography or autonomous driving. It can be seen that traditional image acquisition and processing methods have obvious shortcomings in dealing with dynamic lighting environments, and it is difficult to meet the needs of application scenarios with high precision and real-time requirements.

[0042] In this regard, the present invention provides a new image acquisition unit design, which integrates advanced image preprocessing, multi-dimensional brightness analysis, time series data processing and intelligent illumination change judgment. The processing flow is as follows: Figure 3As shown, it includes: the camera collects the scene image, and pre-processes the scene image, including image denoising, color correction and contrast enhancement; performs brightness analysis on the pre-processed scene image, and extracts the brightness distribution characteristics, wherein the brightness distribution characteristics include but are not limited to the overall average brightness of the image, the brightness standard deviation, the brightness histogram, and the local brightness gradient; performs time series analysis on the brightness distribution characteristics of multiple consecutive frames of scene images, and calculates the brightness change amount and the change rate, wherein the brightness change amount is obtained by calculating the overall average brightness difference between two adjacent frames of images, and the change rate is obtained by performing linear regression analysis on the average brightness of the most recent N frames of images, and taking the slope of the regression line (in this embodiment, the size of N is dynamically adjusted according to the actual scene to improve the system's ability to adapt to different illumination change speeds); based on the brightness change amount and the change rate, the illumination change type is judged, and the illumination change is classified into instantaneous change or continuous change; generates an illumination change judgment result, and outputs the illumination change judgment result to the servo control unit, wherein the illumination change judgment result includes the illumination change type (normal / instantaneous change / continuous change), brightness change amount, and change rate.

[0043] Specifically, the illumination change type judgment process in this embodiment is as follows: if the single-frame brightness change exceeds 20% of the total brightness range and lasts no longer than 3 frames, it is judged as an instantaneous change; if the brightness change rate lasts for more than 5 frames and exceeds 5% of the total brightness range per second, it is judged as a continuous change; other situations are judged as normal illumination status. This judgment method can effectively distinguish different types of illumination changes and provide an important basis for subsequent PTZ control.

[0044] Preferably, by integrating multi-dimensional brightness analysis and time series data processing, the unit can accurately identify and respond to complex lighting changes, improving the system's adaptability in dynamic lighting environments.

[0045] The processing flow of the gravity compensation unit is as follows: Figure 3 As shown, it includes: receiving the compensation attitude vector output by the attitude detection unit; according to the compensation attitude vector, using the quaternion method to calculate the three-dimensional spatial attitude of the gimbal, and obtaining the gravity component of each axis through trigonometric function decomposition; obtaining the gimbal load parameters, including the gimbal body mass, the load equipment mass, the center of gravity position coordinates of each axis and the rotational inertia of each axis, and combining with the pre-established gimbal gravity characteristic model, calculating the static gravity moment and the dynamic inertia compensation moment; superimposing the static gravity moment and the dynamic inertia compensation moment to obtain a comprehensive compensation moment; based on the comprehensive compensation moment, calculating the gravity compensation moment of each axis; converting the gravity compensation moment into a corresponding gravity compensation angle value, and converting it through quaternion attitude solution and inverse kinematics method (firstly obtaining the current attitude information of the gimbal through quaternion attitude solution, and combining with the gravity compensation moment data, using the inverse kinematics method to solve the gravity compensation angle value of each axis); outputting the gravity compensation angle value to the servo control unit.

[0046] It should be noted that the construction of the gimbal gravity characteristic model adopts a piecewise linear fitting method to divide the gimbal motion range into multiple working intervals. A linear model is used in each interval to describe the gravity characteristics. The model parameters include the mass distribution, arm length and bearing friction coefficient of each joint of the gimbal. The gravity characteristic model also has the following characteristics: the gimbal motion range is divided into multiple discrete working intervals based on the joint angle, and the range of each interval is determined according to the actual test data; the mass distribution and arm length of each joint of the gimbal are obtained through precision measurement equipment and calibration procedures, and the bearing friction coefficient is obtained through multiple motion tests and data fitting; at the boundary of adjacent intervals, a weighted average method is used for smooth transition to ensure the continuity of the model output. The gravity compensation unit also includes an automatic calibration program, which regularly tests and updates parameters to adapt to gimbal load changes and mechanical wear; through multiple sets of comparative tests with different loads and postures, it is verified that the accuracy of the model in the entire working range meets the requirements; the lookup table and interpolation algorithm are used to optimize the interval judgment and parameter acquisition process to improve the real-time calculation efficiency. The lookup table-based approach can significantly improve the real-time performance of the gravity compensation unit.

[0047] In addition, in each working range, the static gravitational moment is obtained by calculating the partial derivative of the gravitational potential energy of the gimbal with respect to the joint angle at the current posture, and the bearing friction compensation term is introduced. The specific formula is as follows:

[0048]

[0049] in, is the static gravity moment of the ith joint, is the equivalent mass of the i-th joint, g is the gravitational acceleration, is the equivalent effective arm length of the ith joint, is the angle of the i-th joint relative to the vertical direction, is the bearing friction coefficient of the ith joint, is the angular velocity of the i-th joint, is the friction torque of the ith joint, is a symbolic function.

[0050] It should be noted that The term reflects the component of gravity in the direction of joint rotation. The gravity moment is maximum when the joint axis is horizontal and zero when the joint axis is vertical. The term describes the bearing friction torque, which is always opposite to the direction of motion. It is related to the joint load and speed and can be obtained through experimental calibration.

[0051] At the same time, the dynamic inertia compensation moment is calculated by combining the angular acceleration of each axis and the equivalent moment of inertia related to the attitude. The equivalent moment of inertia is updated in real time with the gimbal attitude. The mapping relationship between the attitude angle and the equivalent moment of inertia is obtained through polynomial fitting. The specific formula is as follows:

[0052]

[0053] in, is the dynamic inertia compensation moment, is the equivalent moment of inertia matrix related to the attitude, is the angular acceleration vector, is the coupling matrix caused by Coriolis force and centrifugal force, is the angular velocity vector.

[0054] It should be noted that the equivalent moment of inertia Obtained by fitting a cubic polynomial: ,in are the fitting coefficients, which are obtained by performing least square fitting on the measured data of the gimbal in different postures.

[0055] It is worth emphasizing that in the dynamic inertia compensation moment formula, Represents the coupling term matrix caused by Coriolis force and centrifugal force. This matrix describes the nonlinear dynamic characteristics of the multi-axis gimbal system when it moves at high speed or large amplitude, and plays an important role in improving the control accuracy of the system under complex motion conditions. The specific form of the matrix depends on the structure and motion characteristics of the gimbal, which can be obtained by analyzing the kinematic and dynamic equations of the system. In practical applications, simplified models or fitting methods based on experimental data can be used to balance the computational complexity and compensation accuracy. The matrix is ​​particularly important for applications that require high-precision control, such as precision observation or photography. It works together with static gravity compensation and basic inertia compensation to form a more comprehensive dynamic compensation system that can adapt to a wider range of working conditions and motion requirements.

[0056] To further improve the control accuracy, the motor characteristic curve conversion adopts an adaptive compensation strategy. Based on the real-time acquisition of the motor back electromotive force and winding temperature, the torque coefficient is dynamically adjusted to improve the conversion accuracy of torque to current. At the same time, a feedforward compensation mechanism is introduced to pre-compensate the motor drive voltage according to the gimbal movement speed, and finally the compensated drive voltage is converted into the duty cycle of the PWM signal to achieve precise control of the motor. The conversion process refers to the rated parameters of the motor and takes into account the driver limitations to ensure safe and stable operation of the system.

[0057] The processing flow of the control parameter generation unit is as follows: parse the preset shooting requirements, including but not limited to shooting scene type, expected subject position and lighting conditions; based on the analysis results, call the pre-established parameter mapping relationship to convert the shooting requirements into the corresponding initial gimbal control parameters, including three-axis angle values, speed and acceleration, etc., and optimize the parameters considering the current environmental factors; determine whether the gimbal control parameters are within the physical limitations and safe operation range of the gimbal, and if so, output the initial gimbal control parameters. This process realizes the effective conversion from high-level shooting requirements to specific gimbal control parameters, providing a reliable foundation for the initial positioning and subsequent precise control of the gimbal.

[0058] The processing flow of the servo control unit is as follows: obtain the initial pan-tilt control parameters generated by the control parameter generation unit; receive the illumination change judgment result output by the image acquisition unit and the gravity compensation angle value output by the gravity compensation unit; select a fast compensation strategy or a progressive compensation strategy according to the illumination change type in the illumination change judgment result to generate a pan-tilt angle compensation value; use the three-axis angle value in the initial pan-tilt control parameter as a reference, superimpose the gravity compensation angle value and the pan-tilt angle compensation value, and generate a comprehensive compensation control parameter; perform range limitation processing on the comprehensive compensation control parameter, convert the comprehensive compensation control parameter that has undergone range limitation processing into a drive signal, and output it to the drive execution unit.

[0059] Specifically, the process of generating the gimbal angle compensation value is as follows: Figure 4 As shown, the following steps are included: analyzing and identifying the type of illumination change in the illumination change judgment result; selecting a corresponding compensation strategy according to the identification result, selecting a fast compensation strategy for instantaneous illumination change, and selecting a gradual compensation strategy for continuous illumination change; obtaining camera parameters under current illumination conditions, including but not limited to exposure time, ISO and aperture value; under the fast compensation strategy, using a preset response curve, based on the amplitude and direction of illumination change, combined with current camera parameters, generating a gimbal angle compensation value; under the gradual compensation strategy, by analyzing the trend and rate of illumination change, combined with current camera parameters, constructing a smooth compensation curve, generating a gradually adjusted gimbal angle compensation value; and performing range limiting and smoothing on the generated gimbal angle compensation value to ensure that the parameter change is within the acceptable range of the system.

[0060] It should be noted that if the illumination change type is normal, there is no need to calculate the gimbal angle compensation value, and the gimbal angle compensation value can be recorded as 0.

[0061] It should be noted that the fast compensation strategy and the gradual compensation strategy are two compensation schemes for dealing with different lighting change situations. The fast compensation strategy is used to deal with instantaneous lighting changes, such as sudden strong light changes in the scene, and the subject entering or leaving the strong light area. In these scenarios, the system needs to quickly adjust the angle of the gimbal to ensure that the camera can quickly adapt to the new lighting conditions to avoid overexposure or dark images. The gradual compensation strategy is suitable for continuous lighting changes, such as sunrise and sunset. In these scenarios, the system needs to gradually adjust the angle of the gimbal to ensure that the camera can smoothly transition to the new lighting conditions, avoiding frequent adjustments and large compensations.

[0062] That is, the adjustment coefficient in the fast compensation strategy is larger, and the compensation amplitude is larger to achieve a fast response; while the adjustment coefficient in the progressive compensation strategy is smaller, the compensation amplitude is smaller, and the adjustment is smoother to adapt to slow changes in illumination.

[0063] It should also be noted that the gimbal angle compensation value is a control parameter used to adjust the gimbal position to cope with changes in lighting. The angle compensation value is mainly used to adjust the pitch axis of the gimbal, but does not rule out the possibility of adjusting the yaw and roll axes in certain circumstances. In a preferred embodiment, the angle compensation value is directly applied to the adjustment of the pitch axis, while the compensation values ​​of the yaw and roll axes can be set to 0. This configuration can effectively cope with most lighting changes, while simplifying the control logic and improving the system response speed and stability.

[0064] However, the control system of the present invention retains the ability to independently adjust all three axes to adapt to complex lighting environments and special shooting requirements. In practical applications, the angle compensation value can be integrated with other control input signals, such as user manual control instructions or the output of the automatic target tracking algorithm, to achieve comprehensive and accurate pan / tilt attitude control. Through this flexible design, the present invention can meet the needs of various complex shooting scenes while ensuring the simplicity of system operation, and effectively improve the image acquisition quality under different lighting conditions.

[0065] Furthermore, the present embodiment also provides a precise control method for an intelligent gimbal integrated with a photographic tripod system, which is as follows: a control parameter generation unit generates initial gimbal control parameters according to preset shooting requirements; a posture detection unit collects gimbal posture data and outputs a compensation posture vector; an image acquisition unit collects scene images and generates a lighting change judgment result; a gravity compensation unit calculates a gravity compensation angle value according to the compensation posture vector; a servo control unit dynamically adjusts the gimbal control parameters based on the lighting change judgment result and the gravity compensation angle value; a drive execution unit controls a stepper motor to drive the gimbal to a corresponding position according to the adjusted gimbal control parameters; the image acquisition unit executes scene shooting after the gimbal is stable, and the system performs a quality assessment on the shooting results; if the quality of the shooting results does not meet the preset threshold and the maximum number of adjustments is not reached, the servo control unit fine-tunes the gimbal control parameters based on the assessment results and returns to the drive execution unit step; if the quality of the shooting results meets the preset threshold or the maximum number of adjustments is reached, the current scene shooting task is completed.

[0066] It should be noted that this preset threshold serves as a quality control standard to ensure that the system can automatically determine whether the shooting results meet the expected quality, thereby deciding whether further adjustments or reshoots are needed.

[0067] In summary, the present invention improves the accuracy and stability of pan-tilt control to a certain extent by integrating functional modules such as posture detection, gravity compensation, image acquisition and servo control. The system can adapt to changes in illumination and help maintain the relative stability of image quality. The filtering, abnormal data removal and temperature compensation technologies used are conducive to improving the reliability of posture data and reducing the impact of temperature changes. The present invention has a certain real-time response capability and can adjust control parameters according to shooting requirements, which helps to improve shooting quality in different environments.

[0068] Example 2, reference Figure 1~Figure 4 , which is the second embodiment of the present invention, provides an intelligent pan-tilt integrated photography tripod system and a precise control method thereof. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0069] To verify the performance of the intelligent gimbal system, a series of experiments were conducted in indoor studios and outdoor scenes. The gimbal system used in the experiment is equipped with a Sony Alpha 7R IV, the lens is FE 24-70mm F2.8 GM, and the total weight of the camera and lens is about 1.8kg. The system's posture detection unit uses the MPU-9250 nine-axis sensor from TDK InvenSense, and the sampling frequency is set to 200Hz. The temperature sensor uses a PT100 platinum resistor with a measurement range of -50℃ to 150℃ and an accuracy of ±0.1℃. The drive system uses a 42 stepper motor, the subdivision is set to 256, and the positioning accuracy reaches 0.014°.

[0070] In the calibration phase, the gyroscope is first subjected to a temperature compensation experiment. In the range of -10°C to 40°C, the static deviation of the gyroscope is measured at intervals of 5°C to obtain the second-order polynomial fitting coefficients: X-axis [0.0023, -0.0156, 0.0892], Y-axis [0.0019, -0.0143, 0.0854], Z-axis [0.0021, -0.0149, 0.0873], and the fitting accuracy R 2 After 24 hours of continuous testing, the temperature-compensated gyro's zero-bias stability increased by 78.3%, from the original 0.46° / h to 0.10° / h.

[0071] The gravity compensation module is calibrated using a high-precision torque sensor ATI Mini45 to measure the actual gravity torque at different postures. The gimbal motion range is divided into 7 working intervals, and each interval is fitted using a linear model. The calibration results show that the maximum residual gravity torque after compensation is reduced to 0.012N·m, which is 93.6% lower than the 0.187N·m without compensation. In the dynamic test, at a rotation frequency of 2Hz, the peak tracking error is reduced from 1.24° to 0.16°.

[0072] The light adaptability test was conducted in different scenarios. Rapid light changes were simulated in an indoor studio, and professional LED lights were used to change the scene illumination from 100 lux to 2000 lux within 0.5 seconds. The system adopted a fast compensation strategy to complete the posture adjustment within 267ms, and the image exposure deviation was controlled within ±0.3EV. For the gradual lighting scene, continuous tracking shooting was performed for 2 hours during the sunset process. The system used a progressive compensation strategy to keep the image brightness standard deviation fluctuation within 4.2%.

[0073] The experimental results of the present invention show that the proposed system exhibits excellent performance in key performance indicators such as temperature adaptability, gravity compensation and illumination response. The temperature compensation module achieves a significant improvement in the gyroscope zero bias stability, the gravity compensation strategy effectively reduces the residual torque, and the illumination adaptation mechanism ensures the stable operation of the system under various lighting conditions. The overall performance of the system meets the high-precision requirements of professional photography, and at the same time has good environmental adaptability, providing reliable technical support for practical applications.

[0074] 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 preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An intelligent pan-tilt integrated photography tripod system, characterized in that: include, The attitude detection unit includes a three-axis accelerometer, a three-axis gyroscope and a temperature sensor, which is used to collect the attitude data of the gimbal and output a compensation attitude vector; An image acquisition unit, comprising a camera, wherein the camera acquires a scene image, and the image acquisition unit is used to extract brightness distribution characteristics of the scene image and generate a light change judgment result; A gravity compensation unit, the gravity compensation unit is connected to the posture detection unit, and the gravity compensation unit calculates a gravity compensation angle value of the gimbal based on the compensation posture vector; A control parameter generating unit, used to generate initial gimbal control parameters according to preset shooting requirements; A servo control unit, the servo control unit is connected to the gravity compensation unit and the image acquisition unit, and dynamically adjusts the pan / tilt control parameters according to the illumination change judgment result and the gravity compensation angle value; A driving execution unit, wherein the driving execution unit is connected to the servo control unit, and the driving execution unit comprises a stepping motor, and the stepping motor drives the pan-tilt head to rotate according to the adjusted pan-tilt head control parameters; The processing flow of the posture detection unit is as follows: The three-axis accelerometer and the three-axis gyroscope collect attitude data of the gimbal, and the attitude data includes three-axis acceleration data and three-axis angular velocity data; Performing low-pass filtering on the posture data to obtain filtered posture data; Using an extended Kalman filter, estimating an initial attitude vector based on the filtered attitude data, wherein the initial attitude vector includes an attitude angle and a gyroscope bias; Based on the temperature data collected by the temperature sensor, the gyroscope deviation in the initial attitude vector is compensated in real time to obtain a compensated attitude vector; Outputting the compensated posture vector to the gravity compensation unit; The processing flow of the image acquisition unit is as follows: The camera collects scene images; Performing brightness analysis on the scene image to extract brightness distribution features; Perform time series analysis on the brightness distribution characteristics of multiple consecutive scene images and calculate the brightness change amount and change rate; Determining the type of illumination change based on the brightness change amount and the change rate, wherein the illumination change type includes normal, instantaneous change and continuous change; generating a light change judgment result, and outputting the light change judgment result to the servo control unit; The processing flow of the gravity compensation unit is as follows: Receiving the compensation posture vector output by the posture detection unit; According to the compensation attitude vector, the three-dimensional spatial attitude of the gimbal is calculated by using the quaternion method, and the gravity component of each axis is obtained by decomposing it through trigonometric functions; Obtain the gimbal load parameters and calculate the static gravity moment and dynamic inertia compensation moment based on the pre-established gimbal gravity characteristic model; The static gravity moment and the dynamic inertia compensation moment are superimposed to obtain a comprehensive compensation moment; Based on the comprehensive compensation torque, calculate the gravity compensation torque of each axis; After converting the gravity compensation torque into a gravity compensation angle value through a motor characteristic curve, the value is output to the servo control unit; The estimating of the initial posture vector based on the filtered posture data comprises the following steps: Initialize the estimated values ​​of attitude angle and gyroscope bias; The quaternion kinematic model is used to predict the attitude angle using the filtered angular velocity data; The filtered acceleration data is used as the observation value to correct the predicted attitude angle; Iteratively perform the prediction and correction steps to update the estimates of attitude angles and gyroscope biases; The iteration termination condition is determined by combining a fixed number of iterations with a convergence threshold; Output the initial attitude vector containing the updated attitude angle and gyroscope bias; The calculation formula of the static gravity moment is as follows: in, is the static gravity moment of the ith joint, is the equivalent mass of the i-th joint, g is the gravitational acceleration, is the equivalent effective arm length of the ith joint, is the angle of the i-th joint relative to the vertical direction, is the bearing friction coefficient of the ith joint, is the angular velocity of the i-th joint, is the friction torque of the ith joint, is a symbolic function.

2. The intelligent pan-tilt integrated photography tripod system as claimed in claim 1, characterized in that: The processing flow of the servo control unit is as follows: Obtaining initial PTZ control parameters generated by a control parameter generation unit; Receive the illumination change judgment result output by the image acquisition unit and the gravity compensation angle value output by the gravity compensation unit; According to the illumination change type in the illumination change judgment result, a corresponding compensation strategy is selected to generate a gimbal angle compensation value; The three-axis angle values ​​in the initial gimbal control parameters are used as a reference, and the gravity compensation angle value and the gimbal angle compensation value are superimposed to generate comprehensive compensation control parameters; The comprehensive compensation control parameter is subjected to range limitation processing, and the comprehensive compensation control parameter subjected to the range limitation processing is converted into a driving signal, which is output to the driving execution unit.

3. A precise control method for an intelligent pan-tilt integrated photography tripod system, based on the intelligent pan-tilt integrated photography tripod system according to any one of claims 1 to 2, characterized in that: Also includes, The control parameter generation unit generates initial gimbal control parameters according to preset shooting requirements; The attitude detection unit collects the gimbal attitude data and outputs the compensation attitude vector; The image acquisition unit acquires scene images and generates illumination change judgment results; The gravity compensation unit calculates a gravity compensation angle value according to the compensation posture vector; The servo control unit dynamically adjusts the pan / tilt control parameters based on the illumination change judgment result and the gravity compensation angle value; The driving execution unit controls the stepper motor to drive the pan / tilt to a corresponding position according to the adjusted pan / tilt control parameters; The image acquisition unit performs scene capture after the gimbal is stabilized, and the system performs quality assessment on the capture results; If the quality of the shooting result does not meet the preset threshold and the maximum number of adjustments is not reached, the servo control unit fine-tunes the gimbal control parameters based on the evaluation result and returns to the drive execution unit step; If the quality of the shooting result meets the preset threshold or reaches the maximum number of adjustments, the current scene shooting task is completed.

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