Cradle head dynamic control method and device

Abstract

The invention discloses a cradle head dynamic control method and device, and the method comprises the steps: obtaining a two-dimensional pixel coordinate of a target object on a display plane, converting the two-dimensional pixel coordinate into a physical space coordinate through a coordinate conversion algorithm, and obtaining the pixel offset of the target object relative to the center of a cradle head; based on the pixel offset and the pixel density parameter, performing angle calculation by using a trigonometric function calculation module to obtain rotation angle parameters required by the horizontal axis and the vertical axis of the holder; pWM control signal conversion is carried out on the rotation angle parameter, a corresponding number of pulse waveforms are generated through a stepping motor driving module, and a holder double-shaft motor is controlled to rotate; and based on the deviation value between the current position of the holder and the target angle, real-time error correction is performed by adopting a PID control algorithm, so that the holder tracks the target object in real time and keeps pointing to the position of the target object. Through the solid geometry correction technology, the problems of precise positioning and dynamic tracking of a traditional pan-tilt control system in a complex scene are solved, and the precision and stability of pan-tilt control are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of automatic control technology, and in particular to a pan-tilt dynamic control method and device, which is particularly suitable for application scenarios such as industrial automation, object detection, and logistics sorting that require precise positioning and dynamic tracking. Background Art

[0002] In fields such as industrial automation, object inspection, and logistics sorting, the gimbal (pan / tilt system) serves as a core motion control component. Its precise positioning and dynamic tracking capabilities directly impact equipment performance and accuracy. Traditional gimbal control technologies often rely on pre-set path planning or simple tracking algorithms based on two-dimensional images. For example, these algorithms directly map the target's pixel offset in the image to the gimbal's rotation angle.

[0003] However, such methods have significant limitations in complex scenarios: target positioning errors accumulate with increasing distance; they struggle to cope with dynamic disturbances such as conveyor belt motion and obstructions, and are prone to tracking lag or loss of lock. Furthermore, existing correction algorithms require additional sensors, which poses significant limitations such as high cost and susceptibility to environmental influences.

[0004] Therefore, there is an urgent need for a pan-tilt dynamic control method that can achieve high-precision positioning, has strong anti-interference ability and is suitable for complex scenarios to meet the needs of industrial automation for precise positioning and dynamic tracking. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and device for dynamic control of a pan-tilt platform, which can achieve high-precision positioning and dynamic tracking of the pan-tilt platform in complex scenes.

[0006] To achieve the above objectives, the technical solutions provided by this disclosure are as follows: A pan / tilt dynamic control method includes: obtaining two-dimensional pixel coordinates of a target object on a display plane, converting the two-dimensional pixel coordinates into physical space coordinates using a coordinate conversion algorithm, and obtaining a pixel offset of the target object relative to the pan / tilt center; performing angle calculation using a trigonometric function calculation module based on the pixel offset and a pixel density parameter calculated according to the physical size and resolution of the display, and obtaining rotation angle parameters required for the pan / tilt horizontal and vertical axes; converting the rotation angle parameters into pulse width modulation (PWM) control signals, generating a corresponding number of pulse waveforms using a stepper motor drive module, and controlling the rotation of the pan / tilt dual-axis motor; and performing real-time error correction using a proportional-integral-differential (PID) controller algorithm based on a deviation between the current pan / tilt position and a target angle, thereby enabling the pan / tilt to track the target object in real time and maintain its position at the target object.

[0007] Optionally, the two-dimensional pixel coordinates are converted into physical space coordinates through a coordinate conversion algorithm to obtain the pixel offset of the target object relative to the center of the gimbal, including: calculating the horizontal pixel density and the vertical pixel density according to the physical parameters and pixel resolution information of the display, and establishing a linear transformation relationship between the pixel coordinates and the physical coordinates; based on the linear transformation relationship and the pixel coordinates of the target object, calculating the pixel deviation value between the target point and the display center point, and converting it into an actual physical displacement distance; performing a coordinate system conversion on the physical displacement distance, converting the displacement in the display coordinate system into an offset parameter in the gimbal coordinate system, and obtaining the pixel offset of the target object relative to the center of the gimbal.

[0008] Optionally, obtaining the two-dimensional pixel coordinates of the target object on the display plane also includes a display plane calibration process: positioning the gimbal at a preset distance directly in front of the display, capturing the boundary feature points of the display through a camera, and obtaining the pixel coordinates of the four corner points of the display; based on the pixel coordinates of the four corner points, using a four-point calibration algorithm to establish a spatial coordinate mapping relationship and generate a geometric transformation matrix; capturing the boundary feature points of the pitch axis and roll axis of the gimbal, eliminating assembly errors through a geometric distortion correction algorithm, and obtaining the corrected two-dimensional pixel coordinate information.

[0009] Optionally, a trigonometric function calculation module is used to perform angle calculation to obtain the rotation angle parameters required for the horizontal and vertical axes of the gimbal, including: obtaining the actual displacement distance of the target object and the gimbal installation distance parameters, calculating the horizontal deflection angle through the inverse tangent function, and obtaining the rotation angle of the horizontal axis of the gimbal; based on the horizontal deflection angle and the installation distance, using the Pythagorean theorem to calculate the spatial hypotenuse distance to obtain the reference side length for vertical axis angle calculation; for the vertical displacement distance and the reference side length, calculating the vertical deflection angle through the inverse tangent function to obtain the rotation angle parameter required for the vertical axis of the gimbal.

[0010] Optionally, a trigonometric function calculation module is used to perform angle calculation, and a layered calculation strategy is adopted, including: obtaining the position information of the target coordinates and the current coordinates, judging the direction of movement and decomposing it into horizontal and vertical components, and determining a single-axis or dual-axis movement mode; based on the movement mode and displacement components, constructing a three-dimensional motion model and calculating the spatial slant distance to generate dual-axis motion parameters; performing dynamic coordinate decomposition on the dual-axis motion parameters, calculating the theoretical rotation angles of the X-axis and Y-axis respectively, and obtaining the rotation angle parameters required for the horizontal and vertical axes of the gimbal.

[0011] Optionally, the rotation angle parameters are converted into PWM control signals, and a corresponding number of pulse waveforms are generated through the stepper motor drive module to control the rotation of the dual-axis motor of the gimbal, including: obtaining the target rotation angles of the horizontal and vertical axes of the gimbal, calculating the required number of pulses according to the angular resolution of the stepper motor, and generating PWM waveform parameters; based on the PWM waveform parameters and the motor control frequency, a corresponding number of square wave signals are generated through the GPIO pin to drive the horizontal axis stepper motor to rotate; for the vertical axis rotation angle and pulse parameters, a vertical axis PWM control signal is generated through the timer module to drive the vertical axis stepper motor to rotate; based on the rotation state of the dual-axis motor, the completion of the pulse signal is monitored to monitor whether the gimbal rotates according to the calculated angle; the motor rotation process is monitored in real time, the rotation accuracy is verified through the position feedback signal, and the coordinated motion control of the dual axes of the gimbal is completed.

[0012] Optionally, a corresponding number of pulse waveforms are generated by a stepper motor drive module, including: obtaining the target number of rotation steps and motion speed parameters, calculating the acceleration and deceleration parameters of the S-shaped acceleration and deceleration curve, and generating speed planning data; based on the speed planning data and motor characteristic parameters, calculating the pulse frequency of each stage through the acceleration buffer, and establishing a segmented speed control sequence; performing timing control on the segmented speed control sequence, gradually increasing the PWM frequency in the acceleration stage to achieve smooth start-up of the motor; based on the motor motion state and the remaining number of steps, gradually reducing the PWM frequency in the deceleration stage to achieve smooth stop of the motor; performing closed-loop control on the entire motion process, and adjusting the pulse timing through position encoder feedback so that the corresponding number of pulse waveforms are executed.

[0013] Optionally, a PID control algorithm is used for real-time error correction to enable the gimbal to track the target object in real time and keep it pointing to the target object position, including: obtaining the current angle and target angle information of the gimbal, calculating the position error, speed error and integral error, and generating PID control parameters; based on the PID control parameters and the system response characteristics, adjusting the response speed through a proportional control link to obtain a proportional control output; processing the integral value of the position error, eliminating the steady-state error through an integral control link to obtain an integral control output; based on the error change rate and the differential time constant, suppressing system oscillation through a differential control link to obtain a differential control output; performing weighted summation on the proportional, integral and differential control outputs to generate a final control signal and output it to the motor driver, so as to enable the gimbal to track the target object in real time and keep it pointing to the target object position.

[0014] Optionally, it also includes stereo geometric correction processing based on a three-dimensional coordinate mapping model, including: obtaining camera calibration parameters and laser pen calibration parameters, establishing a mapping relationship between image pixel coordinates and three-dimensional space coordinates, and generating a stereo geometric correction model; based on the stereo geometric correction model and conveyor belt motion parameters, calculating the spatial position compensation amount of the target object, and obtaining the corrected target coordinates; detecting the geometric distortion in the image acquisition process, eliminating perspective deformation and radial distortion through a distortion correction algorithm, and generating corrected image coordinates; based on environmental interference factors and sensor noise, using a Kalman filter algorithm for data fusion to obtain stable target position information; performing time synchronization processing on multi-sensor data, and achieving data alignment through timestamp calibration and interpolation algorithms to ensure the timeliness and accuracy of the real-time tracking and maintaining the position of the target object.

[0015] The present disclosure also provides a gimbal dynamic control device, including: a coordinate conversion module, used to obtain the two-dimensional pixel coordinates of the target object on the display plane, and convert the two-dimensional pixel coordinates into physical space coordinates through a coordinate conversion algorithm to obtain the pixel offset of the target object relative to the center of the gimbal; an angle calculation module, used to perform angle calculation based on the pixel offset and the pixel density parameter calculated according to the physical size and resolution of the display, using a trigonometric function calculation module to obtain the rotation angle parameters required for the horizontal and vertical axes of the gimbal; a motor control module, used to convert the rotation angle parameters into PWM control signals, generate a corresponding number of pulse waveforms through a stepper motor drive module, and control the dual-axis motor of the gimbal to rotate; a tracking control module, used to perform real-time error correction based on the deviation value between the current position of the gimbal and the target angle, using a PID control algorithm, to achieve real-time tracking of the gimbal to the target object and keep it pointing to the target object position.

[0016] The present disclosure provides another gimbal dynamic control device, including a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory. When the machine-readable instructions are executed by the processor, the processor performs the steps of the gimbal dynamic control method described above.

[0017] The present disclosure further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer device, the computer device executes the steps of the above-mentioned pan-tilt dynamic control method.

[0018] Based on the above description, it can be seen that the disclosed embodiments achieve high-precision positioning and dynamic tracking of the gimbal in complex scenarios by establishing a precise mapping relationship between image pixel coordinates and three-dimensional spatial coordinates. The trigonometric function calculation module is used for angle calculation, improving the accuracy and efficiency of angle calculation. Through PWM control signal conversion and a stepper motor drive module, precise control of the gimbal's dual-axis motor is achieved. The PID control algorithm is used for real-time error correction, improving the stability and response speed of the gimbal control. Thus, the disclosed embodiments can achieve high-precision positioning, strong anti-interference capabilities, and are suitable for gimbal control in complex scenarios, meeting the needs of the industrial automation field for precise positioning and dynamic tracking.

[0019] In addition, stereo geometry correction processing based on a three-dimensional coordinate mapping model is adopted to solve the problems of precise positioning and dynamic tracking of traditional pan-tilt control systems in complex scenes. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following briefly introduces the drawings required for use in the embodiments. The drawings herein are incorporated into and constitute a part of the specification. These drawings illustrate embodiments consistent with the present disclosure and, together with the specification, are used to illustrate the technical solutions of the present disclosure. It should be understood that the following drawings only illustrate certain embodiments of the present disclosure and should not be regarded as limiting the scope. For those of ordinary skill in the art, other relevant drawings can be obtained based on these drawings without inventive effort.

[0021] Figure 1 This is a flow chart of the pan / tilt dynamic control method disclosed herein; Figure 2 A schematic diagram of the process for indicating motor deflection; Figure 3 This is a coordinate conversion flow chart of the present disclosure; Figure 4 This is a schematic diagram of the placement of the PTZ and smart display terminal; Figure 5 This is a flowchart for solving the angle of this disclosure; Figure 6 This is a flow chart of PWM control signal conversion disclosed herein; Figure 7 This is a flow chart of the PID control algorithm disclosed in the present invention; Figure 8 This is a structural diagram of the pan-tilt dynamic control device disclosed herein; Figure 9 Schematic diagram of a computer device provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the embodiments of the present disclosure clearer, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The components of the embodiments of the present disclosure generally described and shown in the drawings herein can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present disclosure provided in the drawings is not intended to limit the scope of the disclosure for which protection is sought, but merely represents selected embodiments of the present disclosure. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present disclosure.

[0023] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0024] The term "and / or" herein simply describes an association relationship, indicating that three relationships can exist. For example, A and / or B can represent the existence of A alone, the simultaneous existence of A and B, and the existence of B alone. In addition, the term "at least one" herein refers to any combination of at least two of any one or more of a plurality of items. For example, "at least one of A, B, and C" can represent any one or more elements selected from the set consisting of A, B, and C.

[0025] The present disclosure will be further described below with reference to the accompanying drawings and embodiments.

[0026] Example 1: like Figure 1 As shown, a pan-tilt dynamic control method includes: In this embodiment, the pan / tilt dynamic control method based on stereo geometry correction mainly includes four core steps, each of which will be described in detail below.

[0027] S1: Obtain the two-dimensional pixel coordinates of the target object on the display plane, convert the two-dimensional pixel coordinates into physical space coordinates through a coordinate conversion algorithm, and obtain the pixel offset of the target object relative to the center of the gimbal.

[0028] This step first uses a camera to capture an image of the target object on the display plane and uses image processing techniques to obtain the target object's two-dimensional pixel coordinates. This system uses the display screen as a visual positioning reference. Its physical parameters are clearly marked as 1366 pixels for a horizontal effective display area of ​​700 mm and 768 pixels for a vertical effective height of 393 mm. Calibration confirms that the display center is located at the pixel coordinates of column 683 and row 384. During deployment, the gimbal maintains a standard mounting distance of 500 mm from the display plane. Geometric calibration calculates a horizontal pixel density of 0.512 mm / pixel (700 mm ÷ 1366) and a vertical pixel density of 0.511 mm / pixel (393 mm ÷ 768). Based on the mapping relationship between the Cartesian coordinate system and the pixel coordinate system, the system converts the target pixel offset into an actual displacement value. For example, a 100-pixel shift to the left on the X-axis corresponds to an actual displacement of 51.2 mm. This provides the pixel offset of the target object relative to the gimbal center.

[0029] S2: Based on the pixel offset and the pixel density parameter calculated according to the physical size and resolution of the display, a trigonometric function calculation module is used to perform angle calculation to obtain the rotation angle parameters required for the horizontal and vertical axes of the gimbal.

[0030] This step adopts a layered solution strategy. First, the pixel deviations ΔPx=|Px-683| and ΔPy=|Py-384| between the target point and the center point are calculated. The actual displacements Sx and Sy are converted through pixel density parameters respectively. Then, a right triangle is constructed with the X-axis displacement to calculate the basic deflection angle θx=arctan(Sx / D), where D is the fixed installation distance of 500 mm. Then, D and Sx are used as adjacent sides to construct the hypotenuse L= , using this as the new reference edge to calculate the Y-axis deflection angle θy = arctan (Sy / L). This algorithm innovatively uses dynamic coordinate decomposition technology. When dealing with oblique positioning requirements, the system automatically constructs a three-dimensional motion model, first solving the spatial slant distance using the Pythagorean theorem, and then decomposing it into dual-axis motion parameters to achieve high-precision positioning in non-orthogonal directions, ultimately obtaining the required deflection angles for the X-axis motor and the Y-axis motor. Figure 2 The figure shows a flow chart indicating the deflection of the motor.

[0031] S3: Convert the rotation angle parameter into a pulse width modulation (PWM) control signal, generate a corresponding number of pulse waveforms through a stepper motor drive module, and control the pan / tilt dual-axis motor to rotate.

[0032] The gimbal control system utilizes a modular design for precise positioning. Upon receiving target coordinate commands, the main control unit first analyzes the coordinate parameters and converts them into motion parameters in the device coordinate system. The control system incorporates a built-in coordinate conversion algorithm that automatically calculates the required X / Y-axis rotation parameters by mapping the display pixel coordinate system to the gimbal's rotation angle. These parameters are processed by the motion planning module, which generates two PWM control signals to drive the gimbal motors. Each square wave generates a 0.001-degree rotation of the gimbal, achieving precise control of every pixel. The system adjusts the X-axis step rate to achieve the target angle, adjusts the X-axis angle to achieve the target coordinate, and adjusts the X-axis target coordinate to move the gimbal to the specified position. The same principle applies to Y-axis control, enabling coordinated motion of the gimbal's dual-axis motors.

[0033] S4: Based on the deviation between the gimbal's current position and the target angle, a proportional-integral-differential controller (PID) algorithm is used to perform real-time error correction, enabling the gimbal to track the target object in real time and keep it pointing to the target object.

[0034] During the dynamic execution phase, the gimbal control system will compare the current posture with the target parameters in real time and start the high-precision motor drive device. Through the built-in PID control algorithm, the system continuously monitors the rotational displacement of the actuator and dynamically corrects the error value between the target angle and the actual position. The PID control algorithm adjusts the response speed through the proportional link, eliminates the steady-state error through the integral link, and suppresses the system oscillation through the differential link. The weighted sum of the three generates the final control signal. Based on the current angle and target angle information of the gimbal, the system calculates the position error, speed error, and integral error, generates PID control parameters, and accurately controls the motor according to these parameters until the gimbal stabilizes at the calculated target azimuth angle, completing the precise indication of the target object, and realizing the gimbal's real-time tracking of the target object and maintaining its position at the target object.

[0035] like Figure 3 As shown, based on Example 1, the two-dimensional pixel coordinates are converted into physical space coordinates through a coordinate conversion algorithm to obtain the pixel offset of the target object relative to the center of the gimbal, including: S1.1: Calculate the horizontal and vertical pixel densities based on the display's physical parameters and pixel resolution information, and establish a linear transformation relationship between pixel coordinates and physical coordinates. In this embodiment, the horizontal and vertical pixel densities are first calculated based on the physical parameters and pixel resolution information of the display. For example, a display with a horizontal effective display area of ​​700 mm corresponds to 1366 pixel units, and a vertical effective height of 393 mm corresponds to 768 pixel units. The horizontal pixel density can be calculated to be 0.512 mm / pixel (700 mm ÷ 1366), and the vertical pixel density is 0.511 mm / pixel (393 mm ÷ 768). Then, based on these parameters and the pixel coordinates of the target object, the pixel deviation between the target point and the display center is calculated and converted into the actual physical displacement distance. Finally, the physical displacement distance is transformed into a coordinate system, converting the displacement in the display coordinate system into an offset parameter in the pan / tilt coordinate system, thereby obtaining the pixel offset of the target object relative to the pan / tilt center.

[0036] Specifically, in the first step of the coordinate conversion algorithm, the system calculates the horizontal and vertical pixel densities based on the display's physical parameters and pixel resolution information, establishing a linear transformation relationship between pixel coordinates and physical coordinates. The display device used in this system has clearly calibrated physical parameters: a horizontal effective display area of ​​700 mm, corresponding to 1366 pixel units; and a vertical effective height of 393 mm, corresponding to 768 pixel units. Through precise calculations, the system obtains a horizontal pixel density of 0.512 mm / pixel (i.e., 700 mm ÷ 1366 pixels) and a vertical pixel density of 0.511 mm / pixel (i.e., 393 mm ÷ 768 pixels). These parameters form the basis for the linear transformation between pixel coordinates and physical coordinates, ensuring the accuracy of subsequent calculations.

[0037] S1.2: Based on the linear transformation relationship and the pixel coordinates of the target object, calculate the pixel deviation between the target point and the display center point, and convert it into an actual physical displacement distance; In the second step, the system calculates the pixel deviation value between the target point and the display center point based on the established linear transformation relationship and the pixel coordinates of the target object, and converts it into the actual physical displacement distance. The system confirms that the center point of the display is located at the pixel coordinate position of the 683rd column and the 384th row through calibration. When the target object is detected at a specific pixel coordinate (Px, Py), the system calculates the pixel deviation value ΔPx=|Px-683| and ΔPy=|Py-384| between the target point and the center point, and converts the pixel deviation into a physical displacement using the aforementioned pixel density parameters, i.e., Sx=ΔPx×0.512 mm / pixel and Sy=ΔPy×0.511 mm / pixel. This conversion process establishes the precise physical position of the target object on the display plane.

[0038] S1.3: Perform coordinate system conversion on the physical displacement distance, convert the displacement in the display coordinate system into an offset parameter in the gimbal coordinate system, and obtain a pixel offset of the target object relative to the center of the gimbal.

[0039] In the third step, the system performs a coordinate system conversion on the physical displacement distance, converts the displacement in the display coordinate system into an offset parameter in the gimbal coordinate system, and obtains the pixel offset of the target object relative to the center of the gimbal. Since the gimbal maintains a standard installation distance of 500 mm from the display plane, the system needs to convert the plane displacement into an angle parameter. In this process, the system establishes a mapping relationship between the display coordinate system and the gimbal coordinate system, and converts the two-dimensional plane coordinates into three-dimensional space parameters in the gimbal coordinate system through spatial geometric transformation. This coordinate system conversion takes into account the installation position, posture, and relative relationship of the gimbal to the display, ensuring the accuracy of subsequent angle calculations.

[0040] like Figure 3 As shown, based on Example 1, obtaining the two-dimensional pixel coordinates of the target object on the display plane also includes a display plane calibration process: S1.4: Position the gimbal at a preset distance directly in front of the display. Use the camera to capture the display's boundary feature points and obtain the pixel coordinates of the display's four corner points. In this embodiment, the gimbal is first positioned at a preset distance (e.g., 50 cm) directly in front of the display. A camera is used to capture the display's boundary feature points, obtaining the pixel coordinates of the display's four corner points. Based on these four corner point pixel coordinates, a four-point calibration algorithm is then used to establish a spatial coordinate mapping relationship, generating a geometric transformation matrix. Finally, boundary feature points are captured for the gimbal's pitch and roll axes, and a geometric distortion correction algorithm is used to eliminate assembly errors, resulting in corrected two-dimensional pixel coordinate information. This ensures the accuracy of subsequent coordinate transformations.

[0041] In the first step of the display plane calibration process, the system positions the gimbal at a preset distance directly in front of the display, captures the display boundary feature points through the camera, and obtains the pixel coordinates of the four corner points of the display. The operator must first position the gimbal vertically at a reference distance of 50 cm directly in front of the display according to the system parameter settings, and align it horizontally with the geometric center line of the display area. The installation orientation of the camera is highly inclusive and only needs to meet the field of view requirements of panoramic coverage (it is recommended to cover the 3° safety area outside the display), but it is necessary to ensure that the angle error between the camera optical axis and the display plane normal during the calibration process is not too large to avoid coordinate conversion distortion caused by perspective deformation. Through high-precision image processing algorithms, the system can accurately identify the pixel coordinates of the four corner points of the display, providing basic data for subsequent spatial coordinate mapping.

[0042] S1.5: Based on the pixel coordinates of the four corner points, a spatial coordinate mapping relationship is established using a four-point calibration algorithm to generate a geometric transformation matrix; Based on the pixel coordinates of the four corner points, the system uses a four-point calibration algorithm to establish a spatial coordinate mapping relationship and generate a geometric transformation matrix. The four-point calibration algorithm is a classic computer vision technology that calculates the transformation matrix from pixel coordinates to physical coordinates by knowing the actual physical coordinates of the four corner points and the corresponding pixel coordinates. This algorithm can effectively handle geometric transformations such as perspective deformation, rotation, and scaling, and generate accurate coordinate mapping relationships. By solving the perspective transformation equations, the system obtains a 3×3 transformation matrix, which contains complete mapping information from pixel coordinates to physical coordinates, providing a mathematical basis for subsequent coordinate conversion.

[0043] S1.6: Capture boundary feature points of the gimbal's pitch axis and roll axis, eliminate assembly errors using a geometric distortion correction algorithm, and obtain the corrected two-dimensional pixel coordinate information.

[0044] The system captures boundary feature points along the gimbal's pitch and roll axes, eliminates assembly errors through a geometric distortion correction algorithm, and obtains corrected two-dimensional pixel coordinate information. During the actual assembly process, slight deviations may exist in the gimbal's installation position and posture, which can lead to systematic errors in coordinate transformation. To eliminate these errors, the system uses a laser-assisted positioning function to fine-tune the gimbal's spatial orientation until the laser mark completely coincides with the system's preset reference point, completing the spatial anchoring of the monitoring device. Simultaneously, the system employs a geometric distortion correction algorithm to capture and analyze boundary feature points, calculate compensation parameters for assembly errors, and thus obtain corrected two-dimensional pixel coordinate information, ensuring the accuracy of subsequent coordinate transformations.

[0045] like Figure 4 The figure below shows the placement of the gimbal and smart display terminal. Combined with the description of the display plane calibration process above, the core of the device positioning phase lies in establishing a spatial reference relationship between the gimbal and the display terminal (display). The operator must first position the gimbal vertically at a reference distance of 50 cm directly in front of the display terminal, aligning it horizontally with the geometric centerline of the display area, based on the system parameter settings. After completing the physical positioning, the calibration process must be executed: the camera captures the display's boundary feature points, and a four-point calibration algorithm is used to establish a spatial coordinate mapping relationship. Boundary feature point capture and geometric distortion correction are performed on the gimbal's pitch and roll axes, eliminating coordinate system offsets caused by assembly errors. The camera's mounting orientation is highly flexible and only needs to meet the field of view requirements for panoramic coverage (recommended to cover a 3° safety zone extending beyond the display). However, during the calibration process, the angle between the camera's optical axis and the display plane normal must be kept within a certain range to avoid coordinate transformation distortion caused by perspective distortion.

[0046] like Figure 5 As shown, based on Example 1, the trigonometric function calculation module is used to perform angle calculation to obtain the required rotation angle parameters of the horizontal axis and vertical axis of the gimbal, including: S2.1: Obtain the actual displacement distance of the target object and the gimbal installation distance parameters, calculate the horizontal deflection angle using the inverse tangent function, and obtain the gimbal horizontal axis rotation angle; In this embodiment, the actual displacement distance of the target object and the gimbal installation distance parameter (e.g., 500 mm) are first obtained. The horizontal deflection angle is calculated using the inverse tangent function to obtain the gimbal's horizontal axis rotation angle. For example, if the target object's horizontal displacement is 51.2 mm, the horizontal deflection angle θx = arctan(51.2 / 500) ≈ 5.85°. Based on the horizontal deflection angle and the installation distance, the Pythagorean theorem is used to calculate the hypotenuse distance to obtain the reference side length for vertical axis angle calculation. Finally, the vertical deflection angle is calculated using the inverse tangent function based on the vertical displacement distance and the reference side length to obtain the required gimbal vertical axis rotation angle parameter.

[0047] The system obtains the actual displacement distance of the target object and the gimbal installation distance parameters, and calculates the horizontal deflection angle using the inverse tangent function to obtain the gimbal's horizontal axis rotation angle. When the system receives a command to move the X-axis to the left, it first converts the target pixel offset into an actual displacement value (for example, Δx = 100 pixels corresponds to Sx = 51.2 mm). The gimbal's horizontal deflection angle is then calculated using the trigonometric function θx = arctan(Sx / D), where D is the fixed installation distance of 500 mm. This calculation method, based on the principles of spatial geometry, converts planar displacement into angular parameters by establishing a right triangle, ensuring accurate calculation of the horizontal axis rotation angle.

[0048] S2.2: Based on the horizontal deflection angle and the installation distance, use the Pythagorean theorem to calculate the spatial hypotenuse distance to obtain the reference side length for vertical axis angle calculation; Based on the horizontal deflection angle and installation distance, the Pythagorean theorem is used to calculate the spatial hypotenuse distance to obtain the reference side length for vertical axis angle calculation. In three-dimensional space, when the horizontal axis of the gimbal rotates, the vertical axis angle calculation needs to consider the change in spatial geometric relationship. The system uses D and Sx as adjacent sides to construct a right triangle, and calculates the hypotenuse length L= using the Pythagorean theorem. This hypotenuse length serves as the new reference length for vertical axis angle calculation, taking into account the impact of horizontal axis rotation on vertical axis angle calculation and ensuring the accuracy of dual-axis coordinated motion.

[0049] S2.3: Calculate the vertical deflection angle using an inverse tangent function based on the vertical displacement distance and the reference side length to obtain the required rotation angle parameter of the vertical axis of the gimbal.

[0050] For the vertical displacement distance and the reference side length, the vertical deflection angle is calculated by the inverse tangent function to obtain the rotation angle parameters required for the vertical axis of the gimbal. Based on the reference side length L calculated in the previous step, the system uses the inverse tangent function θy=arctan(Sy / L) to calculate the vertical deflection angle, where Sy is the vertical displacement distance. This calculation method takes into account the changes in the spatial geometric relationship after the horizontal axis is rotated, ensuring the accurate calculation of the vertical axis rotation angle. For the control requirements of any coordinate point (Px, Py), the system first calculates the horizontal axis rotation angle through this hierarchical solution strategy, and then calculates the vertical axis rotation angle based on the spatial geometric relationship after the horizontal axis is rotated, thereby realizing precise positioning control of the gimbal's dual axes.

[0051] like Figure 5 As shown, based on Example 1, the trigonometric function calculation module is used to solve the angle, and a layered solution strategy is adopted, including: S2.4: Obtain the target coordinates and current coordinates, determine the direction of motion, decompose it into horizontal and vertical components, and determine whether the motion mode is single-axis or dual-axis. Obtain the position information of the target coordinates and the current coordinates, determine the direction of movement and decompose it into horizontal and vertical components, and determine the single-axis or dual-axis movement mode. When the system receives the target coordinate instruction, it first compares the difference between the target position and the current position to determine the required movement direction and mode. If the target position differs from the current position only in the X-axis or Y-axis direction, the system will adopt a single-axis movement mode; if there is a difference in both directions, the dual-axis movement mode will be adopted. This intelligent judgment mechanism can optimize the movement path and improve positioning efficiency. For single-axis movement, the system directly uses the Euler circle method to calculate the angle of rotation of the corresponding axis; for dual-axis movement, it is necessary to further construct a three-dimensional movement model to achieve more complex spatial positioning.

[0052] S2.5: Based on the motion pattern and displacement components, construct a three-dimensional motion model and calculate the spatial slant distance to generate biaxial motion parameters; Based on the motion pattern and displacement components, a three-dimensional motion model is constructed and the spatial slant distance is calculated to generate dual-axis motion parameters. When it is determined that dual-axis coordinated motion is required, the system uses the horizontal and vertical displacement components as the two right-angled sides of a right triangle and calculates the spatial slant distance using the Pythagorean theorem. This spatial slant distance reflects the actual distance between the target point and the current point in three-dimensional space, providing a basis for subsequent angle calculations. At the same time, the system takes into account the motion characteristics and mechanical structure constraints of the gimbal to generate parameters suitable for dual-axis coordinated motion, including motion speed, acceleration, and deceleration, to ensure the smoothness and accuracy of the motion process.

[0053] S2.6: Perform dynamic coordinate decomposition on the dual-axis motion parameters, calculate the theoretical rotation angles of the X-axis and Y-axis respectively, and obtain the required rotation angle parameters of the horizontal axis and vertical axis of the gimbal.

[0054] The dual-axis motion parameters are subjected to dynamic coordinate decomposition, and the theoretical rotation angles of the X-axis and Y-axis are calculated respectively to obtain the required rotation angle parameters of the horizontal and vertical axes of the gimbal. In three-dimensional space, the position of the target point can be represented by a spherical coordinate system, which contains radial distance, horizontal angle and vertical angle. The system uses dynamic coordinate decomposition technology to convert the angle parameters in the spherical coordinate system into the rotation angles of the horizontal and vertical axes of the gimbal. This decomposition method takes into account the mechanical structure and motion characteristics of the gimbal, ensuring the consistency between the theoretical calculation angle and the actual execution angle. By accurately calculating the theoretical rotation angles of the X-axis and Y-axis, the system can achieve precise positioning of the target point, regardless of its spatial position.

[0055] In this embodiment, the position information of the target coordinates and the current coordinates is first obtained. The direction of motion is determined and decomposed into horizontal and vertical components to determine whether the motion mode is single-axis or dual-axis. If only X-axis movement is required, the X-axis rotation angle is calculated using the Euler circle method; if only Y-axis movement is required, the Y-axis rotation angle is calculated using the Euler circle method. If both X and Y axes require movement, a three-dimensional motion model is constructed based on the motion mode and displacement components, and the spatial slant distance is calculated to generate dual-axis motion parameters. Finally, the dual-axis motion parameters are dynamically decomposed to calculate the theoretical rotation angles of the X and Y axes, respectively, to obtain the required rotation angle parameters for the horizontal and vertical axes of the gimbal.

[0056] like Figure 6 As shown, based on Example 1, the rotation angle parameter is subjected to pulse width modulation (PWM) control signal conversion, and a corresponding number of pulse waveforms are generated by a stepper motor drive module to control the pan-tilt dual-axis motor to rotate, including: S3.1: Obtain the target rotation angles of the horizontal and vertical axes of the gimbal, calculate the required number of pulses based on the angular resolution of the stepper motor, and generate PWM waveform parameters; The target rotation angles of the gimbal's horizontal and vertical axes are obtained, and the required number of pulses is calculated based on the stepper motor's angular resolution to generate PWM waveform parameters. The gimbal control system uses a modular design to achieve precise positioning. Upon receiving the target coordinate command, the main control unit first parses the coordinate parameters and converts them into motion parameters in the device coordinate system. Based on the stepper motor's angular resolution (each pulse corresponds to a rotation angle of 0.001 degrees), the system converts the target rotation angle into the required number of pulses. For example, if the horizontal axis needs to rotate 5.85 degrees, 5850 pulses are required. Based on these pulse numbers, the system generates the corresponding PWM waveform parameters, including frequency, duty cycle, and number of pulses, providing the basis for subsequent motor control.

[0057] S3.2: Based on the PWM waveform parameters and the motor control frequency, generate a corresponding number of square wave signals through the General Purpose Input / Output (GPIO) pins to drive the horizontal axis stepper motor to rotate; Based on the PWM waveform parameters and motor control frequency, a corresponding number of square wave signals are generated through the GPIO pins to drive the horizontal-axis stepper motor to rotate. Once the system determines the PWM waveform parameters, it outputs the square wave signals through the microcontroller's GPIO pins. The frequency and number of these square wave signals are calculated in the previous step, with each square wave corresponding to a microstep of the stepper motor. The system controls the angle of the gimbal's X-axis deflection by controlling the number of PWM waves generated. The following is a function implementation for generating a corresponding number of X-axis PWM waves: Through loop control, the system can accurately generate the required number of pulse waveforms to ensure that the horizontal-axis stepper motor rotates according to the predetermined angle. At the same time, the system can also control the motor's rotation speed by adjusting the frequency of the PWM waveform, achieving a smooth start and stop process.

[0058] S3.3: Based on the vertical axis rotation angle and pulse parameters, the timer module generates a vertical axis PWM control signal to drive the vertical axis stepper motor to rotate; Based on the vertical axis rotation angle and pulse parameters, the timer module generates a vertical axis PWM control signal to drive the vertical axis stepper motor. Similar to horizontal axis control, the system calculates the required number of pulses based on the target vertical axis rotation angle and the angular resolution of the stepper motor. However, the system uses a timer module to generate the vertical axis PWM control signal. This method provides more precise timing control and ensures smooth operation of the vertical axis motor. The timer module automatically generates the required PWM waveform in the background through a hardware interrupt mechanism, reducing the burden on the main processor and improving system responsiveness and stability.

[0059] S3.4: Based on the rotation status of the dual-axis motor, monitor the completion of the pulse signal to monitor whether the gimbal rotates according to the calculated angle; Based on the rotational status of the dual-axis motors, the completion of pulse signals is monitored to ensure that the pan / tilt rotates according to the calculated angle. During the motor control process, the system needs to monitor the generation and execution of pulse signals in real time to ensure that all pulses are correctly executed, thereby ensuring that the pan / tilt rotates according to the predetermined angle. The system records the number of pulses generated and executed by setting a status flag or counter. When all pulses have been executed, it indicates that the motor has rotated to the target position. This monitoring mechanism can promptly detect anomalies in the motor control process, such as pulse loss or motor stall, providing the system with a basis for fault diagnosis and troubleshooting.

[0060] S3.5: Monitor the motor rotation process in real time, verify the rotation accuracy through position feedback signals, and complete the coordinated motion control of the gimbal's two axes.

[0061] The motor's rotation process is monitored in real time, and rotation accuracy is verified through position feedback signals to achieve coordinated motion control of the gimbal's two axes. To ensure the accuracy of the gimbal's positioning, the system adopts a closed-loop control strategy, using position feedback signals to monitor the motor's actual rotation in real time. The position feedback signal can come from an encoder, Hall effect sensor, or other position detection device, which can provide information on the motor's actual rotation angle. The system compares this feedback information with the target angle, calculates the position error, and adjusts the control strategy based on the error, such as adjusting the pulse frequency or adding compensation pulses. Through this closed-loop control mechanism, the system can achieve high-precision coordinated motion control of the gimbal's two axes, ensuring that the gimbal accurately points to the target position.

[0062] In this embodiment, the target rotation angles of the horizontal and vertical axes of the gimbal are first obtained. The required number of pulses is calculated based on the stepper motor's angular resolution (e.g., 0.001 degrees / pulse), and PWM waveform parameters are generated. Then, based on the PWM waveform parameters and the motor control frequency, a corresponding number of square wave signals are generated via the GPIO pins to drive the horizontal-axis stepper motor. Simultaneously, based on the vertical-axis rotation angle and pulse parameters, a vertical-axis PWM control signal is generated via a timer module to drive the vertical-axis stepper motor. Next, based on the rotation status of the dual-axis motors, the completion of the pulse signals is monitored to ensure that the gimbal is rotating according to the calculated angles. Finally, the motor rotation process is monitored in real time, and the rotation accuracy is verified using position feedback signals, completing the coordinated motion control of the gimbal's dual axes.

[0063] like Figure 6 As shown, based on Example 1, a corresponding number of pulse waveforms are generated by the stepper motor driving module, including: S3.6: Obtain the target rotation step number and motion speed parameters, calculate the acceleration and deceleration parameters of the S-shaped acceleration and deceleration curve, and generate speed planning data; S3.7: Based on the speed planning data and motor characteristic parameters, calculate the pulse frequency of each stage through the acceleration buffer and establish a segmented speed control sequence; S3.8: Performing timing control on the segmented speed control sequence, gradually increasing the PWM frequency during the acceleration phase to achieve smooth motor startup; S3.9: Based on the motor's motion state and the number of remaining steps, the PWM frequency is gradually reduced during the deceleration phase to achieve a smooth stop of the motor. S3.10: Closed-loop control is performed on the entire motion process, and the pulse timing is adjusted through position encoder feedback so that the corresponding number of pulse waveforms are executed.

[0064] In this embodiment, the target number of rotation steps and motion speed parameters are first obtained, the acceleration and deceleration parameters of the S-shaped acceleration and deceleration curve are calculated, and the speed planning data is generated. Then, based on the speed planning data and the motor characteristic parameters, the pulse frequency of each stage is calculated through the acceleration buffer, and a segmented speed control sequence is established. The segmented speed control sequence is then time-controlled, and the PWM frequency is gradually increased in the acceleration stage to achieve smooth start-up of the motor. Then, based on the motor motion state and the remaining number of steps, the PWM frequency is gradually reduced in the deceleration stage to achieve smooth stop of the motor. Finally, the entire motion process is closed-loop controlled, and the pulse timing is adjusted through position encoder feedback so that a corresponding number of pulse waveforms are executed.

[0065] The system obtains the target number of rotation steps and motion speed parameters, calculates the acceleration and deceleration parameters of the S-type acceleration and deceleration curve, and generates speed planning data. When the system sets the step parameters of the gimbal X-axis, it first receives the target number of rotation steps through the function Tripod_X_Step(int32_t step) and stores it in the Tripod_X_Step_Mode variable. Subsequently, the system calls the Tripod_Buffer.Calculate(tripod_x_buffer, step) function to calculate the parameters of the S-type acceleration and deceleration curve. Compared with the traditional trapezoidal speed curve, the S-type acceleration and deceleration curve has a smoother acceleration and deceleration process, which can effectively reduce the impact and vibration when the motor starts and stops. By analyzing the target number of steps and the preset maximum speed and acceleration limits, the system generates complete speed planning data, providing a basis for subsequent motor control.

[0066] Based on the speed planning data and motor characteristic parameters, the system calculates the pulse frequency for each stage using an acceleration buffer and establishes a segmented speed control sequence. The acceleration buffer is a special data structure used to store speed and acceleration information for each stage of motor motion. Based on the speed planning data generated in the previous step and the characteristic parameters of the stepper motor (such as rated current, phase resistance, step angle, etc.), the system calculates the pulse frequency at each point in time during the motion. These frequency values ​​form a segmented speed control sequence that describes the complete speed change of the motor from start to stop. By precisely controlling the pulse frequency at each stage, the system can achieve smooth motor operation and avoid problems such as mechanical resonance and step loss.

[0067] The system performs timing control on the segmented speed control sequence, gradually increasing the PWM frequency during the acceleration phase to achieve smooth motor startup. During the motor startup phase, the system gradually increases the frequency of the PWM signal according to the precalculated segmented speed control sequence. This gradual frequency adjustment enables smooth acceleration of the motor rotor, avoiding insufficient torque or overshoot caused by sudden startup. The system precisely controls the duration of each frequency point through timer interrupts or software delays, ensuring that the motor operates according to the predetermined acceleration curve. The system also monitors the actual operating status of the motor, such as current changes and position feedback, to adjust the control strategy in a timely manner under abnormal circumstances to ensure a smooth motor startup.

[0068] Based on the motor's motion state and the number of remaining steps, the system gradually reduces the PWM frequency during the deceleration phase to achieve a smooth stop of the motor. When the motor reaches the deceleration point at the predetermined position, the system begins the deceleration process. The deceleration point is determined based on the target number of steps, the current speed, and the preset deceleration parameters to ensure that the motor can stop precisely at the target position. During the deceleration phase, the system gradually reduces the frequency of the PWM signal according to the pre-calculated segmented speed control sequence to smoothly decelerate the motor rotor. This gradual frequency adjustment can avoid overshoot or oscillation caused by sudden stops and improve positioning accuracy. At the same time, the system will dynamically adjust the deceleration curve according to the remaining number of steps to ensure that the motor can stop precisely at the target position.

[0069] The system performs closed-loop control over the entire motion process, adjusting the pulse timing via position encoder feedback to ensure that the corresponding number of pulse waveforms are executed. To ensure accurate motor control, the system employs a closed-loop control strategy, using the position encoder to monitor the actual position of the motor in real time. The position encoder provides highly accurate position feedback signals, which the system compares with the expected position to calculate the position error. Based on the position error, the system dynamically adjusts the pulse timing, such as increasing or decreasing the number of pulses and adjusting the pulse frequency, to ensure that the motor accurately executes the predetermined motion trajectory. This closed-loop control mechanism can effectively compensate for factors such as mechanical transmission errors and motor characteristic deviations, improving the system's positioning accuracy and repeatability.

[0070] like Figure 7 As shown, based on Example 1, a proportional-integral-derivative (PID) control algorithm is used to perform real-time error correction to achieve real-time tracking of the target object by the pan-tilt head and keep it pointing to the target object's position, including: S4.1: Obtain the current and target angles of the gimbal, calculate the position error, velocity error, and integral error, and generate PID control parameters. S4.2: Based on the PID control parameters and the system response characteristics, adjust the response speed through the proportional control link to obtain a proportional control output; S4.3: Process the integral value of the position error, eliminate the steady-state error through the integral control link, and obtain the integral control output; S4.4: Based on the error change rate and the differential time constant, the system oscillation is suppressed through the differential control link to obtain the differential control output; S4.5: Perform weighted summation on the proportional, integral, and differential control outputs to generate a final control signal and output it to the motor driver, so as to enable the gimbal to track the target object in real time and keep pointing to the target object position.

[0071] In this embodiment, the current and target angles of the gimbal are first acquired, and the position error, velocity error, and integral error are calculated to generate PID control parameters. Based on the PID control parameters and the system response characteristics, the response speed is adjusted via a proportional control mechanism to obtain a proportional control output. The integral value of the position error is then processed, and the steady-state error is eliminated via an integral control mechanism to obtain an integral control output. Based on the error change rate and the differential time constant, system oscillations are suppressed via a differential control mechanism to obtain a differential control output. Finally, a weighted summation of the proportional, integral, and differential control outputs is performed to generate a final control signal, which is then output to the motor driver, enabling the gimbal to track the target object in real time and maintain its position.

[0072] The system obtains the current and target angles of the gimbal, calculates the position error, velocity error, and integral error, and generates PID control parameters. When the gimbal control system receives the target angle command, it first obtains the current angle of the gimbal through the position sensor. The position error is equal to the target angle minus the current angle, reflecting the deviation between the gimbal's current position and the target position. The velocity error is the rate of change of the position error, reflecting the speed of the gimbal's movement. The integral error is the accumulation of position error over time, reflecting the system's long-term steady-state deviation. Based on this error information, the system generates PID control parameters, including the proportional coefficient Kp, the integral coefficient Ki, and the differential coefficient Kd. These parameters are selected based on the system's dynamic characteristics and control requirements, and are determined through theoretical analysis and experimental debugging to achieve optimal control results.

[0073] Based on the PID control parameters and system response characteristics, the system adjusts the response speed through the proportional control link to obtain a proportional control output. Proportional control is the basic link in PID control, and its output is proportional to the position error, that is, the proportional control output is equal to the proportional coefficient Kp multiplied by the position error. Proportional control can provide a corrective effect proportional to the size of the error. The larger the error, the greater the correction force, thereby speeding up the system response speed. The selection of the proportional coefficient Kp directly affects the response characteristics of the system: if Kp is too large, the system will respond too quickly, easily causing overshoot and oscillation; if Kp is too small, the system will respond slowly, making it difficult to quickly reach the target position. The system selects an appropriate proportional coefficient based on the mechanical characteristics and load conditions of the gimbal to achieve a fast response and stable control effect.

[0074] The system processes the integral value of the position error, eliminates the steady-state error through the integral control link, and obtains the integral control output. Integral control is a link in PID control used to eliminate steady-state errors. Its output is proportional to the time integral of the position error, that is, the integral control output is equal to the integral coefficient Ki multiplied by the integral value of the position error. When there is a persistent position error in the system, the integral term will continue to accumulate, providing an increasingly larger corrective effect until the error is eliminated. This mechanism can effectively deal with constant interference such as friction and gravity in the system, ensuring that the gimbal can ultimately be accurately positioned at the target position. To prevent integral saturation, the system also sets an integral limiting mechanism to limit the maximum value of the integral term to avoid system overshoot and oscillation caused by excessive integral terms.

[0075] Based on the error rate of change and the differential time constant, the system suppresses system oscillations through the differential control link and obtains a differential control output. Differential control is the damping component of PID control. Its output is proportional to the rate of change of the position error: that is, the differential control output is equal to the differential coefficient Kd multiplied by the rate of change of the position error. When the system responds too quickly and the rate of change of the position error is large, the differential term provides a reverse damping effect, slowing the system response and suppressing oscillations. When the system response is smooth and the rate of change of the position error is small, the influence of the differential term is also reduced. This mechanism can effectively improve the system's dynamic performance, enhancing its stability and anti-interference capabilities. To reduce the impact of high-frequency noise on differential control, the system also uses low-pass filtering technology to filter out high-frequency noise in the position signal, ensuring smooth and effective differential control.

[0076] The system performs a weighted summation of the proportional, integral, and differential control outputs to generate a final control signal, which is output to the motor driver, enabling the gimbal to track the target object in real time and maintain its position. The final output of the PID control algorithm is the weighted sum of the proportional, integral, and differential outputs: the control output equals the proportional control output plus the integral control output plus the differential control output. This combined output signal reflects the system's comprehensive assessment and correction strategy for the current error, including a comprehensive consideration of the error's magnitude, duration, and trend. The system converts this control signal into a form suitable for the motor driver, such as a PWM signal or analog voltage, to drive the gimbal motor. Through the continuous action of the PID control algorithm, the system can achieve real-time tracking of the target object and maintain its stable position in the presence of external interference, meeting the requirements of high-precision positioning and dynamic tracking.

[0077] On the basis of embodiment 1, it also includes a stereo geometry correction process based on a three-dimensional coordinate mapping model, including: A: Obtain camera calibration parameters and laser pointer calibration parameters, establish a mapping relationship between image pixel coordinates and 3D space coordinates, and generate a stereo geometry correction model; B: Based on the three-dimensional geometric correction model and the conveyor belt motion parameters, the spatial position compensation amount of the target object is calculated to obtain the corrected target coordinates; C: Detect geometric distortion during image acquisition, eliminate perspective and radial distortion through distortion correction algorithms, and generate corrected image coordinates; D: Based on environmental interference factors and sensor noise, the Kalman filter algorithm is used for data fusion to obtain stable target position information; E: Time synchronization processing is performed on multi-sensor data, and data alignment is achieved through timestamp calibration and interpolation algorithms to ensure the timeliness and accuracy of the real-time tracking and maintaining the position of the target object.

[0078] In this embodiment, camera and laser pointer calibration parameters are first acquired, a mapping relationship between image pixel coordinates and three-dimensional spatial coordinates is established, and a stereoscopic geometric correction model is generated. Then, based on the stereoscopic geometric correction model and the conveyor belt motion parameters, the spatial position compensation of the target object is calculated to obtain the corrected target coordinates. Next, the geometric distortion during image acquisition is detected, and a distortion correction algorithm is used to eliminate perspective and radial distortion, generating corrected image coordinates. A Kalman filter algorithm is then used to perform data fusion based on environmental interference factors and sensor noise to obtain stable target position information. Finally, multi-sensor data is time-synchronized, and data alignment is achieved through timestamp calibration and interpolation algorithms to ensure real-time tracking and maintain the timeliness and accuracy of the target object's position.

[0079] In the first step of stereo correction, the system obtains camera and laser pointer calibration parameters, establishes a mapping relationship between image pixel coordinates and 3D spatial coordinates, and generates a stereo correction model. Camera calibration is a fundamental technology in computer vision. By photographing a calibration plate of known dimensions, the system calculates the camera's intrinsic parameters (such as focal length, principal point coordinates, and distortion coefficients) and extrinsic parameters (the camera's position and orientation in the world coordinate system). Simultaneously, the system uses the laser pointer as an auxiliary positioning tool, recording the position of the laser point at different depth planes to establish a projection model of the laser pointer. The system combines these two sets of calibration parameters to construct a complete stereo correction model that accurately describes the mapping relationship between image pixel coordinates and 3D spatial coordinates. This mapping relationship is the foundation for high-precision spatial positioning, enabling the conversion of target positions in a 2D image into actual positions in 3D space.

[0080] During implementation, the spatial position compensation of the target object is calculated based on the three-dimensional geometric correction model and the conveyor belt motion parameters to obtain the corrected target coordinates. In industrial automation scenarios, the target object may be located on a moving conveyor belt, and its position changes continuously over time. The system obtains the motion parameters of the conveyor belt, such as speed, direction, and acceleration, and combines the time difference between the target detection moment and the control execution moment to calculate the displacement of the target object during this period. This displacement is used as the spatial position compensation and is combined with the initially detected target position to obtain the corrected target coordinates. This dynamic compensation mechanism can effectively cope with the movement of the target object, ensuring that the gimbal can accurately point to the moving target and realize dynamic tracking function.

[0081] During implementation, geometric distortion during image acquisition is detected, and a distortion correction algorithm is used to eliminate perspective and radial distortion, generating corrected image coordinates. In practical applications, images captured by cameras often exhibit various geometric distortions, primarily perspective distortion (caused by the camera not being perpendicular to the target plane) and radial distortion (caused by the optical properties of the camera lens). These distortions can cause straight lines in the image to become curves and rectangles to become trapezoids, thus affecting the accurate detection of target positions. The system uses a specialized distortion correction algorithm, based on the aforementioned camera calibration parameters, to correct the acquired images and eliminate these geometric distortions. The corrected images more accurately reflect the geometric relationships of the actual scene, providing a reliable data foundation for subsequent target positioning.

[0082] During implementation, a Kalman filter algorithm was used to fuse data based on environmental interference and sensor noise to obtain stable target position information. In real-world environments, target position detection results are often affected by various interference factors, such as lighting variations, shadow interference, and sensor noise, resulting in fluctuations and uncertainty in the detection results. Kalman filtering is a classic state estimation algorithm that optimally estimates the target state (such as position and velocity) based on a system model and observation data. The system uses the target detection results as observation data and, combined with a dynamic model of target motion, performs state estimation using the Kalman filter algorithm. This filter removes random noise and outliers, resulting in smooth and stable target position information. This data fusion mechanism significantly improves the system's anti-interference capability and tracking stability.

[0083] During implementation, multi-sensor data is time-synchronized, with data alignment achieved through timestamp calibration and interpolation algorithms. This ensures the timeliness and accuracy of real-time tracking and pointing to the target object's position. In complex industrial environments, the system may simultaneously use multiple sensors (such as cameras, laser rangefinders, and encoders) to acquire target and environmental information. These sensors may have varying data acquisition frequencies and processing delays, leading to temporal inconsistencies in the data. The system adds precise timestamps to each sensor data, recording the moment of data acquisition, and then aligns the data based on these timestamps. For sensors with different sampling rates, the system uses interpolation algorithms to generate data at intermediate moments, ensuring temporal consistency across all sensor data. This time synchronization mechanism effectively addresses data fusion issues in multi-sensor systems, improving the system's real-time performance and accuracy, and ensuring the gimbal can track and point to the target object's position in a timely and accurate manner.

[0084] like Figure 8 As shown, the present disclosure provides a pan-tilt dynamic control device, comprising: A coordinate conversion module is used to obtain the two-dimensional pixel coordinates of the target object on the display plane, convert the two-dimensional pixel coordinates into physical space coordinates through a coordinate conversion algorithm, and obtain the pixel offset of the target object relative to the center of the gimbal; An angle calculation module, configured to perform angle calculation using a trigonometric function calculation module based on the pixel offset and a pixel density parameter calculated according to the physical size and resolution of the display, to obtain the rotation angle parameters required for the horizontal and vertical axes of the pan / tilt head; The motor control module is used to convert the rotation angle parameter into a PWM control signal, generate a corresponding number of pulse waveforms through the stepper motor drive module, and control the rotation of the pan-tilt dual-axis motor; The tracking control module is used to perform real-time error correction based on the deviation between the current position of the gimbal and the target angle using a PID control algorithm, thereby enabling the gimbal to track the target object in real time and keep it pointing to the target object position.

[0085] Optionally, the coordinate conversion module converts the two-dimensional pixel coordinates into physical space coordinates using a coordinate conversion algorithm to obtain a pixel offset of the target object relative to the center of the gimbal, including: According to the physical parameters and pixel resolution information of the display, the horizontal pixel density and the vertical pixel density are calculated, and the linear transformation relationship between the pixel coordinates and the physical coordinates is established; Based on the linear transformation relationship and the pixel coordinates of the target object, a pixel deviation value between the target point and the display center point is calculated and converted into an actual physical displacement distance; The physical displacement distance is subjected to a coordinate system conversion, and the displacement in the display coordinate system is converted into an offset parameter in the pan-tilt coordinate system to obtain a pixel offset of the target object relative to the pan-tilt center.

[0086] Optionally, the coordinate conversion module obtains the two-dimensional pixel coordinates of the target object on the display plane, and further includes a display plane calibration process: Position the gimbal at a preset distance in front of the display, use the camera to capture the display's boundary feature points, and obtain the pixel coordinates of the display's four corner points; Based on the pixel coordinates of the four corner points, a spatial coordinate mapping relationship is established using a four-point calibration algorithm to generate a geometric transformation matrix; Boundary feature points of the pan / tilt axis and roll axis are captured, and assembly errors are eliminated using a geometric distortion correction algorithm to obtain the corrected two-dimensional pixel coordinate information.

[0087] Optionally, the angle calculation module uses a trigonometric function calculation module to perform angle calculation to obtain the required rotation angle parameters of the horizontal axis and the vertical axis of the gimbal, including: Obtain the actual displacement distance of the target object and the gimbal installation distance parameters, calculate the horizontal deflection angle using the inverse tangent function, and obtain the gimbal horizontal axis rotation angle; Based on the horizontal deflection angle and the installation distance, the spatial hypotenuse distance is calculated using the Pythagorean theorem to obtain the reference side length for vertical axis angle calculation; The vertical deflection angle is calculated based on the vertical displacement distance and the reference side length by using an inverse tangent function to obtain the required rotation angle parameter of the vertical axis of the gimbal.

[0088] Optionally, a trigonometric function calculation module is used to perform angle calculation, including: Obtain the position information of the target coordinates and current coordinates, determine the movement direction and decompose it into horizontal and vertical components, and determine the single-axis or dual-axis movement mode; Based on the motion pattern and displacement components, a three-dimensional motion model is constructed and spatial slant distance is calculated to generate biaxial motion parameters; The dual-axis motion parameters are dynamically decomposed into coordinates, and the theoretical rotation angles of the X-axis and the Y-axis are calculated respectively to obtain the rotation angle parameters required for the horizontal axis and the vertical axis of the gimbal.

[0089] Optionally, the motor control module converts the rotation angle parameter into a PWM control signal, generates a corresponding number of pulse waveforms through the stepper motor drive module, and controls the pan / tilt dual-axis motor to rotate, including: Obtain the target rotation angles of the horizontal and vertical axes of the gimbal, calculate the required number of pulses based on the angular resolution of the stepper motor, and generate PWM waveform parameters; Based on the PWM waveform parameters and the motor control frequency, a corresponding number of square wave signals are generated through the GPIO pins to drive the horizontal axis stepper motor to rotate; For the vertical axis rotation angle and pulse parameters, the timer module generates a vertical axis PWM control signal to drive the vertical axis stepper motor to rotate; Based on the rotation status of the dual-axis motor, the completion of the pulse signal is monitored to monitor the pan-tilt head rotation according to the calculated angle; The motor rotation process is monitored in real time, the rotation accuracy is verified through the position feedback signal, and the coordinated motion control of the gimbal's two axes is completed.

[0090] Optionally, the motor control module generates a corresponding number of pulse waveforms through the stepper motor drive module, including: Obtain the target rotation steps and motion speed parameters, calculate the acceleration and deceleration parameters of the S-shaped acceleration and deceleration curve, and generate speed planning data; Based on the speed planning data and motor characteristic parameters, the pulse frequency of each stage is calculated through the acceleration buffer to establish a segmented speed control sequence; Performing timing control on the segmented speed control sequence, gradually increasing the PWM frequency during the acceleration phase to achieve smooth motor start-up; Based on the motor's motion state and the number of remaining steps, the PWM frequency is gradually reduced during the deceleration phase to achieve a smooth stop of the motor; The entire motion process is closed-loop controlled, and the pulse timing is adjusted through position encoder feedback so that the corresponding number of pulse waveforms are executed.

[0091] Optionally, the tracking control module uses a PID control algorithm to perform real-time error correction to enable the gimbal to track the target object in real time and keep pointing to the target object's position, including: Obtain the current and target angles of the gimbal, calculate the position error, velocity error, and integral error, and generate PID control parameters. Based on the PID control parameters and the system response characteristics, the response speed is adjusted through the proportional control link to obtain a proportional control output; The integral value of the position error is processed, the steady-state error is eliminated through the integral control link, and the integral control output is obtained; Based on the error change rate and the differential time constant, the system oscillation is suppressed through the differential control link to obtain the differential control output; The proportional, integral and differential control outputs are weighted and summed to generate a final control signal which is output to the motor driver, thereby enabling the pan-tilt platform to track the target object in real time and keep pointing to the target object position.

[0092] Optionally, the coordinate conversion module is further used for stereo geometry correction processing based on the three-dimensional coordinate mapping model, including: Obtain camera calibration parameters and laser pointer calibration parameters, establish a mapping relationship between image pixel coordinates and three-dimensional space coordinates, and generate a three-dimensional geometric correction model; Calculating the spatial position compensation of the target object based on the three-dimensional geometric correction model and the conveyor belt motion parameters to obtain the corrected target coordinates; Detect geometric distortion during image acquisition, eliminate perspective and radial distortion through distortion correction algorithms, and generate corrected image coordinates; Based on environmental interference factors and sensor noise, the Kalman filter algorithm is used for data fusion to obtain stable target position information; The multi-sensor data is time-synchronized and aligned through timestamp calibration and interpolation algorithms to ensure the timeliness and accuracy of the real-time tracking and the position of the target object.

[0093] In this embodiment, the coordinate conversion module first obtains the two-dimensional pixel coordinates of the target object on the display plane, and then converts the two-dimensional pixel coordinates into physical space coordinates through a coordinate conversion algorithm to obtain the pixel offset of the target object relative to the center of the gimbal. The angle calculation module uses the trigonometric function calculation module to perform angle calculation based on the pixel offset and pixel density parameters to obtain the required rotation angle parameters for the horizontal and vertical axes of the gimbal. The motor control module converts the rotation angle parameters into PWM control signals, generates a corresponding number of pulse waveforms through the stepper motor drive module, and controls the rotation of the gimbal's dual-axis motor. The tracking control module uses the PID control algorithm to perform real-time error correction based on the deviation value between the current position of the gimbal and the target angle, thereby enabling the gimbal to track the target object in real time and keep it pointing to the target object position.

[0094] The foregoing description is merely a preferred embodiment of the present disclosure and is not intended to limit the present disclosure. Those skilled in the art will readily appreciate that the present disclosure is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present disclosure shall be included within the scope of protection of the present disclosure.

[0095] like Figure 9 As shown, the embodiment of the present disclosure also provides a computer device, which can also be called another pan-tilt dynamic control device, including a processor 91 and a memory 92, wherein the memory 92 stores machine-readable instructions executable by the processor 91, and the processor 91 is used to execute the machine-readable instructions stored in the memory 92. When the machine-readable instructions are executed by the processor 91, the processor 91 executes the steps of the pan-tilt dynamic control method described above.

[0096] The above-mentioned memory 92 includes internal memory 921 and external memory 922; the memory 921 here is also called internal memory, which is used to temporarily store the calculation data in the processor 91 and the data exchanged with the external memory 922 such as the hard disk. The processor 91 exchanges data with the external memory 922 through the internal memory 921.

[0097] The present disclosure also provides a computer-readable storage medium having a computer program stored thereon. When executed by a processor, the computer program executes the steps of the pan / tilt dynamic control method described in the above method embodiment. The storage medium may be a volatile or non-volatile computer-readable storage medium.

[0098] In addition, an embodiment of the present disclosure also provides a computer program product, which stores a computer program. When the computer program is run by a processor, it executes the steps of the pan-tilt dynamic control method provided by any of the above embodiments of the present disclosure. For details, please refer to the above method embodiments, which will not be repeated here.

[0099] The computer program product may be implemented in hardware, software, or a combination thereof. In one alternative embodiment, the computer program product is embodied as a computer storage medium, which may be a volatile or non-volatile computer-readable storage medium. In another alternative embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK).

[0100] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment and devices can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed equipment, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0101] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0102] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0103] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program code, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0104] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The scope of protection of the present disclosure is not limited thereto. Although the present disclosure has been described in detail with reference to the above-mentioned embodiments, those skilled in the art should understand that any person skilled in the art can modify or easily conceive of changes to the technical solutions described in the above-mentioned embodiments within the technical scope disclosed in the present disclosure, or replace some of the technical features therein with equivalents. Such modifications, changes, or replacements do not deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure should be based on the scope of protection of the claims.

Claims

1. A pan-tilt dynamic control method, characterized in that: include: Obtaining the two-dimensional pixel coordinates of the target object on the display plane, converting the two-dimensional pixel coordinates into physical space coordinates using a coordinate conversion algorithm, and obtaining the pixel offset of the target object relative to the center of the gimbal; Based on the pixel offset and the pixel density parameter calculated according to the physical size and resolution of the display, a trigonometric function calculation module is used to perform angle calculation to obtain the required rotation angle parameters of the horizontal and vertical axes of the pan / tilt head; The rotation angle parameter is converted into a pulse width modulation (PWM) control signal, and a corresponding number of pulse waveforms are generated by a stepper motor drive module to control the rotation of the pan / tilt dual-axis motor; Based on the deviation between the current position of the gimbal and the target angle, the proportional-integral-differential controller PID control algorithm is used to perform real-time error correction, so that the gimbal can track the target object in real time and keep pointing to the target object position.

2. The method according to claim 1, characterized in that The two-dimensional pixel coordinates are converted into physical space coordinates through a coordinate conversion algorithm to obtain the pixel offset of the target object relative to the center of the gimbal, including: According to the physical parameters and pixel resolution information of the display, the horizontal pixel density and the vertical pixel density are calculated, and the linear transformation relationship between the pixel coordinates and the physical coordinates is established; Based on the linear transformation relationship and the pixel coordinates of the target object, a pixel deviation value between the target point and the display center point is calculated and converted into an actual physical displacement distance; The physical displacement distance is subjected to a coordinate system conversion, and the displacement in the display coordinate system is converted into an offset parameter in the pan-tilt coordinate system to obtain a pixel offset of the target object relative to the pan-tilt center.

3. The method according to claim 1, characterized in that Obtain the 2D pixel coordinates of the target object on the display plane, including the display plane calibration process: Position the gimbal at a preset distance in front of the display, use the camera to capture the display's boundary feature points, and obtain the pixel coordinates of the display's four corner points; Based on the pixel coordinates of the four corner points, a spatial coordinate mapping relationship is established using a four-point calibration algorithm to generate a geometric transformation matrix; Boundary feature points of the pan / tilt axis and roll axis are captured, and assembly errors are eliminated using a geometric distortion correction algorithm to obtain the corrected two-dimensional pixel coordinate information.

4. The method according to claim 1, wherein The trigonometric function calculation module is used to calculate the angles and obtain the required rotation angle parameters for the horizontal and vertical axes of the gimbal, including: Obtain the actual displacement distance of the target object and the gimbal installation distance parameters, calculate the horizontal deflection angle using the inverse tangent function, and obtain the gimbal horizontal axis rotation angle; Based on the horizontal deflection angle and the installation distance, the spatial hypotenuse distance is calculated using the Pythagorean theorem to obtain the reference side length for vertical axis angle calculation; The vertical deflection angle is calculated based on the vertical displacement distance and the reference side length by using an inverse tangent function to obtain the required rotation angle parameter of the vertical axis of the gimbal.

5. The method according to claim 1, wherein Use the trigonometric function calculation module to solve the angle, including: Obtain the position information of the target coordinates and current coordinates, determine the movement direction and decompose it into horizontal and vertical components, and determine the single-axis or dual-axis movement mode; Based on the motion pattern and displacement components, a three-dimensional motion model is constructed and spatial slant distance is calculated to generate biaxial motion parameters; The dual-axis motion parameters are dynamically decomposed into coordinates, and the theoretical rotation angles of the X-axis and the Y-axis are calculated respectively to obtain the rotation angle parameters required for the horizontal axis and the vertical axis of the gimbal.

6. The method according to claim 1, characterized in that The rotation angle parameter is converted into a PWM control signal, and a corresponding number of pulse waveforms are generated by a stepper motor drive module to control the pan-tilt dual-axis motor to rotate, including: Obtain the target rotation angles of the horizontal and vertical axes of the gimbal, calculate the required number of pulses based on the angular resolution of the stepper motor, and generate PWM waveform parameters; Based on the PWM waveform parameters and the motor control frequency, a corresponding number of square wave signals are generated through the general-purpose input and output (GPIO) pins to drive the horizontal axis stepper motor to rotate; For the vertical axis rotation angle and pulse parameters, the timer module generates a vertical axis PWM control signal to drive the vertical axis stepper motor to rotate; Based on the rotation status of the dual-axis motor, the completion of the pulse signal is monitored to monitor the pan-tilt head rotation according to the calculated angle; The motor rotation process is monitored in real time, the rotation accuracy is verified through the position feedback signal, and the coordinated motion control of the gimbal's two axes is completed.

7. The method according to claim 1, characterized in that Generate a corresponding number of pulse waveforms through the stepper motor driver module, including: Obtain the target rotation steps and motion speed parameters, calculate the acceleration and deceleration parameters of the S-shaped acceleration and deceleration curve, and generate speed planning data; Based on the speed planning data and motor characteristic parameters, the pulse frequency of each stage is calculated through the acceleration buffer to establish a segmented speed control sequence; Performing timing control on the segmented speed control sequence, gradually increasing the PWM frequency during the acceleration phase to achieve smooth motor start-up; Based on the motor's motion state and the number of remaining steps, the PWM frequency is gradually reduced during the deceleration phase to achieve a smooth stop of the motor; The entire motion process is closed-loop controlled, and the pulse timing is adjusted through position encoder feedback so that the corresponding number of pulse waveforms are executed.

8. The method according to claim 1, characterized in that The PID control algorithm is used for real-time error correction to enable the PTZ to track the target object in real time and keep pointing to the target object, including: Obtain the current and target angles of the gimbal, calculate the position error, velocity error, and integral error, and generate PID control parameters. Based on the PID control parameters and the system response characteristics, the response speed is adjusted through the proportional control link to obtain a proportional control output; The integral value of the position error is processed, the steady-state error is eliminated through the integral control link, and the integral control output is obtained; Based on the error change rate and the differential time constant, the system oscillation is suppressed through the differential control link to obtain the differential control output; The proportional, integral and differential control outputs are weighted and summed to generate a final control signal which is output to the motor driver, thereby enabling the pan-tilt platform to track the target object in real time and keep pointing to the target object position.

9. The method according to claim 1, characterized in that It also includes stereo geometry correction processing based on a 3D coordinate mapping model, including: Obtain camera calibration parameters and laser pointer calibration parameters, establish a mapping relationship between image pixel coordinates and three-dimensional space coordinates, and generate a three-dimensional geometric correction model; Calculating the spatial position compensation of the target object based on the three-dimensional geometric correction model and the conveyor belt motion parameters to obtain the corrected target coordinates; Detect geometric distortion during image acquisition, eliminate perspective and radial distortion through distortion correction algorithms, and generate corrected image coordinates; Based on environmental interference factors and sensor noise, the Kalman filter algorithm is used for data fusion to obtain stable target position information; Multi-sensor data is time synchronized and data alignment is achieved through timestamp calibration and interpolation algorithms.

10. A pan-tilt dynamic control device, characterized in that: It includes a processor and a memory, the memory stores machine-readable instructions executable by the processor, the processor is used to execute the machine-readable instructions stored in the memory, and when the machine-readable instructions are executed by the processor, the processor executes the steps of the pan-tilt dynamic control method according to any one of claims 1 to 9.

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