Visual guidance positioning method and system for a tongs loading station

Abstract

This invention discloses a vision-guided positioning method and system for clamping stations, relating to the field of vision-guided positioning technology. It acquires posture change images throughout the entire product flipping process and simultaneously records camera exposure and servo rotation times, establishing a posture change trajectory on the same time axis. Based on the trajectory, it extracts time intervals with stable posture change rates to identify the posture stabilization window. The camera trigger time is adjusted according to the stabilization window, and static images are acquired within the window. Multi-frame comparison of key feature points in the static images is performed, selecting the frame with the smallest positional change as the positioning input frame. The robot's motion path is synchronously adjusted based on the coordinate results of the positioning input frame to achieve rhythm matching. This invention aligns the camera exposure time with the posture stabilization window, eliminating time misalignment caused by end-flip fluctuations and ensuring consistent and reliable positioning results. By synchronously adjusting the motion and visual rhythm, it avoids abrupt trajectory changes, improving the stability of the clamping process and the overall reliability of the production line.

Description

Technical Field

[0001] This invention relates to the field of visual guidance and positioning technology, and specifically to a visual guidance and positioning method and system for fitting stations. Background Technology

[0002] Visual-guided positioning for automated assembly stations refers to using a 2D camera mounted on the equipment to take real-time photos and perform image recognition on products entering the station. This analyzes the product's position, angle, and posture deviations in space, providing a precise positioning reference for robots or robotic arms. The specific implementation process is as follows: When a product enters the assembly station via the conveyor line, the 2D camera captures image information of the product's surface. Using a preset feature template or marker point recognition algorithm, the displacement and rotation deviations of the product relative to the standard installation position are calculated. This posture data is then fed back to the control system, which corrects the trajectory of the robot's end effector, ensuring that actuators such as electric screwdrivers, dispensing valves, or stamp heads accurately align with screw holes, glue dots, or painting positions, achieving precise operations such as automated assembly, automated dispensing, and automated painting. Through this visual-guided positioning process, the equipment can maintain high-precision operation even with slight product placement deviations or tooling errors, ensuring assembly consistency and stability.

[0003] The existing technology has the following shortcomings:

[0004] In the vision-guided positioning process of automated clamping stations, the product's flipping motion is prone to causing temporal drift in the visual calibration coordinate system due to transient posture changes. Specifically, when the camera acquires images, the workpiece's posture is not yet fully stable, resulting in a temporal misalignment between the system-calculated spatial coordinates and the product's actual position. This misalignment is often difficult for the algorithm to detect in real time and can easily cause abrupt changes when the robot updates its execution path, leading to sudden jumps in the end effector's trajectory. If this jump occurs during the clamping stage, the actuator may directly impact the fixture or product surface, causing serious consequences such as equipment damage, clamping mechanism deformation, and screw hole breakage. Long-term temporal drift can also lead to accumulated positioning errors, causing a continuous decline in the alignment accuracy of subsequent operations, ultimately affecting the stability and reliability of the entire assembly line.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a visual guidance and positioning method and system for fitting stations to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a vision-guided positioning method for a fitting station, comprising the following steps:

[0008] Step 1: Collect a continuous image sequence of the product's posture changes throughout the entire flipping process, and simultaneously record the time stamps of camera exposure time and servo rotation time during the acquisition process to establish the basis of the dynamic trajectory of posture changes on the same time axis.

[0009] Step 2: Based on the established dynamic trajectory of attitude change, perform time segmentation processing on the acquired continuous image sequence, extract the time interval where the attitude change rate is in a stable state, and confirm the time interval as the attitude stability window.

[0010] Step 3: Based on the determined attitude stabilization window, adjust the time delay of the camera's trigger signal to lock the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image.

[0011] Step 4: Based on the obtained static image, perform multi-frame continuous comparison of the spatial positions of key feature points, and select the image frame with the smallest position change within the attitude stabilization window as the localization input frame.

[0012] Step 5: Based on the spatial coordinates of the obtained positioning input frame, perform time synchronization control on the robot's motion path, matching the motion initiation rhythm with the visual sampling rhythm on the time axis.

[0013] Preferably, acquiring a continuous image sequence of the product's posture changes throughout the entire flipping process includes the following steps:

[0014] In the initial stage when the product enters the clamping station and begins the flipping action, the camera acquisition timing and servo drive action time reference signals are set. At the moment the flipping action begins, the control device sends a continuous exposure trigger signal to the camera to continuously shoot at a constant frame rate, and simultaneously records the time stamps of the camera exposure time and servo rotation time.

[0015] After completing the acquisition of continuous image sequences of attitude change and synchronous recording of camera exposure time and servo rotation time, the camera exposure time and servo rotation time are arranged in chronological order and mapped onto the same time axis, so that each camera exposure time and its corresponding servo rotation time form a time correspondence, and the dynamic trajectory of attitude change is established on the same time axis.

[0016] Based on the dynamic trajectory established on the time axis, the attitude change of the entire product flipping process is analyzed in the time domain. The time interval between adjacent image frames is calculated and combined with the servo rotation time information to determine the attitude change rate, forming a time distribution of the attitude change rate on the time axis.

[0017] Preferably, extracting the time interval where the attitude change rate is in a stable state and identifying it as the attitude stability window includes the following steps:

[0018] After obtaining the dynamic trajectory of attitude change, the recorded time information is organized, the camera exposure time and servo rotation time are paired in time order, each frame of image corresponds to the corresponding servo rotation time, and the time axis is divided into multiple continuous time intervals, each time interval containing a corresponding number of image frames and servo rotation time points.

[0019] Using the time correspondence information in the dynamic trajectory of attitude change, time comparison is performed on consecutive image frames in each time interval to determine the exposure time interval between adjacent image frames. The attitude change rate is calculated by combining the change in servo rotation time to form the time distribution of attitude change rate.

[0020] The attitude change rate distribution of each time interval is continuously compared, and the relationship between rate changes between adjacent time intervals is analyzed. When the attitude change rate remains constant and the rate changes between adjacent time intervals are stable, the corresponding time interval is determined as the candidate interval for attitude stability.

[0021] Multiple candidate intervals for attitude stabilization are screened. By analyzing the temporal density of consecutive image frames and the servo rotation time interval, the interval that remains continuously stable on the time axis is selected as the attitude stabilization window, which provides a time-based positioning basis for camera shooting trigger.

[0022] Preferably, the attitude stabilization window is determined by using the camera exposure time and servo rotation time recorded in the dynamic trajectory of attitude change as time references. By comparing the start and end positions of the candidate interval of attitude stabilization state with the corresponding time markers, the attitude stabilization window is made to correspond completely with the product attitude stabilization stage on the time axis, thereby ensuring that the camera exposure time and servo rotation time maintain a constant time relationship within the attitude stabilization window.

[0023] Preferably, obtaining a still image by locking the camera exposure start time within the attitude stabilization window includes the following steps:

[0024] Once the attitude stabilization window is determined, the time information recorded in the attitude change dynamic trajectory is read, the start and end time points of the attitude stabilization window are extracted, and a time reference is established based on the positional relationship between the two on the time axis. The original trigger time of the camera is compared with the time range of the attitude stabilization window to determine the relative position of the trigger time and the attitude stabilization window, and continuous time segments are divided as a reference for trigger delay adjustment.

[0025] Based on the time difference between the camera's original trigger time and the start time of the attitude stabilization window, the delay time of the trigger signal is calculated, and delay adjustment is performed during the time control process to make the delayed exposure start time coincide with the middle of the attitude stabilization window, so that the shooting time is within the time range when the product's attitude is completely stable.

[0026] When the trigger signal delay adjustment is completed, the camera exposure process is started. Continuous image frames are acquired within the attitude stabilization window time range, and the exposure start time, exposure duration and image time number are recorded. The exposure start time, exposure duration and image time number corresponding to the image are saved in correspondence with the basic time data of the dynamic trajectory of attitude change, so as to obtain static image data for positioning calculation.

[0027] Preferably, the camera exposure start time is synchronized with the time in the middle of the attitude stabilization window by dividing the attitude stabilization window into millisecond-level time resolution units. Each time unit corresponds to an exposure start point, and the trigger signal delay time is controlled with millisecond-level precision to ensure that the exposure start time strictly falls within the attitude stabilization window. The entire image acquisition process is synchronized with the product attitude stabilization stage on the time axis.

[0028] Preferably, selecting the image frame with the smallest positional change within the attitude stabilization window as the localization input frame includes the following steps:

[0029] All the acquired still images are arranged in order of exposure time. Each frame corresponds to the start and end time of exposure and is numbered sequentially to form a time series image group. Each image frame corresponds one-to-one with the actual position on the time axis, thereby establishing a continuous time series dataset.

[0030] In the completed time series image group, key feature points with stable geometric features on the product surface or structure are selected. The positions of the same feature points are extracted for each frame image within the attitude stabilization window and recorded in the two-dimensional position coordinates in the image coordinate system to form a feature point position sequence containing time information.

[0031] The recorded feature point position data are compared in time sequence, the displacement difference of the same feature points in adjacent image frames is calculated, and the frame group with stable attitude is divided according to the displacement change trend of multiple consecutive frames, and the time interval of remaining stationary within the attitude stability window is determined.

[0032] Select the single frame image corresponding to the middle time from the frame group with the least positional change as the localization input frame, and record its time number, exposure start time and spatial coordinate information of key feature points for subsequent spatial coordinate calculation.

[0033] Preferably, during the selection of the positioning input frame, the time interval of the time series image group is set to a fixed frame rate, the interval between adjacent image frames remains constant, the change of feature point position is judged based on the displacement difference between consecutive frames, the exposure start time of the positioning input frame is located at the middle moment of the attitude stabilization window, and the recorded spatial coordinates of key feature points are used to establish the spatial positioning reference of the product in the workstation coordinate system.

[0034] Preferably, the synchronization control of the robot's motion path execution time based on the spatial coordinates of the positioning input frame includes the following steps:

[0035] The spatial coordinates of key feature points in the positioning input frame are transformed into the workstation coordinate system to form a complete set of spatial position information. Based on the time information in the dynamic trajectory of posture change, the time number of the positioning input frame is matched with the corresponding time on the time axis. A unified time reference point is established on the time axis, and each motion node of the robot from the initial position to the target assembly position is calibrated in chronological order.

[0036] Based on the specific position data of the product in the spatial coordinate results of the positioning input frame, the robot's motion path is time-synchronized and controlled. On the time axis, with the time point corresponding to the positioning input frame as the core, a time interval matching the visual sampling frequency is established. The time of the starting, acceleration, constant speed, deceleration and stopping phases in the robot's motion path is finely adjusted so that each motion node maintains a one-to-one correspondence with the visual sampling time point.

[0037] The clamping operation is performed according to the motion path that has been adjusted by time matching. On the time axis, each motion node of the robot is synchronized with the visual sampling time point, and the corresponding acquired image frame is consistent with the current action time of the robot, so as to achieve continuous and stable positioning execution in the automatic clamping stage.

[0038] A vision-guided positioning system for a fitting station includes an attitude trajectory establishment module, a stable window extraction module, an exposure delay control module, a positioning frame selection module, and a path synchronization control module.

[0039] The attitude trajectory establishment module collects a continuous image sequence of the product's attitude changes during the entire flipping process, and simultaneously records the time stamps of camera exposure time and servo rotation time during the acquisition process, establishing the basis of dynamic attitude change trajectory on the same time axis;

[0040] The stable window extraction module, based on the established dynamic trajectory of attitude change, performs time segmentation processing on the acquired continuous image sequence, extracts the time interval in which the attitude change rate is in a stable state, and identifies the time interval as the attitude stable window.

[0041] The exposure delay control module adjusts the time delay of the camera's trigger signal according to the determined attitude stabilization window, locking the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image.

[0042] The localization frame selection module performs multi-frame continuous comparison of the spatial positions of key feature points in the obtained static image, and selects the image frame with the smallest position change within the attitude stabilization window as the localization input frame.

[0043] The path synchronization control module performs time synchronization control on the robot's motion path based on the spatial coordinate results of the obtained positioning input frame, matching the motion start rhythm with the visual sampling rhythm on the time axis.

[0044] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0045] This invention establishes a time trajectory of attitude changes throughout the entire flipping process and determines the attitude stabilization window accordingly, ensuring a strict correspondence between the camera's exposure time and the product's stable attitude state on the time axis. Consequently, image acquisition is no longer affected by attitude fluctuations at the end of the flipping process, and spatial coordinate acquisition is always based on a stable state. This avoids positioning deviations caused by time misalignment from the outset, ensuring consistency and repeatability of positioning results throughout continuous operation, and providing a reliable foundation for high-precision operations at the clamping station.

[0046] This invention synchronizes the timing information of the positioning input frame with the robot's motion path, ensuring that the motion initiation rhythm and the visual sampling rhythm advance in tandem on a unified time axis. This allows the robot's path execution during the clamping phase to remain continuous and stable. This method effectively suppresses trajectory abrupt changes caused by inconsistent visual data update timing, reduces the risk of abnormal contact between the actuator and the product or fixture, and improves the stability of the automated clamping process and the reliability of the entire production line. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0048] Figure 1 This is a flowchart of the visual guidance positioning method for the fitting station according to the present invention;

[0049] Figure 2 The flowchart for identifying the time interval in which the attitude change rate is in a stable state as the attitude stability window in this invention;

[0050] Figure 3 This is a flowchart illustrating how the present invention locks the camera exposure start time within an attitude stabilization window to obtain a static image;

[0051] Figure 4 This is a schematic diagram of the modules of the vision-guided positioning system for the fitting station of the present invention. Detailed Implementation

[0052] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0053] like Figures 1 to 3 As shown, the present invention provides a vision-guided positioning method for a fitting station, comprising the following steps:

[0054] Step 1: Collect a continuous image sequence of the product's attitude change during the entire flipping process, and simultaneously record the time stamps of camera exposure time and servo rotation time during the acquisition process. Establish the dynamic trajectory basis of attitude change on the same time axis to provide a time reference for subsequent attitude stability judgment.

[0055] The basic steps for establishing dynamic trajectories of attitude changes on the same time axis are as follows:

[0056] In the initial stage when the product enters the clamping station and begins its flipping motion, a time reference signal is set for both camera acquisition timing and servo drive motion. At the start of the flipping motion, the control device sends a continuous exposure trigger signal to the camera. Upon receiving the trigger signal, the camera immediately initiates continuous shooting, capturing images of the product at a constant frame rate from the start to the end of the flipping motion, continuously acquiring image data of the product's posture. Each frame is assigned a unique time number, corresponding to the camera's actual exposure start time. Simultaneously, the servo drive continuously records the correspondence between the servo rotation angle and time throughout the flipping process, forming a servo rotation time sequence. The camera's exposure time information and the servo rotation time information are recorded under the same time reference, ensuring that the visual acquisition process and the mechanical motion process remain synchronized in the time dimension. Through this synchronous recording method, each frame captured by the camera corresponds to a specific servo rotation time, thus forming a continuous image sequence of posture changes containing complete time information, providing continuous time data for the subsequent establishment of a timeline.

[0057] After acquiring a continuous image sequence of attitude changes and synchronously recording camera exposure time and servo rotation time, the acquired time data was organized. The camera exposure time and servo rotation time were arranged in chronological order and mapped onto the same time axis. On this time axis, each camera exposure time and its corresponding servo rotation time form a pair of time-corresponding data, reflecting the temporal positional relationship at each instant of attitude change during the product's flipping process. This correspondence allows for a complete description of the product's flipping process from its initial attitude to its target attitude on the time axis, forming a continuous attitude change time trajectory. To ensure the continuity of the attitude change trajectory, the camera exposure time interval and servo rotation time interval were maintained within a stable temporal resolution, ensuring a definite time interval and servo angle change value between any two adjacent frames. Based on this, the establishment of the time axis yielded a dynamic trajectory foundation for attitude changes. This dynamic trajectory foundation records the attitude change process of the product at every moment during the entire flipping action, forming a complete time change sequence, providing continuous temporal basis for subsequent attitude stability judgment.

[0058] After establishing the dynamic trajectory foundation for attitude change, this foundation is used to perform time-domain analysis of the attitude change process throughout the entire product flipping process, extracting the rate information of the product's attitude change from a temporal dimension. During the analysis, the time interval between adjacent image frames is calculated, and combined with servo rotation time information, the amplitude of the product's attitude change within the corresponding time period is determined. By comparing the time interval between each consecutive image frame with the servo rotation time interval, the attitude change rate curve of the product throughout the flipping process can be obtained. This curve clearly reflects the continuous state of the product's attitude change from the start to the end of the flipping action, including the temporal distribution characteristics of the acceleration phase, transition phase, and attitude stabilization phase. Based on this temporal distribution characteristic, the time range corresponding to the attitude stabilization state can be accurately located on the time axis. The dynamic trajectory foundation for attitude change plays a core role in this process. Through this foundation, the trend of product attitude change can be directly tracked on the time axis, ensuring that the temporal information of attitude change is consistent with the image data. In this way, the attitude change of the product throughout the flipping process is not only completely recorded in the form of an image sequence, but also accurately described on the time axis, thus forming a complete temporal reference system that includes image information, temporal information, and attitude change relationships. With the support of this time reference system, subsequent judgments on the attitude stability state can be based on precise time periods, thereby enabling reasonable scheduling of camera shooting opportunities and providing a reliable time basis for high-precision execution of visual guidance positioning.

[0059] Through the implementation of the above steps, the acquisition of a continuous image sequence of posture changes throughout the entire product flipping process was completed, along with the synchronous recording of camera exposure time and servo rotation time. A dynamic trajectory basis for posture changes was established on the same timeline. This process unifies visual acquisition time information with mechanical motion time information, enabling the posture changes throughout the product flipping process to be fully described in a time-continuous and spatially corresponding manner. The dynamic trajectory basis for posture changes serves as the time reference for subsequent posture stabilization window extraction, camera trigger delay adjustment, and positioning input frame selection. This ensures consistency and coherence in the time dimension of the entire vision-guided positioning process, avoiding time misalignment between acquired images and actual posture states, and providing a foundation for precise positioning at the automated clamping station.

[0060] Step 2: Based on the established dynamic trajectory of attitude change, perform time segmentation processing on the acquired continuous image sequence, extract the time interval where the attitude change rate is stable, and confirm this time interval as the attitude stabilization window to provide time positioning basis for camera shooting trigger.

[0061] The time interval in which the attitude change rate is in a stable state is identified as the attitude stability window. The specific steps are as follows:

[0062] After obtaining the dynamic trajectory of the attitude change, the time information recorded in this trajectory is organized, and the camera exposure time and servo rotation time are paired in chronological order, so that each frame corresponds one-to-one with its corresponding servo rotation time. In this way, the entire timeline of the product's flipping process from start to finish can be completely reconstructed. Each moment in this timeline contains information about the product's attitude change. For ease of analysis, the timeline is divided into several continuous time intervals, each covering a certain number of image frames and servo rotation time points. The divided time intervals cover the start, acceleration, intermediate transition, and stopping phases of the entire flipping motion, thus corresponding each stage of the product's attitude change to a time interval. In this way, the entire flipping process is divided into continuous segments in chronological order, each segment containing attitude change information within its corresponding time period, providing a temporal distribution basis for subsequent extraction of the attitude change rate.

[0063] After dividing the time intervals, the attitude change rate within each time interval is calculated and identified using the time correspondence information recorded in the dynamic trajectory of attitude change. Specifically, the time of consecutive image frames within each time interval is compared to determine the exposure time interval between adjacent image frames. Combined with the change in servo rotation time, the attitude change rate of the product within that time interval is determined. During the calculation process, the time number of each image frame is read one by one and aligned with the corresponding servo rotation time point. The speed of attitude change during the flipping process is determined sequentially along the time axis. Each time interval yields an attitude change rate value, which represents the temporal characteristics of the product's attitude change within that time period. In this way, the entire attitude change process of the flipping motion is unfolded with time as the horizontal axis and rate as the vertical characteristic, revealing the distribution law of the attitude change rate over time. This law will fully demonstrate the continuous change characteristics of the product from the initial attitude to the final stable attitude, providing basic data for determining the stable phase.

[0064] To further understand the technical solution of this embodiment, the specific implementation method of this step is illustrated below:

[0065] For example, during the process of a product flipping from its initial position to its target position, the duration of the flipping motion is set to 2 seconds. The camera continuously captures images at a constant frame rate of 40 frames per second, for a total of 80 frames. The servo rotation device records the rotation angle from 0 degrees to 180 degrees within the same time period and generates corresponding time data points for each rotation moment. The exposure times of consecutive image frames are sequentially labeled T1 to T80 with a time interval of 0.025 seconds, and the corresponding servo rotation time points are S1 to S80. For any two adjacent image frames, such as frame 10 and frame 11, the exposure time interval is 0.025 seconds, and the angle change corresponding to the servo rotation time interval is 4.5 degrees. Therefore, the recorded attitude change rate within this time interval is 4.5 degrees / 0.025 seconds. The same time comparison and angle change calculations were performed on the images from frame 1 to frame 80 in sequence to obtain a complete time interval rate distribution data sequence. For example, the rate corresponding to frames 1 to 10 is 6.8 degrees / 0.025 seconds, the rate corresponding to frames 11 to 40 is 5.2 degrees / 0.025 seconds, and the rate corresponding to frames 41 to 80 is 0.6 degrees / 0.025 seconds.

[0066] In this way, each consecutive image frame in each time interval is assigned a posture change rate value corresponding to a servo rotation time point, forming a time rate sequence of posture changes throughout the product flipping process, providing a specific numerical basis for subsequent time segmentation processing.

[0067] After obtaining the distribution of attitude change rates across time intervals, all time intervals are continuously compared to analyze the trend of attitude change rates along the entire time axis. By observing the relationship between rates between adjacent time intervals, time intervals where the attitude change rate remains constant or fluctuates minimally can be identified. These time intervals typically correspond to the stage where the product attitude gradually stabilizes. To ensure accuracy, the dynamic trajectory of attitude change is used as a reference during the comparison process, ensuring that the start and end points of each time interval on the time axis are consistent with the actual stage of the product's flipping motion. When the product's attitude change rate remains consistent across multiple adjacent frames within a certain time interval, and the rate change is smooth between adjacent time intervals, it can be determined that the product attitude corresponding to that time interval is in a stable state. At this point, this time interval is considered a candidate interval for a stable attitude state. In this way, several candidate intervals for a stable attitude state can be identified from the entire flipping motion's time axis, and these intervals may all become suitable time periods for camera capture.

[0068] After obtaining multiple candidate intervals for attitude stabilization states, these intervals are further filtered to determine the most suitable time range for the attitude stabilization window. Specifically, by comprehensively analyzing the temporal density of consecutive image frames and the servo rotation time interval within the candidate intervals, the interval that remains continuous and stable on the time axis is selected as the final attitude stabilization window. To ensure the accuracy of time positioning, during the filtering process, the camera exposure time and servo rotation time recorded in the dynamic trajectory of attitude change are used as the core reference. The time start and end points of the candidate intervals for attitude stabilization states are correlated with the time markers in the dynamic trajectory, so that the final determined attitude stabilization window is completely consistent with the stable stage of the product's attitude on the time axis. After the attitude stabilization window is determined, the product's attitude no longer changes rapidly within its time range, and the camera exposure time and servo rotation time maintain a constant correspondence within this range, thereby ensuring that the image data acquired by the camera within the attitude stabilization window can accurately reflect the product's attitude information in a stable state. By using the attitude stabilization window as the time-based positioning reference for subsequent camera shooting, the shooting trigger moment is synchronized with the product's attitude stabilization state. This ensures that the image acquisition process is consistent with the actual state of the flipping action in the time dimension, avoiding image errors and positioning deviations caused by unstable attitude change rates.

[0069] It should be noted that:

[0070] The temporal density of continuous image frames within a candidate interval refers to the number of image frames per unit time and their temporal distribution within the time range corresponding to the candidate interval for a stable attitude state. Specifically, it is reflected in whether the exposure time interval between adjacent image frames remains uniform and continuous. For example, if a candidate interval of 0.2 seconds contains 10 images, the temporal density is one frame every 0.02 seconds. If the time interval between each frame is consistent and there are no frame skips or time breaks, it indicates that the candidate interval is sampled continuously on the time axis, which is beneficial for judging the stable attitude state. The servo rotation time interval refers to the time difference between two adjacent servo rotation time recording points within the same candidate interval for a stable attitude state, as well as the change in rotation angle within the corresponding time interval. If the servo rotation time interval remains constant within this time range, and the corresponding angle change is close to zero or remains unchanged, it indicates that the product has not undergone continuous rotation within this time period, and the attitude is stable. Therefore, by comprehensively analyzing the continuity of the image frame temporal distribution and the attitude change corresponding to the servo rotation time interval, the time interval that is truly in a static state can be selected as the attitude stability window.

[0071] Through the above steps, the posture changes during the entire product flipping process are segmented into time intervals. The posture change rate of each interval is extracted and analyzed on the time axis. Finally, the time intervals where the posture change rate is stable are selected and identified as the posture stabilization window. This process allows camera capture to be triggered during the product's posture stabilization phase, ensuring that the acquired images accurately reflect the product's spatial position. This provides a temporal basis for selecting subsequent positioning input frames, enabling continuous control and stable operation of the entire vision-guided positioning process in the time dimension.

[0072] Step 3: Based on the determined attitude stabilization window, adjust the time delay of the camera's trigger signal to lock the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image for subsequent positioning calculations.

[0073] The camera exposure start time is locked within the attitude stabilization window to obtain a static image for subsequent positioning calculations. The specific steps are as follows:

[0074] After the attitude stabilization window is determined, the time information recorded in the dynamic trajectory of attitude change is read, and the start and end times of the attitude stabilization window are extracted. A time reference is established based on the positional relationship of these two times on the time axis. At this point, the entire time distribution of the product flipping action corresponds one-to-one with the continuous image sequence captured by the camera. Therefore, the relative position of the camera's original trigger time and the attitude stabilization window can be determined on the same time axis. By comparing the camera's original trigger time with the time range of the attitude stabilization window, it can be accurately determined whether the original trigger time falls within the attitude stabilization window. If the original trigger time is before the start time of the attitude stabilization window, it indicates that the camera was capturing the image when the product flipping action had not yet completely ended. At this time, the product's attitude still has a slight deviation, which can easily produce attitude blur in the image. If the original trigger time exceeds the end time of the attitude stabilization window, the shooting opportunity has missed the period of most stable attitude. To eliminate this time deviation, the time range of the attitude stabilization window is divided into several continuous time segments, so that the delay adjustment of the camera trigger signal can be performed with reference to precise time segments, thereby ensuring that the trigger time can be strictly controlled within the effective time range of the attitude stabilization window.

[0075] After determining the correspondence between the camera's initial trigger time and the attitude stabilization window time, the specific time delay required for the camera trigger signal is calculated based on the difference between the two on the time axis, and time delay adjustment is performed during the trigger control process. Specifically, by reading the time series data from the dynamic trajectory of attitude change, the time difference between the camera's initial trigger time and the start time of the attitude stabilization window is determined as the delay amount, and this delay amount is used as an adjustment parameter for the timing control of the trigger signal. After the trigger signal is delayed, the camera's exposure start time will coincide with the midpoint of the attitude stabilization window, ensuring that the shooting process occurs within the time interval when the product's attitude is completely stable. During this process, the correspondence at each moment on the time axis is preserved, ensuring that the actual camera exposure time is completely synchronized with the product's attitude stabilization stage. To ensure the accuracy of the delay adjustment, the time range of the attitude stabilization window is further divided into millisecond-level time-resolution units, with each time unit corresponding to a possible camera exposure start point. In this way, the delay time of the trigger signal can be precisely controlled to the millisecond level, ensuring that the exposure start time strictly falls within the attitude stabilization window. After a delay adjustment, the camera starts the exposure within the attitude stabilization window, avoiding the slight attitude fluctuations that occur at the moment the flipping action ends, thus ensuring that the exposure time is within the attitude stabilization range.

[0076] After adjusting the trigger signal delay, the camera exposure process is initiated, and image acquisition is completed within the attitude stabilization window to obtain static image data for positioning calculations. During this stage, the camera initiates exposure based on the delayed trigger signal, with the exposure start time strictly synchronized with the midpoint of the attitude stabilization window. As exposure progresses, the camera continuously acquires multiple frames within the attitude stabilization window, with the exposure start and end times of each frame falling within the attitude stabilization range, ensuring that all acquired images correspond to a completely stable product attitude. Simultaneously, the camera records the exposure start time, exposure duration, and the time number corresponding to each frame, ensuring a perfect match between this time information and the time data in the dynamic trajectory of attitude changes. This fully preserves the correspondence between image data and attitude change time information, providing an accurate time reference for subsequent positioning calculations. During exposure, the images captured by the camera are no longer affected by the aftershocks of the flipping motion; the product's spatial position and attitude remain unchanged, and the acquired images accurately reflect the product's appearance and positional characteristics in a stable attitude. After image acquisition is completed, all image frames are saved in chronological order, and their corresponding exposure start times are marked in the record file to ensure that the time position corresponding to the attitude stabilization window can be traced back based on these time markers in the subsequent data processing stage.

[0077] It should be noted that:

[0078] The end of the flipping motion refers to the time stage during which the product is about to complete the target angle adjustment and the servo rotation transitions from a moving state to a stopped state. Specifically, after the servo drive rotates the product from its initial posture to the set posture, during the deceleration to a stop, due to inertia, the product may experience a brief period of slight swaying or angular rebound near the target position. Although the flipping motion is nearing its end on a macroscopic scale, posture changes still occur on a microscopic time scale, hence the term "end stage of the flipping motion." This stage typically corresponds to the deceleration segment and the instant of stopping in the servo rotation curve, and is the critical time interval for the posture to transition from dynamic change to stable stillness.

[0079] Through the implementation of the above steps, the timing of the camera trigger signal is precisely adjusted, locking the exposure start time within the attitude stabilization window. The delay adjustment process uses the timeline provided by the dynamic trajectory of attitude changes as a reference, ensuring that the camera's shooting moment corresponds perfectly with the product's stable attitude in time, thus eliminating potential inertial vibration interference at the end of the flipping motion. By acquiring images within the attitude stabilization window, the obtained image data remains consistent with the product's stable attitude in time, providing a stable and reliable static image input basis for subsequent positioning calculations, and achieving unified and coordinated time control throughout the entire vision-guided positioning process.

[0080] Step 4: Based on the obtained static image, perform multi-frame continuous comparison of the spatial positions of key feature points, and select the image frame with the smallest position change within the attitude stabilization window as the positioning input frame to ensure that the spatial coordinate calculation is completed under the stable attitude of the product.

[0081] The image frame with the smallest positional change within the attitude stabilization window is selected as the localization input frame. The specific steps are as follows:

[0082] After image acquisition is completed within the attitude stabilization window, all acquired still images are organized in chronological order of exposure time. Each frame corresponds to a specific start and end time of exposure, and this time information is derived from the established dynamic trajectory of attitude changes. To ensure the continuity of comparison, the image frames within the attitude stabilization window are numbered chronologically, and each number is matched with its actual position on the time axis, forming a time-series image group. Each frame in this time series has a clear time marker, allowing its position within the attitude stabilization window to be located via the time axis. After organization, a complete time-series dataset containing consecutive image frames is obtained. For example, with an attitude stabilization window duration of 0.5 seconds and a camera frame rate of 50 frames per second, 25 still images will be obtained, numbered sequentially from T1 to T25, with the corresponding time intervals precisely distributed within the 0.02-second intervals of the attitude stabilization window. This method ensures the continuity and traceability of image acquisition in the time dimension, providing a sequential basis for subsequent spatial location comparison of feature points.

[0083] Subsequently, from the processed time-series image set, key feature points on the product surface or structure used for positioning are selected. These feature points have stable geometric characteristics, such as the center of screw holes, the intersection of assembly positioning pin holes, surface markers, structural corner intersections, or imprint centers, and can be accurately identified in different image frames. For each frame within the attitude stabilization window, the positions of the same key feature points are extracted, and their two-dimensional position coordinates in the image coordinate system are recorded. For example, in frames 1 to 25, the position coordinates (x1, y1) to (x25, y25) of the same screw hole center point are marked and saved in chronological order. During this process, the lighting conditions and camera parameters for image acquisition are kept consistent to ensure that the outlines of the feature points remain clear in consecutive image frames, thereby ensuring that the feature point position data in each frame accurately reflects the product's attitude state at that moment. The feature point position data extracted from each frame is correlated with its exposure time number, thus forming a feature point position sequence containing time information, providing a data basis for subsequent comparisons.

[0084] After obtaining the feature point position sequence within the attitude stabilization window, these position data are compared temporally to identify the spatial position changes of feature points between consecutive frames. Specifically, the coordinates of the same feature points in adjacent frames are continuously compared, and the displacement difference within each time interval is recorded by comparing the changes in their positions in the image coordinate system. Starting from the first frame, the feature point position differences between frames 1 and 2, 2 and 3, and so on, are calculated sequentially until the last frame. For example, if the coordinates of the screw hole center point in frame 10 are (510.3, 382.1) and in frame 11 are (510.5, 382.2), then the displacement difference within that time interval is 0.2 pixels. By comparing all consecutive frames in this way, a complete sequence of feature point position changes can be obtained. By observing the displacement change trend in each time interval of this sequence, the stability of the product's attitude within that time period can be determined. When the displacement difference across multiple consecutive frames remains below a set displacement difference threshold, it indicates that the product's attitude has not changed significantly within that time period. Through this frame-by-frame comparison process, continuous image frames within the attitude stabilization window can be divided into several groups of frames with stable attitude states. Each group of frames corresponds to a specific time interval, and the displacement difference between frames within it is minimal, reflecting that the product's attitude remains stationary during that time period.

[0085] It should be noted that:

[0086] The 0.2 pixel value originates from the calculation of the coordinate difference of the same feature point in two adjacent frames. The displacement difference is obtained by comparing the changes in the horizontal and vertical coordinates between the 10th and 11th frames. The horizontal change is 0.2 pixels, and the vertical change is 0.1 pixels. The combined displacement can be calculated as a two-dimensional distance and approximately represented as 0.2 pixels, which is used to characterize the small spatial displacement of the feature point within this time interval.

[0087] The displacement difference threshold range is typically set based on camera resolution, pixel accuracy, allowable positioning error of the product, and the level of vibration at the site. Specifically, multiple sets of image data are collected with the product completely stationary. The natural fluctuation displacement values ​​of feature points in adjacent frames are statistically analyzed, and the maximum fluctuation value is taken as a reference upper limit. This value is then converted into pixel values ​​based on the allowable spatial error in actual assembly to determine a fixed displacement difference threshold. For example, when the fluctuation range of feature points in a stationary state is within 0.15 pixels, and the allowable assembly accuracy error corresponds to 0.3 pixels, the threshold can be set within the range of 0.2 to 0.25 pixels. This serves as the basis for judging attitude stability, ensuring that stability determination can both eliminate the influence of vibration and meet positioning accuracy requirements.

[0088] After obtaining the frame group division within the attitude stabilization window, the single frame image corresponding to the middle moment of the frame group with the smallest positional change is selected as the positioning input frame. The exposure start time of this frame is located at the middle position of the attitude stabilization window, which can represent the most stable state of the product's attitude on the time axis. After selecting the positioning input frame, the time number, exposure start time, and spatial coordinate information of all key feature points of the frame image are recorded as the input basis for subsequent spatial coordinate calculations. At this time, the image content of the positioning input frame fully reflects the spatial state of the product in the attitude stabilization stage, and its feature point position data can be accurately converted into the product's spatial position information in the three-dimensional spatial coordinate system. In this way, the image frame on which the spatial coordinate calculation is based is synchronized with the attitude stabilization state in time, ensuring that the subsequent positioning results accurately reflect the actual position of the product in the workstation. To further ensure the consistency of time and space, the time point corresponding to the positioning input frame is compared with the time axis in the dynamic trajectory of attitude change, so that the spatial coordinate data corresponding to the frame is completely consistent with the time marker of the product's attitude stabilization stage, thereby achieving synchronization of visual data and motion data in the time dimension.

[0089] This implementation method continuously analyzes images during the posture stabilization phase along the time axis, closely linking the spatial position data of feature points with temporal information. This ensures that spatial coordinate calculations are completed when the product's posture is stable. The selection process for the positioning input frame spans the entire process of time calibration, feature point extraction, position comparison, and time synchronization. This ensures that the final positioning calculation is based on images under stable posture, guaranteeing the temporal continuity and spatial consistency of the visually guided positioning at the clamping station. This provides reliable data support for subsequent robot motion path planning and automatic execution.

[0090] Step 5: Based on the spatial coordinate results of the obtained positioning input frame, the robot motion path is synchronized and controlled in time. The motion start rhythm and the visual sampling rhythm are matched on the time axis to achieve continuous and stable positioning execution in the automatic clamping stage.

[0091] Based on the obtained spatial coordinates of the positioning input frame, the robot's motion path is synchronized and controlled over time. The specific steps are as follows:

[0092] After obtaining the spatial coordinates of the positioning input frame, the spatial coordinates of all key feature points in the image are transformed into the workstation coordinate system, forming a complete set of spatial position information. The exposure time of the positioning input frame corresponds to the center time of the attitude stabilization window, so the feature point positions in this frame image can accurately reflect the actual spatial state of the product under stable attitude. Based on this, the time number of the positioning input frame is matched with a specific moment on the time axis using the time information in the dynamic trajectory of attitude change, forming a unified time reference point. Next, the complete motion path executed by the robot at the fitting station is time-allocated, and all motion nodes of the robot from the initial position to the target assembly position are calibrated in chronological order. Each node corresponds to a specific action execution moment, including the start point, acceleration segment, constant speed segment, deceleration segment, and stop point. On the time axis, these nodes form a continuous motion time sequence. To ensure synchronization between robot motion and visual sampling, the time markers of each motion node in the robot motion path are compared with the visual sampling time axis, so that the two form a one-to-one correspondence on the same time axis. For example, if the exposure time of the localization input frame is T100, then T100 is set as the starting point of the robot's motion path on the time axis, so that the robot begins to execute motion commands at that moment. In this way, the robot's motion time axis is synchronized with the visual sampling time axis, providing an accurate time reference for subsequent time adjustment.

[0093] After establishing the time reference, the robot's motion path is synchronized with the specific position data of the product in the spatial coordinates of the positioning input frame. Specifically, at each key motion node of the robot's motion path, the execution time of the corresponding action is adjusted according to the spatial position of the product in the workstation coordinate system, so that the time distribution of each motion stage corresponds to the visual sampling rhythm. First, on the time axis, with the time point T100 of the positioning input frame as the core, time intervals matching the visual sampling frequency are established forward and backward. For example, when the visual sampling frequency is 50 frames per second, the interval between adjacent sampling points on the time axis is 0.02 seconds, and the time interval of each motion node in the robot's motion path is also allocated according to the same time resolution, so that the robot's motion commands and the visual sampling rhythm form an equidistant correspondence. On this basis, the start, acceleration, constant speed, deceleration, and stopping processes of the robot's motion path are finely adjusted in time, so that the rhythm of the robot's motion state changes is consistent with the visual sampling frequency. In this process, by continuously comparing the time marker of each motion node in the robot's motion path with the visual sampling time sequence, it is ensured that the start time of any action in the robot's motion path matches the visual sampling time point. When the robot accelerates or turns during its motion path, the time interval between visual sampling points remains constant, ensuring that visual sampling and robot movement are synchronized in time throughout the entire motion cycle. This method achieves strict consistency between the time distribution of the robot's motion path and the visual sampling timeline, ensuring complete overlap between the motion rhythm and the visual sampling rhythm, thus providing a basis for synchronized control in the next execution step.

[0094] After completing time synchronization adjustment, the clamping operation is performed according to the time-matched adjusted motion path. The robot starts its movement based on the spatial coordinates of the positioning input frame, and its initial action is aligned with the start time of visual sampling on the time axis. During execution, the movement of each motion node of the robot corresponds to the time point of visual sampling. When the robot performs different stages of the clamping process, such as moving to the assembly position, aligning with the product surface, applying pressure to clamp, or performing locking actions, the visual sampling process continues. The time point of each frame of image acquisition is synchronized with the robot's current action time, thus forming a continuous time-matching chain throughout the clamping process. For example, when the robot receives the spatial coordinate information of the positioning input frame at time T100 and starts its action, visual sampling acquires image frame T100 at the same time; when the robot's motion path reaches time points T101, T102, etc., visual sampling acquires image data at time T101 and T102 respectively. In this way, each frame of visual sampling corresponds to the specific position of the robot's motion trajectory, creating a time-synchronized mapping relationship between the motion process and the visual sampling process. At each stage of the robot's movement, the output time of the control signal and the visual sampling time are kept at a constant interval, so that the robot's actions and the visual sampling process proceed synchronously. Through this time synchronization method, the robot's movement path maintains continuity and temporal consistency throughout the clamping process, and the visual sampling data can correspond to each action stage on the time axis, thereby ensuring the continuous and stable execution of the entire automated clamping operation.

[0095] The entire process achieves strict time-axis matching between the robot's motion path and the visual sampling process by establishing a time reference point, matching the visual sampling rhythm, adjusting the time distribution of motion nodes, and synchronizing these processes during the execution phase. This ensures that the robot's motion rhythm during the automatic clamping phase is completely consistent with the visual sampling rhythm, guaranteeing temporal coordination between motion execution and visual data acquisition. This allows the robot to perform continuous actions in a stable posture, and the visual-guided positioning process remains coherent throughout the entire time domain, thereby achieving high-precision automatic positioning control at the clamping station.

[0096] Beneficial effect 1:

[0097] This invention establishes a time trajectory of attitude changes throughout the entire flipping process and determines the attitude stabilization window accordingly, ensuring a strict correspondence between the camera's exposure time and the product's stable attitude state on the time axis. Consequently, image acquisition is no longer affected by attitude fluctuations at the end of the flipping process, and spatial coordinate acquisition is always based on a stable state. This avoids positioning deviations caused by time misalignment from the outset, ensuring consistency and repeatability of positioning results throughout continuous operation, and providing a reliable foundation for high-precision operations at the clamping station.

[0098] Benefit 2:

[0099] This invention synchronizes the timing information of the positioning input frame with the robot's motion path, ensuring that the motion initiation rhythm and the visual sampling rhythm advance in tandem on a unified time axis. This allows the robot's path execution during the clamping phase to remain continuous and stable. This method effectively suppresses trajectory abrupt changes caused by inconsistent visual data update timing, reduces the risk of abnormal contact between the actuator and the product or fixture, and improves the stability of the automated clamping process and the reliability of the entire production line.

[0100] This invention provides, for example Figure 4 The visual guidance and positioning system shown includes an attitude trajectory establishment module, a stable window extraction module, an exposure delay control module, a positioning frame selection module, and a path synchronization control module.

[0101] The attitude trajectory establishment module collects a continuous image sequence of the product's attitude changes during the entire flipping process, and simultaneously records the time stamps of camera exposure time and servo rotation time during the acquisition process, establishing the basis of dynamic attitude change trajectory on the same time axis;

[0102] The stable window extraction module, based on the established dynamic trajectory of attitude change, performs time segmentation processing on the acquired continuous image sequence, extracts the time interval in which the attitude change rate is in a stable state, and identifies the time interval as the attitude stable window.

[0103] The exposure delay control module adjusts the time delay of the camera's trigger signal according to the determined attitude stabilization window, locking the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image.

[0104] The localization frame selection module performs multi-frame continuous comparison of the spatial positions of key feature points in the obtained static image, and selects the image frame with the smallest position change within the attitude stabilization window as the localization input frame.

[0105] The path synchronization control module performs time synchronization control on the robot's motion path based on the spatial coordinate results of the obtained positioning input frame, matching the motion start rhythm with the visual sampling rhythm on the time axis.

[0106] The present invention provides a visual guidance and positioning method for a fitting station, which is implemented by the aforementioned visual guidance and positioning system for a fitting station. For details of the specific method and process of the visual guidance and positioning system for a fitting station, please refer to the embodiment of the aforementioned visual guidance and positioning method for a fitting station, which will not be repeated here.

[0107] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the above drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the present invention.

Claims

1. A vision-guided positioning method for a fitting station, characterized in that, Includes the following steps: Step 1: Collect a continuous image sequence of the product's posture changes throughout the entire flipping process, and simultaneously record the time stamps of camera exposure time and servo rotation time during the acquisition process to establish the basis of the dynamic trajectory of posture changes on the same time axis. Step 2: Based on the established dynamic trajectory of attitude change, perform time segmentation processing on the acquired continuous image sequence, extract the time interval where the attitude change rate is in a stable state, and confirm the time interval as the attitude stability window. Step 3: Based on the determined attitude stabilization window, adjust the time delay of the camera's trigger signal to lock the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image. Step 4: Based on the obtained static image, perform multi-frame continuous comparison of the spatial positions of key feature points, and select the image frame with the smallest position change within the attitude stabilization window as the localization input frame. Step 5: Based on the spatial coordinates of the obtained positioning input frame, perform time synchronization control on the robot's motion path, matching the motion initiation rhythm with the visual sampling rhythm on the time axis.

2. The vision-guided positioning method for a fitting station according to claim 1, characterized in that, Acquiring a continuous image sequence of the product's posture changes throughout the entire flipping process includes the following steps: In the initial stage when the product enters the clamping station and begins the flipping action, the camera acquisition timing and servo drive action time reference signals are set. At the moment the flipping action begins, the control device sends a continuous exposure trigger signal to the camera to continuously shoot at a constant frame rate, and simultaneously records the time stamps of the camera exposure time and servo rotation time. After completing the acquisition of continuous image sequences of attitude change and synchronous recording of camera exposure time and servo rotation time, the camera exposure time and servo rotation time are arranged in chronological order and mapped onto the same time axis, so that each camera exposure time and its corresponding servo rotation time form a time correspondence, and the dynamic trajectory of attitude change is established on the same time axis. Based on the dynamic trajectory established on the time axis, the attitude change of the entire product flipping process is analyzed in the time domain. The time interval between adjacent image frames is calculated and combined with the servo rotation time information to determine the attitude change rate, forming a time distribution of the attitude change rate on the time axis.

3. The vision-guided positioning method for a fitting station according to claim 1, characterized in that, Extracting the time interval where the attitude change rate is in a stable state and identifying it as the attitude stability window includes the following steps: After obtaining the dynamic trajectory of attitude change, the recorded time information is organized, the camera exposure time and servo rotation time are paired in time order, each frame of image corresponds to the corresponding servo rotation time, and the time axis is divided into multiple continuous time intervals, each time interval containing a corresponding number of image frames and servo rotation time points. Using the time correspondence information in the dynamic trajectory of attitude change, time comparison is performed on consecutive image frames in each time interval to determine the exposure time interval between adjacent image frames. The attitude change rate is calculated by combining the change in servo rotation time, and a time distribution of attitude change rate is formed in each time interval. The attitude change rate distribution of each time interval is continuously compared, and the relationship between rate changes between adjacent time intervals is analyzed. When the attitude change rate remains constant and the rate changes between adjacent time intervals are stable, the corresponding time interval is determined as the candidate interval for attitude stability. Multiple candidate intervals for attitude stability were screened. By analyzing the temporal density of consecutive image frames and the servo rotation time interval, the interval that remained continuously stable on the time axis was selected as the attitude stability window.

4. The vision-guided positioning method for a fitting station according to claim 3, characterized in that, The attitude stabilization window is determined by using the camera exposure time and servo rotation time recorded in the dynamic trajectory of attitude change as time references. The starting and ending positions of the candidate interval of attitude stabilization state are compared with the corresponding time markers to make the attitude stabilization window completely correspond to the attitude stabilization stage of the product on the time axis.

5. A vision-guided positioning method for a fitting station according to claim 3, characterized in that, To obtain a still image by locking the camera exposure start time within a pose stabilization window, the following steps are involved: Once the attitude stabilization window is determined, the time information recorded in the attitude change dynamic trajectory is read, the start and end time points of the attitude stabilization window are extracted, and a time reference is established based on the positional relationship between the two on the time axis. The original trigger time of the camera is compared with the time range of the attitude stabilization window to determine the relative position of the trigger time and the attitude stabilization window, and continuous time segments are divided as a reference for trigger delay adjustment. Based on the time difference between the camera's original trigger time and the start time of the attitude stabilization window, the delay time of the trigger signal is calculated, and delay adjustment is performed during the time control process to make the delayed exposure start time coincide with the middle of the attitude stabilization window; When the trigger signal delay adjustment is completed, the camera exposure process is started. Continuous image frames are acquired within the attitude stabilization window time range, and the exposure start time, exposure duration and image time number are recorded. The exposure start time, exposure duration and image time number corresponding to the image are saved in correspondence with the basic time data of the dynamic trajectory of attitude change, so as to obtain static image data for positioning calculation.

6. A vision-guided positioning method for a fitting station according to claim 5, characterized in that, The camera exposure start time is synchronized with the time in the middle of the attitude stabilization window by dividing the attitude stabilization window into millisecond-level time resolution units. Each time unit corresponds to an exposure start point, and the trigger signal delay time is controlled with millisecond-level precision.

7. A vision-guided positioning method for a fitting station according to claim 5, characterized in that, Selecting the image frame with the smallest positional change within the attitude stabilization window as the localization input frame includes the following steps: All the acquired still images are arranged in order of exposure time. Each frame corresponds to the start and end time of exposure and is numbered sequentially to form a time series image group. Each image frame corresponds one-to-one with the actual position on the time axis, thus establishing a continuous time series dataset. In the completed time series image group, key feature points with stable geometric features on the product surface or structure are selected. The positions of the same feature points are extracted for each frame image within the attitude stabilization window and recorded in the two-dimensional position coordinates in the image coordinate system to form a feature point position sequence containing time information. The recorded feature point position data are compared in time sequence, the displacement difference of the same feature points in adjacent image frames is calculated, and the frame group with stable attitude is divided according to the displacement change trend of multiple consecutive frames, and the time interval of remaining stationary within the attitude stability window is determined. Select the single frame image corresponding to the middle time from the frame group with the least positional change as the localization input frame, and record its time number, exposure start time and spatial coordinate information of key feature points for spatial coordinate calculation.

8. A vision-guided positioning method for a fitting station according to claim 7, characterized in that, During the selection of the positioning input frame, the time interval of the time series image group is set to a fixed frame rate, the interval between adjacent image frames remains constant, the change of feature point position is judged based on the displacement difference between consecutive frames, the exposure start time of the positioning input frame is located at the middle moment of the attitude stabilization window, and the recorded spatial coordinates of key feature points are used to establish the spatial positioning reference of the product in the workstation coordinate system.

9. A vision-guided positioning method for a fitting station according to claim 7, characterized in that, Synchronization control of robot motion path execution time based on spatial coordinate results of positioning input frames includes the following steps: The spatial coordinates of key feature points in the positioning input frame are transformed into the workstation coordinate system to form a complete set of spatial position information. Based on the time information in the dynamic trajectory of posture change, the time number of the positioning input frame is matched with the corresponding time on the time axis. A unified time reference point is established on the time axis, and each motion node of the robot from the initial position to the target assembly position is calibrated in chronological order. Based on the specific position data of the product in the spatial coordinate results of the positioning input frame, the robot's motion path is time-synchronized and controlled. On the time axis, with the time point corresponding to the positioning input frame as the core, a time interval matching the visual sampling frequency is established, and the time of the starting, acceleration, constant speed, deceleration and stopping phases in the robot's motion path is adjusted. The clamping operation is performed according to the motion path that has been adjusted by time matching, so that each motion node of the robot is synchronized with the visual sampling time point on the time axis, and the corresponding acquired image frame is consistent with the current action time of the robot.

10. A vision-guided positioning system for a fitting station, used to implement the vision-guided positioning method for a fitting station as described in any one of claims 1-9, characterized in that, It includes an attitude trajectory establishment module, a stabilization window extraction module, an exposure delay control module, a positioning frame selection module, and a path synchronization control module; The attitude trajectory establishment module collects a continuous image sequence of the product's attitude changes during the entire flipping process, and simultaneously records the time stamps of camera exposure time and servo rotation time during the acquisition process, establishing the basis of dynamic attitude change trajectory on the same time axis; The stable window extraction module, based on the established dynamic trajectory of attitude change, performs time segmentation processing on the acquired continuous image sequence, extracts the time interval in which the attitude change rate is in a stable state, and identifies the time interval as the attitude stable window. The exposure delay control module adjusts the time delay of the camera's trigger signal according to the determined attitude stabilization window, locking the camera's exposure start time within the attitude stabilization window, thereby eliminating the aftershock interference of the product's flipping motion during data acquisition and obtaining a static image. The localization frame selection module performs multi-frame continuous comparison of the spatial positions of key feature points in the obtained static image, and selects the image frame with the smallest position change within the attitude stabilization window as the localization input frame. The path synchronization control module performs time synchronization control on the robot's motion path based on the spatial coordinate results of the obtained positioning input frame, matching the motion start rhythm with the visual sampling rhythm on the time axis.

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