System of fully automatic sampling tube cap screwing and pipetting workstation and operation method thereof

Abstract

The present application relates to the technical field of sample pretreatment automation, and discloses a system of a full-automatic sampling tube cap screwing and pipetting workstation and a running method thereof.The system comprises a motion point definition module, a cap screwing adaptation identification module, a label scanning module, a pipetting planning and execution module, a cap screwing torque calling module and a real-time torque acquisition module.The system realizes continuous scanning and reliable identification of the cap profile in the motion state through a dynamic coordinate system and key motion points, dynamically calls matched torque parameters to execute cap screwing according to the identification result, and simultaneously acquires real-time torque data.The system synchronously completes sample label information analysis, pipetting path planning and pressure monitoring.The scheme realizes adaptive perception and closed-loop cap screwing control of the cap state, and improves the robustness of cap identification, the consistency of cap screwing action and the reliability of the overall process.

Description

Technical Field

[0001] This invention relates to the field of automated sample pretreatment technology, specifically to a fully automated sampling tube capping and pipetting workstation system and its operation method. Background Technology

[0002] In the field of fully automated sample pretreatment, the automated opening, pipetting, and closing of sampling tubes are fundamental and critical processes. Current technologies typically involve conveying the sampling tube to a fixed position and then performing static image acquisition or contour scanning on the tube cap. This method relies on the precise alignment and static state of the sampling tube at the detection station, making it difficult to handle instantaneous positional shifts caused by conveyor vibrations, differences in incoming material posture, or queue compression in actual production lines. Static snapshots from a single location cannot effectively compensate for detection blind spots and are easily affected by changes in lighting, label obstruction on the tube cap, or liquid reflection, resulting in insufficient reliability of cap identification. This, in turn, leads to subsequent mechanical gripping failures, inaccurate pipetting needle positioning, or sample mishandling.

[0003] In the capping process, existing solutions mostly use a preset fixed torque value to control the capping robot arm. The thread condition of the sampling tube cap has inherent manufacturing tolerances, and after manual opening, multiple automated operations, and potential sample residue, its friction coefficient and tightness have changed. A fixed output torque cannot adapt to this dynamically changing physical state. Using a uniform torque can easily lead to two consequences: insufficient torque results in the cap not tightening properly, posing a risk of sample leakage, evaporation, or contamination; excessive torque may damage the thread structure of the cap and tube body, affecting the seal integrity and subsequent capping operations, and even causing the tube body to break. A method is needed that can sense the real-time status of the cap and dynamically adjust the capping strategy to improve the robustness and processing quality of the entire process. Summary of the Invention

[0004] The purpose of this invention is to provide a system and operating method for a fully automated sampling tube capping and pipetting workstation, in order to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides a fully automated sampling tube capping and pipetting workstation system, the system comprising:

[0006] The motion point definition module establishes a dynamic coordinate system for simulating the movement of the sampling tube along the delivery path, and defines several key motion points in the dynamic coordinate system.

[0007] The capping adapter identification module records the contour scanning data of the sampling tube cap in real time at each of the key movement points and generates a sampling tube ready signal;

[0008] The label scanning module, in response to the sampling tube ready signal, initiates a visual scan of the sample label attached to the sampling tube body and parses the sample label to extract the set of pipetting parameters;

[0009] The pipetting planning and execution module inputs the set of pipetting parameters into the pipetting control logic to generate a pipetting path planning diagram, and controls the pipetting needle to perform aspiration and dispensing actions according to the pipetting path planning diagram, while continuously monitoring the pipetting pressure value during the execution process;

[0010] The rotary torque call module receives the capping compatibility recognition result after the pipetting action is completed, and calls the corresponding torque parameters from the capping torque strategy library according to the capping compatibility recognition result to drive the capping robot arm to perform the capping operation.

[0011] The real-time torque acquisition module samples the real-time torque value applied by the cap-screwing robot arm while the cap rotation operation is being performed, and obtains a set of torque sample values.

[0012] Preferably, the contour scan data of the sampling tube cap is recorded in real time at each of the key motion points to generate a sampling tube ready signal, including:

[0013] The contour scan data is compared with a standard cap specification database to generate cap compatibility identification results.

[0014] Based on the cap compatibility recognition result, an attitude adjustment command for the sampling tube is triggered, and the mechanical clamping mechanism is controlled to perform a calibration operation on the attitude of the sampling tube according to the attitude adjustment command. After the calibration operation is completed, a sampling tube ready signal is generated.

[0015] Preferably, the step of establishing a dynamic coordinate system for simulating the movement of the sampling tube along the transport path, and defining several key motion points in the dynamic coordinate system, includes:

[0016] Set the origin of the dynamic coordinate system at the initial feeding position of the conveyor belt;

[0017] Along the direction of the conveyor belt, the center coordinates of multiple workstations are calculated sequentially based on the preset workstation stop points.

[0018] Between any two adjacent workstation center coordinates, multiple path interpolation points are inserted at equal intervals, and the kinematic parameters of all workstation center coordinates and all path interpolation points are calculated.

[0019] Filter out the turning points where the direction of motion changes from all the path interpolation points;

[0020] The origin of the dynamic coordinate system, the coordinates of all the workstation centers, and all the turning points are combined and defined as several key motion points in the dynamic coordinate system.

[0021] Preferably, the step of comparing the contour scan data with a standard cap specification database to generate a cap fit identification result includes:

[0022] When the sampling tube passes through any of the key motion points, the three-dimensional contour scanning device is activated to perform a circular scan on the outer surface of the sampling tube cap to obtain a set of point cloud data on the surface of the cap.

[0023] The point cloud dataset is subjected to noise reduction and feature extraction processing to obtain the outline geometric feature data of the cap.

[0024] Read the standard cap feature template corresponding to the batch to be processed from the standard cap specification database;

[0025] Calculate the matching degree between the contour geometric feature data of the cap and the standard cap feature template;

[0026] If the matching degree value is lower than the preset matching threshold, the standard cap feature template is updated to the alternative cap feature template with the highest matching degree value, and the matching degree value is recalculated.

[0027] The final matching degree value obtained by calculation, together with the specification number of the corresponding standard cap feature template or alternative cap feature template, are used as the cap fit identification result.

[0028] Preferably, the step of triggering an attitude adjustment command for the sampling tube based on the cap compatibility recognition result, and controlling the mechanical clamping mechanism to perform a calibration operation on the sampling tube attitude according to the attitude adjustment command, includes:

[0029] The cap compatibility recognition result is analyzed, and the specification number of the corresponding standard cap feature template is obtained from the cap compatibility recognition result;

[0030] Based on the specification number, query the preset attitude calibration mapping table to obtain the target clamping angle and clamping center offset corresponding to the specification number;

[0031] The visual positioning device is controlled to take pictures of the sampling tube at the current workstation, obtain the real-time position image of the sampling tube, and parse the actual tube body axis angle and the actual tube cap center position of the sampling tube from the real-time position image.

[0032] Calculate the angular deviation between the actual pipe axis angle and the target clamping angle, and calculate the positional deviation between the actual pipe cap center position and the standard workstation center point;

[0033] The angular deviation, the positional deviation, and the clamping center offset are vector-synthesized to generate a three-dimensional spatial compensation amount for the end effector of the mechanical clamping mechanism.

[0034] Based on the three-dimensional spatial compensation amount, the end effector of the mechanical clamping mechanism is controlled to move and perform clamping and attitude fine-tuning on the sampling tube until the actual tube axis angle and the actual tube cap center position meet the preset calibration tolerance range.

[0035] Preferably, the step of inputting the pipetting parameter set into the pipetting control logic to generate a pipetting path planning diagram, and controlling the pipetting needle to perform aspiration and dispensing actions according to the pipetting path planning diagram, includes:

[0036] The set of pipetting parameters is analyzed to extract the liquid level height of the target sample, the target pipetting volume, and the coordinate information of the target dispensing container.

[0037] Based on the liquid level and the target volume of liquid transfer, and combined with the physical property parameters of the pipette, the safe depth of the pipette immersion in the liquid, the aspiration rate curve, and the dispensing rate curve are calculated.

[0038] Using the coordinates of the end effector of the mechanical clamping mechanism after attitude calibration as the starting point of the path, and the coordinate information of the target dispensing container as the ending point of the path, a collision-free three-dimensional spatial movement trajectory is planned between the starting point and the ending point of the path, avoiding all fixed obstacles in the workstation.

[0039] The three-dimensional spatial movement trajectory, the safety depth, the aspiration speed curve, and the dispensing speed curve are integrated to generate the pipetting path planning map containing a spatial coordinate sequence and a speed command sequence;

[0040] According to the spatial coordinate sequence in the pipetting path planning diagram, the pipetting needle is controlled to move sequentially to each coordinate point, and when it reaches the designated coordinate point, the liquid is aspirated and dispensed according to the corresponding speed command sequence in the pipetting path planning diagram.

[0041] Preferably, the step of continuously monitoring the pipetting pressure value during execution includes:

[0042] During the process of the pipetting needle performing the aspiration action according to the aspiration speed curve, the pressure sensor installed in the pipetting line collects the real-time pressure value in the line at a fixed frequency to form a pressure value sequence for the aspiration stage.

[0043] During the dispensing action performed by the pipette according to the dispensing speed curve, the pressure sensor installed in the pipette line collects the real-time pressure value in the line at a fixed frequency to form a pressure value sequence for the dispensing stage.

[0044] From the absorption rate curve, extract several preset key rate monitoring points, and obtain the corresponding pressure values ​​in the absorption stage pressure value sequence collected at the key rate monitoring points.

[0045] From the injection rate curve, extract several preset key speed monitoring points, and obtain the corresponding pressure values ​​in the injection stage pressure value sequence collected at the key speed monitoring points.

[0046] The pressure values ​​corresponding to the key speed monitoring points are compared with the standard pressure range for the corresponding speed retrieved from the standard pressure curve library to determine whether the pressure values ​​deviate from the standard pressure range.

[0047] Preferably, the step of sampling the real-time torque value applied by the cap-screwing robot arm and obtaining a set of torque sample values ​​while the cap rotation operation is being performed includes:

[0048] At the same time the drive motor of the capping robot arm starts to output torque, real-time high-speed sampling of the drive motor current value is initiated to obtain the motor current sampling sequence.

[0049] Based on the torque-current conversion relationship of the drive motor, each current value in the motor current sampling sequence is converted into the corresponding instantaneous torque value in real time, forming an instantaneous torque value sequence;

[0050] During the entire time interval of the cover rotation operation, torque values ​​are extracted from the instantaneous torque value sequence at set time intervals to form a set of discrete torque sampling points.

[0051] Within a preset time window before the end of the cover rotation operation, the instantaneous torque value sequence is subjected to mean filtering to obtain the steady-state torque value.

[0052] The set of discrete torque sampling points is combined with the steady-state torque value to form the set of torque sampling values.

[0053] Preferably, the fully automated sampling tube capping and pipetting workstation system also includes:

[0054] The set of torque sample values ​​is compared and analyzed with the torque parameters retrieved from the cap screw-on torque strategy library to generate a torque consistency verification report, which specifically includes:

[0055] From the cap torque strategy library, retrieve the standard torque upper limit, standard torque lower limit, and standard torque target value corresponding to the specification number in the cap compatibility identification result;

[0056] From the set of torque sampled values, the set of discrete torque sampled points is selected, and the average value of the set of discrete torque sampled points is calculated;

[0057] Determine whether the average value of the set of discrete torque sampling points is within the interval formed by the upper limit of the standard torque and the lower limit of the standard torque;

[0058] Determine whether the steady-state torque value in the set of torque samples is within the interval formed by the upper limit of the standard torque and the lower limit of the standard torque;

[0059] Calculate the absolute difference between the steady-state torque value and the standard torque target value;

[0060] The average value of the discrete torque sampling point set, the steady-state torque value, the absolute difference, and the results of the two judgments are integrated to generate a torque consistency verification report that includes conclusions on torque process stability, final torque accuracy, and torque compliance.

[0061] Preferably, the present invention also includes an operation method for a fully automated sampling tube capping and pipetting workstation system, applied to the fully automated sampling tube capping and pipetting workstation system as described above, the method comprising:

[0062] A dynamic coordinate system is established to simulate the movement of the sampling tube along the delivery path, and several key motion points are defined in the dynamic coordinate system.

[0063] The contour scanning data of the sampling tube cap is recorded in real time at each of the key motion points. The contour scanning data is compared with the standard cap specification database to generate cap compatibility identification results.

[0064] Based on the cap compatibility recognition result, a posture adjustment command for the sampling tube is triggered, and the mechanical clamping mechanism is controlled to perform a calibration operation on the posture of the sampling tube according to the posture adjustment command. After the calibration operation is completed, a sampling tube ready signal is generated.

[0065] In response to the sampling tube ready signal, a visual scan of the sample label attached to the sampling tube body is initiated, and the sample label is parsed to extract the set of pipetting parameters;

[0066] The set of pipetting parameters is input into the pipetting control logic to generate a pipetting path planning diagram, and the pipetting needle is controlled to perform aspiration and dispensing actions according to the pipetting path planning diagram, while continuously monitoring the pipetting pressure value during the execution process;

[0067] After the pipetting operation is completed, the capping compatibility recognition result is received, and the corresponding torque parameters are called from the capping torque strategy library according to the capping compatibility recognition result to drive the capping robot arm to perform the cap rotation operation.

[0068] While the cover rotation operation is being performed, the real-time torque value applied by the cover-spinning robotic arm is sampled to obtain a set of torque sample values;

[0069] The set of torque sample values ​​is compared and analyzed with the torque parameters retrieved from the cap torque strategy library to generate a torque consistency verification report.

[0070] Compared with the prior art, the beneficial effects of the present invention are:

[0071] Multiple key points are set along the motion path and a dynamic coordinate system is established. Contour data of the tube cap is continuously collected at each point during the sampling tube's movement. Multi-point continuous contour scanning replaces single-shot imaging at fixed positions, integrating the shape information of the sampling tube under different spatial poses. This method reduces the probability of recognition errors caused by transmission vibrations, momentary occlusion, or light reflection, ensuring that the positioning and state judgment of the tube cap do not depend on its perfect stillness in a single location. The generated adaptation recognition results contain more complete orientation and morphological features, providing a reliable state basis for subsequent mechanical operations.

[0072] Based on the real-time cap compatibility identification results, matching torque parameters are selected from a pre-set strategy library. This library associates torque settings for different cap specifications, wear levels, and contamination conditions. During capping, the actual torque value of the output shaft is simultaneously collected, forming a process torque dataset. This method adapts the capping action parameters to the actual physical state of the current cap, changing the fixed torque output mode. Dynamic torque matching reduces sealing issues caused by insufficient torque and structural damage caused by excessive torque. Simultaneously, complete torque process data is recorded, preserving the mechanical characteristics of each capping operation. This provides conditions for evaluating capping consistency, analyzing thread condition changes, and optimizing torque strategies. Attached Figure Description

[0073] Figure 1 This is a timing diagram of the fully automated sampling tube capping and pipetting workstation system described in this invention;

[0074] Figure 2 A flowchart for generating the sampling tube ready signal;

[0075] Figure 3 A flowchart for pipetting path planning and execution;

[0076] Figure 4 A torque monitoring diagram of the capping process in a fully automated sampling tube capping and pipetting workstation;

[0077] Figure 5 A bar chart showing the performance ratings of each functional module in the fully automated sampling tube capping and pipetting workstation. Detailed Implementation

[0078] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0079] Please see Figure 1 This invention provides a fully automated sampling tube capping and pipetting workstation system. The system includes: a motion point definition module that first establishes a dynamic coordinate system to simulate the movement of the sampling tube along the conveyor path, and defines several key motion points within this system. As the sampling tube moves on the conveyor belt, passing these key motion points, the capping adapter recognition module records the contour scan data of the sampling tube cap in real time and generates a sampling tube ready signal based on this data. In response to this ready signal, a label scanning module initiates a visual scan of the sample label attached to the sampling tube, parsing the label content to extract a set of pipetting parameters containing information such as liquid volume and target location. Subsequently, a pipetting planning and execution module receives this set of pipetting parameters, inputs it into its internal control logic to generate a detailed pipetting path planning diagram, and controls the pipetting needle to perform aspiration and dispensing actions according to this diagram, continuously monitoring the pressure value within the pipetting tubing during this process. After the pipetting operation is completed, the rotary torque call module receives the capping compatibility recognition result generated by the capping compatibility recognition module, and calls the corresponding torque parameters from the preset capping torque strategy library based on the recognition result, thereby driving the capping robot arm to perform the cap rotation operation. At the same time, the real-time torque acquisition module samples the real-time torque value applied to the capping robot arm during the rotation operation, thereby obtaining a set of torque sample values.

[0080] Example 1: The origin of the dynamic coordinate system is set at the initial feeding position where the sampling tube begins to be received on the conveyor belt. Along the conveyor belt's running direction, multiple station center coordinates are calculated sequentially based on the preset positions of each station's stopping point in the system. Multiple path interpolation points are inserted at equal intervals between any two adjacent station center coordinates, and the kinematic parameters of all station center coordinates and all path interpolation points are calculated. From all path interpolation points, turning points where the direction of motion changes are selected. Finally, the origin of the dynamic coordinate system, all station center coordinates, and all selected turning points are combined and defined as several key motion points in the dynamic coordinate system.

[0081] In practical implementation, the motion point definition module establishes a dynamic coordinate system to simulate the movement of the sampling tube along the conveyor path and defines several key motion points within this system. This is achieved by setting the origin of the dynamic coordinate system at the initial feeding position where the conveyor belt begins receiving the sampling tube. Along the conveyor belt's running direction, the motion point definition module sequentially calculates the center coordinates of multiple workstations based on the preset positions of each workstation in the system. These workstation positions include the capping and scanning workstation, the label recognition workstation, the liquid transfer workstation, and the capping workstation.

[0082] In some embodiments, the motion point definition module inserts multiple path interpolation points at equal intervals between any two adjacent workstation center coordinates, and calculates the kinematic parameters of all workstation center coordinates and all path interpolation points. The kinematic parameters include instantaneous velocity and acceleration. When calculating the coordinates of the path interpolation points, a path parameter u, with a value ranging from 0 to 1, can be introduced for linear interpolation between two known workstation center coordinates. For two adjacent workstation center coordinates... and The first Path interpolation points The coordinates are determined by the following relationship:

[0083]

[0084] in: This represents the coordinate vector of the starting workstation center. Represents the center coordinate vector of the target workstation. It is the first The path parameter values ​​corresponding to each path interpolation point. Path parameters The required number of interpolation points and their evenly distributed spacing are determined.

[0085] In practical implementation, the motion point definition module filters out turning points where the motion direction changes from all calculated path interpolation points. Changes in motion direction are determined by calculating the cross product of vectors connecting adjacent path interpolation points or analyzing the rate of change of coordinates. Essentially, merging the origin of the dynamic coordinate system, the coordinates of all workstation centers, and all selected turning points defines several key motion points in the dynamic coordinate system used for system-wide coordinated control. These key motion points constitute the spatial reference sequence for monitoring and executing operations on the sampling tube along the transport path.

[0086] In some embodiments, when calculating the coordinates of the workstation center, the motion point definition module may optionally incorporate coordinate compensation based on the actual operating speed of the conveyor belt and the installation error of the mechanical structure. It can be understood that the process of calculating the kinematic parameters of the path interpolation points may optionally assign a timestamp and instantaneous speed value to each path interpolation point according to a preset conveyor belt speed curve, thereby constructing a complete motion trajectory model containing time and spatial information in the dynamic coordinate system, providing a synchronization reference for subsequent modules to trigger actions at precise times and locations.

[0087] Example 2: See Figure 2 The cap adaptation recognition module records contour scanning data and generates a sampling tube ready signal at each key motion point, including the generation of cap adaptation recognition results and the calibration of the sampling tube posture. When the sampling tube passes any key motion point, a 3D contour scanning device is activated to perform a circular scan on the outer surface of the sampling tube cap, acquiring a set of point cloud data of the cap surface. This point cloud data set is then processed for noise reduction and feature extraction to obtain the cap's contour geometric feature data. A standard cap feature template corresponding to the current batch is read from the standard cap specification database. The matching degree between the extracted cap contour geometric feature data and the standard cap feature template is calculated. If the matching degree is lower than a preset matching threshold, the standard cap feature template is updated to the alternative cap feature template with the highest matching degree, and the matching degree is recalculated. The final matching degree and the specification number of the corresponding standard or alternative cap feature template are used together as the cap adaptation recognition result. Based on the cap compatibility recognition result, the system triggers an attitude adjustment command for the sampling tube and controls the mechanical clamping mechanism to perform a calibration operation on the attitude of the sampling tube according to the command. After the calibration operation is completed, a sampling tube ready signal is generated.

[0088] In practical implementation, the cap-adaptor recognition module records the contour scanning data of the sampling tube cap in real time at each key motion point and generates a sampling tube ready signal. The implementation involves the following steps: the cap-adaptor recognition module immediately activates the 3D contour scanning device when the sampling tube passes any key motion point defined by the motion point definition module. The 3D contour scanning device performs a circular scan on the outer surface of the sampling tube cap to obtain a point cloud data set of the cap surface. This point cloud data set contains the 3D coordinate information of a large number of points on the cap surface.

[0089] In some embodiments, the cap fitting recognition module performs noise reduction and feature extraction processing on the acquired point cloud data set to obtain the contour geometric feature data of the cap. The noise reduction process removes discrete noise points generated during the scanning process using a filtering algorithm. The cap fitting recognition module reads the standard cap feature template corresponding to the current batch from the standard cap specification database. The standard cap specification database pre-stores standard 3D model feature data of caps of various specifications. The cap fitting recognition module calculates the matching degree value between the obtained contour geometric feature data of the cap and the standard cap feature template. The calculation can be performed based on the following relationship:

[0090]

[0091] in: This indicates the first point extracted from the point cloud of the sampling tube cap. One contour geometric feature data, This represents the corresponding first feature template in the standard pipe cap. Standard feature data, It is a specific function used to calculate the similarity between two feature data. It is to give the first Weight coefficients for each feature data, This represents the total number of feature data points involved in the matching. The calculated matching score... If the value is below the preset matching threshold, the cap fitting recognition module will update the standard cap feature template with the alternative cap feature template that has the highest matching degree and recalculate the matching degree value.

[0092] In practice, the cap fitting recognition module outputs the final calculated matching degree value and the corresponding standard cap feature template or the specification number of the alternative cap feature template as the cap fitting recognition result. Based on the cap fitting recognition result, the module triggers an attitude adjustment command for the sampling tube. Following this command, the module controls the mechanical clamping mechanism to perform a calibration operation on the sampling tube's attitude. After the calibration operation is completed, the module generates a sampling tube ready signal, which triggers the tag scanning module to start operating.

[0093] It is understood that the triggering logic of the attitude adjustment command is directly related to the specification number and matching degree value in the cap fit recognition result. In some embodiments, optionally, each standard cap feature template in the standard cap specification database is associated with a set of preset clamping parameters, which are queried and used in the attitude calibration mapping table. It is understood that the path of the 3D contour scanning device performing the circular scan is precisely spatially synchronized with the stopping position of the sampling tube at key motion points, and this synchronization is guaranteed by the coordinate and time information provided by the motion point definition module. Optionally, the preset matching threshold used when calculating the matching degree value can be dynamically configured according to the specific requirements of different cap specifications or production batches.

[0094] Example 3: See Figure 3 The system retrieves the specification number of the corresponding standard tube cap feature template from the cap compatibility recognition results. Based on this specification number, it queries a preset attitude calibration mapping table to obtain the target clamping angle and clamping center offset corresponding to that number. The system controls the vision positioning device to photograph the sampling tube at the current station, acquiring a real-time position image of the sampling tube and resolving the actual tube axis angle and actual cap center position from it. The system calculates the angular deviation between the actual tube axis angle and the target clamping angle, and the positional deviation between the actual cap center position and the standard station center point. These angular deviations, positional deviations, and clamping center offsets are vector-synthesized to generate the three-dimensional spatial compensation required by the mechanical clamping mechanism's end effector. Based on this three-dimensional spatial compensation, the system controls the mechanical clamping mechanism's end effector to move and perform clamping and attitude fine-tuning on the sampling tube until the actual tube axis angle and actual cap center position meet the preset calibration tolerance range. After attitude calibration is completed, the pipetting planning and execution module begins operation. This module analyzes the set of pipetting parameters obtained from the label scanning module, extracting the liquid level height, target pipetting volume, and coordinate information of the target dispensing container. Based on the liquid level height and target pipetting volume, combined with the physical properties of the pipetting needle, it calculates the safe depth of the pipetting needle immersed in the liquid, the aspiration rate curve, and the dispensing rate curve. Using the coordinates of the end effector of the mechanical clamping mechanism after attitude calibration as the starting point of the path, and the coordinates of the target dispensing container as the ending point, a collision-free three-dimensional spatial movement trajectory is planned between the starting and ending points, avoiding all fixed obstacles within the workstation. The three-dimensional spatial movement trajectory, safe depth, aspiration rate curve, and dispensing rate curve are integrated to generate a pipetting path planning diagram containing a spatial coordinate sequence and a rate command sequence. The system controls the pipetting needle to move sequentially to each coordinate point according to the spatial coordinate sequence in the pipetting path planning diagram, and upon reaching the designated coordinate point, performs the liquid aspiration and dispensing actions according to the corresponding rate command sequence in the planning diagram.

[0095] In specific implementation, the process of parsing the cap compatibility recognition result to control the mechanical clamping mechanism to perform sampling tube posture calibration is as follows: The cap compatibility recognition result generated by the cap compatibility recognition module is sent to the control unit for parsing, and the specification number of the corresponding standard tube cap feature template is obtained from the cap compatibility recognition result. The control unit queries the preset posture calibration mapping table according to the specification number. The posture calibration mapping table stores the correspondence between different specification numbers and target clamping parameters. The control unit obtains the target clamping angle and clamping center offset corresponding to the specification number from the posture calibration mapping table. The control unit then drives the vision positioning device to take a picture of the sampling tube at the current station. The vision positioning device obtains a real-time position image of the sampling tube, and the control unit parses the actual tube body axis angle and the actual tube cap center position of the sampling tube from the real-time position image.

[0096] In some embodiments, the control unit calculates the angular deviation between the actual pipe axis angle and the target clamping angle, and simultaneously calculates the positional deviation between the actual pipe cap center position and the standard workstation center point. The control unit vector-synthesizes the angular deviation, positional deviation, and clamping center offset to generate the required three-dimensional spatial compensation amount for the end effector of the mechanical clamping mechanism. Three-dimensional spatial compensation amount The compositional relationship is expressed by the following equation:

[0097]

[0098] in: It is a position deviation vector consisting of the coordinate difference between the actual center position of the pipe cap and the center point of the standard workstation. It is the angular deviation between the actual tube axis angle and the target clamping angle. It is a rotation about a vertical axis The rotation transformation matrix of the angle. This is the clamping center offset vector obtained from the attitude calibration mapping table. Based on the calculated three-dimensional spatial compensation, the control unit drives the end effector of the mechanical clamping mechanism to move and perform clamping and attitude fine-tuning operations on the sampling tube until the actual tube axis angle and the actual tube cap center position meet the system's preset calibration tolerance range.

[0099] In practice, after the mechanical clamping mechanism completes attitude calibration, the pipetting planning and execution module begins operation. This module parses the pipetting parameter set obtained from the label scanning module. It extracts the liquid level height, target pipetting volume, and coordinates of the target dispensing container from this parameter set. Based on the liquid level height and target pipetting volume, and considering the physical properties of the pipetting needle (including needle diameter and wetting characteristics), the module calculates the safe immersion depth of the pipetting needle, the aspiration rate curve, and the dispensing rate curve.

[0100] It can be understood that the pipetting planning and execution module uses the stable coordinates of the sampling tube after the end effector of the mechanical clamping mechanism completes attitude calibration as the starting point of path planning, and the coordinate information of the target dispensing container as the ending point of path planning. In some embodiments, the pipetting planning and execution module plans a collision-free three-dimensional spatial movement trajectory between the starting point and the ending point of the path, based on the known three-dimensional model of all fixed obstacles within the workstation. The pipetting planning and execution module integrates the three-dimensional spatial movement trajectory, safety depth, aspiration speed curve, and dispensing speed curve to generate a pipetting path planning diagram containing a series of spatial coordinate point sequences and corresponding speed command sequences. The control unit drives the pipetting needle to move sequentially to each coordinate point according to the spatial coordinate sequence in the pipetting path planning diagram, and when the pipetting needle reaches the designated coordinate point, it executes the liquid aspiration and dispensing actions according to the corresponding speed command sequence in the pipetting path planning diagram.

[0101] Example 4: During the aspiration action of the pipette according to the aspiration speed curve, a pressure sensor installed in the pipetting tubing collects real-time pressure values ​​at a fixed frequency, forming a pressure value sequence for the aspiration stage. During the dispensing action of the pipette according to the dispensing speed curve, the same pressure sensor collects real-time pressure values ​​at a fixed frequency, forming a pressure value sequence for the dispensing stage. Several preset key speed monitoring points are extracted from the aspiration speed curve, and the corresponding pressure values ​​in the pressure value sequence collected at these key speed monitoring points are obtained. Several preset key speed monitoring points are extracted from the dispensing speed curve, and the corresponding pressure values ​​in the pressure value sequence collected at these key speed monitoring points are obtained. The pressure values ​​corresponding to the obtained key speed monitoring points are compared with the standard pressure range at the corresponding speed retrieved from the standard pressure curve library to determine whether the pressure value deviates from the standard pressure range. Simultaneously with the cap rotation operation, the real-time torque acquisition module samples the real-time torque value applied by the capping robot arm. Simultaneously with the start of torque output from the drive motor of the cap-spinning robotic arm, real-time high-speed sampling of the drive motor current value is initiated, resulting in a motor current sampling sequence. Based on the torque-current conversion relationship of the drive motor, each current value in the motor current sampling sequence is converted into a corresponding instantaneous torque value in real time, forming an instantaneous torque value sequence. Throughout the entire time interval of the cap-spinning operation, torque values ​​are extracted from the instantaneous torque value sequence at set time intervals, forming a set of discrete torque sampling points. Within a preset judgment time window before the cap-spinning operation ends, the instantaneous torque value sequence undergoes mean filtering to obtain a steady-state torque value. The set of discrete torque sampling points is then merged with this steady-state torque value to form a torque sampling value set.

[0102] In practice, the pipetting planning and execution module continuously monitors pressure changes within the pipetting tubing during aspiration and dispensing operations, according to its internal control logic. This monitoring is achieved through pressure sensors installed within the pipetting tubing. Throughout the entire time interval during which the pipetting needle performs aspiration according to the generated aspiration rate curve, the pressure sensor collects real-time pressure values ​​within the tubing at a fixed sampling frequency, forming a sequence of pressure values ​​for the aspiration stage corresponding to timestamps. Similarly, throughout the entire time interval during which the pipetting needle performs dispensing according to the generated dispensing rate curve, the pressure sensor also collects real-time pressure values ​​within the tubing at a fixed sampling frequency, forming a sequence of pressure values ​​for the dispensing stage corresponding to timestamps. The pipetting planning and execution module extracts several preset key velocity monitoring points from the internal aspiration rate curve data. These key velocity monitoring points correspond to the start and end times of acceleration changes or velocity plateau phases in the velocity curve. The module then obtains the corresponding pressure measurement values ​​recorded from the pressure value sequence for the aspiration stage at the times corresponding to these key velocity monitoring points. The pipetting planning and execution module extracts several preset key velocity monitoring points from the internal dispensing velocity curve data and obtains the corresponding pressure measurement values ​​recorded from the pressure value sequence during the dispensing stage at the corresponding time of each key velocity monitoring point. The module then compares the obtained pressure measurement values ​​corresponding to the key velocity monitoring points with the standard pressure range at the same velocity point retrieved from the standard pressure curve library to determine whether each pressure measurement value deviates from the corresponding standard pressure range. Referring to Table 1, the standard pressure curve library presets pressure range references for combinations of liquids with different viscosities and different needle sizes.

[0103] Table 1: Correspondence between Key Velocity Monitoring Points and Standard Pressure Ranges

[0104]

[0105] In some embodiments, the cap rotation operation is performed by a cap-screwing robotic arm. Simultaneously with the cap rotation operation, the real-time torque acquisition module samples the real-time torque value applied to the drive shaft of the cap-screwing robotic arm. As soon as the drive motor of the cap-screwing robotic arm receives the command and begins outputting torque, the real-time torque acquisition module initiates high-speed real-time sampling of the three-phase current values ​​of the drive motor, obtaining a time-sequential sequence of motor current samples. Based on the inherent torque-current conversion relationship of the drive motor, the real-time torque acquisition module converts each instantaneous current value in the motor current sampling sequence into a corresponding instantaneous torque value in real time, thus forming a time-synchronized sequence of instantaneous torque values. The torque-current conversion relationship can be expressed as:

[0106]

[0107] in: This represents the calculated instantaneous torque value. This represents the fixed torque coefficient determined by the characteristics of the drive motor. This represents the real-time quadrature-axis current component calculated from the motor current sampling sequence. Throughout the entire time interval from the start to the end of the cover rotation operation, the real-time torque acquisition module extracts torque values ​​from the instantaneous torque value sequence at fixed time intervals set by the system, forming a set of discrete torque sampling points uniformly distributed over time.

[0108] In practice, to assess the final tightening state of the cap, the real-time torque acquisition module operates within a preset judgment time window before the cap rotation operation ends. This preset judgment time window corresponds to the final stable segment of the cap rotation action. The real-time torque acquisition module performs mean filtering on the instantaneous torque value sequence within the preset judgment time window. Mean filtering is achieved by calculating the arithmetic mean of all instantaneous torque values ​​within the window, and the calculated average value is recorded as the steady-state torque value. The real-time torque acquisition module merges the previously obtained discrete torque sampling point set with the calculated steady-state torque value to form a complete set of torque sampling values ​​characterizing a single cap rotation process.

[0109] It is understood that the acquisition frequency of the motor current sampling sequence is much higher than the extraction frequency of the torque discrete sampling points to ensure that the instantaneous torque value sequence has a sufficiently high time resolution. In some embodiments, optionally, the length of the preset decision time window can be adjusted according to the capping time required for different cap specifications. It is understood that the torque coefficient... The torque is accurately measured during system calibration and stored in the configuration parameters of the real-time torque acquisition module. Optionally, the mean filtering process can be replaced by weighted averaging or other digital filtering algorithms to suppress noise interference at specific frequencies.

[0110] See Figure 4 This is a torque monitoring chart for the capping process in a fully automated sampling tube capping and pipetting workstation. The core of the chart is a comparative analysis of the instantaneous torque sequence and discrete sampling points. It exhibits high-frequency fluctuations, reflecting the real-time dynamic changes in torque during capping. Evenly distributed along the time axis, the data is representative data extracted from the high-frequency instantaneous sequence, simplifying subsequent torque analysis. This type of data corresponds to the capping torque acquisition stage of the workstation. The instantaneous sequence ensures the completeness of the details of torque changes, while discrete sampling points balance data volume and analysis efficiency, providing fundamental data for subsequent "steady-state torque calculation" and "torque consistency verification." This chart is used for torque stability assessment during the capping process, intuitively determining whether torque fluctuations are within a reasonable range, and verifying whether discrete sampling points can effectively represent the overall trend of instantaneous torque. It is a key monitoring basis for ensuring compliant capping tightening effects.

[0111] Example 5: The system compares and analyzes the set of torque sample values ​​with the torque parameters retrieved from the capping torque strategy library, generating a torque consistency verification report. From the capping torque strategy library, it retrieves the standard torque upper limit, standard torque lower limit, and standard torque target value corresponding to the specification number in the capping compatibility identification result. From the torque sample value set, it filters out a set of discrete torque sampling points and calculates the average value of this set. It determines whether the average value of the set of discrete torque sampling points is within the interval formed by the standard torque upper limit and standard torque lower limit. It also determines whether the steady-state torque value in the torque sample value set is within the interval formed by the standard torque upper limit and standard torque lower limit. The absolute difference between the steady-state torque value and the standard torque target value is calculated. The average value of the set of discrete torque sampling points, the steady-state torque value, the absolute difference, and the results of the two determinations are integrated to generate a torque consistency verification report containing conclusions on torque process stability, final torque accuracy, and torque compliance.

[0112] In practice, the system generates a torque consistency verification report by comparing the set of torque sample values ​​with the torque parameters retrieved from the capping torque strategy library. After the capping torque retrieval module completes the capping rotation operation, the set of torque sample values ​​output by the real-time torque acquisition module is sent to the data analysis unit for processing. The data analysis unit retrieves the standard torque parameters from the capping torque strategy library that match the specification number contained in the capping compatibility identification result corresponding to this capping operation. The standard torque parameters include the upper limit value, the lower limit value, and the target value of the standard torque.

[0113] In some embodiments, the data analysis unit filters a set of discrete torque sampling points from the received set of torque sampled values. This set of discrete torque sampling points contains multiple instantaneous torque values ​​extracted at time intervals during the capping process. The data analysis unit calculates the average value of all values ​​in the set of discrete torque sampling points, which reflects the average torque level during the capping process. The data analysis unit determines whether the calculated average value of the set of discrete torque sampling points is within the closed interval formed by the standard upper and lower torque limits retrieved from the capping torque strategy library. This determination is used to assess the torque stability of the capping process. The data analysis unit also determines whether the steady-state torque values ​​included in the set of torque sampled values ​​are also within the closed interval formed by the standard upper and lower torque limits. This determination is used to assess the torque compliance of the final capping state.

[0114] In practice, the data analysis unit calculates the absolute difference between the steady-state torque value and the standard torque target value retrieved from the capping torque strategy library. The calculation method is as follows:

[0115]

[0116] in: This represents the steady-state torque value in the set of torque samples. This represents the standard torque target value retrieved from the capping torque strategy library. The data analysis unit integrates the average value of the discrete torque sampling point set, the steady-state torque value, the calculated absolute difference, and two judgment results regarding whether the average value and steady-state torque value are within the standard range. The integrated information is formatted into a structured torque consistency verification report. The torque consistency verification report includes a description of the torque stability during the capping process, a description of the accuracy of the final capping torque, and a clear conclusion on torque operation compliance.

[0117] It is understood that the average value of the discrete torque sampling point set and the steady-state torque value are two independent data points used for different purposes in the report. The average value is used for process analysis, while the steady-state torque value is used for result determination. In some embodiments, the torque consistency verification report may optionally include a simplified curve graph of torque changing over time as a supplementary illustration. It is understood that the logic for generating the torque consistency verification report is an independently running module, and its triggering depends on the signal from the real-time torque acquisition module completing data acquisition and the capping robot arm ending its movement. Optionally, the standard torque target value, the standard torque upper limit value, and the standard torque lower limit value are stored as a set of parameters associated with the cap specification number in the capping torque strategy library.

[0118] See Figure 5 This is a bar chart showing the performance ratings of each functional module in a fully automated sampling tube capping and pipetting workstation. The core feature is a quantitative comparison of the performance of different modules. All modules have performance ratings at a high level (approaching or reaching above 95%), indicating good stability and accuracy in the operation of each functional module. This type of chart is used during the performance evaluation and optimization phase of the workstation. It can quickly identify relatively weak modules, providing a priority reference for subsequent maintenance and parameter tuning, while also verifying whether the overall operational capability of the workstation meets the automation requirements for sampling tube processing. This chart is one of the core reference data for workstation acceptance and daily operation and maintenance. A high score means that the workstation has a low error rate in key processes such as capping and pipetting, ensuring the efficiency and accuracy of sample processing.

[0119] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A fully automated sampling tube capping and pipetting workstation system, characterized in that, The system includes: The motion point definition module establishes a dynamic coordinate system for simulating the movement of the sampling tube along the delivery path, and defines several key motion points in the dynamic coordinate system. The capping adapter identification module records the contour scanning data of the sampling tube cap in real time at each of the key movement points and generates a sampling tube ready signal; The label scanning module, in response to the sampling tube ready signal, initiates a visual scan of the sample label attached to the sampling tube body and parses the sample label to extract the set of pipetting parameters; The pipetting planning and execution module inputs the set of pipetting parameters into the pipetting control logic to generate a pipetting path planning diagram, and controls the pipetting needle to perform aspiration and dispensing actions according to the pipetting path planning diagram, while continuously monitoring the pipetting pressure value during the execution process; The rotary torque call module receives the capping compatibility recognition result generated by the capping compatibility recognition module after the pipetting action is completed, and calls the corresponding torque parameters from the capping torque strategy library according to the capping compatibility recognition result to drive the capping robot arm to perform the capping operation. The real-time torque acquisition module samples the real-time torque value applied by the cap-screwing robot arm while the cap rotation operation is being performed, and obtains a set of torque sample values. At each of the key motion points, the contour scan data of the sampling tube cap is recorded in real time to generate a sampling tube ready signal, including: The contour scan data is compared with a standard cap specification database to generate cap compatibility identification results. Based on the cap compatibility recognition result, a posture adjustment command for the sampling tube is triggered, and the mechanical clamping mechanism is controlled to perform a calibration operation on the posture of the sampling tube according to the posture adjustment command. After the calibration operation is completed, a sampling tube ready signal is generated. The step of comparing the contour scan data with a standard cap specification database to generate a cap fit identification result includes: When the sampling tube passes through any of the key motion points, the three-dimensional contour scanning device is activated to perform a circular scan on the outer surface of the sampling tube cap to obtain a set of point cloud data on the surface of the cap. The point cloud dataset is subjected to noise reduction and feature extraction processing to obtain the outline geometric feature data of the cap. Read the standard cap feature template corresponding to the batch to be processed from the standard cap specification database; Calculate the matching degree between the contour geometric feature data of the cap and the standard cap feature template; If the matching degree value is lower than the preset matching threshold, the standard cap feature template is updated to the alternative cap feature template with the highest matching degree value, and the matching degree value is recalculated. The final matching degree value obtained by calculation, together with the specification number of the corresponding standard cap feature template or alternative cap feature template, are used as the cap fit identification result.

2. The fully automated sampling tube capping and pipetting workstation system according to claim 1, characterized in that, The step of establishing a dynamic coordinate system for simulating the movement of the sampling tube along the delivery path, and defining several key motion points in the dynamic coordinate system, includes: Set the origin of the dynamic coordinate system at the initial feeding position of the conveyor belt; Along the direction of the conveyor belt, the center coordinates of multiple workstations are calculated sequentially based on the preset workstation stop points. Between any two adjacent workstation center coordinates, multiple path interpolation points are inserted at equal intervals, and the kinematic parameters of all workstation center coordinates and all path interpolation points are calculated. Filter out the turning points where the direction of motion changes from all the path interpolation points; The origin of the dynamic coordinate system, the coordinates of all the workstation centers, and all the turning points are combined and defined as several key motion points in the dynamic coordinate system.

3. The fully automated sampling tube capping and pipetting workstation system according to claim 1, characterized in that, The step of triggering an attitude adjustment command for the sampling tube based on the cap compatibility recognition result, and controlling the mechanical clamping mechanism to perform a calibration operation on the sampling tube attitude according to the attitude adjustment command, includes: The cap compatibility recognition result is analyzed, and the specification number of the corresponding standard cap feature template is obtained from the cap compatibility recognition result; Based on the specification number, query the preset attitude calibration mapping table to obtain the target clamping angle and clamping center offset corresponding to the specification number; The visual positioning device is controlled to take pictures of the sampling tube at the current workstation, obtain the real-time position image of the sampling tube, and parse the actual tube body axis angle and the actual tube cap center position of the sampling tube from the real-time position image. Calculate the angular deviation between the actual pipe axis angle and the target clamping angle, and calculate the positional deviation between the actual pipe cap center position and the standard workstation center point; The angular deviation, the positional deviation, and the clamping center offset are vector-synthesized to generate a three-dimensional spatial compensation amount for the end effector of the mechanical clamping mechanism. Based on the three-dimensional spatial compensation amount, the end effector of the mechanical clamping mechanism is controlled to move and perform clamping and attitude fine-tuning on the sampling tube until the actual tube axis angle and the actual tube cap center position meet the preset calibration tolerance range.

4. The fully automated sampling tube capping and pipetting workstation system according to claim 3, characterized in that, The step of inputting the set of pipetting parameters into the pipetting control logic to generate a pipetting path planning diagram, and controlling the pipetting needle to perform aspiration and dispensing actions according to the pipetting path planning diagram, includes: The set of pipetting parameters is analyzed to extract the liquid level height of the target sample, the target pipetting volume, and the coordinate information of the target dispensing container. Based on the liquid level and the target volume of liquid transfer, and combined with the physical property parameters of the pipette, the safe depth of the pipette immersion in the liquid, the aspiration rate curve, and the dispensing rate curve are calculated. Using the coordinates of the end effector of the mechanical clamping mechanism after attitude calibration as the starting point of the path, and the coordinate information of the target dispensing container as the ending point of the path, a collision-free three-dimensional spatial movement trajectory is planned between the starting point and the ending point of the path, avoiding all fixed obstacles in the workstation. The three-dimensional spatial movement trajectory, the safety depth, the aspiration speed curve, and the dispensing speed curve are integrated to generate the pipetting path planning map containing a spatial coordinate sequence and a speed command sequence; According to the spatial coordinate sequence in the pipetting path planning diagram, the pipetting needle is controlled to move sequentially to each coordinate point, and when it reaches the designated coordinate point, the liquid is aspirated and dispensed according to the corresponding speed command sequence in the pipetting path planning diagram.

5. The fully automated sampling tube capping and pipetting workstation system according to claim 4, characterized in that, The step of continuously monitoring the pipetting pressure value during execution includes: During the process of the pipetting needle performing the aspiration action according to the aspiration speed curve, the pressure sensor installed in the pipetting line collects the real-time pressure value in the line at a fixed frequency to form a pressure value sequence for the aspiration stage. During the dispensing action performed by the pipette according to the dispensing speed curve, the pressure sensor installed in the pipette line collects the real-time pressure value in the line at a fixed frequency to form a pressure value sequence for the dispensing stage. From the absorption rate curve, extract several preset key rate monitoring points, and obtain the corresponding pressure values ​​in the absorption stage pressure value sequence collected at the key rate monitoring points. From the injection rate curve, extract several preset key speed monitoring points, and obtain the corresponding pressure values ​​in the injection stage pressure value sequence collected at the key speed monitoring points. The pressure values ​​corresponding to the key speed monitoring points are compared with the standard pressure range for the corresponding speed retrieved from the standard pressure curve library to determine whether the pressure values ​​deviate from the standard pressure range.

6. The fully automated sampling tube capping and pipetting workstation system according to claim 1, characterized in that, The step of sampling the real-time torque value applied by the cap-screwing robot arm and obtaining a set of torque sample values ​​while the cap rotation operation is being performed includes: At the same time the drive motor of the capping robot arm starts to output torque, real-time high-speed sampling of the drive motor current value is initiated to obtain the motor current sampling sequence. Based on the torque-current conversion relationship of the drive motor, each current value in the motor current sampling sequence is converted into the corresponding instantaneous torque value in real time, forming an instantaneous torque value sequence; During the entire time interval of the cover rotation operation, torque values ​​are extracted from the instantaneous torque value sequence at set time intervals to form a set of discrete torque sampling points. Within a preset time window before the end of the cover rotation operation, the instantaneous torque value sequence is subjected to mean filtering to obtain the steady-state torque value. The set of discrete torque sampling points is combined with the steady-state torque value to form the set of torque sampling values.

7. The fully automated sampling tube capping and pipetting workstation system according to claim 6, characterized in that, The fully automated sampling tube capping and pipetting workstation system also includes: The set of torque sample values ​​is compared and analyzed with the torque parameters retrieved from the cap screw-on torque strategy library to generate a torque consistency verification report, which specifically includes: From the cap torque strategy library, retrieve the standard torque upper limit, standard torque lower limit, and standard torque target value corresponding to the specification number in the cap compatibility identification result; From the set of torque sampled values, the set of discrete torque sampled points is selected, and the average value of the set of discrete torque sampled points is calculated; Determine whether the average value of the set of discrete torque sampling points is within the interval formed by the upper limit of the standard torque and the lower limit of the standard torque; Determine whether the steady-state torque value in the set of torque samples is within the interval formed by the upper limit of the standard torque and the lower limit of the standard torque; Calculate the absolute difference between the steady-state torque value and the standard torque target value; The average value of the discrete torque sampling point set, the steady-state torque value, the absolute difference, and the results of the two judgments are integrated to generate a torque consistency verification report that includes conclusions on torque process stability, final torque accuracy, and torque compliance.

8. A method for operating a fully automated sampling tube capping and pipetting workstation system, applied to the fully automated sampling tube capping and pipetting workstation system as described in any one of claims 1 to 7, characterized in that, The method includes: A dynamic coordinate system is established to simulate the movement of the sampling tube along the delivery path, and several key motion points are defined in the dynamic coordinate system. The contour scanning data of the sampling tube cap is recorded in real time at each of the key motion points. The contour scanning data is compared with the standard cap specification database to generate cap compatibility identification results. Based on the cap compatibility recognition result, a posture adjustment command for the sampling tube is triggered, and the mechanical clamping mechanism is controlled to perform a calibration operation on the posture of the sampling tube according to the posture adjustment command. After the calibration operation is completed, a sampling tube ready signal is generated. In response to the sampling tube ready signal, a visual scan of the sample label attached to the sampling tube body is initiated, and the sample label is parsed to extract the set of pipetting parameters; The set of pipetting parameters is input into the pipetting control logic to generate a pipetting path planning diagram, and the pipetting needle is controlled to perform aspiration and dispensing actions according to the pipetting path planning diagram, while continuously monitoring the pipetting pressure value during the execution process; After the pipetting operation is completed, the capping compatibility recognition result is received, and the corresponding torque parameters are called from the capping torque strategy library according to the capping compatibility recognition result to drive the capping robot arm to perform the cap rotation operation. While the cover rotation operation is being performed, the real-time torque value applied by the cover-spinning robotic arm is sampled to obtain a set of torque sample values; The set of torque sample values ​​is compared and analyzed with the torque parameters retrieved from the cap torque strategy library to generate a torque consistency verification report.

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