A robot clamping assembly for a CNC automatic loading and unloading device

Abstract

The application discloses a robot clamping assembly for a CNC automatic feeding and discharging device, the automatic feeding and discharging device comprising a moving machine box, a controller, a mechanical arm, a transportation and positioning module; the mechanical arm is provided with a torque sensing module at the tail end, connected with a four-jaw clamping assembly, which comprises a cylindrical base, a sliding cylinder, a connecting rod transmission mechanism, a clamping jaw, a fixed intermediate shaft, an integrated force sensor and a visual detection camera; the system defines three coordinate systems of a camera, a base and a tool, collects an image of a reference block through vision, realizes high-precision calibration through pixel and physical coordinate conversion, coordinate system mapping and tool coordinate system calibration, and realizes high-precision calibration in combination with an error compensation formula Delta S=k*Delta E; the workpiece defect detection is also completed based on vision, the defects are classified according to defect area and geometric position deviation, the clamping force is controlled in real time through a force sensor, and the risk of slippage and overload is avoided. The application has high integration, high precision and high safety, realizes the cooperative closed loop of visual positioning, force feedback and precise execution, and improves production efficiency and quality traceability ability.

Description

Technical Field

[0001] This invention relates to the field of robotics, and more particularly to a robot gripping assembly for a CNC automatic loading and unloading device. Background Technology

[0002] In CNC machining of precision electronic product parts, the automation level, positioning accuracy, gripping reliability, and pre-inspection capabilities of the loading and unloading process directly determine the yield rate, production line efficiency, and maintenance costs. Existing CNC automated loading and unloading technologies have gradually upgraded from manual loading and unloading and single-function robotic arms to integrated and intelligent systems. Among them, Chinese invention patent CN202610244791.5 discloses an automated CNC loading and unloading device for electronic product parts. This device integrates a moving chassis, controller, six-axis robotic arm, three-channel conveyor belt transport module, workpiece and pallet dual positioning module, and dual-camera vision inspection module. It uses dual suction cups for gripping and transfer, and AI deep learning for post-processing defect detection and sorting. It can adapt to the continuous processing of multi-specification electronic product parts, improving the automation level of loading, unloading, and inspection to a certain extent.

[0003] However, the existing integrated solutions mentioned above still have significant technical deficiencies in key areas such as precision clamping, coaxial calibration, long-term accuracy maintenance, force control safety, and pre-defect detection, and cannot meet the requirements of micron-level precision machining and highly reliable unmanned operation for high-end electronic product parts, as detailed below:

[0004] 1. The end effector lacks sensing capability, resulting in insufficient clamping reliability and workpiece protection. Existing solutions use dual vacuum suction cups as the end effector, relying solely on negative pressure adsorption to transfer the workpiece to the tray. There is no clamping force or torque sensing feedback. For thin-walled, irregularly shaped, and easily scratched precision electronic parts, problems such as adsorption slippage, workpiece deformation, and surface damage are prone to occur. Furthermore, it cannot identify working conditions such as gripping posture deviation, foreign object clamping, and dimensional abnormalities, which can easily lead to workpiece scrapping or workstation interference.

[0005] Second, the vision and actuator are not on the same axis, and there is no multi-coordinate system linkage calibration and dynamic error compensation. The existing solution uses external dual cameras deployed independently, which are not on the same axis as the end effector of the robotic arm. The precise mapping relationship between the camera coordinate system, robot base coordinate system and tool coordinate system has not been established. It can only realize defect detection after processing, and there is no online accuracy calibration mechanism. It cannot compensate for the positioning drift caused by wear of robotic arm joints, thermal expansion and contraction, and mechanical vibration. It is difficult to achieve stable positioning accuracy in long-term repeated operation.

[0006] Third, the defect detection is done after the workpiece is processed, and the defective products cannot be intercepted in advance. The existing solution only performs defect detection after the workpiece is processed, and does not complete the initial state detection of the workpiece before it is picked up and loaded. This results in defective products with surface defects, scratches, and out-of-tolerance dimensions entering the CNC machining process, causing tool wear, wasted time and production capacity loss.

[0007] Fourth, the system lacks closed-loop control and has insufficient safety robustness. The entire process of clamping, transferring, and positioning is controlled in an open-loop manner, without real-time force feedback and abnormal protection logic. When clamping overload, workpiece slippage, or abnormal station occurs, the system cannot stop the machine in time, alarm, or handle the situation in a tiered manner, which can easily amplify equipment failure and production losses.

[0008] The system lacks separate calibration and detection functions, resulting in high system redundancy. Accuracy calibration, workpiece detection, and conveyor belt monitoring all rely on independent hardware. Coordinate conversion is cumbersome and the debugging cycle is long. The system fails to achieve integrated "calibration-detection-grabbing-compensation" and is difficult to adapt to the needs of compact workshop layouts and rapid changeover.

[0009] In summary, existing CNC automated loading and unloading devices still suffer from core pain points such as lack of end-effector sensing, misaligned calibration, lack of precision compensation, post-processing detection, and missing force control. These shortcomings prevent them from meeting the requirements of high-end electronic product CNC precision machining for high positioning accuracy, high gripping safety, pre-defect interception, and long-term stable operation. Therefore, developing an automated loading and unloading robot that integrates coaxial vision, integrated force sensing, multi-coordinate system precise calibration, closed-loop clamping force control, and pre-defect detection has become a pressing technical problem to be solved in this field. Summary of the Invention

[0010] This invention addresses the core pain points of existing CNC automatic loading and unloading devices, such as lack of end-effector sensing, misaligned calibration, lack of accuracy compensation, post-detection, and missing force control. It provides a robot gripping component for CNC automatic loading and unloading devices that integrates coaxial vision, integrated force sensing, multi-coordinate system precise calibration, clamping force closed-loop control, and pre-defect detection.

[0011] This invention provides the following technical solution: A robot gripping component for a CNC automatic loading and unloading device. The automatic loading and unloading device includes a mobile chassis and a controller. The mobile chassis houses a robotic arm, a transport module, and a positioning module. The transport module is used for conveying workpieces and pallets; the positioning module is used for precise pallet positioning; the robotic arm is used for gripping and transferring workpieces and pallets, and for loading and unloading CNC machine tools; the controller is used for the linkage control, signal processing, timing scheduling, and accuracy compensation of each module. A torque sensing module is fixed at the end of the robotic arm. The lower end of the torque sensing module is rigidly connected to a four-jaw gripping component via a connecting flange. The four-jaw gripping component includes a cylindrical base, a sliding cylinder, a cylinder slider, four sets of linkage transmission mechanisms, four gripping jaws, a fixed intermediate shaft, an integrated force sensor, and a vision inspection camera. The sliding cylinder is coaxially mounted inside the cylindrical base, and the cylinder slider can slide up and down along the axis of the cylindrical base. The four sets of linkage transmission mechanisms are symmetrically distributed in a cross shape, with one end hinged to the side wall of the cylinder slider and the other end... Hinged to the gripping jaws, the cylinder slider slides up and down, driving the linkage transmission mechanism to move, achieving synchronous opening and closing of the four gripping jaws; the fixed intermediate shaft is coaxially fixed to the center bottom of the cylindrical base and does not move with the cylinder slider throughout the process; the vision inspection camera is precisely installed on the top end face of the fixed intermediate shaft and is located at the geometric center of the four gripping jaws, with the lens facing the same direction as the gripping; the integrated force sensor is embedded in the inner side of the gripping surface of each gripping jaw; the movable chassis has a preset fixed positioning mark, and a precision calibration reference block is installed at the fixed positioning mark. Precision calibration and preliminary defect detection of the workpiece are both completed by the fixed coaxial vision inspection camera.

[0012] In some embodiments, the specific calibration process for precision calibration is as follows: S1. Define three coordinate systems; S2. Calibration trigger: The controller initiates the precision calibration process according to preset trigger conditions, such as power-on startup, timer cycle, and abnormal reset, driving the robotic arm to move the four-jaw gripper assembly to the fixed calibration position inside the mobile chassis, so that the lens of the visual inspection camera is vertically aligned with the precision calibration reference block; S3. Image acquisition: The visual inspection camera acquires a clear image of the precision calibration reference block under preset exposure parameters, ensuring that the feature points of the precision calibration reference block are completely within the camera's field of view; S4. Coordinate calculation and mapping: The controller preprocesses the acquired calibration image, including noise reduction, grayscale conversion, and edge enhancement, extracting the sub-pixel coordinates of preset feature points on the precision calibration reference block based on the camera coordinate system, and then converting the pixel coordinates to physical coordinates using preset camera focal length and pixel size to obtain the physical coordinates of the feature points in the camera coordinate system; wherein, the dimensions of the focal length f and pixel size d in the camera intrinsic parameters are kept consistent; S5. Base coordinate system calibration: The controller calls the theoretical absolute coordinates of the preset precision calibration reference block in the robot base coordinate system, compares the physical coordinates of the feature points in the camera coordinate system obtained in S4 with the theoretical absolute coordinates, and calculates the rotation matrix and translation vector between the camera coordinate system and the robot base coordinate system to complete the mapping calibration of the two coordinate systems; S6, Tool coordinate system calibration: Using the feature points of the precision calibration reference block as a reference, the controller drives the robotic arm to fine-tune the four-jaw gripper assembly so that the geometric centers of the four grippers are precisely aligned with the feature center points of the precision calibration reference block. The geometric centers of the four grippers are the origin of the tool coordinate system. The joint angle data of the robotic arm at this time are recorded, and the coordinate offset of the tool coordinate system relative to the robot base coordinate system is calculated to complete the zero-point calibration of the tool coordinate system; S7, Error compensation: Based on the calculation results of S5 and S6, the controller calculates the position deviation value of the robotic arm end effector, drives the robotic arm end effector to adjust the robotic arm joints to perform fine-tuning compensation until the coordinate transformation error of the three coordinates meets the preset requirements, and completes the entire precision calibration process.

[0013] In some embodiments, the three coordinate systems are defined as follows: S11, the camera coordinate system is a two-dimensional reference system when the vision inspection camera captures images, with the optical center of the camera lens as the origin, the horizontal direction of the image as the X-axis, and the vertical direction of the image perpendicular to the horizontal direction as the V-axis; S12, the robot base coordinate system is the absolute three-dimensional reference for all robot movements, with the geometric center of the fixed mounting surface of the mobile chassis as the origin, the horizontal direction as the X-axis, the vertical direction as the Z-axis, and the horizontal direction perpendicular to the X-axis as the Y-axis; S13, the tool coordinate system is the working center point of the robot's end effector, with the geometric center of the four gripping claws, i.e., the center point of the optical axis of the vision inspection camera, as the origin, and is defined as an axis system that is in the same direction as the robot base coordinate system.

[0014] In some embodiments, during the accuracy calibration process, coordinate calculation, offset calculation, and error compensation are all completed using preset formulas. The specific formula steps are as follows: Pixel coordinate to physical coordinate conversion formula: Where (u,v) are the sub-pixel coordinates of the feature point in the camera coordinate system. Let be the coordinates of the camera's imaging center pixel, d be the camera pixel size, f be the camera focal length (with dimensions consistent with d), Zcam be the perpendicular distance from the feature point to the camera lens, and (Xcam, Ycam) be the two-dimensional physical coordinates of the feature point in the camera coordinate system. The mapping formula between the camera coordinate system and the robot base coordinate system is as follows: Where Pbase is the 3D coordinate of the feature point in the robot base coordinate system, Pcam is the 3D coordinate of the feature point in the camera coordinate system, Zcam is the Z-axis coordinate, R is the rotation matrix, and T is the translation vector. Both are calculated using S5. The rotation matrix R is a 3×3 matrix, and the translation vector T is a 3×1 vector. The formula for calculating the tool coordinate system offset is as follows: Where ΔPTCP is the coordinate offset of the tool coordinate system relative to the robot base coordinate system, Pbase_target is the theoretical coordinate of the feature center point of the accuracy calibration reference block in the robot base coordinate system, and PTCP_actual is the actual coordinate of the origin of the tool coordinate system in the robot base coordinate system after fine-tuning; the formula for calculating the position deviation of the robotic arm end effector is as follows: Where ΔE is the end-effector position deviation, and ΔX, ΔY, and ΔZ are the offset components of the tool coordinate system origin in the X, Y, and Z axes of the robot base coordinate system, respectively; the displacement compensation calculation formula is as follows: Where ΔS is the fine-tuning compensation amount of the robotic arm joint, k is the compensation coefficient, which is preset to 0.9~1.1, ΔE is the position deviation value calculated by S7, which must satisfy ΔE≤ε after compensation, and ε is the preset accuracy threshold, which is less than or equal to 0.05mm.

[0015] In some embodiments, the preliminary defect detection process for the workpiece is triggered based on the system state after the accuracy calibration is completed, specifically including the following steps: S8, Detection trigger: After the tool coordinate system calibration is completed and the error compensation meets the preset threshold, the controller drives the robotic arm to move the four-jaw gripping assembly to the preset shooting position of the workpiece to be gripped, so that the vision inspection camera lens is vertically aligned with the workpiece surface to acquire the initial image of the workpiece; S9, Image registration and comparison: The controller calls the mapping relationship between the calibrated camera coordinate system and the robot base coordinate system in S4, S5 and S6. The initial image of the acquired workpiece is matched with a preset standard workpiece template image for feature matching and grayscale normalization. S10, Defect Feature Extraction: The controller extracts edge contours and performs texture analysis on the registered workpiece image to accurately identify notches, scratches, pits, stains, and dimensional defects on the workpiece surface. The minimum pixel resolution for defect identification is no greater than the camera pixel size. For the corresponding physical dimensions, the repeatability of defect detection should not exceed [a certain value]. S11, Defect Judgment and Classification: By calculating the area of ​​the defect region. ,perimeter and form and position deviation Compare with the preset qualified threshold: If ≤ and ≤ If it is determined to be a qualified workpiece, the controller sends a grabbing execution command; if > or > If the workpiece is found to be defective, the controller immediately triggers a sorting signal and drives the robotic arm to move the defective workpiece to a dedicated waste area. S12, Data Archiving: The controller synchronously stores the image feature data and size detection data of the qualified workpieces, as well as the defect type and defect location coordinates of the defective workpieces, into the local database.

[0016] In some embodiments, an integrated force sensor collects and feeds back the clamping force value in real time during the closing process of the four-jaw clamping assembly clamping the workpiece. The controller will collect data in real time. With the preset safety clamping force range Real-time comparison is performed, and the following control logic is executed accordingly: If If the error is determined to be workpiece slippage, gripping posture deviation, or failure to grip the workpiece, the controller immediately stops the gripping action, triggers a re-gripping process, drives the robotic arm to reset the four-jaw gripping assembly, and then performs the gripping operation again; if If the error is detected, it is determined that a foreign object is caught in the workpiece clamping surface, the clamping is overloaded, or the workpiece size is abnormal. The controller will immediately stop all actions, issue an audible and visual alarm signal, and upload the abnormal information to the cloud database. The system can only be reset and the operation restarted after the abnormality is manually investigated.

[0017] Compared with the prior art, the advantages of the present invention are as follows:

[0018] I. An integrated and high-precision "eye-hand-brain" collaborative system: This invention achieves closed-loop control of "visual positioning, force feedback, and precise execution" by highly integrating a visual inspection camera, an integrated force sensor, and a four-jaw gripper assembly. Compared with traditional CNC loading and unloading robots, this solution does not require an external additional vision workstation or independent force measuring device. It directly completes high-precision calibration and defect detection on the robot's end effector, greatly simplifying the system architecture and shortening the operation cycle.

[0019] II. Innovative Multi-Sensor Fusion Accuracy Calibration and Error Compensation Mechanism: This solution discloses a complete coordinate system definition and calibration process, covering the precise mapping of the camera coordinate system, base coordinate system, and tool coordinate system. In particular, in the tool coordinate system calibration stage, the geometric center of the gripper is used as the origin, and dynamic adjustment is performed in combination with the real-time error compensation formula ΔS=k×ΔE. This effectively overcomes the positional deviation problem caused by wear of the robotic arm joints and thermal expansion and contraction. This design ensures that the system can maintain extremely high absolute accuracy during long-term continuous operation, solving the industry pain point of accuracy drift in industrial settings.

[0020] Third, intelligent and safe closed-loop control of clamping force. The four-jaw clamping assembly of this invention is not a simple mechanical structure, but an intelligent actuator with "tactile" capabilities. By integrating a force sensor to collect the clamping force Fclamp in real time and dynamically comparing it with the safe range [Fmin, Fmax], it can not only intelligently identify whether the workpiece has slipped or whether the gripping posture has deviated, but also immediately trigger an audible and visual alarm and upload abnormal information when foreign objects are clamped or dimensions are out of tolerance. This avoids secondary accidents such as tool damage or workpiece scrapping, and greatly improves the safety and robustness of the production system.

[0021] IV. Efficient end-to-end quality inspection and classification archiving of workpieces: Based on accuracy calibration, this solution seamlessly integrates the initial defect detection process of workpieces. Utilizing a calibrated vision system, it performs feature matching, edge contour extraction, and texture analysis on workpieces, accurately identifying various defects such as notches, scratches, and stains. The detection results are not only used for immediate pass / fail classification, but also completely archive data such as image features and defect coordinates into a local database, providing valuable first-hand data support for subsequent process optimization, quality traceability, and big data analysis. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1This is a schematic diagram of the structure of the present invention;

[0024] Figure 2 This is a schematic diagram of the internal structure of the mobile chassis of the present invention;

[0025] Figure 3 This is a schematic diagram of the structure of the robotic arm of the present invention;

[0026] Figure 4 This is a schematic diagram of the structure of the four-claw clamping assembly of the present invention;

[0027] Figure 5 This is a schematic diagram of the calibration process for the accuracy calibration of this invention;

[0028] Figure 6 This is a schematic diagram of the process for preliminary defect detection of workpieces according to the present invention.

[0029] In the diagram: 1. Mobile chassis; 11. Precision calibration reference block; 2. Controller; 3. Robotic arm; 4. Transportation module; 5. Positioning module; 6. Four-jaw gripper assembly; 61. Cylindrical base; 62. Sliding cylinder; 63. Cylinder slider; 64. Linkage transmission mechanism; 65. Gripping jaw; 66. Fixed intermediate shaft; 67. Integrated force sensor; 68. Visual inspection camera. Detailed Implementation

[0030] The present application will now be described in detail with reference to the accompanying drawings and specific embodiments.

[0031] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. This application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, in the absence of conflict, the following embodiments and features in the embodiments can be combined with each other. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0032] It should be noted that various aspects of embodiments within the scope of the appended claims are described below. It will be apparent that the aspects described herein can be embodied in a wide variety of forms, and any particular structure and / or function described herein is merely illustrative. Based on this application, those skilled in the art will understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number and aspects set forth herein can be used to implement the device and / or practice the method. Additionally, this device and / or method can be implemented using structures and / or functionalities other than one or more of the aspects set forth herein.

[0033] It should also be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of this application. The drawings only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0034] Additionally, specific details are provided in the following description to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that practice can be carried out without these specific details.

[0035] The technical solutions provided by the various embodiments of this application are described below with reference to the accompanying drawings.

[0036] Please see Figure 1-4 As shown in this embodiment: an automatic loading and unloading robot for CNC machining, the automatic loading and unloading device includes a mobile chassis 1 and a controller 2. The interior of the chassis is divided into a mechanical installation area, a control area, and a power supply area by a partition. The mechanical installation area is equipped with a robotic arm 3, a transport module 4, and a positioning module 5. The control area is equipped with the controller 2 and a matching signal transmission module. The power supply area is equipped with a switching power supply to provide stable, interference-resistant power to all functional modules of the machine. The robotic arm 3 is a six-axis industrial robotic arm. The base of the robotic arm is fastened to the preset mounting surface of the mechanical installation area of ​​the mobile chassis 1 by expansion bolts. The end of the robotic arm 3 is fixed to a torque sensing module by a threaded structure. The torque sensing module uses an HBM T40B torque sensor with a range of... With an accuracy level of 0.1, it can collect the torque changes at the end of the robotic arm in real time, preventing damage to the workpiece or mechanical structure caused by torque overload during gripping operations, and forming a dual force data linkage verification with the force sensor 67 integrated with the gripper 65.

[0037] The lower end of the torque sensing module is rigidly assembled with a four-jaw clamping assembly 6 via a connecting flange. The four-jaw clamping assembly 6 consists of a cylindrical base 61, a sliding cylinder 62, a cylinder slider 63, four sets of linkage transmission mechanisms 64, four clamping jaws 65, a fixed intermediate shaft 66, an integrated force sensor 67, and a vision inspection camera 68. The four sets of linkage transmission mechanisms 64 are arranged in a cross-shaped symmetrical pattern. Each set of linkage transmission mechanisms 64 includes two connecting rods that are hinged to each other. One end of the connecting rod is hinged to a pre-set hinge hole on the side wall of the cylinder slider 63 via a pin, and the other end is hinged to the upper end of the clamping jaw 65 via a pin. The linkage transmission mechanism 64 is driven by the up-and-down sliding of the cylinder slider 63 to achieve synchronous opening and closing of the four jaws. It can be adapted to gripping round, square, and conventional irregular-shaped small and medium-sized workpieces, ensuring uniform force on the workpiece and preventing workpiece displacement and collision damage.

[0038] The fixed intermediate shaft 66 is coaxially fixed to the bottom center of the cylindrical base 61 and locked with a locking nut, and does not move with the cylinder slider 63 throughout the operation; the vision inspection camera 68 is an industrial camera with a resolution of 1920×1080, a frame rate of 155fps, and a lens focal length of 8mm; the camera is precisely mounted on the top end face of the fixed intermediate shaft 66, at the geometric center of the four gripping jaws 65, and the lens is oriented in the same direction as the workpiece gripping, ensuring that the field of view can completely cover the workpiece gripping area and the accuracy calibration reference block 11.

[0039] The integrated force sensor 67 is a miniature force sensor, which is embedded in the inner side of the clamping surface of each clamping jaw 65 and flush with the clamping surface. It does not interfere with the normal gripping of the workpiece and can collect clamping force data in real time during the clamping process and upload it to the controller 2.

[0040] The transport module 4 uses a belt conveyor and is installed on one side of the mobile chassis 1.

[0041] The mobile chassis 1 has a fixed positioning mark inside, which is located on one side of the mechanical installation area and falls within the movement range of the robotic arm 3. The positioning mark is fixed to the precision calibration reference block 11 by bolts. The precision calibration reference block 11 is made of marble and has a total of 6 preset circular marker feature points on its surface. The marker diameter is 2mm and the feature point position accuracy is ±0.005mm. The precision calibration and the preliminary defect detection of the workpiece share the same coaxial vision inspection camera 68, which eliminates the need for additional inspection equipment, simplifies the overall structure of the machine, and reduces equipment costs. The reference block coordinate system supports one-click self-learning and input on site, without the need for hard coding of fixed coordinates in the program.

[0042] Accuracy calibration method:

[0043] S1. Definition of the three coordinate systems

[0044] S11. Camera Coordinate System: The origin is the optical center of the camera lens. The horizontal direction of the image is the X-axis, and the vertical direction perpendicular to the horizontal direction is the V-axis. The unit of the coordinate system is pixels. The image center pixel coordinates are determined by pre-calibration of the camera. The coordinates are (960, 540), corresponding to the 1920×1080 resolution of the camera; S12, Robot base coordinate system: with the geometric center of the fixed mounting surface of the mobile chassis 1 as the origin, the horizontal direction is set as the X-axis, the vertical direction is set as the Z-axis, and the horizontal direction perpendicular to the X-axis is set as the Y-axis, with the coordinate system unit being mm; the origin is pre-calibrated by a laser rangefinder, and on-site self-learning calibration is supported to ensure accurate and reliable reference coordinates; S13, Tool coordinate system: with the geometric center of the four gripping claws 65, i.e., the center point of the optical axis of the vision inspection camera 68, as the origin, the axis direction is consistent with the robot base coordinate system, and the coordinate system unit is mm; the origin of the tool coordinate system can be calibrated and corrected in real time by the vision inspection camera 68.

[0045] S2, Calibration Trigger

[0046] Controller 2 automatically starts the accuracy calibration process according to preset trigger conditions. The trigger conditions are set as follows: Power-on trigger: The robot automatically performs an accuracy calibration once every time it is powered on; Periodic trigger: The timed calibration period can be customized within the range of 1 to 4 hours on the touch screen; Reset trigger: The accuracy calibration is automatically triggered after the robot experiences a mechanical failure, power failure and restart or other abnormalities and completes a reset.

[0047] After calibration is triggered, controller 2 drives robotic arm 3 to move four-jaw gripper 6 to the top of the fixed positioning of the chassis. With the assistance of positioning module 5, the lens of visual inspection camera 68 is vertically oriented towards the accuracy calibration reference block 11.

[0048] S3, Image Acquisition

[0049] The visual inspection camera 68 uses adaptive exposure and automatic white balance algorithms, which can automatically adjust imaging parameters according to the lighting environment in the workshop. The system default reference parameters are: exposure time 10ms and gain 1.0. The camera continuously acquires 3 frames of images and automatically selects the image with the best clarity and no noise interference as the calibration image to ensure that the feature points of the reference block have complete outlines and clear and identifiable edges.

[0050] S4. Coordinate Calculation and Mapping

[0051] Controller 2 preprocesses the acquired calibration images. The preprocessing steps include: noise reduction: using a 3×3 kernel Gaussian filter algorithm, and simultaneously superimposing a workshop dust-specific filter algorithm to filter out random noise and dust interference on site; grayscale conversion: using a weighted average method to convert the color image into a grayscale image to improve the accuracy of feature point extraction; edge enhancement: using the Sobel operator to enhance the edge contrast of feature points, which facilitates accurate extraction of feature contours.

[0052] After image preprocessing, the sub-pixel coordinates (u, v) of 6 preset feature points on the accuracy calibration reference block 11 in the camera coordinate system are extracted and solved using the centroid method, achieving a sub-pixel positioning accuracy of 0.1 pixels. The pixel coordinates are then converted to physical coordinates based on the camera's inherent parameters. The camera focal length f = 8 mm, the pixel size d = 3.45 μm, and the vertical distance from the feature point to the lens Zcam = 100 mm. Substituting these parameters into the conversion formula, the two-dimensional physical coordinates (Xcam, Ycam) of the feature point in the camera coordinate system are obtained, in mm.

[0053] S5, Base Coordinate System Calibration

[0054] Controller 2 calls the theoretical absolute coordinates of the accuracy calibration reference block 11 in the robot base coordinate system. The coordinate parameters support on-site self-learning input and update. The two-dimensional physical coordinates of the camera coordinate system obtained by S4 are combined with the Zcam height value to construct the three-dimensional coordinates of the feature points. Using the simultaneous equations of 6 feature points, the 3×3 rotation matrix R and the 3×1 translation vector T between the camera coordinate system and the robot base coordinate system are solved by the least squares method to complete the mapping calibration of the two coordinate systems. After calibration, the coordinate transformation error is controlled within ±0.01mm.

[0055] S6, Tool Coordinate System Calibration

[0056] Using the feature center point of the precision calibration reference block 11 as a reference, the controller 2 drives the robotic arm 3 to drive the four-jaw gripping assembly 6 to make fine adjustments in 0.005mm increments; the visual inspection camera 68 collects feature center images in real time and feeds back the position deviation until the geometric center of the four jaws is precisely aligned with the feature center point of the reference block, with an alignment error ≤0.005mm.

[0057] The controller 2 records the angles of each joint of the robotic arm 3 at this time, and calculates the coordinate offset ΔPTCP of the tool coordinate system relative to the robot base coordinate system through inverse kinematics calculation. The offset is then substituted into the offset calculation formula to complete the zero-point calibration of the tool coordinate system.

[0058] S7, Error Compensation

[0059] The controller 2 calculates the end-effector position deviation value ΔE of the robotic arm 3 and substitutes it into the position deviation calculation formula. The system has three preset compensation coefficients k of 0.8, 1.0, and 1.2 that can be adaptively selected. The optimal compensation parameters are matched according to the workshop vibration and temperature change conditions. The controller drives the joints of the robotic arm 3 to perform end-effector fine-tuning compensation, and repeatedly detects and iterates until the position deviation ΔE ≤ 0.03 mm.

[0060] Preliminary defect detection process for workpieces:

[0061] This embodiment of the preliminary defect detection process for workpieces automatically starts when the system is calibrated to be qualified and the error compensation meets the standard. It is suitable for batch processing and inspection of small and medium-sized precision hardware parts and electronic components. The specific implementation details are as follows:

[0062] S8, Detection Trigger

[0063] After the tool coordinate system calibration and error compensation meet the preset threshold, the controller 2 drives the robotic arm 3 to move the four-jaw gripper 6 to the preset shooting position of the workpiece, and the vision lens is vertically aligned with the workpiece surface to collect the initial detection image of the workpiece.

[0064] S9. Image Registration and Comparison

[0065] Controller 2 calls the calibrated mapping relationship between the camera coordinate system and the robot base coordinate system, Pbase=R×Pcam+T, to perform feature matching between the acquired real-time image of the workpiece and the pre-stored standard workpiece template image, and performs grayscale normalization processing. The standard workpiece template image is pre-acquired and stored in the local database of controller 2. Grayscale normalization adopts a linear algorithm to uniformly map the image grayscale to the range of 0 to 255, eliminating the influence of illumination differences on image comparison. Feature matching adopts the SIFT algorithm.

[0066] S10, Defect Feature Extraction

[0067] Controller 2 performs edge contour extraction and texture analysis on the registered workpiece image: the Canny operator is used to extract the workpiece outline and compare it with the standard template outline; the gray-level co-occurrence matrix algorithm is used to analyze the surface texture features of the workpiece, which can accurately identify defects such as notches, scratches, pits, surface stains and overall dimensional deviations on the workpiece surface; the system is set with a minimum physical resolution of 3.45μm for defect recognition and a defect detection repeatability of 0.03mm, which meets the requirements for precision workpiece inspection.

[0068] S11. Defect Judgment and Classification

[0069] The system has multiple built-in workpiece accuracy threshold templates. Based on different workpiece types such as hardware and electronic components, the defect judgment threshold (Sdefect, ΔPdefect) can be switched with one click on the touch screen. The defect area, perimeter, and shape and position deviation are compared with the preset qualified threshold to implement a three-level judgment of qualified parts, slightly defective parts, and scrapped parts. Qualified workpieces are directly put into the feeding process, slightly defective parts are subject to manual re-inspection, and scrapped workpieces are automatically transferred to an independent and dedicated waste area by a robotic arm to prevent unqualified workpieces from being mixed with good products.

[0070] S12, Data Archiving

[0071] The controller 2 stores locally the image features and key dimension data of qualified workpieces, as well as the defect types and base coordinates of unqualified workpieces. The system has a reserved interface for standard MES system integration, which can upload inspection data to the cloud for full-process traceability of product quality. Operators can query, export, and print inspection reports in real time via the touch screen.

[0072] Clamping force control logic:

[0073] The integrated force sensor 67 collects the clamping force value Fclamp in real time at a frequency of 100Hz and uploads it to the controller 2. In addition to the default basic clamping force range of 5-20N, the system has built-in dedicated clamping force ranges for multiple materials such as aluminum, steel, and small precision parts. The specific preset ranges are: 8-20N for steel, 5-15N for aluminum, and 3-10N for small precision parts. The parameters can be switched with one click according to the workpiece material specifications. The controller 2 compares the real-time clamping force with the preset safety range Fmin-Fmax in real time and executes closed-loop control logic.

[0074] When Fclamp < Fmin, it is determined that the workpiece is slipping, the gripping posture is off, or there is no gripping. Controller 2 immediately stops the gripping action, issues a prompt sound, and starts the automatic re-grip process, with a preset number of 3 re-grip attempts. If the 3 re-grip attempts are still unsuccessful, the system automatically fine-tunes the pallet positioning position and the robotic arm gripping posture, and tries to grab again. If the re-grip attempts still fail, a fault alarm is triggered and the machine is stopped, waiting for manual troubleshooting.

[0075] When Fclamp > Fmax (the upper limit), it is determined that foreign objects have entered the clamping surface, the clamping force is overloaded, or the actual size of the workpiece is abnormal. Controller 2 immediately stops all mechanical actions, activates the warning light, and synchronously uploads the abnormality type, occurrence time, and clamping force data to the cloud. The operation can only be restarted after the foreign objects are manually removed, the clamping parameters are adjusted, or the unqualified workpiece is replaced, and the system reset button is pressed.

[0076] Overall work process:

[0077] Upon powering on, the equipment automatically initiates precision calibration and calibration validity verification, completing the calibration of the three major coordinate systems and end-point error compensation. The equipment maintains a rigid locking state throughout operation, with no micro-displacement of the base. The operator places the workpiece-loaded pallet at the input end of transport module 4, the belt conveyor starts transporting, and positioning module 5 precisely stops the pallet at its end. Controller 2 drives robotic arm 3 to move to the workpiece imaging position, and the vision system adaptively adjusts the distance to complete workpiece image acquisition and preliminary defect classification detection. The system processes the detection results by category: qualified workpieces are gripped by the four-jaw clamping component 6 and transferred to the CNC machine tool's feed port for automatic loading; slightly defective parts are retained for manual re-inspection; scrapped workpieces are automatically sorted to a dedicated waste area. After the CNC machine tool completes workpiece processing, the robotic arm automatically grips the finished workpiece and transfers it to a pallet or designated unloading station for automatic unloading. This cyclical conveying, inspection, and loading / unloading process enables continuous automated processing of batches of small and medium-sized precision workpieces. The system automatically triggers recalibration according to a user-defined cycle, continuously ensuring long-term positioning and loading / unloading accuracy.

[0078] The same or similar parts between the various embodiments in this specification can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments.

[0079] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A robot gripping assembly for a CNC automatic loading and unloading device, the automatic loading and unloading device comprising a moving chassis (1) and a controller (2), characterized in that: The mobile chassis (1) is equipped with a robotic arm (3), a transport module (4), and a positioning module (5); the transport module (4) is used for transporting workpieces and pallets, the positioning module (5) is used for precise positioning of pallets, the robotic arm (3) is used for gripping and transferring workpieces and pallets and loading and unloading CNC machine tools, and the controller (2) is used for linkage control, signal processing, timing scheduling and accuracy compensation of each module; The end of the robotic arm (3) is fixed with a torque sensing module. The lower end of the torque sensing module is rigidly connected to a four-jaw gripping assembly (6) through a connecting flange. The four-jaw gripping assembly (6) includes a cylindrical base (61), a sliding cylinder (62), a cylinder slider (63), four sets of linkage transmission mechanisms (64), four gripping jaws (65), a fixed intermediate shaft (66), an integrated force sensor (67), and a vision inspection camera (68). The sliding cylinder (62) is coaxially mounted inside the cylindrical base (61), and the cylinder slider (63) can slide up and down along the axis of the cylindrical base (61); the four sets of linkage transmission mechanisms (64) are arranged in a cross-shaped symmetrical distribution, with one end hinged to the side wall of the cylinder slider (63) and the other end hinged to the clamping jaws (65). The cylinder slider (63) slides up and down, driving the linkage transmission mechanism (64) to move, thereby realizing the synchronous opening and closing of the four clamping jaws (65); the fixed intermediate shaft (66) is coaxially fixed to the center bottom of the cylindrical base (61). The part does not move with the cylinder slider (63) throughout the process; the visual inspection camera (68) is precisely installed on the top end face of the fixed intermediate shaft (66) and located at the geometric center of the four clamping claws (65), with the lens facing the same direction as the clamping direction; the integrated force sensor (67) is embedded in the inner side of the clamping surface of each clamping claw (65); the mobile housing (1) has a preset fixed positioning mark, and a precision calibration reference block (11) is installed at the fixed positioning mark. The precision calibration and the preliminary defect detection of the workpiece are both completed by the fixed coaxial visual inspection camera (68).

2. The robot gripping assembly for a CNC automatic loading and unloading device according to claim 1, characterized in that: The specific calibration process for the accuracy calibration is as follows: S1. Define the three coordinate systems: S2, Calibration Trigger: The controller (2) starts the accuracy calibration process according to the preset trigger conditions. The trigger conditions are power-on start, timer cycle and abnormal reset. The controller drives the robotic arm (3) to move the four-jaw gripping assembly (6) to the fixed positioning position inside the mobile chassis (1), so that the lens of the visual inspection camera (68) is vertically aligned with the accuracy calibration reference block (11). S3, Image Acquisition: The visual inspection camera (68) acquires a clear image of the precision calibration reference block (11) under preset exposure parameters to ensure that the feature points of the precision calibration reference block (11) fall completely within the field of view of the camera. S4. Coordinate calculation and mapping: The controller (2) preprocesses the acquired calibration image. The preprocessing method is noise reduction, grayscale conversion and edge enhancement. It extracts the sub-pixel coordinates of the preset feature points on the precision calibration reference block (11) based on the camera coordinate system. Then, it completes the conversion from pixel coordinates to physical coordinates through the preset camera focal length and pixel size to obtain the physical coordinates of the feature points in the camera coordinate system. Among them, the dimensions of the focal length f and the pixel size d in the camera intrinsic parameters are kept consistent. S5, Base Coordinate System Calibration: The controller (2) calls the preset theoretical absolute coordinates of the precision calibration reference block (11) in the robot base coordinate system, compares the physical coordinates of the feature point camera coordinate system obtained in S4 with the theoretical absolute coordinates, calculates the rotation matrix and translation vector between the camera coordinate system and the robot base coordinate system, and completes the mapping calibration of the two coordinate systems. S6. Tool coordinate system calibration: With the feature points of the precision calibration reference block (11) as a reference, the controller (2) drives the robotic arm (3) to drive the four-jaw gripping assembly (6) to make fine adjustments so that the geometric centers of the four gripping jaws (65) are precisely aligned with the feature center points of the precision calibration reference block (11). The geometric centers of the four gripping jaws (65) are the origin of the tool coordinate system. The joint angle data of the robotic arm (3) at this time are recorded, and the coordinate offset of the tool coordinate system relative to the robot base coordinate system is calculated to complete the zero-point calibration of the tool coordinate system. S7. Error Compensation: The controller (2) calculates the position deviation value of the end of the robotic arm (3) according to the calculation results of S5 and S6, drives the end of the robotic arm (3) to adjust the joint of the robotic arm (3) to perform fine-tuning compensation until the coordinate transformation error of the three meets the preset requirements, and completes the entire accuracy calibration process.

3. A robot gripping assembly for a CNC automatic loading and unloading device according to claim 2, characterized in that: The three coordinate systems are defined as follows: S11, the camera coordinate system is a two-dimensional reference system when the visual inspection camera (68) captures images. The origin is the optical center of the camera lens, the horizontal direction of the image is the X-axis, and the vertical direction of the image perpendicular to the horizontal direction is the V-axis; S12, the robot base coordinate system is the absolute three-dimensional reference for all robot movements. The origin is the geometric center of the fixed mounting surface of the mobile chassis (1), the horizontal direction is the X-axis, the vertical direction is the Z-axis, and the horizontal direction perpendicular to the X-axis is the Y-axis; S13, the tool coordinate system is the working center point of the robot end effector. The origin is the geometric center of the four gripping claws (65), i.e., the optical axis center point of the visual inspection camera (68), and the axis system is defined in the same direction as the robot base coordinate system.

4. A robot gripping assembly for a CNC automatic loading and unloading device according to claim 3, characterized in that: During the accuracy calibration process, coordinate calculation, offset calculation, and error compensation are all completed using preset formulas. The specific formula steps are as follows: Formula for converting pixel coordinates to physical coordinates: Where (u,v) are the sub-pixel coordinates of the feature point in the camera coordinate system. Let be the pixel coordinates of the camera imaging center, d be the camera pixel size, f be the camera focal length (with dimensions consistent with d), Zcam be the vertical distance from the feature point to the camera lens, and (Xcam, Ycam) be the two-dimensional physical coordinates of the feature point in the camera coordinate system. The mapping formula between the camera coordinate system and the robot base coordinate system is: Pbase = R × Pcam + T; where Pbase is the three-dimensional coordinate of the feature point in the robot base coordinate system, Pcam is the three-dimensional coordinate of the feature point in the camera coordinate system, the Z-axis coordinate is Zcam, R is the rotation matrix, and T is the translation vector. The two are obtained by S5 calculation. The rotation matrix R is a 3×3 matrix, and the translation vector T is a 3×1 vector. Formula for calculating tool coordinate system offset: ; where ΔPTCP is the coordinate offset of the tool coordinate system relative to the robot base coordinate system, Pbase_target is the theoretical coordinate of the feature center point of the precision calibration reference block (11) in the robot base coordinate system, and PTCP_actual is the actual coordinate of the origin of the tool coordinate system in the robot base coordinate system after fine adjustment. The formula for calculating the end position deviation of the robotic arm (3) is: ΔE = (ΔX)² + (ΔY)² + (ΔZ)²; where ΔE is the end position deviation value, and ΔX, ΔY, and ΔZ are the offset components of the origin of the tool coordinate system in the X, Y, and Z axes of the robot base coordinate system, respectively. The formula for calculating displacement compensation is: ΔS = k × ΔE; where ΔS is the joint fine-tuning compensation of the robotic arm (3), k is the compensation coefficient, which is preset to 0.9~1.1, ΔE is the position deviation value calculated by S7, and after compensation, ΔE≤ε must be satisfied, where ε is the preset accuracy threshold, and the value range is less than or equal to 0.05mm.

5. A robot gripping assembly for a CNC automatic loading and unloading device according to claim 1, characterized in that: The preliminary defect detection process for the workpiece is triggered based on the system status after accuracy calibration is completed, and specifically includes the following steps: S8, Detection trigger: After the tool coordinate system calibration is completed and the error compensation meets the preset threshold, the controller (2) drives the robotic arm (3) to move the four-jaw gripping assembly (6) to the preset shooting position of the workpiece to be gripped, so that the lens of the visual inspection camera (68) is vertically aligned with the workpiece surface and the initial image of the workpiece is collected. S9. Image registration and comparison: The controller (2) calls the calibrated camera coordinate system and robot base coordinate system mapping relationship Pbase=R×Pcam+T in S4, S5 and S6, and performs feature matching and grayscale normalization processing on the acquired initial image of the workpiece and the preset standard workpiece template image. S10, Defect feature extraction: The controller (2) performs edge contour extraction and texture analysis on the registered workpiece image to accurately identify notches, scratches, pits, stains and dimensional defects on the workpiece surface. The minimum pixel resolution for defect identification is not greater than the physical size corresponding to the camera pixel size d, and the repeatability of defect detection is not greater than 0.05mm. S11. Defect Judgment and Classification: The area Sdefect, perimeter Ldefect, and shape and position deviation ΔPdefect of the defective region are calculated and compared with the preset acceptable threshold. If Sdefect ≤ Stresold and ΔPdefect ≤ ΔPtresold, then the workpiece is deemed qualified and the controller (2) sends a grabbing execution command. If Sdefect > Stresold or ΔPdefect > ΔPtresold, it is determined to be a defective workpiece. The controller (2) immediately triggers the sorting signal and drives the robotic arm (3) to transfer the defective workpiece to the special waste area. S12. Data Archiving: The controller (2) synchronously stores the image feature data and dimension detection data of qualified workpieces, as well as the defect types and defect position coordinates of unqualified workpieces in the local database.

6. A robot gripping assembly for a CNC automatic loading and unloading device according to claim 5, characterized in that: The integrated force sensor (67) collects and feeds back the clamping force value Fclamp in real time during the closing process of the four-jaw clamping assembly (6) clamping the workpiece. The controller (2) compares the real-time collected Fclamp with the preset safe clamping force range. Real-time comparison is performed, and the following control logic is executed accordingly: If Fclamp < Fmin, it is determined that the workpiece has clamping slippage, grasping posture deviation, or the workpiece is not grasped. The controller (2) immediately stops the clamping action, triggers the re-grasping process, drives the robotic arm (3) to reset the four-jaw clamping component (6), and then performs the grasping operation again. If Fclamp > Fmax, it is determined that foreign objects are夹入 (should be "夹入异物" translated as "foreign objects are clamped into") the workpiece clamping surface, clamping overload, or workpiece size abnormality. The controller (2) immediately stops all actions and synchronously uploads this abnormal information to the cloud database. Only after manual troubleshooting of the abnormality can the system be reset and the operation be restarted. It should be noted that there is an inaccuracy in the original Chinese text "夹入异物" which was misspelled in the provided English translation. It should be "foreign objects are clamped into" instead of the incorrect "夹入".

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