A vision closed-loop based robot end position calibration method

Abstract

The application discloses a kind of mechanical arm end position calibration methods based on visual closed loop, this method first uses industrial camera to obtain the oblique projection point coordinate of the center point above mechanical arm end on target plane, estimate the vertical projection point position of industrial camera, and calculate the height of industrial camera distance target plane.Mechanical arm uses before, through the image obtained by industrial camera to obtain the position information of mechanical arm, using the vertical projection point position of industrial camera and the height of industrial camera distance target plane, calculate the zero error of mechanical arm current, carry out automatic iteration compensation adjustment to zero point.After zero compensation of mechanical arm, in the operation of mechanical arm, through the image obtained by industrial camera to obtain the position information of mechanical arm, calculate the current position error of mechanical arm, and compensate calibration to the actual position of mechanical arm end.The application effectively avoids artificial measurement error, and significantly improves the efficiency of data acquisition, improves the efficiency of mechanical arm calibration.

Description

Technical Field

[0001] This invention belongs to the fields of robot control and image processing, and in particular relates to a method for end-effector calibration of a robotic arm based on visual closed-loop. Background Technology

[0002] Industrial robots widely adopt a serial architecture, possessing a structure similar to a human arm, multiple rotational degrees of freedom, each with a large range of motion, and a compact structure. Because robots can be programmed offline or taught online, the manufacturing industry's move towards intelligent and digital transformation gives robots a broad future of applications. The combination of robots with the aforementioned technologies provides more solutions for industrial production, freeing workers from repetitive and arduous labor.

[0003] Industrial robots are key equipment in industrial automation and intelligentization. With the rapid development of technologies such as computers, robot control, and artificial intelligence, diverse intelligent robots are constantly emerging and being applied in various industries. In practical applications, robots are developing towards higher precision, higher stability, and higher flexibility. Domestic and international researchers have conducted extensive research on maintaining the precision and performance of industrial robots, mainly focusing on compensation methods and calibration techniques.

[0004] During use, industrial robots experience continuous changes in the tightness of their components and parameters due to wear and tear over time. This positional deviation can cause losses in industrial production. In a production environment, the typical solution is to replace or repair parts, which incurs significant time and labor costs and does not meet future production requirements.

[0005] Currently, most methods to solve the above problems involve constructing an error model to compensate for errors in industrial robots and then recalibrating them. However, due to the many uncontrollable factors in the industrial production environment, such as temperature changes, vibration, and mechanical wear, these factors can affect the accuracy and stability of the compensation model, making it difficult to maintain the compensation effect in the long term and resulting in poor real-time performance. Therefore, calibration methods based on model parameters for error compensation need further improvement in terms of practicality. Summary of the Invention

[0006] In view of the shortcomings of the prior art described above, the present invention provides a method for calibrating the end-effector position of a robotic arm based on a vision closed loop. This method combines industrial camera vision inspection, zero-point compensation of the robotic arm body, and real-time compensation of the end-effector position to form a vision closed loop feedback control, thereby achieving the purpose of end-effector position calibration. This solves the problem of inaccurate end-effector position on the target plane in the robotic arm's motion space during long-term use due to factors such as aging, wear, and environmental changes, while also taking into account real-time performance and stability.

[0007] This method includes the following steps:

[0008] S1. Use an industrial camera to obtain the coordinates of the oblique projection point of the center point above the end of the robotic arm onto the target plane, estimate the position of the vertical projection point of the industrial camera, and calculate the height of the industrial camera from the target plane.

[0009] S2. Before using the robotic arm, the position information of the robotic arm is obtained through images acquired by an industrial camera. The current zero-point error of the robotic arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the zero point is automatically iteratively compensated and adjusted.

[0010] S3. During the operation of the robotic arm, based on the completion of the zero-point compensation of the robotic arm, the position information of the robotic arm is obtained through the image acquired by the industrial camera based on the visual closed loop. The current position error of the robotic arm is calculated by using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the actual position of the end of the robotic arm is compensated and calibrated.

[0011] Further, the specific implementation of obtaining the coordinates of the oblique projection point of the upper center point of the robotic arm end on the target plane in step S1 is as follows: The coordinates of the vertical projection point of the industrial camera on the target plane and its height from the target plane are calculated. First, the industrial camera is calibrated using the Zhang Zhengyou calibration method to obtain the camera's intrinsic parameter matrix mtx. Distortion correction is then performed on the images acquired by the industrial camera.

[0012] The robotic arm is sequentially moved above five preset reference points on the target plane, with the center point of the lower part of the robotic arm's end cap precisely aligned with each reference point. Once the robotic arm is stable above the reference points, a distortion-corrected image is acquired using an industrial camera. The coordinates of the oblique projection point A of the center point above the robotic arm's end cap onto the target plane are then identified.

[0013] Furthermore, the estimation of the vertical projection point position of the industrial camera and the calculation of the height of the industrial camera from the target plane in step S1 are specifically as follows: the target plane is xoy, triangle FAC is perpendicular to plane xoy, line segment ED lies on triangle FAC, and together with point A, forms triangle EAD. The length of line segment ED is the distance from the upper vertex E of the robotic arm's end effector to plane xoy. Point A is the oblique projection of the center point E above the end of the robotic arm in the view of industrial camera F onto the target plane xoy; point B is on the plane xoy, and point C is the perpendicular projection of industrial camera F onto the plane xoy, where line AB is parallel to the x-axis, line segment BC is parallel to the y-axis, and line segment AB is perpendicular to line segment BC; angle The angle formed by the intersection of line segment AF and line segment AC; angle Let G be the angle formed by line segment AC and line segment AB. Point G lies on line segment AB, and line segment DG is parallel to line segment CB. Let be the distance between point A and point D in the x-direction on the plane xoy. Let be the distance between point A and point D in the y-direction on the plane xoy. The distance from the industrial camera F to the plane xoy is... .

[0014] Using the similarity between triangles EAD and FAC, and combining the coordinates of the oblique projection point A, the coordinates of the center point D below the end effector of the robotic arm are calculated. A straight line is constructed between each reference point and its corresponding oblique projection point, resulting in a total of five straight lines. Due to actual errors, these five lines will not intersect at the same point. The least squares method is used to obtain the optimal estimate of the vertical projection point C of the industrial camera F on the xoy plane. The least squares method is used as shown in Equation 1: On the plane xoy, find the target point C such that it intersects with all points... The sum of squared distances is minimized:

[0015]

[0016] Based on the known coordinates of points A, C, and D, the height of the robotic arm's end effector... And since triangle EAD and triangle FAC are similar, the length of line segment AC is... The length of line segment AD is ,but Calculated using the following formula 2:

[0017]

[0018] Furthermore, in step S2, before using the robotic arm, the vertical projection point position C of the industrial camera and the height of the industrial camera from the target plane are used. It calculates the current zero-point error of the robotic arm and performs automatic iterative compensation and adjustment of the zero point.

[0019] Further, step S2 specifically involves: controlling the robotic arm to move to the reference point position coordinate P on the target plane, and calculating the coordinates of the center point D below the end effector of the robotic arm. The center point coordinate D below the end effector is subtracted from the reference point position coordinate P. In this state, the end effector of the robotic arm is... , The positioning error in the direction is .

[0020] The positioning accuracy error of the robotic arm in the x and y directions is represented by the Jacobian matrix. Related to the joint angles of the robotic arm, the robotic arm has three rotary joints with parallel axes for positioning and orientation in the x and y directions within the target plane. The other joint is a translating joint, used to complete the movement of the end effector perpendicular to the plane. The position of the wrist reference point is determined by the angles of the two rotary joints. and Confirmed. Its kinematic equations are shown in Formula 3 below:

[0021] Differentiating both sides of the equation with respect to time t, we obtain the relationship between the operating speed and the joint speed as shown in Equation 4 below:

[0022]

[0023] In the above equation, the first matrix on the right-hand side is the Jacobian matrix, i.e.:

[0024]

[0025] That is to say ,in, This is the operating velocity vector at the end of the robotic arm; Represents the joint velocity vector To operating speed A linear mapping.

[0026] Zero-point compensation for the joint angles of the robotic arm. As shown in Equation 6 below:

[0027]

[0028] Control the robotic arm to move to the zero point position on the target plane. If it is within the allowable error range, complete the zero point compensation; otherwise, continue with the zero point compensation.

[0029] Further, the specific implementation process of step S3 is as follows: based on the completion of zero-point compensation of the robotic arm, during the operation of the robotic arm, the position information of the robotic arm is obtained through the image acquired by the industrial camera, the current position error of the robotic arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the actual position of the end effector of the robotic arm is compensated and calibrated, as follows:

[0030] Further, following the steps described above: obtain the coordinates of the center point D below the end effector of the robotic arm. When the robotic arm's end effector moves to a certain point, the expected target position it will reach is P: To obtain the end effector of the robotic arm based on vision closure, a specific length needs to be calibrated, that is, the pixel length that needs to be corrected in the x-direction is... The pixel length that needs to be corrected in terms of direction is Let the actual length corresponding to a unit pixel be... Then the end of the robotic arm is at The actual length of the direction that needs to be corrected The actual length of the direction that needs to be corrected As shown in Equation 7 below:

[0031]

[0032] The positioning error value is fed back to the control system to compensate and calibrate the position of the robotic arm end in real time, thus completing the actual position compensation and calibration of the robotic arm end.

[0033] Compared with the prior art, the beneficial effects of the present invention are: using an industrial camera to obtain the coordinates of the oblique projection point of the center point above the end effector of the robotic arm on the target plane, and estimating the position of the vertical projection point of the industrial camera using the least squares method.

[0034] 1. This invention proposes a method combining image recognition and least squares to determine the position of the vertical projection point of an industrial camera on a target plane, and based on this, to determine the height of the industrial camera from the target plane. This method effectively avoids errors from manual measurement and significantly improves the efficiency of data acquisition.

[0035] 2. This invention proposes a method combining image recognition and Jacobian matrix to achieve visual closed-loop and perform automated iterative zero-point compensation for the robotic arm. Before use, the positioning accuracy error in the x and y directions of the robotic arm is correlated with the joint angles of the robotic arm using the Jacobian matrix, enabling automated zero-point compensation of the joint angles. This method achieves automated operation and significantly improves the efficiency of robotic arm calibration.

[0036] 3. This invention proposes a method for feeding back the actual position of a robotic arm's end effector through image recognition, achieving visual closed-loop control and compensating for and calibrating the actual position of the end effector. After the robotic arm moves to any target position above the target plane, the actual position of the end effector is fed back through image recognition, and the positioning error is fed back to the control system for real-time compensation and calibration of the end effector position. This method, combined with image recognition, has high real-time performance and accuracy. Attached Figure Description

[0037] Figure 1 This is a flowchart of the robotic arm end-effector position calibration method based on visual closed loop proposed in this invention;

[0038] Figure 2 This is a schematic diagram of the similar spatial geometry representation of the relationship between the robotic arm and the target plane in this invention;

[0039] Figure 3 This is a schematic diagram of the reference point for selecting the image target space according to the present invention;

[0040] Figure 4 This is a schematic diagram of the vertical projection points of the industrial camera on the target plane at the intersection points of multiple sets of intersecting lines according to the present invention;

[0041] Figure 5 This is a top-view planar model of the SCARA robotic arm of the present invention;

[0042] Figure 6 This is a bar chart showing the error between the actual position and the target position of the robotic arm end before and after correction according to the present invention. Detailed Implementation

[0043] The purpose of this invention is to address the shortcomings of existing technologies by providing a method for calibrating the end effector position of a robotic arm based on vision-closed loop, such as... Figure 1 As shown, it includes the following steps:

[0044] S1. First, calibrate the industrial camera to remove image distortion. Use the industrial camera to obtain the coordinates of the oblique projection point of the center point above the end of the robotic arm on the target plane. Estimate the position of the vertical projection point of the industrial camera using the least squares method, and calculate the height of the industrial camera from the target plane based on the principle of similar triangles.

[0045] S2. Before using the robotic arm, the position information of the robotic arm is obtained through images acquired by an industrial camera. The current zero-point error of the robotic arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the zero point is automatically iteratively compensated and adjusted.

[0046] S3. During the operation of the robotic arm, based on the completion of the zero-point compensation of the robotic arm, the position information of the robotic arm is obtained through the image acquired by the industrial camera. The current position error of the robotic arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the actual position of the end of the robotic arm is compensated and calibrated.

[0047] The present invention will be further described in detail below with reference to the embodiments. The following embodiments are explanations of the present invention, and the present invention is not limited to the following examples.

[0048] Example 1:

[0049] A visual closed-loop calibration method for a Go-playing robot is proposed. The center point of the upper part of the robotic arm is calculated using the blue feature region at the top of the robotic arm's end effector, hereinafter referred to as the blue feature region. The top view of the robotic arm is shown below. Figure 5 As shown, it includes the following steps:

[0050] First, the industrial camera of the Go-playing robot is calibrated to obtain distortion-free images.

[0051] Twenty images containing complete checkerboard patterns were collected. The checkerboard patterns in each image have different angles, orientations, and positions. The intrinsic parameter matrix mtx and lens distortion coefficient dist of the calibrated camera were calculated to complete the distortion correction of the camera images.

[0052] The specific process is as follows:

[0053] 1. Collect 20 images containing a complete checkerboard pattern. Each image should have a different angle, orientation, and position. Ideally, the checkerboard pattern in all images should cover the entire field of view of the camera.

[0054] 2. After acquiring the chessboard images, use the cv2.findChessboardCorners function from the OpenCV image processing library to identify the corner points in the image set and extract the corner point information.

[0055] 3. Perform camera calibration to obtain the camera's intrinsic parameter matrix and distortion coefficients, as shown in Equations 1 and 2 below:

[0056] Intrinsic parameter matrix:

[0057]

[0058] Lens distortion coefficient:

[0059]

[0060] For each original image (img) obtained, the function cv2.getOptimalNewCameraMatrix is ​​used to obtain the free scale parameter new_cameramtx. Finally, the distortion-corrected image new_img is obtained through the function cv2.undistort.

[0061] Second, using the chessboard as the target plane, determine the coordinates of the vertical projection point C of the industrial camera onto the target plane. The distance from the industrial camera to the target plane is .

[0062] like Figure 2 As shown, Figure 2 This is a schematic diagram of the similarity space geometric representation of the relationship between the Go-playing robot and its workspace. An industrial camera F acquires images, and the Go board region is extracted from these images. Let the coordinates of the top-left grid point be (0,0), with the positive x-axis pointing to the right and the positive y-axis pointing downwards. One grid point represents 1 unit of length. In the 19×19 grid of the Go board, nine "stars" occupy nine positions: top, bottom, left, right, top-left, bottom-left, top-right, bottom-right, and center. This divides the Go board into nine regions. (3,3), For example, (9,3), and so on.

[0063] Select a reference point and move the robotic arm to the reference point position on the target plane. The coordinates of the center point D below the end effector of the robotic arm are: The host computer identifies the coordinates of the oblique projection point A on the target plane of the center point of the blue feature area above the end effector of the robotic arm using the acquired image: :

[0064] A straight line is constructed by drawing a line from the center point D below the end effector of the robotic arm and the oblique projection point A of the end effector. The vertical projection point of the industrial camera on the target plane falls on this straight line. Five star positions—upper left, upper right, lower left, lower right, and center—are selected as reference points. Figure 3 As shown, a straight line is constructed for each reference point, resulting in a total of 5 straight lines. The coordinates of the intersection points of any two straight lines are then used to obtain the optimal estimated coordinates of the camera's vertical projection point C on the target plane using the least squares method. like Figure 4 As shown, the coordinates are (476.42, 128.51).

[0065] Based on the known height of the robotic arm's end effector If triangle EAD and triangle FAC are similar, then the distance from the industrial camera to the target plane is... The height is calculated as shown in Equation 3 below. It is 521.2mm:

[0066]

[0067] Third, before using the Go-playing robot arm, the position information of the robot arm is obtained through images acquired by an industrial camera. The current zero point of the robot arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane. , The positioning error in the direction is automatically compensated and adjusted by the zero point through automatic iteration.

[0068] Determine as Figure 3 Five reference points are used to control the robotic arm to move to reference point P on the target plane: For each reference point location, the coordinates of the oblique projection point A on the target plane of the center point of the blue feature region are identified using the image acquired by the industrial camera: Using the similarity between triangle EAD and triangle FAC, the coordinates of the center point D below the end effector of the robotic arm are calculated: Subtracting the coordinates of point D from the coordinates of reference point P, we can determine the positioning error of the robotic arm's end effector in the x and y directions under this condition. The corresponding joint angle is .

[0069] Based on the above description and known quantities, it can be calculated using the following formula:

[0070] First, the length of line segment AC can be obtained using the coordinates of the vertical projection point C and the oblique projection point A of the industrial camera. :

[0071]

[0072] Given the coordinates of the vertical projection point C and the oblique projection point A, the line segment relationship between triangle ACB in the plane xoy can be obtained. horn:

[0073]

[0074] By using the line segments and angle relationships in triangle AFC, we can obtain Tangent of the angle:

[0075]

[0076] In right triangle AED, because Given the tangent of the angle and ED, the length of AD can be obtained:

[0077]

[0078] Finally, in right triangle ADG, since the length of AD is known, Given the angle, the pixel difference between D and A in the x and y directions can be calculated using formulas (8) and (8). and Value:

[0079]

[0080]

[0081] In this similar spatial geometric representation, the relationship between the coordinates of the center point D below the end effector of the robotic arm and the coordinates of the oblique projection point A is shown in Equation 10 below:

[0082]

[0083] Subtract the coordinates of the center point below the end from the coordinates of the reference point, and let the actual length corresponding to each unit pixel be... In this state, the end effector of the robotic arm is... , Positioning error in direction As shown in Equation 11 below:

[0084]

[0085] The positioning error in the x and y directions of the robotic arm is represented by the Jacobian matrix. Associated with the joint angles of the robotic arm, Substituting the value into Formula 6 above, zero-point compensation is performed on the joint angle of the robotic arm. .

[0086] To make the compensation results more accurate, select as follows Figure 3 5 points , , , , Based on the known data: length of the first joint 399mm, second joint length 310mm. Five sets of compensation angles were obtained. The zero-point compensation values ​​corresponding to the five positions were superimposed. The specific values ​​are shown in Table 1 below:

[0087] Table 1. Parameters and values ​​related to zero-point compensation of the robotic arm

[0088]

[0089] From the data in the table above , The values ​​are summed to obtain the final zero-point compensation values: joint 1 compensation -0.1875°, joint 2 compensation 0.2179°.

[0090] Finally, control the robotic arm to move to the zero point position on the target plane. If it is within the allowable error range, the zero point compensation is completed; otherwise, continue with error compensation. Finally, control the robotic arm to move to the zero point with an error of 0.50mm. For a Go-playing robot, an error within 1mm is acceptable, so there is no need to perform the above steps again.

[0091] Fourth, during the operation of the Go-playing robot's robotic arm, the position information of the robotic arm is obtained through images acquired by an industrial camera. The current position error of the robotic arm is calculated using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the actual position of the robotic arm's end is compensated and calibrated.

[0092] The robotic arm moves to any target position P on the target plane. Let the actual length corresponding to a unit pixel be... Then the end of the robotic arm is at Actual length requiring correction The actual length of the direction that needs to be corrected As shown in Equation 12 below:

[0093] Positioning error value The feedback is directly sent to the control system to compensate and calibrate the position of the robotic arm's end effector in real time. and Before correction, the target position at the end of the robotic arm was... and The length of the offset in the direction, and After correction, the target position at the end of the robotic arm is at... and The length of the offset in the direction, down Figure 6 The figure shows the error between the actual position and the target position of the robotic arm end effector before and after correction at the nine selected reference points. As can be seen from the figure, the pose error after calibration is basically kept within 1mm, indicating that this method has good calibration capability.

[0094] The visual closed-loop end-effector calibration method identifies the blue feature area above the end of the robotic arm to provide feedback on the actual position of the end of the robotic arm, compares it with the target position to obtain the difference, and finally calibrates the position of the end of the robotic arm.

[0095] In this process, a similar spatial geometric representation was proposed, the position of the vertical projection point of the industrial camera was determined by the least squares method, the height of the industrial camera from the target plane was calculated based on the principle of similar triangles, visual feedback was provided, and finally this method was applied to actual production.

[0096] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for calibrating the end effector position of a robotic arm based on vision-loop closed-loop control, characterized in that, Includes the following steps: S1. Use an industrial camera to obtain the coordinates of the oblique projection point of the center point above the end effector of the robotic arm onto the target plane, estimate the position of the vertical projection point of the industrial camera, and calculate the height of the industrial camera from the target plane. The specific process is as follows: The target plane is xoy. Triangle FAC is perpendicular to plane xoy. Line segment ED lies on triangle FAC and forms triangle EAD with point A. The length of line segment ED is the distance from the upper vertex E of the robotic arm's end effector to plane xoy. Point A is the oblique projection of the center point E above the end of the robotic arm in the view of industrial camera F onto the target plane xoy; point B is on the plane xoy, and point C is the perpendicular projection of industrial camera F onto the plane xoy, where line AB is parallel to the x-axis, line segment BC is parallel to the y-axis, and line segment AB is perpendicular to line segment BC; angle The angle formed by the intersection of line segment AF and line segment AC; angle Let G be the angle formed by line segment AC and line segment AB; point G is on line segment AB, and line segment DG is parallel to line segment CB. Let be the distance between point A and point D in the x-direction on the plane xoy. Let be the distance between point A and point D in the y-direction on the plane xoy; let be the distance from industrial camera F to the plane xoy. ; Using the similarity between triangles EAD and FAC, and combining the coordinates of the oblique projection point A, the coordinates of the center point D below the end effector of the robotic arm are calculated. A straight line is constructed for each reference point and its corresponding oblique projection point, for a total of five straight lines. The least squares method is used to find the target point C on the xoy plane, such that it intersects with all other points... To minimize the sum of squared distances, we obtain the optimal estimate of the vertical projection point C of the industrial camera F on the plane xoy. ; Based on the known coordinates of points A, C, and D, the height of the robotic arm's end effector... And since triangle EAD and triangle FAC are similar, the length of line segment AC is... The length of line segment AD is , obtain The value; S2. Before using the robotic arm, the position information of the robotic arm is obtained through the image acquired by the industrial camera. The current zero-point error of the robotic arm is calculated by using the vertical projection point position of the industrial camera and the height of the industrial camera from the target plane, and the zero point is automatically iteratively compensated and adjusted. S3. After zero-point compensation of the robotic arm, during the operation of the robotic arm, based on the visual closed loop, the position information of the robotic arm is obtained through images acquired by an industrial camera, the current position error of the robotic arm is calculated, and the actual position compensation and calibration of the robotic arm end effector is performed. The specific implementation process is as follows: Obtain the coordinates of the center point D below the end effector of the robotic arm. When the end effector of the robotic arm moves to a certain point, the target position that the end effector is expected to reach is P. The end effector of the robotic arm, based on a vision-closed loop, needs to be calibrated to determine its specific length. The pixel length for orientation correction is The pixel length for orientation correction is Let the actual length corresponding to a unit pixel be... Then the end of the robotic arm is at Actual length of orientation correction Actual length of orientation correction As shown below: The actual length of the correction is used to compensate and calibrate the position of the robotic arm's end effector in real time, thus completing the actual position compensation and calibration of the robotic arm's end effector.

2. The method for calibrating the end effector position of a robotic arm based on vision closed-loop as described in claim 1, characterized in that, The specific implementation process for obtaining the coordinates of the oblique projection point of the center point above the end effector of the robotic arm onto the target plane is as follows: Using Zhang Zhengyou's calibration method, the intrinsic parameter matrix of the industrial camera is obtained as mtx and the distortion coefficient is dist, and distortion correction is performed on the images acquired by the industrial camera. The robotic arm is moved sequentially above five preset reference points on the target plane. The center point at the bottom of the robotic arm's end is precisely aligned with each reference point. Once the robotic arm is stable above the reference points, the coordinates of the oblique projection point A of the center point at the top of the robotic arm's end on the target plane are identified through the distortion-corrected image.

3. The method for calibrating the end effector position of a robotic arm based on visual closed-loop as described in claim 2, characterized in that, The specific implementation process of step S2 is as follows: The robotic arm is moved to the reference point coordinate P on the target plane, and the coordinates of the center point D below the end effector are calculated. This center point D is subtracted from the reference point coordinate P. In this state, the end effector... , The positioning error in the direction is ; The positioning accuracy error of the robotic arm in the x and y directions is represented by the Jacobian matrix. Related to the joint angles of the robotic arm, the robotic arm has three rotary joints with parallel axes for positioning and orientation in the x and y directions within the target plane. The other joint is a translating joint, used to complete the movement of the end effector perpendicular to the plane. The position of the wrist reference point is determined by the angles of the two rotary joints. and Determined; its kinematic equations are as follows: Differentiating both sides of the equation with respect to time t, the relationship between the operating speed and the joint speed is as follows: In the above equation, the first matrix on the right-hand side is the Jacobian matrix, i.e.: Zero-point compensation for the joint angles of the robotic arm. As shown below: Control the robotic arm to move to the zero point position on the target plane. If it is within the allowable error range, complete the zero point compensation; otherwise, continue with the zero point compensation.

Images