A fast calibration method for coordinate transformation between an industrial robot base coordinate system and a TCP point coordinate

Abstract

The application provides a kind of fast calibration method of industrial robot base coordinate system and TCP point coordinate conversion relationship, the application is to solve the problem of prior art depending on expensive equipment or tool itself geometric shape, proposes a two-stage cascade calibration framework.First stage, using a coordinate known fixed reference point and physical contact method, the fixed conversion relationship of tool coordinate system and flange coordinate system is solved;Second stage, only need to hold camera to shoot feature point on tool and TCP with arbitrary multi-pose, through multi-view three-dimensional reconstruction, non-contact calculates the coordinate of TCP under tool coordinate system.Finally, combined with real-time flange pose, completes the high-precision calibration of TCP under base coordinate system.The application is extremely low in cost, simple in operation, high in precision, and can be used for any shape end effector.

Description

Technical Field

[0001] This invention relates to the field of industrial field measurement technology, specifically to a rapid calibration method for the transformation relationship between the industrial robot base coordinate system and TCP point coordinates. Background Technology

[0002] This invention relates to the field of industrial robot calibration and measurement technology, and in particular to a calibration method for the pose transformation relationship between the base coordinate system of an industrial robot and the tool center point.

[0003] When industrial robots perform tasks such as welding, handling, assembly, and gluing, they need to accurately know the position and orientation of the end effector's working reference point relative to the robot's base coordinate system (TCP). The TCP is typically fixed to the robot's base and serves as the robot's absolute reference system. The tool's center point is a spatial point defined on the working part of the end effector, representing the tool's operational position in the task space. Only when the transformation relationship between the base coordinate system and the TCP is accurately calibrated can the robot's motion control program perform path planning and precise operation based on the TCP.

[0004] In existing technologies, the mainstream methods for TCP calibration are the four-point method and the six-point method. The basic operation of these methods is as follows: a fixed reference point is set within the robot's workspace; the operator controls the robot via a teach pendant, causing the TCP to contact the reference point from four or six different postures; by recording the robot's joint angles or flange poses in each posture, a pose constraint equation is established, and then the coordinates of the TCP in the end flange coordinate system are solved. The calibration accuracy of this method depends on the operator's accurate judgment of the state of "TCP precisely contacting the reference point," as well as the uniformity and sufficiency of multiple posture adjustments.

[0005] However, the above methods have the following shortcomings in practical applications: First, they are complex and time-consuming—each calibration requires the operator to repeatedly fine-tune the robot's posture to align the TCP with the reference point, and a single calibration usually takes more than 15 minutes, requiring high operator skills; second, the direct contact calibration method is not friendly to small or fragile TCPs, and repeated contact may lead to wear or deformation; third, if high-precision external measuring equipment such as laser trackers is used to replace contact calibration, although the accuracy can be improved, the equipment cost is high, and the on-site deployment is complex, making it difficult to adapt to scenarios with frequent tool changes or rapid production line switching. Therefore, a new calibration method that balances calibration accuracy, operational efficiency, and deployment cost is needed. Summary of the Invention

[0006] This invention provides a rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points based on multi-coordinate system step-by-step transformation and visual measurement. It breaks down the traditional "one-step" contact calibration into a tool calibration stage and a TCP visual positioning stage, and connects the two through a coordinate system transformation chain to finally solve the coordinates of the TCP in the robot base coordinate system, thus completing the calibration.

[0007] In some embodiments, the present invention provides a rapid calibration method for the transformation relationship between the industrial robot base coordinate system and TCP point coordinates, comprising the following steps: Step S1. Place multiple feature points on the robot's tool to establish a tool coordinate system, where the coordinates of all feature points in the tool coordinate system are known.

[0008] Step S2. Using a fixed reference point with known coordinates and robot pose transformation, obtain the coordinates of each feature point on the tool in the robot flange coordinate system. Then, combine the known coordinates of the feature points in the tool coordinate system to calculate a fixed first transformation relationship from the tool coordinate system to the flange coordinate system.

[0009] Step S3. During the robot's movement, the second transformation relationship between the flange coordinate system and the robot base coordinate system is obtained in real time through the robot controller; combined with the first transformation relationship, the third transformation relationship between the tool coordinate system and the robot base coordinate system can be calculated in real time.

[0010] Step S4. Set an additional feature point on the tool center point (TCP) of the tool; use a camera to capture images containing the feature point on the tool and the additional feature point on the TCP in at least two different poses; based on the multi-view image sequence, calculate the coordinates of the additional feature point in the tool coordinate system using a visual 3D reconstruction algorithm.

[0011] Step S5. Based on the coordinates of the TCP in the tool coordinate system and the real-time third transformation relationship, calculate the real-time coordinates of the TCP point in the robot base coordinate system, thereby completing the calibration.

[0012] Furthermore, one specific implementation of step S2 is as follows: Step S2.1. Set a fixed reference point in the robot's workspace and obtain the known coordinates of the fixed reference point in the robot's base coordinate system.

[0013] Step S2.2. Control the robot to change its pose so that a feature point on the tool is physically contacted with the fixed reference point. Record the fourth transformation relationship of the robot's flange coordinate system relative to the base coordinate system at this time. Based on the known coordinates of the fixed reference point and the fourth transformation relationship, calculate the coordinates of the feature point in the flange coordinate system.

[0014] Step S2.3. Repeat step S2.2 for all feature points on the tool to obtain the coordinate set of all feature points in the flange coordinate system.

[0015] Step S2.4. Using the known coordinates of all feature points in the tool coordinate system and the calculated coordinates in the flange coordinate system, the first transformation relationship from the tool coordinate system to the flange coordinate system is solved by the point set registration algorithm.

[0016] Furthermore, one specific implementation of step S4 is as follows: Step S4.1. Establish a camera coordinate system based on the pose of the camera when it takes the first image.

[0017] Step S4.2. Based on the images of at least two different poses, calculate the pose of each shooting pose relative to the camera coordinate system using an algorithm based on Structure for Motion Restoration (SfM) or a Simultaneous Localization and Mapping (SLAM) algorithm; and calculate the three-dimensional coordinates of the feature points on the tool and the additional feature points on the TCP in the camera coordinate system using the principle of triangulation.

[0018] Step S4.3. Using the three-dimensional coordinates of the feature points on the tool in the camera coordinate system and their known three-dimensional coordinates in the tool coordinate system, the fifth transformation relationship from the tool coordinate system to the camera coordinate system is solved by a point set registration algorithm.

[0019] Step S4.4. Using the three-dimensional coordinates of the additional feature points on the TCP in the camera coordinate system and the fifth transformation relationship, calculate the coordinates of the TCP point in the tool coordinate system.

[0020] In some embodiments, the feature points on the tool or the additional feature points on the TCP are reflective coded points. In this case, by identifying the coded ring around the center of the reflective coded point in the image, unique coded information is assigned to each feature point to achieve unique feature point identification.

[0021] In some embodiments, the feature points are reflective non-coded points. In this case, the uniqueness of each feature point is determined by measuring the relative distance between the reflective non-coded points and performing an optimal match with the point spacing in the preset theoretical layout when the feature points are laid out.

[0022] In some embodiments, reflective coded points and reflective non-coded points are combined and deployed. In this case, the acquired image is subjected to an affine transformation using the identified reflective coded points, and the uniqueness of all feature points is determined by the relative positions of the non-coded points after the transformation.

[0023] In some embodiments, the point set registration algorithm in step S2.4 or S4.3 is the singular value decomposition (SVD) method.

[0024] In some embodiments, the triangulation principle in step S4.2 is the triangulation method in multi-view stereo vision.

[0025] The present invention also provides a vision-based robot tool center point calibration system, the system comprising: The feature point module is used to place feature points on the robot tool and TCP points, and to establish the tool coordinate system.

[0026] The fixed reference point module is used to provide a fixed spatial reference point with known coordinates to assist in solving the first transformation relationship.

[0027] An image acquisition module is used to capture images containing the feature points in multiple poses.

[0028] The data processing and calculation module is used to execute the calculation steps in any of the above methods and output the final TCP calibration result.

[0029] In some embodiments, the image acquisition module is a handheld high-resolution camera.

[0030] In some embodiments, the tool coordinate system is established in step S1 by selecting three non-collinear first feature points, taking the first point as the origin, the direction from the first point to the second point as the X-axis, the normal vector of the plane determined by the three points as the Z-axis, and the cross product direction of the X-axis and Z-axis as the Y-axis.

[0031] In some embodiments, the tool is a welding torch, a pneumatic gripper, or an adhesive applicator. Compared with the prior art, the present invention has the following beneficial effects: The calibration process is simplified, and efficiency is significantly improved. This invention completely liberates the TCP from cumbersome contact-based alignment operations. The TCP only needs to be captured by the vision system without touching any reference points. The contact operation is transferred to easily observable and locating feature points on the tool, greatly reducing the difficulty of alignment. The entire calibration process can be completed within 10 minutes, which is more than 50% more efficient than traditional methods.

[0032] The calibration accuracy is reliable. The 3D coordinates of feature points are reconstructed using multi-view stereo vision, and global optimization is performed using redundant information from multiple images, effectively suppressing single-view observation noise. When solving for the rigid transformation between coordinate systems, least-squares fitting is used, utilizing multiple known spatial points to average out local measurement errors, ensuring that the overall translation error can be stably controlled within 1mm, meeting the requirements of high-precision operations.

[0033] The equipment is low-cost and easy to deploy. This invention requires only a standard industrial camera, several feature points, and a fixed reference point for calibration, eliminating the need for expensive laser trackers or specialized calibration fixtures. The camera can be used handheld for flexible shooting, without the need for a precision gimbal or guide rail, making on-site deployment extremely convenient, especially suitable for rapid production line changeovers and mobile robot systems.

[0034] It boasts high versatility and adaptability to various tools and robots. The calibration process does not rely on a specific robot kinematic model, requiring only the reading of standard flange pose information; the feature point layout can be flexibly designed according to the geometry of different end effectors, requiring only that the coordinates of the feature points in the tool coordinate system be known. Therefore, it can seamlessly adapt to various brands and models of industrial robots and various end effectors, demonstrating extremely high adaptability and engineering promotion value in multi-variety, small-batch production. Attached Figure Description

[0035] Figure 1 This is a flowchart of the present invention. Figure 2 This is a schematic diagram of the structure of the present invention.

[0036] Reference numerals: 1. Robot base coordinate system; 2. Tool coordinate system; 3. TCP point; 4. Robot; 5. Simplified tool; 6. Feature point on the tool. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings, but the embodiments of the present invention are not limited thereto.

[0038] See Figure 1 One embodiment of the present invention provides a method for calibrating TCP points of a robot, the overall process of which is as follows: Step S1: On the rigid body of the robot tool, attach or fix multiple feature points, and establish the tool coordinate system by selecting specific points.

[0039] Step S2: Using a fixed reference point with known coordinates within the robot's workspace, calculate the coordinates of all feature points on the tool in the flange coordinate system, and then solve for the fixed transformation relationship from the tool coordinate system to the flange coordinate system. .

[0040] Step S3: Combining the flange-base coordinate system transformation that can be obtained in real time by the robot controller, calculate the transformation from the tool coordinate system to the base coordinate system in real time. .

[0041] Step S4: Add a feature point at the TCP position of the tool, and use a handheld camera to capture images of the tool and the TCP feature point from multiple perspectives. Solve for the coordinates of the TCP feature point in the tool coordinate system through visual 3D reconstruction.

[0042] Step S5: Utilize the coordinates of the TCP point in the tool coordinate system and the transformation relationship between the tool coordinate system and the robot base coordinate system. The coordinates of the TCP point in the robot's base coordinate system are calculated, enabling rapid calibration of the relationship between the robot's base coordinate system and the TCP point.

[0043] See Figure 2 The coordinate systems and their relationships involved in this method include: robot base coordinate system 1, tool coordinate system 2, flange coordinate system (not directly labeled in the figure, but it is the coordinate system at the flange), camera coordinate system (not labeled in the figure), and the position of TCP point 3. In the figure, 4 represents the robot, 5 represents the simplified tool, and 6 represents the feature points on the tool.

[0044] The flowchart of this embodiment is as follows: Figure 1 As shown.

[0045] Multiple feature points are placed on the robotic tool. A tool coordinate system is established using these feature points.

[0046] Specifically, the tool must have at least six feature points. These feature points can be a combination of reflective coded points, reflective non-coded points, or a combination of reflective coded points and reflective non-coded points.

[0047] Specifically, if reflective coded points are used, the uniqueness of feature points is determined through coded recognition. Subsequent image processing of the coded points analyzes the coded ring around the center point, assigning unique coded information to each feature point, ensuring its uniqueness. If reflective non-coded points are used, the uniqueness of feature points is determined through relative distance and relative positional relationships. By comparing the relative positions of the reflective non-coded points with their preset placement positions, the optimal matching point is fitted by minimizing the fitting error. If a combination of reflective coded and non-coded points is used, information about several specific points is determined through the coded points. Affine transformations are then performed on these specific points to fix the relative positions of all feature points in each image, thus ensuring the uniqueness of the feature points.

[0048] Specifically, after confirming the uniqueness of the feature points, select three points from the feature points and set them as follows: , , .by As the origin of the tool coordinate system Establish the X-axis in the direction of direction. Establish the Z-axis in the direction perpendicular to the plane, and set it as... .pass The calculated direction is used as the Y-axis to establish the tool coordinate system.

[0049] Obtain the coordinates of a fixed external reference point of the robot in the robot's base coordinate system. The robot is controlled to change its pose, aligning the feature point with the reference point so that their centers coincide. At this point, the coordinates of the feature point's center point are the same as the coordinates of the reference point. The robot's pose at this moment is recorded, i.e., the transformation relationship between the robot's base coordinate system and the end flange coordinate system. The coordinates of the feature point in the flange coordinate system are then... Repeat the above steps to obtain the coordinates of all feature points on the tool in the flange coordinate system.

[0050] By using the coordinates of feature points on the tool in both the flange coordinate system and the tool coordinate system, the transformation relationship between the flange coordinate system and the tool coordinate system can be solved. Because the relative transformation relationship between the flange coordinate system and the tool coordinate system is fixed, and the transformation relationship between the flange coordinate system and the robot base coordinate system changes after each pose change of the robot. This information can be read from the teach pendant. Through coordinate system transformation, the transformation relationship between the robot's base coordinate system and the tool coordinate system after each robot pose change can be calculated. .

[0051] A feature point is placed at the end effector position of the robot tool, with its center point coinciding with the TCP point (meaning the center point coordinates are the same as the TCP point coordinates). Multiple sets of images of the feature point on the robot tool and the feature point on the TCP are captured by a handheld camera in different poses. A camera coordinate system is established based on the camera's first pose. The correspondence between the first feature point 5 and the second feature point 8 in each image is determined through feature matching, and the three-dimensional coordinates of all feature points in the camera coordinate system are calculated using the triangulation principle. The transformation relationship between the tool coordinate system and the camera coordinate system is solved using the coordinates of the feature points on the tool in both the camera and tool coordinate systems. This utilizes the coordinates of feature points in the camera coordinate system and the transformation relationship between the camera coordinate system and the tool coordinate system on the TCP. Solve for the coordinates of the feature points on the TCP in the tool coordinate system.

[0052] Utilizing the coordinates of feature points in the tool coordinate system on the TCP and the transformation relationship between the robot base coordinate system and the tool coordinate system. The coordinates of feature points on the TCP in the robot's base coordinate system are calculated, enabling rapid calibration of the relationship between the robot's base coordinate system and TCP points.

[0053] Multiple feature points are placed on the robotic tool. These feature points can be implemented using reflective coded points, reflective non-coded points, or a combination of both. Specifically, if reflective coded points are used, their uniqueness is determined through coding identification; if reflective non-coded points are used, their uniqueness is determined by the relative distance and position between them; if a combination of reflective coded and non-coded points is used, the uniqueness of the reflective coded points is determined through coding identification. An affine transformation is performed on all the graphics using the determined reflective coded points, and the uniqueness of all feature points is determined by the relative positional relationships of all the reflective non-coded points. A tool coordinate system is established using these feature points. Specifically, three feature points are selected and set as... , , ,set up The origin of the target coordinate system is... The direction is the X-axis, and... Establish a tool coordinate system by taking the vertical direction of the plane as the Z-axis and the cross product of the X-axis and Z-axis as the Y-axis.

[0054] The robot is controlled to change its pose so that feature points on the tool align with a fixed reference point outside the robot. The coordinates of the reference point in the robot's base coordinate system are known. Let the coordinates of the reference point be... Simultaneously record the transformation relationship between the robot's base coordinate system and the robot's end flange coordinate system. At this time, the coordinates of the feature point in the robot's base coordinate system are: Then the coordinates of the feature point in the robot flange coordinate system can be obtained from Therefore, because the relative relationship between the tool and the robot's end flange is fixed, the coordinates of the feature point in the flange coordinate system are always [value missing]. After each pose change of the robot, the coordinates of the feature points on the tool in the robot's base coordinate system can be obtained. Using the coordinates of the feature points in the tool's coordinate system and the coordinates in the robot's base coordinate system, the transformation relationship between the robot's base coordinate system and the tool's coordinate system can be solved. .

[0055] Feature points are deployed on the TCP. A handheld camera is used to acquire multiple sets of image information of feature points on the tool and on the TCP from different poses. A camera coordinate system is established using the camera's first pose, and the PnP method is used to solve for the coordinates of the feature points on the tool and on the TCP in the camera coordinate system. Using the coordinates of the feature points on the tool in the tool coordinate system and the coordinates in the camera coordinate system, the transformation relationship between the tool coordinate system and the camera coordinate system is solved. This utilizes the coordinates of feature points in the camera coordinate system and the transformation relationship between the tool coordinate system and the camera coordinate system on the TCP. The coordinates of feature points on the TCP in the tool coordinate system are determined. Using the coordinates of the feature points on the TCP in the tool coordinate system and the transformation relationship between the tool coordinate system and the robot base coordinate system, the coordinates of the feature points on the TCP in the robot base coordinate system are determined, enabling rapid calibration of the relationship between the robot base coordinate system and TCP points.

[0056] Example 1: Welding torch TCP calibration This invention is implemented on the welding torch of an arc welding robot. Eight reflective coded points (ID: M1-M8) are firmly affixed around the perimeter of the welding torch body. A precision conical hole is fixed on the robot's worktable as a fixed reference point P_ref_base, and its coordinates are measured in one go using a laser tracker. A temporary TCP is coarsely calibrated using the traditional "four-point method" to accurately import each point M1-M8 into the conical hole, recording eight sets of flange poses and calculating the P_flange set. The T_tool_flange is solved using the SVD method.

[0057] At the point where the welding wire extends from the tip of the welding torch, a coded feature point T1 is installed, with its center coinciding with the tip of the welding wire. The operator holds an 18-megapixel digital SLR camera and takes photos of the welding torch and point T1 from three different positions with large spacing and wide angles. The software executes step S4 to calculate the coordinates of point T1 in the tool coordinate system.

[0058] Based on the current robot flange pose, the TCP coordinates in the base coordinate system were calculated. Comparison with the measured values ​​from the laser tracker showed a translation error of 0.7 mm. The entire calibration process (excluding preparation) took less than 2 minutes.

[0059] Example 2: Pneumatic gripper TCP calibration On a material handling robot, an irregularly shaped pneumatic gripper is calibrated. Because the gripper lacks regular cylindrical features, the D1 method (CN102087096B) cannot be used. Nine reflective, non-coded points are affixed to the gripper body, and its theoretical layout point-to-point matrix is ​​recorded.

[0060] The operation process is similar to that of Example 1. In step S2, a non-coded point matching algorithm is used to automatically identify each point. In step S4, TCP feature points are installed on the final working contact point (fingertip) of the gripper. A handheld camera is used to take pictures and perform 3D reconstruction. The results show that the present invention can successfully establish a high-precision TCP for this irregular gripper, meeting the positioning accuracy requirements (±0.5mm) for material handling and loading / unloading.

[0061] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A rapid calibration method for the transformation relationship between the base coordinate system and TCP point coordinates of an industrial robot, characterized in that, Includes the following steps: Step S1. Arrange multiple first feature points on the robot's tool to establish a tool coordinate system, wherein the coordinates of all first feature points in the tool coordinate system are known; Step S2. By using a fixed reference point whose coordinates are known in the robot base coordinate system, and by controlling the robot to change its pose so that the first feature point is sequentially attached to the fixed reference point, the coordinates of the first feature point in the robot flange coordinate system are obtained; then, combined with its known coordinates in the tool coordinate system, a fixed first transformation relationship from the tool coordinate system to the flange coordinate system is calculated. Step S3. During the robot's movement, obtain the real-time second transformation relationship between the flange coordinate system and the robot base coordinate system; and calculate the real-time third transformation relationship between the tool coordinate system and the robot base coordinate system in conjunction with the first transformation relationship. Step S4. Set a second feature point on the TCP point of the tool; use a camera to capture images containing the first feature point and the second feature point in at least two different poses; based on the multi-view images, calculate the coordinates of the second feature point in the tool coordinate system using a visual 3D reconstruction algorithm; Step S5. Based on the coordinates of the second feature point in the tool coordinate system and the real-time third transformation relationship, calculate the real-time coordinates of the TCP point in the robot base coordinate system to complete the calibration.

2. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, Step S2 specifically includes: Step S2.

1. Control the robot to change its pose so that a first feature point is physically contacted and attached to the fixed reference point, and record the fourth transformation relationship between the flange coordinate system and the base coordinate system at this time; Step S2.

2. Based on the known coordinates of the fixed reference point and the fourth transformation relationship, calculate the coordinates of the first feature point in the flange coordinate system; Step S2.

3. Repeat steps S2.1-S2.2 for all first feature points to obtain the coordinate set of all first feature points in the flange coordinate system; Step S2.

4. Using the known coordinates of all the first feature points in the tool coordinate system and the calculated coordinates in the flange coordinate system, the first transformation relationship is solved by the first point set registration algorithm.

3. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, Step S4 specifically includes: Step S4.

1. Establish a camera coordinate system based on the pose of the camera when it takes the first image; Step S4.

2. Based on the images of at least two different poses, calculate the pose of each shooting pose relative to the camera coordinate system, and calculate the three-dimensional coordinates of the first feature point and the second feature point in the camera coordinate system using the principle of triangulation. Step S4.

3. Using the three-dimensional coordinates of the first feature point in the camera coordinate system and its known three-dimensional coordinates in the tool coordinate system, the fifth transformation relationship from the tool coordinate system to the camera coordinate system is solved by the second point set registration algorithm. Step S4.

4. Using the three-dimensional coordinates of the second feature point in the camera coordinate system and the fifth transformation relationship, calculate the coordinates of the TCP point in the tool coordinate system.

4. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 2 or 3, characterized in that, The point set registration algorithm is the singular value decomposition method.

5. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The first feature point is a reflective coded point, and its uniqueness is determined by identifying its code in the image.

6. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The first feature point is a reflective non-coded point. The uniqueness of each first feature point is determined by measuring the relative distance between the reflective non-coded points and performing an optimal matching fit with a preset theoretical layout.

7. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The first feature points are arranged by combining reflective coded points and reflective non-coded points; the acquired image is subjected to affine transformation using the identified reflective coded points, and the uniqueness of all first feature points is determined by the relative positions of the non-coded points after the transformation.

8. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The method for establishing the tool coordinate system in step S1 is as follows: select three non-collinear first feature points, take the first point as the origin, take the direction from the first point to the second point as the X-axis, take the normal vector of the plane determined by the three points as the Z-axis, and take the cross product direction of the X-axis and Z-axis as the Y-axis.

9. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The camera is a handheld camera, and the at least two different postures are arbitrary postures that do not need to meet specific parallel or vertical constraints.

10. The rapid calibration method for the relationship between the industrial robot base coordinate system and TCP points according to claim 1, characterized in that, The tools mentioned are welding torches, pneumatic grippers, or glue applicators.

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