Carbon bowl positioning method and device based on key point detection and medium

Abstract

The invention discloses a carbon bowl positioning method and device based on key point detection and a medium, and the method comprises the steps: carrying out the circle fitting and key point detection of a carbon bowl depth map of a carbon block, and obtaining a fitting circle center, a circle center key point and a key groove key point position set; according to the center of the fitting circle and the center key point, calculating center coordinates of the carbon bowl; according to the angle value between the key groove key point position set and the carbon bowl circle center coordinate, the carbon bowl angle is obtained through calculation; and positioning the carbon bowls in the carbon bowl depth map according to the center coordinates of the carbon bowls and the angles of the carbon bowls. According to the carbon bowl positioning method and device based on key point detection and the medium, the center coordinates of the carbon bowl are obtained through comprehensive calculation, the angle of the carbon bowl is obtained through calculation in combination with the key point position set of the key groove, and interference of factors such as noise can be resisted; therefore, the carbon bowl is accurately positioned in a three-dimensional space by combining the center coordinate of the carbon bowl and the angle of the carbon bowl, and the problem that the carbon bowl is difficult to accurately position when the carbon block is polished can be solved.

Description

Technical Field

[0001] The invention relates to the field of industrial automation, and in particular to a carbon bowl positioning method, device and medium based on key point detection. Background Art

[0002] Carbon block grinding is an indispensable part of the carbon block production process. For carbon blocks produced by primary processing, their outer surface is usually very rough, with cracks, defects, and carbon residues. They need to be polished to make their surface smooth before they can be shipped out of the factory for sale; the positioning of the center of the carbon bowl and the polishing of the inner wall of the carbon bowl are the most critical and difficult links in the production process. Common carbon blocks usually contain 4 carbon bowls, and each carbon bowl has 6 keyways on the edge. Any two adjacent keyways are 60 degrees apart, but the keyway directions of each carbon bowl are different. At present, there are two main methods for carbon bowl positioning: one is to rely on manual search for the center of the carbon bowl and mobile polishing device to polish the inner wall of the carbon bowl; the other is to use keyway segmentation model or template matching to find the keyway of the carbon bowl, and then estimate the center of the carbon bowl and the direction of the keyway.

[0003] However, on the one hand, the method of manually finding the center of the charcoal bowl and grinding the inner wall of the charcoal bowl with a mobile grinding device is inefficient and has high labor costs. At the same time, the on-site working environment is dusty and harmful to the human body, which is not conducive to manufacturers improving their own competitiveness. On the other hand, the method of using keyway segmentation models or template matching to find the keyway position and thus estimate the angle of the charcoal bowl lacks accuracy. When the quality of the charcoal block is not high and the keyway of the charcoal bowl is not obvious, this method has a high false alarm rate and cannot meet actual production needs. Summary of the invention

[0004] The present invention provides a carbon bowl positioning method, device and medium based on key point detection, so as to solve the problem that it is difficult to accurately position the carbon bowl when the carbon block is polished.

[0005] Acquire point cloud data of the carbon block, and map the point cloud data into a carbon bowl depth map;

[0006] Performing circle fitting on the carbon bowl depth map to obtain the center of the fitting circle;

[0007] Performing key point detection on the carbon bowl depth map to obtain a center key point and a key slot key point position set;

[0008] The coordinates of the center of the charcoal bowl are calculated according to the center of the fitting circle and the key point of the center;

[0009] Calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate;

[0010] The charcoal bowl in the charcoal bowl depth map is positioned according to the charcoal bowl center coordinates and the charcoal bowl angle.

[0011] The present invention can more accurately represent the shape and outline of the carbon block in three-dimensional space by acquiring the point cloud data of the carbon block and mapping it into a depth map. The carbon bowl depth map is fitted with a circle, and an optimal circular boundary can be found by mathematical methods based on the pixel points or depth data of the edge of the carbon bowl, so as to determine the center position of the carbon bowl, effectively reducing the errors caused by factors such as irregular shape of the carbon bowl, blurred edges or noise interference, and ensuring the accuracy of the center of the fitting circle. Using key point detection technology, the center of the circle and the key groove center point in the carbon bowl depth map can be accurately identified. The coordinates of the center of the carbon bowl are calculated based on the center of the fitting circle and the key points of the center, which can reduce the errors that may be caused by a single center calculation method and ensure the validity of the coordinates of the center of the carbon bowl. In practical applications, the depth map of the carbon bowl may be interfered by multiple factors such as noise, illumination changes, and surface defects. The angle of the carbon bowl is calculated based on the specific feature of the key groove key point position, which can resist these interference factors to a certain extent and ensure the accuracy of the angle of the carbon bowl. Therefore, according to the coordinates of the center of the carbon bowl and the angle of the carbon bowl, the carbon bowl in the depth map of the carbon bowl can be effectively positioned.

[0012] Compared with the prior art, the present invention preliminarily calculates the center of the charcoal bowl through two different methods, and then comprehensively calculates the coordinates of the center of the charcoal bowl, which can reduce the error that may be caused by a single center calculation method; then the charcoal bowl angle is calculated based on the coordinates of the center of the charcoal bowl combined with the key point position set of the keyway, which can resist the interference of factors such as noise; finally, by combining the coordinates of the center of the charcoal bowl and the angle of the charcoal bowl, the charcoal bowl can be accurately positioned in three-dimensional space, thereby solving the problem of difficulty in accurately positioning the charcoal bowl when grinding the charcoal block.

[0013] As a preferred solution, a circle fitting is performed on the carbon bowl depth map to obtain the center of the fitting circle, specifically:

[0014] Performing carbon bowl circle labeling on the carbon bowl depth map to obtain a carbon bowl circle label map;

[0015] Segmenting the charcoal bowl circle label image to obtain a segmented image;

[0016] Generating a mask having the same size as the carbon bowl depth map for the segmented pattern to obtain a carbon bowl mask;

[0017] The boundary points of the carbon bowl mask are fitted into a standard circle, and the center of the standard circle is used as the center of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center.

[0018] This preferred solution marks the charcoal bowl depth map with a charcoal bowl circle, which can provide data information for subsequent accurate distinction and positioning of the charcoal bowl area. By segmenting the charcoal bowl circle label map, the background and other unnecessary information are removed. By fitting the boundary points of the charcoal bowl mask to a standard circle, a best-fitting circle can be found to represent the shape of the charcoal bowl, making it easier to determine the center of the circle.

[0019] As a preferred solution, key point detection is performed on the carbon bowl depth map to obtain a center key point and a key slot key point position set, specifically:

[0020] Generate a regular hexagon according to the center of the charcoal bowl circle of the charcoal bowl circle label diagram, align the six vertices of the regular hexagon with the center of the charcoal bowl keyway, and obtain a hexagon key point labeling diagram;

[0021] The key point detection is performed on the hexagonal key point annotation diagram using a preset key point detection model to obtain the center key point and the keyway key point position set.

[0022] This preferred solution is based on the regular hexagonal generation of the center of the charcoal bowl, which can provide a preliminary and relatively accurate estimation of the keyway center position. This geometric constraint helps the key point detection model to locate the keyway center more accurately when the image quality is not high or the keyway features are not obvious. In addition, compared with unconstrained key point detection directly on the entire image, since the key point detection model only needs to search for key points within the vertex range of the hexagon without traversing the entire image, detection based on the hexagonal key point annotation map can significantly reduce the complexity and time of calculation.

[0023] As a preferred solution, the coordinates of the center of the charcoal bowl are calculated based on the center of the fitting circle and the key point of the center, specifically:

[0024] Calculate the Euclidean distance between the center of the fitted circle and the key point of the center to obtain a first distance;

[0025] If the first distance is greater than or equal to a preset threshold, grinding the carbon block by rechecking;

[0026] If the first distance is less than the preset threshold, the average of the center of the fitting circle and the center key point is used as the center coordinate of the charcoal bowl.

[0027] This preferred solution can quantify the deviation between the center of the fitting circle and the key point of the center obtained by key point detection by calculating the Euclidean distance between the two. When the distance between the center of the fitting circle and the key point of the center is greater than or equal to the preset threshold, it means that there is a large deviation or irregularity in the shape or position of the charcoal bowl. At this time, the problem can be discovered and corrected in time by re-inspection and polishing to ensure the quality and consistency of the final product. In addition, when the first distance is less than the preset threshold, the error that may be caused by a single method can be reduced by averaging the coordinates of the center of the circle obtained by two different methods.

[0028] As a preferred solution, the carbon bowl angle is calculated based on the angle value between the key slot key point position set and the carbon bowl center coordinates, specifically:

[0029] Taking the vertical direction of the center coordinate of the carbon bowl as a reference, calculating the clockwise rotation angle of the first key groove key point position in the key groove key point position set to obtain a first angle value;

[0030] Converting the first angle value into a preset angle range to obtain an initial carbon bowl angle;

[0031] Traversing the key slot key point position set to obtain a number of initial carbon bowl angles;

[0032] The average of the several initial charcoal bowl angles is used as the charcoal bowl angle.

[0033] This preferred solution uses the vertical direction of the center coordinates of the charcoal bowl as the reference for angle measurement, ensuring the consistency and stability of the measurement reference, and helping to reduce errors caused by reference changes. In practical applications, images or data may be affected by noise, interference and other factors. By measuring multiple points and taking the average, it is possible to better resist the interference of these factors on the measurement results, and significantly reduce the impact of single-point measurement errors on the final results, thereby improving the accuracy and robustness of the measurement.

[0034] The present invention provides a charcoal bowl positioning device based on key point detection, comprising a depth module, a fitting module, a detection module, a coordinate module, an angle module and a positioning module;

[0035] Wherein, the depth module is used to obtain point cloud data of the carbon block and map the point cloud data into a carbon bowl depth map;

[0036] The fitting module is used to perform circle fitting on the carbon bowl depth map to obtain the center of the fitting circle;

[0037] The detection module is used to perform key point detection on the carbon bowl depth map to obtain a center key point and a key slot key point position set;

[0038] The coordinate module is used to calculate the coordinates of the center of the charcoal bowl according to the center of the fitting circle and the key point of the center;

[0039] The angle module is used to calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate;

[0040] The positioning module is used to position the charcoal bowl in the charcoal bowl depth map according to the charcoal bowl center coordinates and the charcoal bowl angle.

[0041] As a preferred solution, the fitting module includes a labeling unit, a segmentation unit, a mask unit and a circle center unit;

[0042] The labeling unit is used to label the carbon bowl depth map with a carbon bowl circle to obtain a carbon bowl circle label map;

[0043] The segmentation unit is used to segment the charcoal bowl circle label image to obtain a segmentation graph;

[0044] The mask unit is used to generate a mask with the same size as the carbon bowl depth map for the segmented pattern to obtain a carbon bowl mask;

[0045] The center unit is used to fit the boundary points of the carbon bowl mask into a standard circle, and use the center of the standard circle as the center of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center.

[0046] As a preferred solution, the detection module includes a label unit and a detection unit;

[0047] The label unit is used to generate a regular hexagon according to the center of the charcoal bowl circle of the charcoal bowl circle label diagram, so that the six vertices of the regular hexagon are aligned with the center of the charcoal bowl keyway to obtain a hexagon key point labeling diagram;

[0048] The detection unit is used to perform key point detection on the hexagonal key point annotation diagram through a preset key point detection model to obtain the center key point and the keyway key point position set.

[0049] As a preferred solution, the coordinate module includes a distance unit, a polishing unit and a coordinate unit;

[0050] The distance unit is used to calculate the Euclidean distance between the center of the fitting circle and the key point of the center to obtain a first distance;

[0051] The grinding unit is used to grind the carbon block by rechecking if the first distance is greater than or equal to a preset threshold;

[0052] The coordinate unit is used to use the average of the center of the fitting circle and the center key point as the coordinate of the center of the charcoal bowl if the first distance is less than the preset threshold.

[0053] As a preferred solution, the angle module includes a rotation unit, a conversion unit, a synthesis unit and a calculation unit;

[0054] The rotation unit is used to calculate the clockwise rotation angle of the first key slot key point position in the key slot key point position set based on the vertical direction of the center coordinate of the carbon bowl to obtain a first angle value;

[0055] The conversion unit is used to convert the first angle value into a preset angle range to obtain an initial carbon bowl angle;

[0056] The synthesis unit is used to traverse the key slot key point position set to obtain a number of initial carbon bowl angles;

[0057] The calculation unit is used to take the average of the several initial carbon bowl angles as the carbon bowl angle.

[0058] The present application also provides a storage medium, on which a computer program is stored. The computer program is called and executed by a computer to implement the above-mentioned charcoal bowl positioning method based on key point detection. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of a charcoal bowl positioning method based on key point detection provided in an embodiment of the present application;

[0060] Figure 2 It is a global depth map of carbon blocks provided in an embodiment of the present application;

[0061] Figure 3 It is a charcoal bowl area diagram provided in an embodiment of the present application;

[0062] Figure 4 It is a semantic segmentation model data annotation diagram provided in an embodiment of the present application;

[0063] Figure 5 It is a segmentation diagram provided in an embodiment of the present application;

[0064] Figure 6 It is a structural diagram of the deep learning model Pointrend provided in an embodiment of the present application;

[0065] Figure 7 It is a hexagonal key point marking diagram provided in an embodiment of the present application;

[0066] Figure 8 It is a schematic diagram of the center of the carbon bowl and the center of the keyway provided in the embodiment of the present application;

[0067] Fig. 9 It is a structural diagram of the deep learning model RTMPose provided in an embodiment of the present application;

[0068] Fig.10 It is a schematic diagram of calculating key point angles provided in an embodiment of the present application;

[0069] Fig.11 It is an overall flow chart provided by the embodiment of the present application;

[0070] Fig.12 It is a structural schematic diagram of a charcoal bowl positioning device based on key point detection provided in an embodiment of the present application. DETAILED DESCRIPTION

[0071] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0072] In the description of the present application, it should be understood that the terms "first", "second" and "third" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first", "second" and "third" may explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, "several" means two or more.

[0073] A carbon bowl positioning method based on key point detection provided in an embodiment of the present application is mainly used in situations where the carbon bowl in a carbon block needs to be accurately positioned so as to accurately grind the inner wall of the carbon bowl.

[0074] Embodiment 1:

[0075] See also Figure 1 The embodiment of the present application provides a charcoal bowl positioning method based on key point detection, including S1 to S6, and the specific implementation steps are as follows:

[0076] S1. Obtain point cloud data of the carbon block, and map the point cloud data into a carbon bowl depth map.

[0077] Step S1 of the embodiment of the present application is specifically as follows:

[0078] The point cloud data of the carbon block is obtained by a 3D camera directly above the carbon block, and the point cloud data is mapped into a global depth map;

[0079] Four charcoal bowl regions are cut out from the global depth map to obtain four charcoal bowl depth maps; and, since the positions of the four charcoal bowls on the charcoal block are relatively fixed, this embodiment only requires that the cutout region of the global depth map include the complete charcoal bowl;

[0080] Among them, the point cloud data of the carbon block and the global depth map can be mapped to each other, and the mapping relationship is:

[0081]

[0082] Among them, u and v are arbitrary coordinate points of the image, u0 and v0 are the center coordinates of the image, and x w ,y w and z w Represents the three-dimensional coordinate point of the point cloud data; z c Represents the z-axis value of the camera coordinates, that is, the distance from the target to the camera; dx, dy, and f are the parameters of the camera itself.

[0083] To apply the embodiments of this application, please refer to Figure 2 , Figure 2 This is a global depth map of the carbon block provided in an embodiment of the present application.

[0084] To apply the embodiments of this application, please refer to Figure 3 , Figure 3 is a charcoal bowl area diagram provided in an embodiment of the present application, Figure 3 The first module and the second module in the figure both represent four carbon bowl areas cut out from the global depth map, but the carbon blocks shown in the first module are of better quality, while the carbon blocks shown in the second module are of poor quality.

[0085] S2. Perform circle fitting on the carbon bowl depth map to obtain the center of the fitting circle.

[0086] Step S2 of the embodiment of the present application is specifically as follows:

[0087] Carrying out carbon bowl circle labeling on the carbon bowl depth map A1 among the four carbon bowl depth maps, and obtaining a carbon bowl circle labeling map;

[0088] Segment the charcoal bowl circle label image to obtain a segmented image;

[0089] Use the segmentation model PointRend to generate a mask of the same size as the charcoal bowl depth map A1 for the segmentation graph, and obtain the charcoal bowl mask;

[0090] Then, the boundary points of the carbon bowl mask are fitted into a standard circle, and the center of the standard circle is used as the center C1 of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center;

[0091] Among them, the construction process of the segmentation model PointRend is:

[0092] Collect a large number of charcoal bowl images for manual annotation, and then use the annotated charcoal bowl images to train the segmentation model PointRend;

[0093] Finally, the trained segmentation model PointRend is integrated into the hardware, so that whenever a carbon bowl image is input, the system can immediately output the position of the mask through the segmentation model PointRend for the subsequent steps of carbon block polishing.

[0094] To apply the embodiments of this application, please refer to Figure 4 , Figure 4 is a semantic segmentation model data annotation diagram provided in an embodiment of the present application, Figure 4 In the figure, the first module represents the original image of the charcoal bowl, the second module represents the labeling process, and the third module represents the charcoal bowl circle label image after the labeling is completed.

[0095] To apply the embodiments of this application, please refer to Figure 5 , Figure 5 is a segmentation diagram provided in an embodiment of the present application, Figure 5 In the figure, the first module represents the original image of the charcoal bowl; the second module represents the mask superimposed on the original image of the charcoal bowl.

[0096] To apply the embodiments of this application, please refer to Figure 6 , Figure 6 It is a structural diagram of the deep learning model Pointrend provided in an embodiment of the present application, which represents the network structure of the segmentation model Pointrend.

[0097] Embodiment S2 of the present application annotates the charcoal bowl depth map with a charcoal bowl circle, which can provide data information for subsequent accurate distinction and location of the charcoal bowl area. By segmenting the charcoal bowl circle label map, the background and other unnecessary information are removed. By fitting the boundary points of the charcoal bowl mask to a standard circle, a best-fitting circle can be found to represent the shape of the charcoal bowl, making it easier to determine the center of the circle.

[0098] S3. Perform key point detection on the carbon bowl depth map to obtain a center key point and a key slot key point position set.

[0099] Step S3 of the embodiment of the present application is specifically as follows:

[0100] Generate a regular hexagon according to the center of the charcoal bowl circle label diagram, and the regular hexagon can be scaled and rotated; align the six vertices of the regular hexagon with the center of the charcoal bowl keyway to obtain a hexagon key point labeling diagram; and the labels of the hexagon key point labeling diagram are the coordinates of the center of the charcoal bowl circle and the coordinates of the six vertices of the regular hexagon;

[0101] The key point detection is performed on the hexagonal key point annotation graph through the preset key point detection model RTMPose to obtain the circle center key point C2 and the key slot key point position set P6; wherein the key slot key point refers to the key slot center;

[0102] Among them, the construction process of the key point detection model RTMPose is:

[0103] A large number of charcoal bowl images were collected and manually annotated, and then the annotated charcoal bowl images were used to train the key point detection model RTMPose;

[0104] Finally, the trained key point detection model RTMPose is integrated into the hardware;

[0105] Whenever a carbon bowl diagram is input, the system can immediately output the center key points and keyway key points in the carbon bowl diagram through the key point detection model RTMPose, which will be used in the subsequent steps of carbon block grinding.

[0106] To apply the embodiments of this application, please refer to Figure 7 , Figure 7 It is a hexagonal key point marking diagram provided in an embodiment of the present application, which shows the result of hexagonal key point marking of the charcoal bowl.

[0107] To apply the embodiments of this application, please refer to Figure 8 , Figure 8 : is a schematic diagram of the center of the carbon bowl and the keyway provided in the embodiment of the present application, which shows the center of the carbon bowl and the keyway obtained based on the key point detection model RTMPose. Figure 8 The six points roughly evenly distributed on the center circle represent the centers of the six keyways, and the point in the center of the circle represents the center of the charcoal bowl.

[0108] To apply the embodiments of this application, please refer to Fig. 9 , Fig. 9 It is a structural diagram of the deep learning model RTMPose provided in an embodiment of the present application, which represents the network structure of the key point detection model RTMPose.

[0109] The embodiment S3 of the present application is based on the regular hexagon generated by the center of the charcoal bowl, which can provide a preliminary and relatively accurate estimation of the keyway center position. This geometric constraint helps the key point detection model to locate the keyway center more accurately when the image quality is not high or the keyway features are not obvious. In addition, compared with the unconstrained key point detection directly on the entire image, since the key point detection model only needs to search for key points within the vertex range of the hexagon without traversing the entire image, detection based on the hexagonal key point annotation map can significantly reduce the complexity and time of calculation.

[0110] S4. Calculate the coordinates of the center of the charcoal bowl according to the center of the fitting circle and the key point of the center.

[0111] Step S4 of the embodiment of the present application is specifically as follows:

[0112] Calculate the Euclidean distance between the center C1 of the fitting circle and the key point C2 of the center to obtain a first distance D1;

[0113] If the first distance D1 is greater than or equal to the preset threshold, the carbon block flows out to the manual re-inspection area, and the position of the carbon bowl is recorded. The system alarms and notifies manual processing: manually check whether the carbon bowl is normal and whether the carbon block is usable. If it is usable, it is manually polished;

[0114] If the first distance D1 is less than the preset threshold, the average value of the center of the fitting circle C1 and the key point of the center C2 is used as the center coordinate C of the charcoal bowl;

[0115] The preset threshold may be 5 pixels.

[0116] It should be noted that if the first distance D1 is greater than or equal to the preset threshold, it means that the charcoal bowl is very irregular and the center of the charcoal bowl cannot be accurately calculated. Since the purpose of locating the charcoal bowl is to allow the robotic arm to grind and clean the charcoal block, if the center of the circle cannot be accurately located (indicating that the shape of the charcoal bowl may be damaged or irregular), the background system will not issue instructions to the robotic arm for grinding, so the charcoal block will directly flow out to the manual re-inspection area for inspection; if the first distance D1 is less than the preset threshold, it means that the center positions obtained by the two methods are close, and the accurate center position of the charcoal bowl can be obtained.

[0117] In Example S4 of the present application, by calculating the Euclidean distance between the center of the fitting circle and the key point of the center obtained by key point detection, the deviation between the two can be quantified. When the distance between the center of the fitting circle and the key point of the center is greater than or equal to the preset threshold, it means that there is a large deviation or irregularity in the shape or position of the charcoal bowl. At this time, the problem can be discovered and corrected in time by re-inspection and polishing to ensure the quality and consistency of the final product. In addition, when the first distance is less than the preset threshold, the error that may be caused by a single method can be reduced by averaging the coordinates of the center of the circle obtained by two different methods.

[0118] S5. Calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate.

[0119] Step S5 of the embodiment of the present application includes S5.1 to S5.2, specifically:

[0120] S5.1. Taking the vertical 12 o'clock direction of the center coordinate C of the carbon bowl as a reference, calculate the clockwise rotation angle of the first key slot key point position P[1] in the key slot key point position set P6 to obtain a first angle value;

[0121] Convert the first angle value to the range of [0°, 60°) to obtain the initial carbon bowl angle A[1];

[0122] Traverse the key point position set of the key slot to obtain several initial carbon bowl angles A[6];

[0123] The average value of several initial carbon bowl angles A[6] is taken as the carbon bowl angle A.

[0124] It should be noted that each carbon bowl has 6 keyways, which are equally spaced on the edge of the carbon bowl; that is, the angle between any two adjacent keyways is 60 degrees. It should be noted that although the angles between any two adjacent keyways are equal, the distribution of the 6 keyways on the edge of the carbon bowl is different, so it can be considered that the angle range of the carbon bowl is: it can be 0° but cannot be 60°.

[0125] To apply the embodiments of this application, please refer to Fig.10 , Fig.10 is a schematic diagram of the angle of the key points of calculation provided in the embodiment of the present application, which shows the angle value when the angle conversion is performed to obtain the initial carbon bowl angle. Fig.10 C is the center coordinate of the carbon bowl, T represents the vertical 12 o'clock direction of the center coordinate C of the carbon bowl, and P represents the key point position of the keyway. After the angle value is converted, the initial carbon bowl angle (i.e. the clockwise angle between TC and PC) needs to be less than 60°;

[0126] For example, assuming that the calculated angle value is 119°, the initial charcoal bowl angle after conversion is 59°; assuming that the calculated angle value is 120°, the initial charcoal bowl angle after conversion is 0°; assuming that the calculated angle value is 121°, the initial charcoal bowl angle after conversion is 1°.

[0127] Embodiment S5.1 of the present application uses the vertical direction of the center coordinate of the charcoal bowl as a reference for angle measurement, which ensures the consistency and stability of the measurement reference and helps reduce errors caused by reference changes. In practical applications, images or data may be affected by noise, interference and other factors. By measuring multiple points and taking the average, it is possible to better resist the interference of these factors on the measurement results and significantly reduce the impact of single-point measurement errors on the final results, thereby improving the accuracy and robustness of the measurement.

[0128] S5.2, respectively calculating the absolute values ​​of the differences between the initial carbon bowl angles A[6] and the carbon bowl angles A to obtain an absolute value set;

[0129] If all absolute values ​​in the absolute value set are less than 2°, it means that the detected key points are evenly distributed, and the average angle A is taken as the final charcoal bowl angle;

[0130] If any absolute value in the absolute value set is greater than or equal to 2°, it means that the detected key point is abnormal. The control background system prohibits issuing instructions to the robotic arm for grinding, and directly flows the carbon block to the manual re-inspection area. At the same time, the position of the carbon bowl is recorded. The system alarm notifies manual processing: manually check whether the carbon bowl is normal and whether the carbon block is usable. If it is usable, it will be manually ground.

[0131] In Example S5.2 of the present application, verifying the accuracy of the keyway key point position can ensure the validity of the charcoal bowl angle; because the six keyways of the charcoal bowl are equidistantly distributed, the six keyway angle values ​​A[6] calculated based on the six keyway key points should not differ much, and the average angle A calculated at the same time should also be similar to the six keyway angle values ​​A[6]. Therefore, by calculating the absolute value of the difference between the six keyway angle values ​​A[6] and the average angle A, the validity of the average angle can be judged.

[0132] S6. Positioning the charcoal bowl in the charcoal bowl depth map according to the charcoal bowl center coordinates and the charcoal bowl angle.

[0133] Step S6 of the embodiment of the present application is specifically as follows:

[0134] The charcoal bowl in the charcoal bowl depth map A1 is positioned according to the charcoal bowl center coordinate C and the average angle A;

[0135] Traverse the remaining charcoal bowl depth maps in the four charcoal bowl depth maps, obtain the corresponding charcoal bowl center coordinates and charcoal bowl angles respectively to locate the charcoal bowl in the remaining charcoal bowl depth maps, and obtain the positioning result;

[0136] Polish the inner wall of the charcoal bowl of the charcoal block according to the positioning results.

[0137] To apply the embodiments of this application, please refer to Fig.11 , Fig.11 It is an overall flow chart provided in an embodiment of the present application, which shows the general process of positioning the charcoal bowl by calculating the center coordinates C and the average angle A of the charcoal bowl in the first embodiment.

[0138] Overall, this embodiment has the following beneficial effects:

[0139] The present invention can more accurately represent the shape and outline of the carbon block in three-dimensional space by acquiring the point cloud data of the carbon block and mapping it into a depth map. By fitting a circle on the carbon bowl depth map, an optimal circular boundary can be found through mathematical methods based on the pixel points or depth data of the edge of the carbon bowl, thereby determining the center position of the carbon bowl, effectively reducing the errors caused by factors such as the irregular shape of the carbon bowl, blurred edges or noise interference, and ensuring the accuracy of the center of the fitting circle. Using key point detection technology, the center of the circle and the key groove center point in the carbon bowl depth map can be accurately identified. The coordinates of the center of the carbon bowl are calculated based on the center of the fitting circle and the key points of the center, which can reduce the errors that may be caused by a single center calculation method and ensure the validity of the coordinates of the center of the carbon bowl. In practical applications, the depth map of the carbon bowl may be interfered by multiple factors such as noise, illumination changes, and surface defects. The angle of the carbon bowl is calculated based on the specific feature of the key groove key point position, which can resist these interference factors to a certain extent and ensure the accuracy of the angle of the carbon bowl. Therefore, according to the coordinates of the center of the carbon bowl and the angle of the carbon bowl, the carbon bowl in the depth map of the carbon bowl can be effectively positioned;

[0140] In addition, the key point detection model is used to directly detect the six key points of the carbon bowl, which can obtain the accurate angle of the carbon bowl even when the carbon bowl image quality is not high. At the same time, regular hexagonal annotation is used when annotating data, and the distribution of label coordinate points is strictly controlled to provide a high-quality data set for the training model. In addition, sophisticated logical judgment is designed to make the key slot angle judgment very accurate, with an error of about 0.2 degrees.

[0141] Embodiment 2:

[0142] See also Fig.12 , an embodiment of the present application provides a charcoal bowl positioning device based on key point detection, including a depth module 10, a fitting module 20, a detection module 30, a coordinate module 40, an angle module 50 and a positioning module 60;

[0143] The depth module 10 is used to obtain the point cloud data of the carbon block and map the point cloud data into a carbon bowl depth map;

[0144] A fitting module 20 is used to perform circle fitting on the carbon bowl depth map to obtain the center of the fitting circle;

[0145] A detection module 30 is used to perform key point detection on the carbon bowl depth map to obtain a center key point and a key groove key point position set;

[0146] A coordinate module 40 is used to calculate the coordinates of the center of the charcoal bowl according to the center of the fitting circle and the key point of the center;

[0147] An angle module 50, used to calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate;

[0148] The positioning module 60 is used to position the charcoal bowl in the charcoal bowl depth map according to the coordinates of the charcoal bowl center and the charcoal bowl angle.

[0149] In one embodiment, the depth module 10 is specifically:

[0150] The point cloud data of the carbon block is obtained by a 3D camera directly above the carbon block, and the point cloud data is mapped into a global depth map;

[0151] Four charcoal bowl regions are cut out from the global depth map to obtain four charcoal bowl depth maps; and, since the positions of the four charcoal bowls on the charcoal block are relatively fixed, this embodiment only requires that the cutout region of the global depth map include the complete charcoal bowl;

[0152] Among them, the point cloud data of the carbon block and the global depth map can be mapped to each other, and the mapping relationship is:

[0153]

[0154] Among them, u and v are arbitrary coordinate points of the image, u0 and v0 are the center coordinates of the image, and x w ,y w and z w Represents the three-dimensional coordinate point of the point cloud data; z c Represents the z-axis value of the camera coordinates, that is, the distance from the target to the camera; dx, dy, and f are the parameters of the camera itself.

[0155] To apply the embodiments of this application, please refer to Figure 2 , Figure 2 This is a global depth map of the carbon block provided in an embodiment of the present application.

[0156] To apply the embodiments of this application, please refer to Figure 3 , Figure 3 is a charcoal bowl area diagram provided in an embodiment of the present application, Figure 3 The first module and the second module in the figure both represent four carbon bowl areas cut out from the global depth map, but the carbon blocks shown in the first module are of better quality, while the carbon blocks shown in the second module are of poor quality.

[0157] In one embodiment, the fitting module 20 includes a labeling unit, a segmentation unit, a mask unit, and a circle center unit;

[0158] The labeling unit is used to label the carbon bowl circle of the carbon bowl depth map A1 among the four carbon bowl depth maps to obtain a carbon bowl circle label map;

[0159] A segmentation unit is used to segment the charcoal bowl circle label image to obtain a segmentation image;

[0160] The mask unit is used to generate a mask with the same size as the charcoal bowl depth map A1 for the segmented graph using the segmentation model PointRend to obtain the charcoal bowl mask;

[0161] The circle center unit is used to fit the boundary points of the carbon bowl mask mask into a standard circle, and the center of the standard circle is used as the center C1 of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center;

[0162] Among them, the construction process of the segmentation model PointRend is:

[0163] Collect a large number of charcoal bowl images for manual annotation, and then use the annotated charcoal bowl images to train the segmentation model PointRend;

[0164] Finally, the trained segmentation model PointRend is integrated into the hardware, so that whenever a carbon bowl image is input, the system can immediately output the position of the mask through the segmentation model PointRend for the subsequent steps of carbon block polishing.

[0165] To apply the embodiments of this application, please refer to Figure 4 , Figure 4 is a semantic segmentation model data annotation diagram provided in an embodiment of the present application, Figure 4 In the figure, the first module represents the original image of the charcoal bowl, the second module represents the labeling process, and the third module represents the charcoal bowl circle label image after the labeling is completed.

[0166] To apply the embodiments of this application, please refer to Figure 5 , Figure 5 is a segmentation diagram provided in an embodiment of the present application, Figure 5 In the figure, the first module represents the original image of the charcoal bowl; the second module represents the mask superimposed on the original image of the charcoal bowl.

[0167] To apply the embodiments of this application, please refer to Figure 6 , Figure 6 It is a structural diagram of the deep learning model Pointrend provided in an embodiment of the present application, which represents the network structure of the segmentation model Pointrend.

[0168] The fitting module 20 of the embodiment of the present application marks the carbon bowl depth map with a carbon bowl circle, which can provide data information for subsequent accurate distinction and positioning of the carbon bowl area. By segmenting the carbon bowl circle label map, the background and other unnecessary information are removed. By fitting the boundary points of the carbon bowl mask to a standard circle, a best-fitting circle can be found to represent the shape of the carbon bowl, which facilitates the determination of the center of the circle.

[0169] In one embodiment, the detection module 30 includes a label unit and a detection unit;

[0170] Among them, the label unit is used to generate a regular hexagon according to the center of the charcoal bowl of the charcoal bowl circle label diagram, and the regular hexagon can be scaled and rotated; the six vertices of the regular hexagon are aligned with the center of the charcoal bowl keyway to obtain a hexagon key point labeling diagram; and the labels of the hexagon key point labeling diagram are the coordinates of the center of the charcoal bowl and the coordinates of the six vertices of the regular hexagon;

[0171] A detection unit is used to perform key point detection on the hexagonal key point annotation graph through a preset key point detection model RTMPose to obtain a circle center key point C2 and a key slot key point position set P6; wherein the key slot key point refers to the key slot center;

[0172] Among them, the construction process of the key point detection model RTMPose is:

[0173] A large number of charcoal bowl images were collected and manually annotated, and then the annotated charcoal bowl images were used to train the key point detection model RTMPose;

[0174] Finally, the trained key point detection model RTMPose is integrated into the hardware;

[0175] Whenever a carbon bowl diagram is input, the system can immediately output the center key points and keyway key points in the carbon bowl diagram through the key point detection model RTMPose, which will be used in the subsequent steps of carbon block grinding.

[0176] To apply the embodiments of this application, please refer to Figure 7 , Figure 7 It is a hexagonal key point marking diagram provided in an embodiment of the present application, which shows the result of hexagonal key point marking of the charcoal bowl.

[0177] To apply the embodiments of this application, please refer to Figure 8 , Figure 8 : is a schematic diagram of the center of the carbon bowl and the keyway provided in the embodiment of the present application, which shows the center of the carbon bowl and the keyway obtained based on the key point detection model RTMPose. Figure 8 The six points roughly evenly distributed on the center circle represent the centers of the six keyways, and the point in the center of the circle represents the center of the charcoal bowl.

[0178] To apply the embodiments of this application, please refer to Fig. 9 , Fig. 9 It is a structural diagram of the deep learning model RTMPose provided in an embodiment of the present application, which represents the network structure of the key point detection model RTMPose.

[0179] The detection module 30 of the embodiment of the present application is generated based on the regular hexagon of the center of the charcoal bowl, which can provide a preliminary and relatively accurate estimation of the keyway center position. This geometric constraint helps the key point detection model to more accurately locate the keyway center when the image quality is not high or the keyway features are not obvious. In addition, compared with unconstrained key point detection directly on the entire image, since the key point detection model only needs to search for key points within the vertex range of the hexagon without traversing the entire image, detection based on the hexagonal key point annotation map can significantly reduce the complexity and time of calculation.

[0180] In one embodiment, the coordinate module 40 includes a distance unit, a grinding unit, and a coordinate unit;

[0181] The distance unit is used to calculate the Euclidean distance between the center C1 of the fitting circle and the key point C2 of the center to obtain a first distance D1;

[0182] The grinding unit is used to flow the carbon blocks to the manual re-inspection area if the first distance D1 is greater than or equal to the preset threshold value, and record the position of the carbon bowl at the same time. The system alarms and notifies manual processing: manually check whether the carbon bowl is normal and whether the carbon blocks are usable. If they are usable, manually perform grinding processing;

[0183] A coordinate unit, used to take the average value of the center C1 of the fitting circle and the key point C2 of the center as the coordinate C of the center of the charcoal bowl if the first distance D1 is less than a preset threshold;

[0184] The preset threshold may be 5 pixels.

[0185] It should be noted that if the first distance D1 is greater than or equal to the preset threshold, it means that the charcoal bowl is very irregular and the center of the charcoal bowl cannot be accurately calculated. Since the purpose of locating the charcoal bowl is to allow the robotic arm to grind and clean the charcoal block, if the center of the circle cannot be accurately located (indicating that the shape of the charcoal bowl may be damaged or irregular), the background system will not issue instructions to the robotic arm for grinding, so the charcoal block will directly flow out to the manual re-inspection area for inspection; if the first distance D1 is less than the preset threshold, it means that the center positions obtained by the two methods are close, and the accurate center position of the charcoal bowl can be obtained.

[0186] In the coordinate module 40 of the embodiment of the present application, by calculating the Euclidean distance between the center of the fitting circle and the key point of the center obtained by key point detection, the deviation between the two can be quantified. When the distance between the center of the fitting circle and the key point of the center is greater than or equal to the preset threshold, it means that there is a large deviation or irregularity in the shape or position of the charcoal bowl. At this time, the problem can be discovered and corrected in time by re-inspection and polishing to ensure the quality and consistency of the final product. In addition, when the first distance is less than the preset threshold, the error that may be caused by a single method can be reduced by averaging the coordinates of the center of the circle obtained by two different methods.

[0187] In one embodiment, the angle module 50 includes a rotation unit, a conversion unit, a synthesis unit, a calculation unit and an optimization unit, specifically:

[0188] The rotation unit is used to calculate the clockwise rotation angle of the first key slot key point position P[1] in the key slot key point position set P6 based on the vertical 12 o'clock direction of the center coordinate C of the carbon bowl to obtain a first angle value;

[0189] A conversion unit, used to convert the first angle value into a range of [0°, 60°) to obtain an initial carbon bowl angle A[1];

[0190] The comprehensive unit is used to traverse the key point position set of the key slot and obtain several initial carbon bowl angles A[6];

[0191] The calculation unit is used to take the average value of several initial carbon bowl angles A[6] as the carbon bowl angle A.

[0192] It should be noted that each charcoal bowl has 6 keyways, which are equally spaced along the edge of the charcoal bowl. In other words, the angle between any two adjacent keyways is 60 degrees. It should be noted that although the angles between any two adjacent keyways are equal, the distribution of the 6 keyways along the edge of the charcoal bowl is different, so it can be considered that the angle range of the charcoal bowl is: it can reach 0° but cannot reach 60°.

[0193] To apply the embodiments of this application, please refer to Fig.10 , Fig.10 is a schematic diagram of the calculation key point angle provided in the embodiment of the present application, which indicates the preset range when performing angle conversion to obtain the initial carbon bowl angle. Fig.10 C is the center coordinate of the carbon bowl, T represents the vertical 12 o'clock direction of the center coordinate C of the carbon bowl, and P represents the key point position of the keyway. After the angle value is converted, the initial carbon bowl angle (i.e. the clockwise angle between TC and PC) needs to be less than 60°;

[0194] For example, assuming that the calculated angle value is 119°, the initial charcoal bowl angle after conversion is 59°; assuming that the calculated angle value is 120°, the initial charcoal bowl angle after conversion is 0°; assuming that the calculated angle value is 121°, the initial charcoal bowl angle after conversion is 1°.

[0195] The rotation unit, conversion unit, integration unit and calculation unit of the embodiment of the present application use the vertical direction of the center coordinates of the charcoal bowl as the reference for angle measurement, which ensures the consistency and stability of the measurement reference and helps reduce errors caused by changes in the reference. In practical applications, images or data may be affected by factors such as noise and interference. By measuring multiple points and taking the average, it is possible to better resist the interference of these factors on the measurement results and significantly reduce the impact of single-point measurement errors on the final results, thereby improving the accuracy and robustness of the measurement.

[0196] The optimization unit is used to calculate the absolute values ​​of the initial carbon bowl angles A[6] and the carbon bowl angle A differences respectively to obtain an absolute value set;

[0197] The optimization unit is also used to take the average angle A as the final charcoal bowl angle if all absolute values ​​in the absolute value set are less than 2°, indicating that the detected key points are evenly distributed;

[0198] The optimization unit is also used to control the background system to prohibit issuing instructions to the robot arm for grinding if any absolute value in the absolute value set is greater than or equal to 2°, and directly flow the carbon block to the manual re-inspection area. At the same time, the position of the carbon bowl is recorded, and the system alarm notifies manual processing: manually check whether the carbon bowl is normal and whether the carbon block is available. If available, manual grinding is performed.

[0199] In the optimization unit of the embodiment of the present application, verifying the accuracy of the keyway key point position can ensure the effectiveness of the charcoal bowl angle; because the six keyways of the charcoal bowl are equidistantly distributed, the six keyway angle values ​​A[6] calculated based on the six keyway key points should not differ much, and the average angle A calculated at the same time should also be similar to the six keyway angle values ​​A[6]. Therefore, by calculating the absolute value of the difference between the six keyway angle values ​​A[6] and the average angle A, the effectiveness of the average angle can be judged.

[0200] In one embodiment, the positioning module 60 is specifically:

[0201] The charcoal bowl in the charcoal bowl depth map A1 is positioned according to the charcoal bowl center coordinate C and the average angle A;

[0202] Traverse the remaining charcoal bowl depth maps in the four charcoal bowl depth maps, obtain the corresponding charcoal bowl center coordinates and charcoal bowl angles respectively to locate the charcoal bowl in the remaining charcoal bowl depth maps, and obtain the positioning result;

[0203] Polish the inner wall of the charcoal bowl of the charcoal block according to the positioning results.

[0204] To apply the embodiments of this application, please refer to Fig.11 , Fig.11 It is an overall flow chart provided in the embodiment of the present application, which shows the general process of positioning the charcoal bowl by calculating the center coordinates C and the average angle A of the charcoal bowl in the second embodiment.

[0205] Overall, this embodiment has the following beneficial effects:

[0206] The present invention can more accurately represent the shape and outline of the carbon block in three-dimensional space by acquiring the point cloud data of the carbon block and mapping it into a depth map. By fitting a circle on the carbon bowl depth map, an optimal circular boundary can be found through mathematical methods based on the pixel points or depth data of the edge of the carbon bowl, thereby determining the center position of the carbon bowl, effectively reducing the errors caused by factors such as the irregular shape of the carbon bowl, blurred edges or noise interference, and ensuring the accuracy of the center of the fitting circle. Using key point detection technology, the center of the circle and the key groove center point in the carbon bowl depth map can be accurately identified. The coordinates of the center of the carbon bowl are calculated based on the center of the fitting circle and the key points of the center, which can reduce the errors that may be caused by a single center calculation method and ensure the validity of the coordinates of the center of the carbon bowl. In practical applications, the depth map of the carbon bowl may be interfered by multiple factors such as noise, illumination changes, and surface defects. The angle of the carbon bowl is calculated based on the specific feature of the key groove key point position, which can resist these interference factors to a certain extent and ensure the accuracy of the angle of the carbon bowl. Therefore, according to the coordinates of the center of the carbon bowl and the angle of the carbon bowl, the carbon bowl in the depth map of the carbon bowl can be effectively positioned;

[0207] In addition, the key point detection model is used to directly detect the six key points of the carbon bowl, which can obtain the accurate angle of the carbon bowl even when the carbon bowl image quality is not high. At the same time, regular hexagonal annotation is used when annotating data, and the distribution of label coordinate points is strictly controlled to provide a high-quality data set for the training model. In addition, sophisticated logical judgment is designed to make the key slot angle judgment very accurate, with an error of about 0.2 degrees.

[0208] Embodiment three:

[0209] The embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the carbon bowl positioning method based on key point detection;

[0210] Wherein, the carbon bowl positioning method based on key point detection, if implemented in the form of a software functional unit and used as an independent product, can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Wherein, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc.

[0211] The above are preferred embodiments of the present invention. It should be noted that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A charcoal bowl positioning method based on key point detection, characterized in that: include: Acquire point cloud data of the carbon block, and map the point cloud data into a carbon bowl depth map; Performing circle fitting on the carbon bowl depth map to obtain the center of the fitting circle; Performing key point detection on the carbon bowl depth map to obtain a center key point and a key slot key point position set; The coordinates of the center of the charcoal bowl are calculated according to the center of the fitting circle and the key point of the center; Calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate; The charcoal bowl in the charcoal bowl depth map is positioned according to the charcoal bowl center coordinates and the charcoal bowl angle.

2. A charcoal bowl positioning method based on key point detection as claimed in claim 1, characterized in that: The carbon bowl depth map is subjected to circle fitting to obtain the center of the fitting circle, specifically: Performing carbon bowl circle labeling on the carbon bowl depth map to obtain a carbon bowl circle label map; Segmenting the charcoal bowl circle label image to obtain a segmented image; Generating a mask having the same size as the carbon bowl depth map for the segmented pattern to obtain a carbon bowl mask; The boundary points of the carbon bowl mask are fitted into a standard circle, and the center of the standard circle is used as the center of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center.

3. A method for positioning a charcoal bowl based on key point detection as claimed in claim 2, characterized in that: The key point detection is performed on the carbon bowl depth map to obtain the center key point and key slot key point position set, specifically: Generate a regular hexagon according to the center of the charcoal bowl circle of the charcoal bowl circle label diagram, align the six vertices of the regular hexagon with the center of the charcoal bowl keyway, and obtain a hexagon key point labeling diagram; The key point detection is performed on the hexagonal key point annotation diagram using a preset key point detection model to obtain the center key point and the keyway key point position set.

4. The method for positioning a charcoal bowl based on key point detection according to claim 1, characterized in that: According to the center of the fitting circle and the key point of the center, the coordinates of the center of the charcoal bowl are calculated, specifically: Calculate the Euclidean distance between the center of the fitted circle and the key point of the center to obtain a first distance; If the first distance is greater than or equal to a preset threshold, grinding the carbon block by rechecking; If the first distance is less than the preset threshold, the average of the center of the fitting circle and the center key point is used as the center coordinate of the charcoal bowl.

5. The method for locating a charcoal bowl based on key point detection as claimed in claim 1, characterized in that: The carbon bowl angle is calculated based on the angle value between the key slot key point position set and the carbon bowl center coordinates, specifically: Taking the vertical direction of the center coordinate of the carbon bowl as a reference, calculating the clockwise rotation angle of the first key groove key point position in the key groove key point position set to obtain a first angle value; Converting the first angle value into a preset angle range to obtain an initial carbon bowl angle; Traversing the key slot key point position set to obtain a number of initial carbon bowl angles; The average of the several initial charcoal bowl angles is used as the charcoal bowl angle.

6. A charcoal bowl positioning device based on key point detection, characterized in that: Including depth module, fitting module, detection module, coordinate module, angle module and positioning module; Wherein, the depth module is used to obtain point cloud data of the carbon block and map the point cloud data into a carbon bowl depth map; The fitting module is used to perform circle fitting on the carbon bowl depth map to obtain the center of the fitting circle; The detection module is used to perform key point detection on the carbon bowl depth map to obtain a center key point and a key slot key point position set; The coordinate module is used to calculate the coordinates of the center of the charcoal bowl according to the center of the fitting circle and the key point of the center; The angle module is used to calculate the carbon bowl angle according to the angle value between the key slot key point position set and the carbon bowl center coordinate; The positioning module is used to position the charcoal bowl in the charcoal bowl depth map according to the charcoal bowl center coordinates and the charcoal bowl angle.

7. The charcoal bowl positioning device based on key point detection as claimed in claim 6, characterized in that: The fitting module includes a labeling unit, a segmentation unit, a mask unit and a circle center unit; The labeling unit is used to label the carbon bowl depth map with a carbon bowl circle to obtain a carbon bowl circle label map; The segmentation unit is used to segment the charcoal bowl circle label image to obtain a segmentation graph; The mask unit is used to generate a mask with the same size as the carbon bowl depth map for the segmented pattern to obtain a carbon bowl mask; The center unit is used to fit the boundary points of the carbon bowl mask into a standard circle, and use the center of the standard circle as the center of the fitting circle; wherein the standard circle refers to a circle with a fixed radius and center.

8. The charcoal bowl positioning device based on key point detection as claimed in claim 7, characterized in that: The detection module includes a label unit and a detection unit; The label unit is used to generate a regular hexagon according to the center of the charcoal bowl circle of the charcoal bowl circle label diagram, so that the six vertices of the regular hexagon are aligned with the center of the charcoal bowl keyway to obtain a hexagon key point labeling diagram; The detection unit is used to perform key point detection on the hexagonal key point annotation diagram through a preset key point detection model to obtain the center key point and the keyway key point position set.

9. The charcoal bowl positioning device based on key point detection according to claim 6, characterized in that: The coordinate module includes a distance unit, a polishing unit and a coordinate unit; The distance unit is used to calculate the Euclidean distance between the center of the fitting circle and the key point of the center to obtain a first distance; The grinding unit is used to grind the carbon block by rechecking if the first distance is greater than or equal to a preset threshold; The coordinate unit is used to use the average of the center of the fitting circle and the center key point as the coordinate of the center of the charcoal bowl if the first distance is less than the preset threshold.

10. The charcoal bowl positioning device based on key point detection according to claim 6, characterized in that: The angle module includes a rotation unit, a conversion unit, a synthesis unit and a calculation unit; The rotation unit is used to calculate the clockwise rotation angle of the first key slot key point position in the key slot key point position set based on the vertical direction of the center coordinate of the carbon bowl to obtain a first angle value; The conversion unit is used to convert the first angle value into a preset angle range to obtain an initial carbon bowl angle; The synthesis unit is used to traverse the key slot key point position set to obtain a number of initial carbon bowl angles; The calculation unit is used to take the average of the several initial carbon bowl angles as the carbon bowl angle.

11. A storage medium, characterized in that: The storage medium stores a computer program, which is called and executed by a computer to implement any one of the key point detection-based charcoal bowl positioning methods of claims 1 to 5 above.

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