Intelligent three-dimensional sorting warehouse for plates

Abstract

This application relates to the field of sheet metal sorting technology, and particularly to an intelligent three-dimensional sheet metal sorting warehouse including a rack, multi-layer storage positions, a material conveying platform, load-bearing columns, telescopic lifting forks, monitoring components, and a controller. The controller is configured to: acquire sheet metal images; determine the sheet metal outline based on the image and determine the coordinates of the sheet metal center point and the angular deviation from a preset direction; analyze the coordinates of the sheet metal center point and the angular deviation from the preset direction to obtain a theoretical distance; when the theoretical distance is less than a preset threshold, monitor the actual distance between the insert rod and the sheet metal in real time; compare the actual distance and the theoretical distance in real time to obtain first extension information or second extension information and determine the actual thickness of the sheet metal; process the actual thickness of the sheet metal to obtain the horizontal deviation and placement endpoint position, and perform sorting control on the sheet metal. This can solve the problem of insert rod collision and unstable storage caused by relying on preset parameters and fixed programs.

Description

Technical Field

[0001] This application belongs to the field of sheet material sorting technology, and in particular relates to an intelligent three-dimensional sheet material sorting warehouse. Background Technology

[0002] An intelligent automated sorting warehouse for sheet materials is a type of warehousing equipment used for storing and sorting sheet materials. It is widely used in industries such as whole-house custom furniture and integrated home decoration. An intelligent automated sorting warehouse for sheet materials typically includes racks, multi-level storage locations, material conveying platforms, and telescopic lifting forks. The telescopic lifting forks are mounted on load-bearing columns on the side of the racks. The forks can extend under control to pick up sheet materials located on the material conveying platform and transport and store them in designated multi-level storage locations, or perform the reverse picking process.

[0003] However, due to positioning errors during the conveying and feeding of the boards, and manufacturing tolerances in the actual thickness of different batches of boards, the multi-layer storage positions may experience slight deformation after long-term load-bearing. This, combined with the transmission gaps and repetitive positioning errors in the lifting and telescopic mechanisms, ultimately leads to the insertion rod easily colliding with boards that are misaligned when moving along the preset theoretical path, or becoming unstable during storage due to a mismatch between the actual height of the storage position and the actual thickness of the board. Furthermore, in the final stage of the insertion rod approaching the board, the actual gap between it and the bottom surface of the board is affected by the board's own bending deformation. If not properly controlled, a single preset movement path may fail to adapt to this real-time changing gap, causing rubbing or jamming.

[0004] Related technologies typically rely on mechanical positioning and preset motion programs, or are supplemented by simple position detection sensors to trigger single-step actions. These methods not only fail to completely solve the aforementioned technical problems, but may also create other threats. For example, excessively increasing the rigidity and processing precision of mechanical parts in pursuit of absolute accuracy can lead to a sharp increase in equipment costs; excessively reducing the approach speed of the insertion rod to avoid collisions can result in a decrease in sorting efficiency; and when faced with new types of thick plates that have never been entered into the system, the lack of awareness of their physical properties may prevent safe access operations. Summary of the Invention

[0005] This application provides an intelligent three-dimensional sorting warehouse for sheet materials, which can solve the problem that the lack of perception and adaptation ability for sheet material position, actual thickness and warehouse position status due to reliance on preset parameters and fixed programs leads to easy collision of insertion rods and unstable storage.

[0006] This application provides an intelligent three-dimensional sorting warehouse for sheet metal, including a rack, multi-layer storage positions on the rack, a material conveying platform installed at the bottom of the rack, load-bearing columns installed on the sides of the rack, and telescopic lifting forks installed on the load-bearing columns. The intelligent three-dimensional sorting warehouse for sheet metal further includes: A monitoring component is mounted on the telescopic lifting fork; the monitoring component includes a vision sensor and a distance sensor; the vision sensor is mounted on one side of the insertion rod of the telescopic lifting fork and is used to acquire an image of the plate at the end of the plate; the distance sensor is mounted along the extension direction of the insertion rod and is used to measure the actual distance between the end of the insertion rod and the position where the plate is to be contacted; and The controller is communicatively connected to the visual sensing unit and the ranging sensing unit; the controller is configured to: The visual sensing unit acquires an image of the board material and determines the outline of the board material based on the image. The coordinates of the center point of the board and its angular deviation from the preset direction are determined based on the board's outline. The theoretical distance is obtained by analyzing the coordinates of the center point of the plate and the angular deviation from the preset direction; When the theoretical distance is less than a preset threshold, the actual distance between the insert rod and the plate is monitored in real time based on the ranging sensor; wherein, the insert rod is a sub-component of the telescopic lifting fork; The first extension information or the second extension information is obtained by comparing the actual distance and the theoretical distance in real time; wherein, the first extension information is used to indicate to continue extending at the current speed, and the second extension information is used to indicate to reduce the extension speed to a preset speed; The actual thickness of the plate is determined based on the first or the second protrusion information; The actual thickness of the board material is used to obtain the horizontal deviation and the placement endpoint position, and the board material is sorted and controlled according to the horizontal deviation and the placement endpoint position.

[0007] The technical solutions described in this application embodiment have at least the following technical effects: The intelligent three-dimensional sorting warehouse for sheet metal provided in this application, by installing a monitoring component on a telescopic lifting fork to collect images and distance information, can perceive the actual placement and state of the sheet metal before performing storage and retrieval operations, rather than relying entirely on preset fixed parameters; then, it acquires images of the sheet metal and determines its outline based on the images; based on the outline, it determines the coordinates of the center point of the sheet metal and its angular deviation from the preset direction; based on the analysis of the coordinates of the center point of the sheet metal and the angular deviation from the preset direction, it obtains the theoretical distance; when the theoretical distance is less than a preset threshold, it monitors the actual distance between the insert rod and the sheet metal in real time based on the monitoring component; based on the actual distance and the theoretical distance, it obtains first extension information or second extension information, and based on the first extension information or second extension information, it determines the actual distance between the insert rod and the sheet metal. The actual thickness of the material is used to obtain the horizontal deviation and placement endpoint position. The material is then sorted and controlled based on the horizontal deviation and placement endpoint position. This method can adapt to the thickness tolerances existing in the material manufacturing process and can also offset the deformation errors caused by long-term use of the storage location, ensuring that the material is placed stably. This solves the problem of traditional solutions that lack the ability to perceive and adapt to the material's posture, actual thickness, and storage location status due to reliance on preset parameters and fixed programs, which leads to collisions and unstable storage. Compared with the prior art, this application does not require excessive improvement in the processing accuracy and rigidity of the mechanical structure. Under the premise of controlling the equipment manufacturing cost, it significantly improves the equipment's adaptability to errors under different working conditions, while also taking into account the safety and efficiency of sorting operations. Attached Figure Description

[0008] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0009] Figure 1 This is a schematic diagram of the structure of an intelligent three-dimensional sorting warehouse for sheet metal provided in one embodiment of this application; Figure 2 This is a schematic diagram of the structure of the intelligent three-dimensional sorting warehouse for sheet metal provided in one embodiment of this application from another direction; Figure 3 This is a schematic diagram of the controller implementation process of an intelligent three-dimensional sorting warehouse for sheet metal provided in one embodiment of this application; Figure 4 This is a schematic diagram of a scenario for obtaining the theoretical distance, provided in one embodiment of this application; Figure 5This is a schematic diagram of a scenario provided by an embodiment of the present application, in which the actual distance between the plug and the plate is monitored in real time based on the monitoring component when the theoretical distance is less than a preset threshold. Figure 6 This is a schematic diagram of a scenario provided by an embodiment of this application for determining the coordinates of the center point of a board and its angular deviation from a preset direction; Figure 7 This is a schematic diagram illustrating a scenario where the actual thickness of a plate is determined, according to an embodiment of this application. Figure 8 This is a schematic diagram of a scenario provided by an embodiment of this application, which obtains the horizontal deviation and the placement endpoint position and performs sorting control on the board according to the horizontal deviation and the placement endpoint position. Figure 9 This is a schematic diagram of the process for obtaining the first extension information or the second extension information provided in the embodiments of this application; Figure 10 This is a schematic diagram of the controller provided in the embodiments of this application.

[0010] The figures in the diagram are labeled as follows: 100. Intelligent three-dimensional sorting warehouse for sheet materials; 10. Warehouse rack; 20. Multi-layer storage location; 30. Material conveyor platform; 40. Load-bearing column; 50. Telescopic lifting forklift; 60. Controller; 70. Monitoring components. Detailed Implementation

[0011] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0012] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0013] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0014] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0015] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0016] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0017] An intelligent automated sorting warehouse for sheet materials is a type of warehousing equipment used for storing and sorting sheet materials. It is widely used in industries such as whole-house custom furniture and integrated home decoration. An intelligent automated sorting warehouse for sheet materials typically includes racks, multi-level storage locations, material conveying platforms, and telescopic lifting forks. The telescopic lifting forks are mounted on load-bearing columns on the side of the racks. The forks can extend under control to pick up sheet materials located on the material conveying platform and transport and store them in designated multi-level storage locations, or perform the reverse picking process.

[0018] However, due to positioning errors during the conveying and feeding of the boards, and manufacturing tolerances in the actual thickness of different batches of boards, the multi-layer storage positions may experience slight deformation after long-term load-bearing. This, combined with the transmission gaps and repetitive positioning errors in the lifting and telescopic mechanisms, ultimately leads to the insertion rod easily colliding with boards that are misaligned when moving along the preset theoretical path, or becoming unstable during storage due to a mismatch between the actual height of the storage position and the actual thickness of the board. Furthermore, in the final stage of the insertion rod approaching the board, the actual gap between it and the bottom surface of the board is affected by the board's own bending deformation. If not properly controlled, a single preset movement path may fail to adapt to this real-time changing gap, causing rubbing or jamming.

[0019] Related technologies typically rely on mechanical positioning and preset motion programs, or are supplemented by simple position detection sensors to trigger single-step actions. These methods not only fail to completely solve the aforementioned technical problems, but may also create other threats. For example, excessively increasing the rigidity and processing precision of mechanical parts in pursuit of absolute accuracy can lead to a sharp increase in equipment costs; excessively reducing the approach speed of the insertion rod to avoid collisions can result in a decrease in sorting efficiency; and when faced with new types of thick plates that have never been entered into the system, the lack of awareness of their physical properties may prevent safe access operations.

[0020] To address the aforementioned issues, this application provides an intelligent three-dimensional sorting warehouse for sheet metal. By installing a monitoring component on a telescopic lifting fork to acquire images and distance information, the actual placement and state of the sheet metal can be perceived before storage and retrieval operations, rather than relying entirely on preset fixed parameters. Then, by acquiring sheet metal images and determining the sheet metal outline based on the images, the coordinates of the sheet metal's center point and its angular deviation from a preset direction are determined based on the sheet metal outline. The theoretical distance is obtained by analyzing the coordinates of the sheet metal's center point and its angular deviation from the preset direction. If the theoretical distance is less than a preset threshold, the actual distance between the insertion rod and the sheet metal is monitored in real time based on the monitoring component. A first extension information or a second extension information is obtained by comparing the actual distance and the theoretical distance in real time. The actual thickness of the sheet metal is determined based on the first extension information or the second extension information. The actual thickness is processed to obtain the horizontal deviation and placement endpoint position. The sorting control of the boards is then performed based on the horizontal deviation and placement endpoint position. This method can adapt to the thickness tolerances existing in the board manufacturing process and can also offset the deformation errors caused by long-term use of the storage location, ensuring that the boards are placed stably. This solves the problem of traditional solutions that lack the ability to perceive and adapt to the board's posture, actual thickness, and storage location status due to reliance on preset parameters and fixed programs, which leads to collisions and unstable storage of the insertion rods. Compared with the prior art, this application does not require excessive improvement in the processing accuracy and rigidity of the mechanical structure. Under the premise of controlling the equipment manufacturing cost, it significantly improves the equipment's adaptability to errors under different working conditions, while also taking into account the safety and efficiency of the sorting operation.

[0021] For example, please refer to the following: Figure 1 , Figure 2 as well as Figure 10 A smart three-dimensional sorting warehouse 100 for sheet metal includes a rack 10, multi-layer storage positions 20 disposed on the rack 10, a material conveying platform 30 installed at the bottom of the rack 10, load-bearing columns 40 installed on the sides of the rack 10, and telescopic lifting forks 50 installed on the load-bearing columns 40. The smart three-dimensional sorting warehouse 100 for sheet metal further includes a monitoring component 70 and a controller 60, wherein: The monitoring component 70 is mounted on the telescopic lifting fork 50. The monitoring component 70 includes a vision sensor 71 and a distance measuring sensor 72. The vision sensor 71 is mounted on one side of the insertion rod of the telescopic lifting fork 50 and is used to acquire images of the end of the sheet metal. The distance measuring sensor 72 is mounted along the extension direction of the insertion rod and is used to measure the actual distance between the end of the insertion rod and the position where the sheet metal is to be contacted. The controller 60 is communicatively connected to the vision sensor 71 and the distance measuring sensor 72.

[0022] Understandably, the following details the storage rack 10, the multi-layer storage positions 20 set on the storage rack 10, the material conveying platform 30 installed at the bottom of the storage rack 10, the load-bearing columns 40 installed on the side of the storage rack 10, and the telescopic lifting forks 50 installed on the load-bearing columns 40. The storage rack 10 can be welded from high-strength industrial steel. According to the actual production needs for the size, weight, and storage volume of the stored boards, the overall floor area and the number of vertical layers can be flexibly adjusted to meet the site and production capacity requirements of customized furniture manufacturing enterprises of different sizes. The multi-layer storage positions 20 are set up in layers along the vertical direction of the storage rack 10. Each storage position corresponds to an independent storage area for storing boards of different specifications and orders. Limit bars are set on the side of the storage position to prevent the boards from sliding sideways during storage and improve storage safety.

[0023] The material conveying platform 30 adopts a roller conveyor structure, which can receive the plates to be stored from the automatic unloading equipment. The load-bearing column 40 is made of rectangular square steel with a phosphated and powder-coated surface, providing good corrosion resistance and deformation resistance. It can stably support the weight of the telescopic lifting fork 50 and the plates it carries, and is not prone to bending or deformation over long-term use. The telescopic lifting fork 50 adopts a two-stage telescopic structure, which can drive the plates to complete the horizontal telescopic fork lifting and vertical lifting and transfer, transporting the plates on the material conveying platform 30 to the target storage location, or taking plates from the target storage location and transporting them to the material conveying platform 30 for outbound processing.

[0024] The vision sensing unit 71 can be a vision camera or a high-definition industrial camera; the vision camera can clearly capture images of the end face of the sheet metal and the opening of the storage location; the high-definition industrial camera is installed on the side of the extension rod of the telescopic lifting fork 50 and can acquire images of the current placement position of the sheet metal and the internal space of the target storage location. The distance sensing unit 72 can be a laser distance sensor; the laser distance sensor is installed synchronously with the industrial camera and can accurately measure the distance between the end face of the extension rod and the side of the sheet metal, and between the bottom surface of the sheet metal and the support surface of the storage location.

[0025] The controller 60 can be an industrial computer with an integrated computing module, or a PLC control unit, but is not limited to these. The controller 60 can independently complete the board sensing and sorting control calculations, or it can be connected to the factory's existing MES production management system to achieve real-time synchronization of board information, order information, and storage location.

[0026] The controller provided in this application embodiment can be applied to an intelligent three-dimensional sorting warehouse for sheet materials. In this case, the controller is the execution subject of the intelligent three-dimensional sorting warehouse for sheet materials provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of intelligent three-dimensional sorting warehouse for sheet materials.

[0027] To better understand the configuration of the controller of the intelligent three-dimensional sorting warehouse for sheet metal provided in this application embodiment, the specific working process of the controller of the intelligent three-dimensional sorting warehouse for sheet metal provided in this application embodiment will be described by way of example below.

[0028] Figure 3 The diagram illustrates the workflow of the controller for the intelligent automated sorting warehouse for sheet metal provided in this embodiment of the application. The controller of the intelligent automated sorting warehouse for sheet metal is used to perform the following steps: S100: The vision sensing unit acquires an image of the board material and determines the board material outline based on the image.

[0029] For example, the board outline refers to the boundary lines of the board's shape. The board image is preprocessed by this module, and then edge extraction and outline recognition algorithms are used to filter out the board's boundary lines from the preprocessed image, ultimately determining a complete and accurate board outline. Alternatively, the board image can be converted to grayscale to obtain a grayscale image, and edge detection processing can be performed on the grayscale image to obtain edge features. Then, outline fitting processing can be performed based on the edge features to obtain the board outline.

[0030] In one possible implementation, please refer to Figure 2 S100, acquire the board image and determine the board outline based on the board image, including: S110: The image of the board material is converted to grayscale to obtain a grayscale image, and edge detection processing is performed on the grayscale image to obtain edge features.

[0031] As can be understood, grayscale processing refers to converting the acquired color board image (containing red, green, and blue channels) into a grayscale image with only black, white, and gray gradients, reducing the amount of image data and removing color interference; edge detection processing refers to identifying areas with drastic brightness changes in the grayscale image through specific algorithms, and these areas are the edges of the board; edge features refer to the position, direction, length, etc. of the edge, which are the basic units that constitute the outline of the board.

[0032] For example, by calling the grayscale algorithm in the image processing module, the acquired color board image is processed. The brightness values ​​of the red, green, and blue channels of each pixel in the image are weighted and averaged (for example, using the textual description of the common grayscale formula: the red brightness value, green brightness value, and blue brightness value of each pixel are added in a certain proportion to obtain the grayscale value of the pixel). Each pixel is converted into the corresponding grayscale value, and finally a grayscale image is generated. At this time, the board area and the background area will show obvious distinction due to the difference in brightness. Then, a preset edge detection algorithm (such as the Canny algorithm) is used to perform edge detection on the grayscale image. That is, the grayscale image is first smoothed to further remove noise interference, and then the brightness gradient of each pixel in the image is calculated. Pixels with gradient values ​​exceeding a preset threshold are selected (these pixels are edge points). Adjacent edge points are connected to form continuous edge lines, and finally the edge features of the board are obtained.

[0033] S120, the profile of the board is obtained by contour fitting based on the edge features.

[0034] For example, based on edge features, including the coordinates of all edge points, the direction and length of edge lines, this data is filtered to remove isolated edge points and invalid edge lines (such as edge lines that are too short or do not conform to the overall direction of the board). By selecting the start and end points of the edge lines, adjacent edge lines are connected. The connected lines are then smoothed to correct any bending deviations. For discrete edge points, they are incorporated into adjacent edge lines to fill in any missing parts of the lines, and finally, a complete board outline is fitted.

[0035] This setup, through contour fitting, integrates discrete edge features into a complete and continuous board contour, solving the problem of scattered and discontinuous edge features. This ensures that the obtained board contour is highly consistent with the actual board shape, avoiding contour deviations caused by invalid edge information, and providing contour basis for subsequent determination of board center point, angle deviation, etc.

[0036] S200 determines the coordinates of the center point of the board and its angular deviation from the preset direction based on the board's outline.

[0037] It can be understood that the center point of the board refers to the geometric center of the board, which is the core positioning point of the board and is used to determine the specific position of the board; the center point coordinates refer to the specific position data of the center point in a preset coordinate system (such as the equipment coordinate system, with a fixed point of the sorting equipment as the origin, the horizontal direction as the X-axis, and the vertical direction as the Y-axis); the preset direction refers to the preset warehouse reference axis direction (that is, the standard direction in which the board should be placed after sorting, such as the horizontal axis direction of the warehouse); the angle deviation refers to the angle between the current main axis direction of the board and the preset warehouse reference axis direction, which is used to determine whether the placement direction of the board meets the sorting requirements.

[0038] For example, by statistically analyzing the X-axis and Y-axis coordinates of all boundary points of the profile, the average value of all X-axis coordinates is calculated as the X-axis coordinate of the center point; the average value of all Y-axis coordinates is calculated as the Y-axis coordinate of the center point. Combining the two coordinates gives the coordinates of the center point of the board. By determining the principal axis direction of the board profile, which refers to the direction of the longest axis of symmetry in the board profile, the circumscribed rectangle of the profile is calculated, and the direction of the long side of the circumscribed rectangle is the principal axis direction of the board. The angle data of the principal axis direction is obtained (the angle calculated clockwise or counterclockwise with the X-axis of the preset coordinate system as the reference). Then, the angle data of the preset storage location reference axis direction is obtained. The angle of the principal axis direction is compared with the angle of the storage location reference axis direction, and the included angle is calculated. This included angle is the angle deviation.

[0039] In one possible implementation, please refer to Figure 6 S200, determining the coordinates of the center point of the board and its angular deviation from the preset direction based on the board profile, including: S210, geometric center processing is performed on the outline of the board to obtain the coordinates of the center point of the board.

[0040] For example, by using a complete set of boundary coordinate points of the defined board outline (including the X-axis and Y-axis coordinates of all pixels on the outline), these coordinate points are filtered to remove abnormal coordinate points (such as coordinate points that exceed the actual range of the board due to outline fitting deviation). Then, geometric calculations are performed on the filtered valid coordinate points. That is, first, the X-axis coordinates of all coordinate points are added together to obtain the sum of the X-axis coordinates, and then the sum is divided by the number of coordinate points to obtain the average value of the X-axis coordinates. This average value is the X-axis coordinate of the center point of the board. Then, the Y-axis coordinates of all coordinate points are added together to obtain the sum of the Y-axis coordinates, and the sum is divided by the number of coordinate points to obtain the average value of the Y-axis coordinates. This average value is the Y-axis coordinate of the center point of the board. Finally, the calculated X-axis coordinates and Y-axis coordinates are combined to form the complete coordinates of the center point of the board.

[0041] S220, determine the main axis direction of the plate outline, and obtain the angle deviation by comparing and analyzing the main axis direction with the preset storage location reference axis direction.

[0042] For example, by fitting a bounding rectangle to the outline of the board material, i.e., drawing a minimum rectangle that can completely enclose the outline of the board material, the direction of the long side of this rectangle is the principal axis direction of the board material outline. Then, by obtaining the angle data of the principal axis direction (calculated clockwise with the X-axis of the preset equipment coordinate system as the reference, the angle range is 0-360 degrees), the preset parameter library is called to obtain the angle data of the preset warehouse location reference axis direction. Then, the angle of the principal axis direction is compared with the angle of the warehouse location reference axis direction, and the absolute angle between the two is calculated: if the angle of the principal axis direction is greater than the reference axis angle, the angle is obtained by subtracting the reference axis angle from the principal axis angle; if the angle of the principal axis direction is less than the reference axis angle, the angle is obtained by subtracting the principal axis angle from the reference axis angle; if the two angles are the same, the angle is 0 degrees, and this angle is the angle deviation.

[0043] This setup, by determining the spindle direction and comparing it with the reference direction to obtain the angular deviation, can accurately judge the difference between the current placement posture of the board and the standard posture, providing a directional basis for the subsequent optimization of the forklift path, and avoiding problems such as collision between the forklift rod and the board, and unstable forklifting caused by the tilt of the board.

[0044] S300, the theoretical distance is obtained by analyzing the coordinates of the center point of the board and the angular deviation from the preset direction.

[0045] For example, the theoretical distance can be obtained by determining the position information of the fork arm, and determining the target point of the forking action based on the position information, the coordinates of the center point of the plate and the angle deviation from the preset direction. Then, based on the target point of the forking action, an optimized forking path with the actual center of the plate as the reference is obtained, and a theoretical distance function between the front end of the insertion rod and the bottom surface of the plate under the optimized forking path is generated. The theoretical distance is then obtained based on the theoretical distance function.

[0046] In one possible implementation, S300, please refer to... Figure 4 The theoretical distance is obtained by analyzing the coordinates of the center point of the board and its angular deviation from the preset direction, including: S310: Obtain the position information of the fork arm, and determine the target point for the fork-picking action based on the position information, the coordinates of the center point of the plate, and the angular deviation from the preset direction.

[0047] For example, the position information of the fork arm can be obtained in real time by a position encoder installed on the telescopic lifting fork. The position encoder can accurately record the current height coordinate of the fork arm on the load-bearing column and the horizontal coordinate corresponding to the current extension length of the telescopic fork. The combination of these coordinates gives the current actual position coordinates of the fork arm. After determining the position coordinates of the fork arm, the preset target point for the picking action is corrected by combining the obtained coordinates of the center point of the plate and the angle deviation. The original preset target point is pre-set based on the standard plate size and standard placement posture. Now, by using the angle deviation, the extension angle of the fork arm can be corrected first, so that the extension direction of the insert is parallel to the long side of the plate. Then, by using the difference between the coordinates of the center point of the plate and the preset center point coordinates, the horizontal and vertical positions of the target point are adjusted, and finally, the target point for the picking action that adapts to the current actual placement state of the plate is obtained. For example, if the X-axis coordinate of the current center point of the board is 20 mm to the left of the preset center point, and the angle deviation is 3 degrees clockwise, then the target point of the fork action will be shifted to the left by 20 mm, and the fork arm will rotate 3 degrees clockwise to ensure that the insert can be aligned with the fork gap of the board in the correct direction.

[0048] S320: Based on the target point of the forklift action, obtain the optimized forklift path with the actual center of the plate as the reference, and generate the theoretical distance function between the front end of the insertion rod and the bottom surface of the plate under the optimized forklift path.

[0049] For example, using the determined coordinates of the target point for the fork action and the current position coordinates of the fork arm, a path planning algorithm is used to plan and optimize the fork action path: First, by calculating the straight-line distance from the current position of the fork arm to the target point, a straight path (shortest path) is prioritized. At the same time, obstacles (such as equipment parts or other materials) are detected on the path. If obstacles exist, the path is adjusted to a polyline or curve to ensure that no collision occurs during the extension of the fork arm. Second, the direction of the path is adjusted based on the actual center of the material (center point) to ensure that the fork arm is always aligned with the center of the material when it extends, avoiding deviation. Finally, the starting point (the front end of the fork arm at the current position) and the ending point (the target point for the fork action) of the path are determined, and the speed curve of the fork arm extension is defined (rapid extension in the early stage, deceleration when approaching the target point), thus completing the planning of the optimized fork action path. Based on the optimized fork path, the relationship between the extension length of the insert rod and the theoretical distance is analyzed. That is, as the insert rod extends, the distance between the front end of the insert rod and the bottom surface of the board gradually decreases. Based on parameters such as the extension length of the insert rod, the angle of the fork path, and the height of the bottom surface of the board, the correspondence between the theoretical distance and the extension length of the insert rod is established, and the theoretical distance function is generated.

[0050] S330, the theoretical distance is obtained based on the theoretical distance function.

[0051] For example, based on the current extension length of the insertion rod, the previously generated theoretical distance function is substituted into the calculation to directly obtain the current theoretical distance between the front end of the insertion rod and the bottom surface of the plate. The specific formula for the theoretical distance function can be... , where d is the current theoretical distance, D is the preset total horizontal distance from the center of the plate to the origin of the fork arm, l is the current extension length of the insertion rod, and θ is the deflection angle of the fork arm after correction due to angle deviation.

[0052] This setup, by combining the actual position of the board and the current position of the fork arm to calculate the theoretical distance, provides a data benchmark for the precise control of the subsequent forking action, avoiding the problem of the insertion rod scraping the bottom surface of the board or failing to accurately insert into the fork gap caused by the distance calculation deviation under the default standard size.

[0053] In one possible implementation, S330, the theoretical distance is obtained based on the theoretical distance function, including: S331, determine the current extension length of the insertion rod, the plate size parameters determined based on the plate profile, and the preset safety margin parameters.

[0054] For example, the current extension length of the insert rod can be read by a stroke sensor installed at the drive end of the telescopic fork; the plate size parameters are calculated based on the fitted plate profile, the length and width of the profile are calculated to obtain the actual external dimensions of the plate, including the length of the plate along the main axis and the width perpendicular to the main axis, as well as the approximate thickness range of the plate (estimated by combining the thickness data of historical plates of the same type and the size correspondence of the current profile's circumscribed rectangle); the preset safety margin parameter is a fixed value stored in the controller parameter library in advance, which is generally set according to the accuracy of the forklift equipment in the sorting warehouse and the common processing errors of the plate, usually between 5 mm and 15 mm, to avoid the insert rod colliding with the plate due to equipment errors or plate size deviations.

[0055] S332: Input the current extension length, plate size parameters, and safety margin parameters into the theoretical distance function to calculate the theoretical distance.

[0056] For example, after substituting the current extension length into the function to calculate the basic distance, the distance value is corrected by combining the estimated thickness range of the plate, and then a preset safety margin parameter is added. That is, a fixed buffer distance is reserved according to the safety margin parameter, and finally the theoretical distance that conforms to the current actual working conditions is obtained.

[0057] This design takes into account the deviation of the actual size of the board material and reserves a safe buffer space for the operation of the equipment, further improving the accuracy of the theoretical distance calculation and reducing the probability of collisions during the picking process.

[0058] S400, when the theoretical distance is less than a preset threshold, monitors the actual distance between the insert rod and the plate in real time based on the ranging sensor; the insert rod is a sub-component of the telescopic lifting fork.

[0059] It is understandable that the preset threshold refers to a pre-set critical distance used to determine whether the insertion rod is close to the board. When the theoretical distance is less than the threshold, it means that the insertion rod is close to the board, and the actual distance needs to be monitored in real time to avoid collision. The actual distance refers to the real distance between the front end of the insertion rod and the bottom surface of the board in the actual scenario. It may differ from the theoretical distance due to factors such as equipment error and board placement deviation. The insertion rod is a sub-component of the telescopic lifting fork, used to insert into the bottom of the board and drive the board to rise, fall and move. It is the core execution component for realizing the fork picking action.

[0060] For example, a miniature laser ranging sensor, specifically a detection component, can be embedded on the side of the insertion rod near the bottom surface of the board. The sensor's emitting end faces the bottom surface of the board and can emit a laser beam in real time at a sampling frequency of 100Hz, and receive the laser signal reflected back from the bottom surface of the board. By calculating the round-trip time of the laser, the real-time actual distance between the insertion rod and the bottom surface of the board can be directly obtained, and this distance data can then be transmitted to the main controller of the sorting warehouse in real time. Alternatively, the monitoring component can also use an ultrasonic ranging sensor. For low-density boards with large thickness variations, ultrasonic ranging can avoid interference from burrs on the board surface and obtain more stable actual distance data. The monitoring component can be replaced according to different application scenarios.

[0061] In one possible implementation, please refer to Figure 5 S400, when the theoretical distance is less than a preset threshold, monitors the actual distance between the insertion rod and the plate in real time based on the ranging sensor, including: S410 compares the theoretical distance with a preset threshold. When the theoretical distance is determined to be less than the preset threshold, the monitoring component collects the measured distance data between the front end of the insertion rod and the bottom surface of the plate in real time.

[0062] For example, the calculated theoretical distance is compared with a preset threshold, which can be 50 mm. When the theoretical distance is less than 50 mm, it indicates that the tip of the insertion rod has moved close enough to the plate, and the controller triggers the monitoring component without collecting the measured distance data. Each set of measured data collected by the monitoring component is transmitted to the main controller within 5 milliseconds, enabling the controller to obtain the latest distance information immediately and preventing delays in action control due to data transmission latency.

[0063] S420 processes the measured spacing data to obtain the actual distance.

[0064] For example, multiple sets of continuously acquired measured distance data are filtered. First, outliers caused by surface irregularities or environmental dust interference are removed. Then, the average of the remaining valid data is calculated to eliminate random errors from single measurements, resulting in a stable and accurate actual distance. For instance, if one set of data out of 10 continuously acquired data deviates by more than 10 millimeters from the others, it is identified as an outlier caused by interference and directly removed. The average of the remaining 9 sets of data is then calculated and used as the actual distance at the current moment. This avoids misjudgments by the controller due to interference data, improving the stability of distance monitoring. This setup, through outlier removal and averaging filtering, yields a more stable and accurate actual distance, avoiding measurement errors caused by environmental interference and providing reliable data support for precise control of subsequent forking actions.

[0065] In one possible implementation, the method also includes: A prompt message is received when the theoretical distance is greater than or equal to a preset threshold; the prompt message is used to indicate that the current position of the board deviates from the preset fork-and-grab range and to issue a reminder.

[0066] For example, when the theoretical distance is greater than or equal to a preset threshold, a prompt message is received. Specifically, this can be achieved through an audible and visual alarm device on the sorting warehouse control panel. The corresponding abnormal point indicator light on the control panel will flash, and a buzzer will sound at 1-second intervals to remind on-site maintenance personnel to check the current placement of the boards and confirm whether there are any problems such as boards tipping over or being seriously misaligned. In the case of unattended fully automated sorting operations, the prompt message can be directly transmitted to the back-end monitoring system, and an abnormal alarm window will pop up on the monitoring screen, recording the time of the abnormality, the aisle number where the abnormal board is located, and its approximate coordinates, facilitating remote troubleshooting and handling by maintenance personnel.

[0067] This setup allows for the early detection of boards with excessively large positional deviations, preventing the forklift equipment from repeatedly adjusting but still failing to complete the pick-up, wasting sorting time, or even causing equipment collision damage, thus improving the fault tolerance and safety of the entire automated sorting warehouse operation.

[0068] S500 obtains first extension information or second extension information by comparing the actual distance and the theoretical distance in real time; wherein, the first extension information is used to indicate to continue extending at the current speed, and the second extension information is used to indicate to reduce the extension speed to a preset speed.

[0069] For example, it can be achieved by comparing the actual distance and the theoretical distance in real time. If the difference between the actual distance and the theoretical distance within the absolute value is less than or equal to a preset allowable error threshold, the first extension information is obtained. If the difference between the actual distance and the theoretical distance within the absolute value is greater than the preset allowable error threshold, the second extension information is obtained.

[0070] In one possible implementation, please refer to Figure 9 The S500 obtains first or second extension information by comparing the actual distance with the theoretical distance in real time, including: S510, compare the actual distance and the theoretical distance in real time, and if the difference between the actual distance and the theoretical distance within the absolute value is less than or equal to the preset allowable error threshold, the first extension information is obtained.

[0071] For example, the preset allowable error threshold is usually set in advance according to the equipment accuracy and the type of board material, and is usually set between 3 mm and 8 mm. When the absolute value of the difference between the two does not exceed this value, it means that the deviation between the current actual distance and the theoretical distance is within an acceptable range, and the actual direction of the fork path is consistent with the pre-planned optimized path. At this time, the first extension information is generated, and the control lever continues to move towards the board material at the current deceleration extension speed without additional speed adjustment, ensuring the smoothness of the fork action and preventing the sorting efficiency from being reduced due to frequent speed adjustments.

[0072] S520, if the difference between the actual distance and the theoretical distance within the absolute value is greater than the preset allowable error threshold, the second extension information is obtained.

[0073] For example, when the absolute value of the difference exceeds the preset allowable error threshold, it indicates that there is a large deviation between the current actual distance and the theoretical distance. This may be due to the discrepancy between the actual thickness of the board and the pre-estimated thickness, or it may be due to slight warping of the board during placement, causing a change in the height of the bottom surface of the board. At this time, a second extension information is immediately generated, and the control rod is reduced to a preset low speed level. Typically, the preset low speed is only one-third to one-half of the original extension speed, allowing the rod to approach the board at a slow speed, giving the controller sufficient adjustment time, and preventing the rod from scraping the bottom surface of the board due to excessive deviation, thus improving safety.

[0074] With this setup, when the deviation exceeds the allowable range, a second extension message is generated in a timely manner and the speed is reduced, which can effectively prevent the insertion rod from colliding with the plate and ensure the safety of the equipment and the plate. After deceleration, there is sufficient time to adjust the deviation and ensure the accuracy of the forklift action. At the same time, continuous comparison and speed adjustment based on deviation changes can achieve dynamic control, improve the stability and safety of the forklift process, and avoid sorting failures caused by deviation.

[0075] S600 determines the actual thickness of the sheet material based on the first or second protrusion information.

[0076] For example, determining the actual thickness of the board can be achieved by gradually extending the insertion rod along the optimized fork path until the actual distance collected by the monitoring component becomes 0, indicating that the tip of the insertion rod has reached the bottom surface of the board. At this point, the final extension length of the insertion rod is recorded, and this length is substituted into the corrected theoretical distance function for reverse calculation to obtain the actual thickness of the board at the current position. Specifically, when the insertion rod reaches the bottom surface of the board, the coordinates of the tip of the insertion rod can be directly calculated using the extension length and deflection angle. The vertical coordinates of the target point of the fork action are known fixed values. The actual thickness of the board can be deduced from the difference in the vertical coordinates. For example, if the estimated thickness of the board is 18 mm, and the calculated actual thickness is 17.2 mm, it means that the actual thickness of the board is 0.8 mm thinner than the standard value. In the case of warping deformation of the board, the actual distance at different extension lengths can be collected multiple times during the extension of the insertion rod. The thickness of the board at different positions can be obtained through multiple calculations, and the average value is taken as the actual thickness of the board. Alternatively, the actual thickness of the board can be obtained by combining the first extension information or the second extension information with the monitoring component to confirm that the insertion rod has fully entered the bottom of the board.

[0077] In one possible implementation, please refer to Figure 7 S600, based on the first protrusion information or the second protrusion information, determines the actual thickness of the sheet metal, including: S610, after the monitoring component confirms that the insertion rod has fully entered the bottom of the plate, it determines the position feedback information in combination with the first extension information or the second extension information; wherein, the position feedback information is used to indicate the coordinates of the starting point of the insertion rod extension and the coordinates of the ending point of the insertion rod.

[0078] For example, when the insertion rod extends continuously until the actual distance is detected to be zero, it can be determined that the front end of the insertion rod has been in contact with the bottom surface of the board and has completed the action of entering the bottom of the board. At this time, the total displacement of the insertion rod from the starting point to the end point can be directly read by the stroke sensor of the insertion rod. Combined with the coordinate information of the initial position of the fork arm, the coordinates of the starting point of the insertion rod extension and the coordinates of the ending point of the insertion rod can be clearly recorded, that is, the position feedback information.

[0079] S620 determines the actual thickness of the sheet material based on location feedback information and the actual distance measured by the monitoring components at the last monitoring point.

[0080] For example, first calculate the difference between the endpoint coordinates and the starting coordinates in the horizontal direction in the position feedback information to obtain the actual total extension length of the insertion rod. Then, combine the deflection angle of the fork arm to calculate the displacement increment of the insertion rod in the vertical direction. Then, combine the preset starting height of the fork gap, subtract the vertical displacement increment, and add the actual distance correction value obtained from the last monitoring to obtain the actual thickness of the plate.

[0081] For example, if the preset starting height of the fork gap is 1200 mm, the total extension length of the insert is 800 mm, and the deflection angle of the fork arm after correction is 3 degrees, then the displacement increment of the insert in the vertical direction is 800 × sin3° ≈ 41.8 mm. The actual distance correction value obtained from the last monitoring is 0.3 mm. The final calculated actual thickness of the plate is 1200 - 41.8 + 0.3 = 1158.5 mm.

[0082] This setup, which combines location feedback information with the final actual distance for thickness calculation, eliminates the need for additional large-scale detection equipment. It can obtain accurate actual thickness data solely by relying on the existing sensors during the forklift operation, without increasing the equipment cost of the sorting warehouse. At the same time, the calculation process is completed synchronously with the forklift action, without requiring additional stops for detection, and will not reduce the overall efficiency of sheet material sorting.

[0083] The S700 process obtains the horizontal deviation and placement endpoint position based on the actual thickness of the board material, and then performs sorting control on the board material according to the horizontal deviation and placement endpoint position.

[0084] It's understandable that comparing the actual thickness obtained with the standard thickness of the same board material allows for the calculation of the horizontal deviation after placement. This means determining the board's tilt angle relative to a horizontal reference point, based on the difference in thickness at different locations. This is then combined with the total actual thickness of the board to adjust the height of the placement endpoint. For example, a standard board material labeled as 18 mm thick might have actual thicknesses of 18.1 mm and 17.3 mm at its left and right positions, respectively, with a horizontal distance of 1200 mm between them. The calculated tilt angle is approximately 0.038 degrees, and the corresponding horizontal deviation is this angle. The height of the placement endpoint is then adjusted based on the average of the actual thicknesses at multiple locations plus the total height of the stacked boards, ensuring accurate placement and preventing stacking errors due to thickness discrepancies.

[0085] This setup, by calculating the actual thickness to obtain the horizontal deviation and accurate placement endpoint, can adapt to the thickness tolerances present in the board manufacturing process and can also offset the deformation errors caused by long-term use of the storage location, keeping the board stable. It can solve the problem that traditional solutions lack the ability to perceive and adapt to the board's posture, actual thickness, and storage location status due to reliance on preset parameters and fixed programs, which leads to the insertion rods being prone to collisions and unstable storage.

[0086] In one possible implementation, please refer to Figure 8 S700 processes the actual thickness of the board material to obtain the horizontal deviation and placement endpoint position, and performs sorting control on the board material based on the horizontal deviation and placement endpoint position, including: S710 obtains the actual height and level deviation based on the actual thickness of the plate and by performing multi-point scanning of the target storage location support surface using monitoring components.

[0087] For example, after the insertion rod transports the sheet material to the target storage location, the insertion rod is first controlled to drive the monitoring component to complete height detection at the four corners and center of the target storage location's support surface, obtaining the actual height values ​​of five detection points. The difference between these five height values ​​and the preset standard horizontal reference height is used to obtain the height deviation at each detection point. Then, the tilt angle of the entire support surface is calculated using a spatial plane fitting algorithm, thus obtaining the levelness deviation. For instance, if the preset standard horizontal reference height of the target storage location's support surface is 2400 mm, and the actual heights obtained at the five detection points are 2400.1 mm, 2399.8 mm, 2400.3 mm, 2399.7 mm, and 2400.0 mm respectively, after plane fitting calculation, the levelness deviation of the support surface is found to be 0.02 degrees, meeting the storage requirements.

[0088] S720 determines the placement endpoint based on the actual thickness and height of the board.

[0089] For example, the placement endpoint can be obtained by adding the average actual height calculated from the actual thickness of the target material and the actual height of the five detection points on the support surface of the target storage location. This gives the endpoint height coordinates where the insertion rod will be in place when the material is placed. Combining this with the preset horizontal placement coordinates of the target storage location yields the complete placement endpoint position. For instance, if the average actual height of the target storage location support surface is 2400.02 mm and the actual thickness of the material to be placed is 17.9 mm, then the height coordinates of the placement endpoint would be 2400.02 + 17.9 = 2417.92 mm. Compared to directly using the standard thickness of 18 mm to calculate 2418 mm, the error is reduced by 0.08 mm, resulting in a significant improvement in accuracy.

[0090] The S730 controls the sorting of boards by measuring horizontal deviation and placement endpoint position.

[0091] For example, the tilt angle of the insertion rod is adjusted according to the calculated levelness deviation so that the bottom surface of the board is always parallel to the support surface of the storage location, avoiding stress deformation caused by local suspension after the board is placed. Then, the insertion rod is controlled to descend into place according to the obtained placement endpoint position to complete the storage and sorting of the board.

[0092] This setup allows for the accurate measurement of the levelness deviation and placement height by scanning and detecting the actual support surface of the target storage location. This can accommodate errors caused by the natural settlement and wear deformation of the storage location support components after long-term use of the automated warehouse, preventing the panels from tilting and slipping after placement. This significantly improves the stability and safety of the panels during storage. At the same time, the automatic identification and alerting of abnormal storage locations reduces the workload of manual inspections and improves operation and maintenance efficiency.

[0093] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0094] Figure 10 This is a schematic diagram of the controller provided in one embodiment of this application. Figure 10 As shown, the controller 60 of this embodiment includes: at least one processor 61 ( Figure 10 Only one is shown in the image), at least one memory 62 ( Figure 10 (Only one is shown in the image) and a computer program 63 stored in the at least one memory 62 and executable on the at least one processor 61. When the processor 61 executes the computer program 63, it causes the controller 60 to implement the steps in any of the above embodiments of the controller 60 of the intelligent three-dimensional sorting warehouse for sheet materials, or causes the controller 60 to implement the functions of each module / unit in the above system embodiments.

[0095] Exemplarily, the computer program 63 may be divided into one or more modules / units, which are stored in the memory 62 and executed by the processor 61, thus fulfilling this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 63 in the controller 60.

[0096] The controller 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will understand that... Figure 10The example of controller 60 is merely an illustration and does not constitute a limitation on controller 60. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0097] The processor 61 can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0098] In some embodiments, the memory 62 may be an internal storage unit of the controller 60, such as a hard disk or memory of the controller 60. In other embodiments, the memory 62 may be an external storage device of the controller 60, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the controller 60. Furthermore, the memory 62 may include both internal storage units and external storage devices of the controller 60. The memory 62 is used to store operating systems, applications, bootloaders, data, and other programs, such as the program code of computer programs. The memory 62 can also be used to temporarily store data that has been output or will be output.

[0099] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A plate intelligent three-dimensional sorting warehouse, comprising a warehouse frame, a plurality of layers of storage positions arranged on the warehouse frame, a material conveying table installed at the bottom of the warehouse frame, load-bearing columns installed at the side of the warehouse frame, and telescopic lifting forks installed on the load-bearing columns, characterized in that, The intelligent three-dimensional sorting warehouse for sheet materials also includes: A monitoring component is mounted on the telescopic lifting fork; the monitoring component includes a vision sensor and a distance sensor; the vision sensor is mounted on one side of the insertion rod of the telescopic lifting fork and is used to acquire an image of the plate at the end of the plate; the distance sensor is mounted along the extension direction of the insertion rod and is used to measure the actual distance between the end of the insertion rod and the position where the plate is to be contacted; and The controller is communicatively connected to the visual sensing unit and the ranging sensing unit; the controller is configured to: The visual sensing unit acquires an image of the board material and determines the outline of the board material based on the image. The coordinates of the center point of the board and its angular deviation from the preset direction are determined based on the board's outline. The theoretical distance is obtained by analyzing the coordinates of the center point of the plate and the angular deviation from the preset direction; When the theoretical distance is less than a preset threshold, the actual distance between the insert rod and the plate is monitored in real time based on the ranging sensor; wherein, the insert rod is a sub-component of the telescopic lifting fork; The first extension information or the second extension information is obtained by comparing the actual distance and the theoretical distance in real time; wherein, the first extension information is used to indicate to continue extending at the current speed, and the second extension information is used to indicate to reduce the extension speed to a preset speed; The actual thickness of the plate is determined based on the first or the second protrusion information; The actual thickness of the board material is used to obtain the horizontal deviation and the placement endpoint position, and the board material is sorted and controlled according to the horizontal deviation and the placement endpoint position.

2. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The step of analyzing the coordinates of the center point of the plate and the angular deviation from the preset direction to obtain the theoretical distance includes: The position information of the fork arm is obtained, and the target point of the fork-taking action is determined based on the position information, the coordinates of the center point of the plate and the angular deviation from the preset direction. Based on the target point of the forking action, an optimized forking path is obtained with the actual center of the plate as the reference, and a theoretical distance function between the front end of the insertion rod and the bottom surface of the plate is generated under the optimized forking path. The theoretical distance is obtained based on the theoretical distance function.

3. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, When the theoretical distance is less than a preset threshold, the method of real-time monitoring of the actual distance between the insertion rod and the plate based on the ranging sensor includes: The theoretical distance is compared with a preset threshold. When the theoretical distance is determined to be less than the preset threshold, the measured distance data between the front end of the insertion rod and the bottom surface of the plate is collected in real time according to the ranging sensor. The actual distance is obtained by processing the measured distance data.

4. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The step of determining the coordinates of the center point of the board and its angular deviation from the preset direction based on the board's contour includes: Geometric center processing is performed on the outline of the plate to obtain the coordinates of the center point of the plate. The main axis direction of the plate profile is determined, and the angle deviation is obtained by comparing and analyzing the main axis direction with the preset storage location reference axis direction.

5. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 2, characterized in that, The process of obtaining the theoretical distance based on the theoretical distance function includes: Determine the current extension length of the insertion rod, the plate size parameters determined based on the plate profile, and the preset safety margin parameters; The theoretical distance is calculated by inputting the current extension length, the plate size parameters, and the safety margin parameters into the theoretical distance function.

6. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The visual sensing unit acquires an image of the board material and determines the board material outline based on the image, including: The image of the board material is converted to grayscale to obtain a grayscale image, and edge detection processing is performed on the grayscale image to obtain edge features; The profile of the plate is obtained by contour fitting based on the edge features.

7. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, Determining the actual thickness of the plate based on the first protrusion information or the second protrusion information includes: When the monitoring component confirms that the insertion rod has fully entered the bottom of the plate, it determines position feedback information by combining the first extension information or the second extension information; wherein, the position feedback information is used to indicate the coordinates of the insertion rod extension start point and the insertion rod end point. The actual thickness of the plate is obtained based on the location feedback information and the actual distance measured by the monitoring component in the last monitoring.

8. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The process of obtaining the horizontal deviation and placement endpoint position based on the actual thickness of the board material, and then performing sorting control on the board material according to the horizontal deviation and placement endpoint position, includes: The actual height and levelness deviation are obtained based on the actual thickness of the plate and by performing multi-point scanning of the target storage location support surface using the monitoring component. The placement endpoint position is obtained based on the actual thickness and actual height of the plate. The sorting control of the boards is achieved by using the levelness deviation and the placement endpoint position.

9. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The method includes: A prompt message is obtained when the theoretical distance is greater than or equal to a preset threshold; wherein, the prompt message is used to indicate that the current position of the board deviates from the preset fork-and-take range and to issue a reminder message.

10. The intelligent three-dimensional sorting warehouse for sheet metal as described in claim 1, characterized in that, The step of obtaining the first extension information or the second extension information by real-time comparison of the actual distance and the theoretical distance includes: The actual distance and the theoretical distance are compared in real time. If the difference between the actual distance and the theoretical distance in absolute value is less than or equal to a preset allowable error threshold, the first extension information is obtained. If the difference between the actual distance and the theoretical distance within the absolute value is greater than the preset allowable error threshold, the second extension information is obtained.

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