Control method and system for automatic feeding and assembling of plywood

Abstract

The invention provides a control method and system for automatic feeding and assembling of plywood, and the method comprises the steps: obtaining the formula information of to-be-assembled plywood input by a user and the demand quantity of each plate type, according to the formula information, all plate types needed by the plywood to be assembled are input into the corresponding chain machines, and whether the plates needed by the plywood to be assembled are sufficient or not is judged based on the stock information of the plates on all the chain machines and the demand quantity of all the plate types; and the robot is controlled to carry out feeding operation on the plates on the chain machines on the basis of the formula information, the multiple grabbed target plates are placed at the preset positions to be assembled, the target plywood is obtained, and automatic plywood feeding and assembling which is flexible, efficient and capable of meeting diversified assembling requirements is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of automatic plywood feeding and blanking, and in particular to a control method and system for automatic plywood feeding and blanking. Background Art

[0002] In current industrial production, the assembly process of plywood is usually done manually, which has problems such as low efficiency and high labor intensity. In order to improve the automation degree and production efficiency of the assembly process, some studies have explored the method of using robots to automatically load and assemble plywood. However, most of the existing methods are limited to simple assembly of a single type of board, lacking flexibility and adaptability.

[0003] For example, some studies use robots to arrange pre-defined boards in a specified quantity and order through visual recognition and grasping technology to complete basic assembly. However, this method is difficult to adapt to the production needs of plywood of different models and grades, and requires detailed manual programming and adjustment of the robot, which is complicated to operate. In addition, some studies use manipulators in conjunction with chain systems to achieve automatic handling and assembly of boards. However, this system relies on fixed board size and arrangement, and cannot cope with plywood of different specifications and that requires flexible assembly.

[0004] In the technical solution with application number CN 202210168300.5, although it sets up standard sections, each standard section includes a horizontal-grained board station and a vertical-grained board station, obtains plywood processing data and robot information, sets the number of robots on the horizontal-grained board station and the vertical-grained board station according to the plywood processing data and robot information, sets a corresponding number of robots on the horizontal-grained board station and the vertical-grained board station, establishes an equipment matching table, obtains on-site installation conditions, obtains the corresponding type and quantity of equipment to be used in combination from the equipment matching table according to the number of robots set and on-site installation conditions, sets the equipment to be used in combination at the corresponding position in the standard section, sets a corresponding number of standard sections according to on-site installation conditions, and completes the layout of the processing production line. However, this method also relies on fixed board size and arrangement, and cannot cope with plywood of different specifications and that requires flexible assembly.

[0005] Therefore, based on the above situation, there is an urgent need for a more flexible and efficient plywood automatic loading and assembly method that can meet the diverse assembly needs. Summary of the invention

[0006] The invention provides a control method and system for automatic plywood feeding and blanking, so as to realize the automatic plywood feeding and blanking which is flexible and efficient and can meet the diversified blanking requirements.

[0007] To solve the above problems, the present invention adopts the following technical solutions: The present invention provides a control method for automatic plywood feeding and assembly, which is applied to a control device and comprises: Obtain the formula information of the plywood to be assembled and the demand for each type of board entered by the user; Entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the recipe information; Based on the inventory information of the panels on each chain machine and the demand for each type of panels, determine whether the panels required for the plywood to be assembled are sufficient; When it is determined that the required panels for the plywood to be assembled are sufficient, the robot is controlled based on the recipe information to load the panels on each of the chain machines, and the captured multiple target panels are placed at preset positions for assembly to obtain the target plywood.

[0008] Furthermore, before entering the types of panels required for the plywood to be assembled into the corresponding chain machine based on the recipe information, the method further includes: Check that all fields in the recipe information are filled in; When all fields in the recipe information have been filled in, determining that the integrity verification of the recipe information has passed; Verify the accuracy of the formula information; When the accuracy of the formula information is verified, the step of entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the formula information is performed; When the accuracy verification of the formula information fails, a prompt message for correcting the formula information is sent to the terminal to which the engineer belongs.

[0009] Preferably, verifying the accuracy of the recipe information includes: Based on each parameter of the recipe information, converting the recipe information into a probability matrix; Calculating the information entropy of each parameter based on the probability matrix, and calculating the natural logarithm of the information entropy of each parameter to obtain a coefficient of variation of each parameter, wherein the coefficient of variation reflects the degree of variation between the parameters; Calculate the ratio of the coefficient of difference of each parameter to the sum of the coefficients of difference of all parameters to obtain the weight of each parameter; Compare the formula information with the optimal formula information in the database parameter by parameter, calculate the difference between every two parameters, and perform weighted summation of the difference between every two parameters and the corresponding weight to obtain a comprehensive difference value; When the comprehensive difference value is less than a preset value, it is determined that the accuracy verification of the recipe information has passed.

[0010] Furthermore, after judging whether the required panels for the assembled plywood are sufficient based on the inventory information of the panels on each chain machine and the demand for each panel type, the method further includes: When it is determined that the required panels for the plywood to be assembled are insufficient, determining the first missing panel; generating a delivery instruction for the first panel, wherein the delivery instruction includes panel information of the first panel and a target production line entrance; Sending the delivery instruction to a panel warehouse, and controlling the panel warehouse to perform material retrieval and picking of the first panel based on the inventory location and material status of the first panel; The automatic guided vehicle of the panel warehouse is controlled to transport the picked first panel to the entrance of the target production line, and the automatic guided vehicle inside the production line is controlled to distribute the first panel from the entrance of the target production line to the corresponding chain machine.

[0011] Furthermore, after the automatic guided vehicle controlling the panel warehouse transports the picked first panel to the entrance of the target production line, the method further includes: Monitor whether there is a pad that needs to be recovered at the entrance of the target production line; When a backing plate needs to be recovered, the backing plate is preferentially transported to the backing position on the automatic guided vehicle of the panel warehouse; When the automatic guided vehicle inside the production line delivers the first panel from the entrance of the target production line to the corresponding chain machine, the automatic guided vehicle controlling the panel warehouse transports the pad to the recycling area.

[0012] Preferably, the controlling the robot to load the panels on each of the chain machines based on the recipe information comprises: Based on the recipe information and the requirements of the robot feeding operation task, determine the scale of the robot, the initial position and speed of the robot; A fitness function is defined according to the optimization objective of the loading operation task, and based on the fitness function, an initial fitness value is calculated for each robot, and an initial global fitness value of all robots is calculated; Update the robot's speed and position according to the robot's current speed, individual optimal position and global optimal position; Based on the fitness function, calculate the current fitness value for each robot, and calculate the current global fitness value of all robots; Compare the current fitness value of each robot with the corresponding individual optimal fitness value. If the current fitness value is greater than the corresponding individual optimal fitness value, update the robot's individual optimal position and initial fitness value. Compare the current global fitness value of all robots with the optimal global fitness value. If the current global fitness value is greater than the optimal global fitness value, update the global optimal position and initial global fitness value of the robot. When the initial global fitness value reaches the optimal value, an optimal feeding operation plan is generated; Based on the optimal loading operation plan, the robot is controlled to perform loading operations on the panels on each of the chain machines.

[0013] Preferably, the controlling the robot to load the panels on each of the chain machines based on the recipe information comprises: Based on the recipe information, each robot is controlled to grab the plate on the corresponding chain machine, and the position and movement state of each robot is monitored in real time; Dynamically calculating the stopping point of each robot according to the position, motion state and geometric dimensions of each robot; According to the vector distance constraint between the current posture of each robot and the stop point, when controlling each robot to perform a loading operation on the grasped panel, avoidance measures are executed, and the avoidance measures include deceleration or pause.

[0014] Preferably, the controlling the robot to load the panels on each of the chain machines based on the recipe information comprises: Based on the recipe information, a plurality of feeding operation tasks for feeding the plates on each of the chain machines are generated, and based on a preset ant colony algorithm, each of the feeding operation tasks is arranged in order to form a near-field related task chain; Dividing the task chain into near-field subsets according to the task locations to obtain a plurality of task subsets, wherein the tasks in each task subset are geographically close and are collaboratively completed by the same robot or the same group of robots; Each of the task subsets is assigned to each robot, and each of the robots is controlled to execute the corresponding task subset.

[0015] Preferably, placing the captured multiple target panels at preset positions for assembly to obtain target plywood comprises: Control each robot to place the captured multiple target panels to a preset position, and control the visual sensor and laser radar on the robot to start working to detect the edge position of each target panel; Inputting the detected edge position of each target plate into a preset particle swarm algorithm, optimizing the trajectory of each target plate, and obtaining the optimal adjustment trajectory of each target plate; According to the optimal adjustment trajectory of each target plate, the optimal motion trajectory is planned for each robot using a polynomial trajectory planning method; Each of the robots is controlled to adjust the edge position of the corresponding target panel according to the optimal motion trajectory, and the adjusted multiple target panels are assembled to obtain a target plywood.

[0016] In one embodiment, the present invention also provides a control system for automatic feeding and assembly of plywood, comprising a chain machine, a robot and a control device, wherein the control device is connected to the chain machine and the robot respectively, wherein the control device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the control method for automatic feeding and assembly of plywood as described above.

[0017] Compared with the prior art, the technical solution of the present invention has at least the following advantages: The control method and system for automatic feeding and assembling of plywood provided by the present invention can automatically transfer the type of panels required by the formula to the corresponding chain machine by obtaining the plywood formula information and the required number of panels input by the user, and control the robot to perform feeding operations on the panels on each chain machine based on the formula information, and place the captured multiple target panels to the preset position for assembly to obtain the target plywood. Therefore, when the production demand changes, such as the adjustment of the formula or the change of the panel type, the robot can be quickly adapted to different production tasks by updating the formula information and adjusting the robot's feeding strategy, so as to adapt to the production demand of plywood of different models and different formulas, and there is no need for manual detailed programming and adjustment of the robot, the operation is simple, and it does not rely on fixed sheet size and arrangement, so as to realize plywood of different specifications and flexible assembly requirements. In addition, by obtaining the inventory information of the panels on each chain machine in real time and comparing it with the demand in the formula, it is possible to accurately judge whether the panels required for the plywood to be assembled are sufficient, so as to avoid production delays caused by insufficient inventory and ensure the smooth progress of the production process. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of an embodiment of a control method for automatic plywood feeding and assembly according to the present invention; Figure 2 It is a flowchart of another embodiment of the control method for automatic feeding and assembling of plywood of the present invention; Figure 3 It is a flowchart of another embodiment of the control method for automatic feeding and assembling of plywood of the present invention; Figure 4 It is a structural block diagram of an embodiment of a control device for automatic plywood feeding and assembly according to the present invention; Figure 5 This is a structural block diagram of an embodiment of the control device of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0020] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The sequence numbers of the operations, such as S11, S12, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0021] It will be understood by those of ordinary skill in the art that, unless expressly stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0022] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as herein.

[0023] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] Please refer to Figure 1 The present invention provides a control method for automatic plywood feeding and assembly, which is applied to a control device of a control system for automatic plywood feeding and assembly. The control method may include the following steps: S11, obtaining the formula information of the plywood to be assembled and the demand quantity of each type of board entered by the user; S12, entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the recipe information; S13, judging whether the required panels for the plywood to be assembled are sufficient based on the inventory information of the panels on each chain machine and the demand for each panel type; S14. When it is determined that the panels required for the plywood to be assembled are sufficient, the robot is controlled based on the recipe information to load the panels on each of the chain machines, and the captured multiple target panels are placed at preset positions for assembly to obtain the target plywood.

[0025] This embodiment can provide an intuitive and easy-to-use user interface, through which the user can input the formula information of the plywood to be assembled, and the formula information can include the type of board for each layer of the plywood to be assembled and the chain hangar position where each board type is located, as well as the required quantity of each board type. The interface can be in the form of a table, a drop-down menu, an input box, etc., so that the user can quickly and accurately enter information.

[0026] The information entered by the user will be stored in the database in real time for subsequent processing and calling. The database can be a relational database or a non-relational database, which can be selected according to the structure of the data and the query requirements. At the same time, this embodiment will manage and maintain the data to ensure the integrity and accuracy of the data.

[0027] Secondly, this embodiment will parse the types and quantities of each board required for the plywood to be assembled based on the recipe information entered by the user. Then, according to the layout of the production line and the configuration of the chain machine, the corresponding board type is assigned to the corresponding chain machine. For example, if the recipe contains hardwood boards and softwood boards, the system will assign the hardwood boards to chain machine A and the softwood boards to chain machine B.

[0028] This embodiment can send the assigned panel type information to the corresponding chain machine through the communication interface with the chain machine. After receiving the information, the chain machine will start to prepare and transport the corresponding panels according to the preset program and parameters. At the same time, the control device will monitor the working status of the chain machine in real time to ensure the smooth supply of panels.

[0029] In addition, the control device will obtain the inventory information of the panels on each chain machine in real time, including the type, quantity, location and other data of the panels. Then, the acquired inventory information will be compared and analyzed with the demand in the formula. If the inventory quantity of a certain panel type is greater than or equal to the demand, it is considered that the panel is sufficient; if the inventory quantity is less than the demand, it is considered that the panel is insufficient. The control device will generate corresponding prompt information or alarm signals based on the judgment results.

[0030] Finally, this embodiment can plan the loading task for the robot according to the recipe information and the inventory of the panels. Task planning includes determining the robot's motion path, grasping sequence, placement position and other parameters to ensure that the robot can complete the loading operation efficiently and accurately.

[0031] The control device sends the loading task instructions and control parameters through the communication interface with the robot. After receiving the instructions, the robot will automatically move to the side of the chain machine according to the planned path and parameters to grab the target plate. Then, the robot places the grabbed plate in the preset assembly position, stacks and arranges it according to the recipe requirements. During the assembly process, this embodiment will also monitor the position and status of each layer of plate in real time to ensure that the alignment and tightness of the plate meet the requirements. If it is found that the plate is not placed in place or there is a quality problem, the robot's action will be adjusted in time or the loading task will be replanned.

[0032] For example, suppose a furniture manufacturing company needs to produce a batch of customized plywood. The user enters the formula information of the plywood to be assembled through the system interface, including the type, thickness and required quantity of hardwood and softwood boards. The control device allocates the hardwood and softwood boards to the corresponding chain machines according to the formula information, and obtains the inventory information of the chain machines in real time to determine whether the required panels are sufficient. After confirming that there are sufficient panels, the robot is controlled to load the materials. The robot grabs the hardwood and softwood boards from the chain machines according to the planned path and sequence, and places them in the preset assembly position for precise stacking and arrangement, and finally obtains plywood that meets the requirements.

[0033] The control method for automatic feeding and assembling of plywood provided by the present invention can automatically transfer the type of panels required by the formula to the corresponding chain machine by obtaining the plywood formula information and the required number of panels input by the user, and control the robot to perform feeding operations on the panels on each chain machine based on the formula information, and place the captured multiple target panels to the preset position for assembly to obtain the target plywood. Therefore, when the production demand changes, such as the adjustment of the formula or the change of the panel type, the robot can be quickly adapted to different production tasks by updating the formula information and adjusting the feeding strategy of the robot, so as to adapt to the production demand of plywood of different models and different formulas, and there is no need for manual detailed programming and adjustment of the robot, the operation is simple, and it does not rely on fixed sheet size and arrangement, so as to realize plywood of different specifications and flexible assembly. In addition, by obtaining the inventory information of the panels on each chain machine in real time and comparing it with the demand in the formula, it is possible to accurately judge whether the panels required for the plywood to be assembled are sufficient, so as to avoid production delays caused by insufficient inventory and ensure the smooth progress of the production process.

[0034] In one embodiment, the control system may be composed of 12 robots, 4 RGVs, 4 heavy-load lifting and transplanting machines, 4 heavy-load hydraulic lifts, 24 heavy-load chain machines, three sets of rear-end conveyor lines and a set of panel warehouse distribution system. Among them, the heavy-load hydraulic lift is used to achieve docking with the automatic guided vehicle of the front-end panel warehouse to realize the supply and return of materials. The heavy-load lifting and transplanting is used to realize the connection between the heavy-load hydraulic lift and the automatic guided vehicle inside the production line for supply and return of materials. The automatic guided vehicle inside the production line can be used to realize the supply and return of materials for the heavy-load chain machine. The heavy-load chain machine is used to realize feeding of the robot. The robot is used to realize the removal of the heavy-load chain machine and feed the rear-end conveyor line.

[0035] Specifically, workers can input or select the formula information of the plywood to be processed through the production line system interface, and the system will automatically verify the completeness and accuracy of the formula information. If the formula information is incorrect, the system will prompt the worker to make corrections. If there is no board of the corresponding board type on the chain machine and the storage location is empty, the production line system will automatically generate delivery instructions. These instructions include the specific information of the required board and the delivery destination.

[0036] After receiving the instruction, the panel warehouse automatically retrieves and picks the materials. The system optimizes the picking path and time according to the inventory location and material status. The automatic guided vehicle in the panel warehouse delivers the required panels to the entrance of the designated production line accurately.

[0037] During the distribution process, the system monitors the material status in real time to ensure that data transmission is not lost. At the same time, during the distribution process of the automatic guided vehicle in the panel warehouse, the system monitors in real time whether there are pads that need to be recycled at the entrance of the production line. If there are pads to be recycled, the pads will be automatically transported to the unloading position on the automatic guided vehicle first, and then the distribution task will continue. After the distribution is completed, it will switch to the task of transporting the pads to the recycling area.

[0038] The automated guided vehicles inside the production line deliver the panels from the production line entrance to the corresponding chain conveyor. The automated guided vehicles can efficiently complete internal transportation tasks according to the preset route, and have precise positioning capabilities, which can accurately place the panels at the designated position of the chain conveyor. This process does not require human intervention, greatly improving production efficiency and accuracy.

[0039] When the required panels are in place, the robot starts to perform automatic loading operations. The robot accurately grabs and places the panels to the specified location based on the recipe information and the required quantity of each panel type. When configuring panels, the robot will comprehensively consider the recipe requirements, the avoidance of adjacent robots, and the conveyor line signals.

[0040] In addition, the system can also optimize the configuration order and path of the panels through improved algorithms to improve production efficiency. At the same time, the system can also realize the reasonable scheduling of robot tasks through programming to avoid robots entering the same area at the same time due to unreasonable task allocation, and reasonably arrange the tasks and work areas of each robot according to the order tasks and the working status of the robots through the system to ensure that the robots work in an orderly manner without interfering with each other. In addition, according to the specific situation of the panels, workers can switch whether the robot needs to perform the automatic edge placement function through the system interface. When this function is enabled, the robot will automatically detect and adjust the position of the edge of the panel to align it accurately. This function further improves the quality and consistency of the product.

[0041] The entrance inspection process of the heavy-duty hydraulic lift is as follows: when there are no panels on each line, and the panels on the panel warehouse delivery cart are delivered to the line and are the panels required by the line, the panels on the panel warehouse delivery cart are allowed to enter the heavy-duty hydraulic lift. If the panel types of all lines are already the required panel types, the panels on the panel warehouse delivery cart will be directly prohibited from entering the heavy-duty hydraulic lift.

[0042] When the heavy-load hydraulic lifting platform receives the plate and enters the heavy-load jacking and transplanting, it will request the automatic guided vehicle inside the production line to perform the feeding operation. If there is already a pad on the automatic guided vehicle, it will complete the feeding task first and then perform the pad withdrawal task. After completing the material connection, it will use the positions of each chain machine pre-stored in the system for precise positioning, and then start the feeding process.

[0043] In one embodiment, before entering the types of panels required for the to-be-assembled plywood into the corresponding chain machine based on the recipe information, the method further includes: Check that all fields in the recipe information are filled in; When all fields in the recipe information have been filled in, determining that the integrity verification of the recipe information has passed; Verify the accuracy of the formula information; When the accuracy of the formula information is verified, the step of entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the formula information is performed; When the accuracy verification of the formula information fails, a prompt message for correcting the formula information is sent to the terminal to which the engineer belongs.

[0044] After receiving the recipe information entered by the user, a data integrity check is first performed to ensure that each required field in the recipe information has been filled in. The required fields may include panel type, required quantity, size, glue type, etc. For example, a preset field list can be used to verify whether each field has valid data.

[0045] If any fields are found to be missing, the control device will immediately provide feedback to the user, indicating which fields are missing and prompting the user to complete the information to ensure that the data basis for subsequent processing is complete.

[0046] Once all fields are confirmed filled, the control device marks the integrity verification of the recipe information as passed.

[0047] After the integrity verification is passed, the control device further verifies the accuracy of the recipe information, including checking whether the field data conforms to the preset format and logic rules. For example, the required quantity field should be a positive integer, the size field should conform to the actual production range, and the plate type should exist in the predefined type list.

[0048] In addition to format and range checks, logical consistency checks are also performed. For example, if a recipe requires a special treatment (such as waterproofing), the corresponding board type and glue type should be compatible with it.

[0049] If the accuracy of the recipe information is also verified, the types of panels required for the plywood to be assembled are entered into the corresponding chain machines according to the recipe information.

[0050] If the accuracy verification of the recipe information fails, the control device will send a detailed error report and correction tips to the terminal to which the engineer belongs. The report will indicate which fields have problems and the recommended correction direction to ensure that the engineer can find and correct the errors in time to avoid production delays or quality problems caused by erroneous information.

[0051] This embodiment can ensure the high quality of recipe information through integrity checking and accuracy verification, provide reliable data support for the production process, and promptly discover and correct erroneous information, thereby avoiding production delays and quality problems caused by erroneous recipes and improving production efficiency and product quality.

[0052] In one embodiment, verifying the accuracy of the recipe information includes: Based on each parameter of the recipe information, converting the recipe information into a probability matrix; Calculating the information entropy of each parameter based on the probability matrix, and calculating the natural logarithm of the information entropy of each parameter to obtain a coefficient of variation of each parameter, wherein the coefficient of variation reflects the degree of variation between the parameters; Calculate the ratio of the coefficient of difference of each parameter to the sum of the coefficients of difference of all parameters to obtain the weight of each parameter; Compare the formula information with the optimal formula information in the database parameter by parameter, calculate the difference between every two parameters, and perform weighted summation of the difference between every two parameters and the corresponding weight to obtain a comprehensive difference value; When the comprehensive difference value is less than a preset value, it is determined that the accuracy verification of the recipe information has passed.

[0053] In this embodiment, each parameter in the recipe information may be standardized first so that its value range is between 0 and 1.

[0054] The standardized parameter values ​​are then converted into a probability matrix. Each element in the probability matrix represents the relative importance or probability of the corresponding parameter in the recipe information. For example, if there are three parameters A, B, and C in the recipe information, and their standardized values ​​are 0.2, 0.5, and 0.3, respectively, the probability matrix can be expressed as [0.2, 0.5, 0.3].

[0055] Information entropy is an indicator to measure parameter uncertainty. For each parameter, its information entropy is calculated based on the probability matrix. The calculation formula of the information entropy is: ; Wherein, n is the number of parameters, is a probability matrix, which represents the probability value of the i-th parameter under the j-th index. is the information entropy.

[0056] The coefficient of difference is the natural logarithm of information entropy, and the calculation formula is D(j)=ln( ), where D(j) is the coefficient of variation. The coefficient of variation reflects the degree of variation between parameters. The larger the coefficient of variation, the greater the degree of variation between parameters.

[0057] The sum of the coefficients of variation of all parameters is calculated, and the ratio of the coefficient of variation of each parameter to the sum of the coefficients of variation of all parameters is calculated to obtain the weight of each parameter, which is a measure of the relative importance of the parameter in the formulation.

[0058] Finally, each parameter in the recipe information is compared with the corresponding parameter in the optimal recipe information in the database, and the difference between them is calculated. The difference value can be calculated as an absolute difference or a relative difference. The difference between each two parameters is multiplied by the corresponding weight, and then summed to obtain a comprehensive difference value. The comprehensive difference value reflects the overall degree of difference between the recipe information and the optimal recipe information.

[0059] The preset value is a threshold used to judge the accuracy of the recipe information, which can be set according to actual production experience and requirements. For example, it can be set to 0.1.

[0060] When the comprehensive difference value is less than the preset value, it means that the difference between the recipe information and the optimal recipe information is small, and it can be considered that the accuracy of the recipe information has been verified and meets the production requirements.

[0061] This embodiment can accurately evaluate the accuracy of the recipe information through information entropy and difference coefficient, avoid the subjectivity and error of human judgment, and comprehensively consider the differences and weights of various parameters in the recipe information, and can comprehensively evaluate the degree of difference between the recipe information and the optimal recipe, thereby improving the reliability of the verification results. At the same time, when the accuracy verification of the recipe information fails, the key parameters affecting the accuracy can be found out based on the comprehensive difference value and weight analysis, providing guidance for the optimization of the recipe. In addition, ensuring the accuracy of recipe information helps to improve production efficiency and product quality, reduce production delays and product defects caused by recipe errors, and reduce production costs.

[0062] Please refer to Figure 2 In one embodiment, after judging whether the required panels for the assembled plywood are sufficient based on the inventory information of the panels on each chain machine and the demand for each panel type, the method further includes: S15, when it is determined that the panels required for the plywood to be assembled are insufficient, determining the missing first panel; S16, generating a delivery instruction for the first panel, wherein the delivery instruction includes panel information of the first panel and a target production line entrance; S17, sending the delivery instruction to the panel warehouse, and controlling the panel warehouse to perform material retrieval and picking for the first panel based on the inventory location and material status of the first panel; S18, controlling the automatic guided vehicle of the panel warehouse to transport the picked first panel to the entrance of the target production line, and controlling the automatic guided vehicle inside the production line to deliver the first panel from the entrance of the target production line to the corresponding chain machine.

[0063] When it is found that the inventory quantity of a certain type of board is less than the required quantity, the board will be determined as the first vacant board. For example, if 10 hardwood boards are required for the plywood to be assembled, but there are only 8 hardwood boards in the storage space on the chain conveyor, then the hardwood board is the first vacant board.

[0064] Generate a delivery instruction based on the determined missing panel information. The delivery instruction contains detailed information about the panel, such as panel type, specification, quantity, etc., as well as the location information of the target production line entrance, to ensure that the panel can be accurately delivered to the designated location. At the same time, the delivery instruction is formatted into a format that can be recognized and executed by the panel warehouse and the automatic guided vehicle, such as JSON, XML and other data formats, to facilitate subsequent transmission and processing.

[0065] The control device sends the generated delivery instructions to the management system of the panel warehouse through the network or other communication methods. After receiving the instructions, the warehouse management system will retrieve the materials in the warehouse according to the panel information in the instructions.

[0066] The warehouse management system controls the picking equipment or staff in the warehouse to accurately pick the first required board according to the inventory location and material status of the boards, such as storage area, shelf number, and whether the material is available. For example, an automated picking robot can quickly locate the storage location of hardwood boards according to instructions and pick them out from the shelf.

[0067] Control the AGV in the panel warehouse and plan an optimal transportation route based on the target production line entrance location in the delivery instruction. The AGV safely and efficiently transports the first panel picked to the target production line entrance along the planned route.

[0068] The control system of the production line takes over the distribution task of the panels, controls the automatic guided vehicles or conveyor belts inside the production line, and further distributes the first panel from the production line entrance to the corresponding chain conveyor. For example, the automatic guided vehicle inside the production line can identify the position of the chain conveyor and accurately place the hardwood board in the loading area of ​​the chain conveyor to ensure the smooth progress of the production process.

[0069] This embodiment can quickly respond to the material needs of the production line through automated and intelligent material retrieval, picking and distribution processes, improve material supply efficiency, reduce production delays caused by material shortages, and reduce the workload of manual material picking and handling, reducing labor costs and labor intensity, while avoiding errors and omissions that may occur in manual operations. In addition, it can monitor inventory conditions and production line needs in real time, adjust material distribution plans in a timely manner, and improve production flexibility and response speed to market changes.

[0070] In one embodiment, after the automatic guided vehicle controlling the panel warehouse transports the picked first panel to the entrance of the target production line, the method further comprises: Monitor whether there is a pad that needs to be recovered at the entrance of the target production line; When a backing plate needs to be recovered, the backing plate is preferentially transported to the backing position on the automatic guided vehicle of the panel warehouse; When the automatic guided vehicle inside the production line delivers the first panel from the entrance of the target production line to the corresponding chain machine, the automatic guided vehicle controlling the panel warehouse transports the pad to the recycling area.

[0071] In this embodiment, a sensor, such as a photoelectric sensor or a proximity sensor, can be installed at the entrance of the target production line to monitor in real time whether there is a pad. The sensor will send the detected signal to the control device of the production line. In addition to sensor detection, image acquisition devices such as industrial cameras can also be used to take real-time photos of the production line entrance area. Through image processing and recognition algorithms, it is determined whether there is a pad in the image, as well as the number and status of the pad.

[0072] After receiving the sensor signal or image recognition result, the control device performs data processing and judgment. If the pad is detected, it is determined that the pad needs to be recycled and the subsequent recycling process is triggered.

[0073] The control device generates a recovery instruction based on the detected pad information, which includes the recovery path of the pad, the position information of the backing plate, etc.

[0074] The recycling instruction is sent to the automated guided vehicle in the panel warehouse. After receiving the instruction, the automated guided vehicle will automatically plan an optimal transportation route based on the path and location information in the instruction, and transport the pad to the unloading position on the automated guided vehicle. The unloading position on the automated guided vehicle is a special area for placing the pads to be recycled, and is designed with corresponding fixtures or signs to ensure that the pads can be placed safely and accurately.

[0075] In the task scheduling of the automated guided vehicle, the priority of the pad recovery task is set higher than other tasks, such as the plate delivery task. This ensures that the pad can be recovered in time to avoid affecting the normal operation of the production line and the turnover of materials.

[0076] The control device communicates and coordinates with the AGV in the panel warehouse in real time. When the AGV in the production line successfully delivers the first panel to the chain conveyor, the control device sends a signal to the AGV in the panel warehouse to instruct it to start the task of recovering the pad.

[0077] The automated guided vehicle in the panel warehouse starts from the unloading position and transports the pallet to the recycling area along the planned path according to the path information in the recycling instruction. The recycling area is an area dedicated to storing recycled pallets, which is usually equipped with corresponding storage facilities or equipment, such as recycling boxes and recycling racks.

[0078] When the pad is successfully transported to the recycling area, the pad's recycling status information will be updated, recording the pad's recycling time, quantity and other data. This data can be used for subsequent inventory management and material analysis to help companies better understand the use and recycling of pads.

[0079] This embodiment can speed up the material turnover by recycling the pads in time, reduce the accumulation of pads at the entrance of the production line, and avoid affecting the normal entry of panels and the smooth progress of the production process. At the same time, the recycling and reuse of pads can reduce the demand for new pads, reduce the material procurement cost of the enterprise, and also reduce the economic losses caused by the waste of pads.

[0080] Please refer to Figure 3 In one embodiment, the step of controlling the robot to load the panels on each of the chain machines based on the recipe information includes: S141. Determine the scale, initial position and speed of the robot based on the recipe information and the requirements of the robot feeding operation task; S142, defining a fitness function according to the optimization goal of the loading operation task, and calculating an initial fitness value for each robot based on the fitness function, and calculating an initial global fitness value for all robots; S143, updating the speed and position of the robot according to the current speed, individual optimal position and global optimal position of the robot; S144. Based on the fitness function, calculate the current fitness value for each robot, and calculate the current global fitness value of all robots; S145, comparing the current fitness value of each robot with the corresponding individual optimal fitness value, if the current fitness value is greater than the corresponding individual optimal fitness value, updating the individual optimal position and initial fitness value of the robot; S146, comparing the current global fitness value of all robots with the optimal global fitness value, if the current global fitness value is greater than the optimal global fitness value, updating the global optimal position and initial global fitness value of the robot; S147, when the initial global fitness value reaches the optimal value, an optimal feeding operation plan is generated; S148. Based on the optimal loading operation plan, control the robot to load the panels on each of the chain machines.

[0081] In this embodiment, the control device parses the recipe information to determine the type, quantity and position of the required panels. The scale of the robot (i.e., the number of robots involved in the task), initial position and speed are determined according to the requirements of the loading operation task. For example, if the task requires grabbing panels on multiple chain machines, multiple robots may be required to work together, and the initial position and speed of each robot are set according to the position of the chain machine and the urgency of the task.

[0082] Among them, the fitness function is used to evaluate the completion of the robot's loading operation task, and is usually defined according to the optimization goal, such as minimizing the loading time, maximizing the task completion rate, etc. For example, the fitness function can be defined as the inverse of the time required to complete the task.

[0083] Calculate the initial fitness value for each robot, that is, the evaluation value of the robot completing the task at the initial position and speed. At the same time, calculate the initial global fitness value of all robots, that is, the overall evaluation value of all robots completing the task.

[0084] Based on the robot's current speed, individual optimal position, and global optimal position, the particle swarm optimization algorithm is used to update the robot's speed and position. After updating the position and speed, the fitness value is recalculated for each robot to evaluate its task completion in the new position. The current global fitness value of all robots is calculated to evaluate the overall task completion.

[0085] If the current fitness value of a robot is better than its individual optimal fitness value, the individual optimal position and fitness value of the robot are updated to ensure that each robot continuously moves to a better position during the search process.

[0086] If the current global fitness value is better than the optimal global fitness value, the global optimal position and fitness value are updated to ensure that the entire group continues to approach the global optimal solution during the search process.

[0087] When the updated initial global fitness value does not reach the optimal value, the steps S143-S146 are continued to be iterated until the updated initial global fitness value does not reach the optimal value. When the updated initial global fitness value reaches the preset optimal value, for example, when the change amplitude of the initial global fitness value in multiple consecutive iterations is lower than the preset threshold, it is determined that the initial global fitness value reaches the optimal value, and it is considered that the optimal feeding operation plan has been found. At this time, the position and speed of each robot are recorded as the optimal feeding operation plan.

[0088] According to the generated optimal loading operation plan, the robot is controlled to perform the loading operation. The robot grabs the panel according to the optimal path and speed and places it at the specified position to complete the loading task.

[0089] This embodiment can optimize the robot's feeding operation path and speed through the particle swarm optimization algorithm, reduce the robot's moving time and waiting time between different task locations, and improve production efficiency. At the same time, the tasks are reasonably assigned to each robot, which realizes the optimal allocation of resources, avoids task conflicts and resource waste between robots, and improves the utilization rate of equipment. In addition, by optimizing the task execution sequence and resource allocation, the robot's energy consumption and maintenance cost are reduced, the production cost is reduced, and the economic benefits of the enterprise are improved.

[0090] In one embodiment, the step of controlling the robot to load the panels on each of the chain machines based on the recipe information includes: Based on the recipe information, each robot is controlled to grab the plate on the corresponding chain machine, and the position and movement state of each robot is monitored in real time; Dynamically calculating the stopping point of each robot according to the position, motion state and geometric dimensions of each robot; According to the vector distance constraint between the current posture of each robot and the stop point, when controlling each robot to perform a loading operation on the grasped panel, avoidance measures are executed, and the avoidance measures include deceleration or pause.

[0091] In this embodiment, the type and quantity of panels that each robot needs to grab can be parsed based on the recipe information entered by the user, and this information can be assigned to the corresponding robot. The position and motion status of each robot are monitored in real time through sensors and visual systems. The data includes the robot's current position, speed, acceleration, etc., to ensure that the robot performs the task according to the predetermined path and speed.

[0092] The control device dynamically calculates the stopping point based on the current position, motion state and geometry of each robot. The calculation of the stopping point takes into account the robot's current position, speed, acceleration and safety parameters to ensure that the robot can stop safely when necessary.

[0093] The types of stop points include following stop points, calming stop points and curve protection stop points. Following stop points are used to avoid collisions between robots, calming stop points are used to handle path conflicts, and curve protection stop points are used to handle special path situations.

[0094] Calculate the vector distance constraint between the robot's current position and the stop point. When the vector distance is less than the set deceleration threshold, the robot is controlled to perform a deceleration operation; when the vector distance is less than the set stop threshold, the robot performs a stop operation.

[0095] According to the vector distance constraint, when the robot is performing a loading operation, if it detects a potential collision risk, it will automatically decelerate or pause to ensure safety.

[0096] This embodiment can perform avoidance measures by real-time monitoring and dynamically calculating the stop point according to the position, motion state and geometric dimensions of each robot, and according to the vector distance constraint between the current position and the stop point of each robot, so as to ensure that the robot can stop safely when necessary, avoid collision accidents, and improve the safety of the production environment. In addition, the robot can automatically adjust the motion state according to real-time data, reduce unnecessary waiting and delays, and improve production efficiency.

[0097] In one embodiment, the step of controlling the robot to load the panels on each of the chain machines based on the recipe information includes: Based on the recipe information, a plurality of feeding operation tasks for feeding the plates on each of the chain machines are generated, and based on a preset ant colony algorithm, each of the feeding operation tasks is arranged in order to form a near-field related task chain; Dividing the task chain into near-field subsets according to the task locations to obtain a plurality of task subsets, wherein the tasks in each task subset are geographically close and are collaboratively completed by the same robot or the same group of robots; Each of the task subsets is assigned to each robot, and each of the robots is controlled to execute the corresponding task subset.

[0098] First, the recipe information entered by the user is parsed to extract key parameters such as the type and quantity of each panel required for the plywood assembly, as well as the corresponding chain conveyor position. Based on the parsed recipe information, a loading operation task is generated for each panel. Each task contains detailed information such as the type, quantity, chain conveyor position, and target position of the panel.

[0099] Among them, the ant colony algorithm is an optimization algorithm that simulates the foraging behavior of ants and has good path search and optimization capabilities. The ant colony algorithm can be used to arrange the generated multiple feeding operation tasks in an orderly manner.

[0100] In the ant colony algorithm, each "ant" represents a task arrangement scheme, and the order of tasks is continuously updated through an iterative process. The algorithm gradually builds a near-field related task chain based on the correlation between tasks and the near-field relationship of geographical locations. The tasks in the task chain are arranged in a certain order so that the geographical locations of adjacent tasks are close, which facilitates subsequent task execution and resource allocation.

[0101] Secondly, according to the geographical location information of the tasks in the task chain, the task chain is divided into multiple task subsets. The tasks in each task subset are geographically close, for example, tasks located in the same area of ​​the production line are divided into one subset.

[0102] When dividing task subsets, the coordination between tasks and resource utilization are considered, and the tasks in each subset should be completed by the same robot or the same group of robots as much as possible to reduce task switching and moving distance between robots.

[0103] In addition, the divided task subsets can be assigned to each robot based on the robot's performance, location, and current working status. The robot's load balance and the urgency of the task are considered during the assignment to ensure that the task can be executed efficiently and reasonably.

[0104] After receiving the assigned task subset, the robot performs the loading operation according to the task requirements. The control device monitors the robot's execution in real time to ensure the smooth progress of the task and dynamically adjusts and optimizes according to the actual situation.

[0105] This embodiment can optimize the task arrangement and near-field subset division through the ant colony algorithm, reduce the movement distance and time of the robot between different task locations, improve production efficiency, and enable the robot to quickly respond to task requirements and shorten the production cycle. Reasonable allocation of task subsets to each robot realizes the optimal allocation of resources, avoids task conflicts and resource waste between robots, and improves the utilization rate of equipment. At the same time, it can flexibly adjust the task chain and task subsets according to changes in production needs and recipe information, adapt to different production tasks and panel types, and enhance production flexibility and adaptability. In addition, by optimizing the task execution sequence and resource allocation, multiple robots are centrally controlled to work together, feeding materials uninterruptedly, and automated control reduces manual intervention, reduces error rates, and significantly improves production efficiency.

[0106] In one embodiment, placing the captured multiple target panels at a preset position for assembly to obtain a target plywood comprises: Control each robot to place the captured multiple target panels to a preset position, and control the visual sensor and laser radar on the robot to start working to detect the edge position of each target panel; Inputting the detected edge position of each target plate into a preset particle swarm algorithm, optimizing the trajectory of each target plate, and obtaining the optimal adjustment trajectory of each target plate; According to the optimal adjustment trajectory of each target plate, the optimal motion trajectory is planned for each robot using a polynomial trajectory planning method; Each of the robots is controlled to adjust the edge position of the corresponding target panel according to the optimal motion trajectory, and the adjusted multiple target panels are assembled to obtain a target plywood.

[0107] This embodiment can allocate the captured multiple target panels to each robot according to the recipe information and production requirements, and specify them to be placed in the preset positions. The preset positions are determined according to the production process and equipment layout to ensure that the panels can smoothly enter the subsequent assembly process.

[0108] Start the visual sensor and laser radar on the robot. The visual sensor identifies the edge contour of the panel by taking an image of the panel; the laser radar accurately measures the distance between the panel edge and the preset position by emitting a laser beam and receiving the reflected signal. The data collected by the sensor includes the position coordinates, shape characteristics and other information of the panel edge.

[0109] Among them, the particle swarm optimization algorithm can also be used for trajectory optimization. The algorithm takes the edge position of each plate as input and searches for the optimal adjustment trajectory by simulating the movement process of the particle swarm. Each particle in the algorithm represents a possible trajectory solution. The particle moves in the search space and evaluates the quality of each solution according to the fitness function (such as minimizing the edge deviation). By iteratively updating the position and velocity of the particles, it eventually converges to the optimal solution, that is, the optimal adjustment trajectory of each plate.

[0110] Polynomial trajectory planning methods, such as 3-5-3 polynomial interpolation, are used to plan a smooth and continuous motion trajectory for the robot. This method can ensure that the robot moves smoothly when adjusting the edge position of the panel, avoiding panel displacement or damage caused by excessive acceleration. For example, according to the optimal adjustment trajectory of the panel and the kinematic constraints of the robot, the parameters of the polynomial trajectory, such as position, velocity, and acceleration, are determined to form the optimal motion trajectory.

[0111] The robot follows the planned optimal motion trajectory and accurately adjusts the edge position of the target panel to align it with the preset position. The adjusted panel is placed in the assembly position, and the robots work together to stack and arrange multiple panels according to the recipe requirements, completing the assembly operation and obtaining the target plywood.

[0112] This embodiment can ensure the alignment and tightness of the panels during assembly through accurate edge position detection and optimized trajectory adjustment, thereby improving the quality and consistency of plywood. At the same time, the robot can quickly and accurately complete the adjustment and assembly tasks of the panels, reducing the time and labor intensity of manual operations and improving production efficiency. In addition, it can also reduce rework and material waste caused by inaccurate placement of panels, thereby reducing production costs.

[0113] Please refer to Figure 4 In one embodiment of the present invention, there is also provided a control device for automatic feeding and assembling of plywood, comprising: The acquisition module 11 is used to acquire the formula information of the plywood to be assembled and the demand quantity of each type of board entered by the user; An input module 12 is used to input various types of panels required for the plywood to be assembled into corresponding chain machines based on the recipe information; A judgment module 13 is used to judge whether the required panels for the plywood to be assembled are sufficient based on the inventory information of the panels on each chain machine and the demand for each panel type; The loading module 14 is used to control the robot to load the panels on each of the chain machines based on the recipe information when it is determined that there are sufficient panels required for the plywood to be assembled, and place the captured multiple target panels at preset positions for assembly to obtain the target plywood.

[0114] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0115] In one embodiment, the present invention also provides a control system for automatic feeding and assembly of plywood, comprising a chain machine, a robot and a control device, wherein the control device is connected to the chain machine and the robot respectively, wherein the control device comprises a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the control method for automatic feeding and assembly of plywood as described above.

[0116] In one embodiment, the control device provided in one embodiment of the present application refers to Figure 5 The control device may be a computer device, and its internal structure may be as follows: Figure 5As shown. In addition, the control device can also be a PLC control device, which will not be repeated here. Among them, the computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data of the control method for automatic feeding and assembly of plywood. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the control method for automatic feeding and assembly of plywood described in the above embodiment is implemented.

[0117] In one embodiment, the present invention further proposes a storage medium storing computer-readable instructions, which, when executed by one or more processors, enables one or more processors to execute the above-mentioned control method for automatic plywood feeding and assembly. The storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0118] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0119] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0120] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A control method for automatic feeding and assembly of plywood, characterized in that: Applied to control equipment, including: Obtain the formula information of the plywood to be assembled and the demand for each type of board entered by the user; Entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the recipe information; Based on the inventory information of the panels on each chain machine and the demand for each type of panels, determine whether the panels required for the plywood to be assembled are sufficient; When it is determined that the required panels for the plywood to be assembled are sufficient, the robot is controlled based on the recipe information to load the panels on each of the chain machines, and the captured multiple target panels are placed at preset positions for assembly to obtain the target plywood.

2. The control method for automatic plywood feeding and assembly according to claim 1 is characterized in that: Before entering the types of panels required for the plywood to be assembled into the corresponding chain machine based on the recipe information, the method further includes: Check that all fields in the recipe information are filled in; When all fields in the recipe information have been filled in, determining that the integrity verification of the recipe information has passed; Verify the accuracy of the formula information; When the accuracy of the formula information is verified, the step of entering each type of board required for the plywood to be assembled into a corresponding chain machine based on the formula information is performed; When the accuracy verification of the formula information fails, a prompt message for correcting the formula information is sent to the terminal to which the engineer belongs.

3. The control method for automatic plywood feeding and assembly according to claim 2 is characterized in that: The verifying the accuracy of the recipe information includes: Based on each parameter of the recipe information, converting the recipe information into a probability matrix; Calculating the information entropy of each parameter based on the probability matrix, and calculating the natural logarithm of the information entropy of each parameter to obtain a coefficient of variation of each parameter, wherein the coefficient of variation reflects the degree of variation between the parameters; Calculate the ratio of the coefficient of difference of each parameter to the sum of the coefficients of difference of all parameters to obtain the weight of each parameter; Compare the formula information with the optimal formula information in the database parameter by parameter, calculate the difference between every two parameters, and perform weighted summation of the difference between every two parameters and the corresponding weight to obtain a comprehensive difference value; When the comprehensive difference value is less than a preset value, it is determined that the accuracy verification of the recipe information has passed.

4. The control method for automatic plywood feeding and assembly according to claim 1, characterized in that: After judging whether the required panels for the assembled plywood are sufficient based on the inventory information of the panels on each chain machine and the demand for each panel type, the method further includes: When it is determined that the required panels for the plywood to be assembled are insufficient, determining the first missing panel; generating a delivery instruction for the first panel, wherein the delivery instruction includes panel information of the first panel and a target production line entrance; Sending the delivery instruction to a panel warehouse, and controlling the panel warehouse to perform material retrieval and picking of the first panel based on the inventory location and material status of the first panel; The automatic guided vehicle of the panel warehouse is controlled to transport the picked first panel to the entrance of the target production line, and the automatic guided vehicle inside the production line is controlled to distribute the first panel from the entrance of the target production line to the corresponding chain machine.

5. The control method for automatic plywood feeding and assembly according to claim 4 is characterized in that: After the automatic guided vehicle controlling the panel warehouse transports the picked first panel to the entrance of the target production line, the method further includes: Monitor whether there is a pad that needs to be recovered at the entrance of the target production line; When a backing plate needs to be recovered, the backing plate is preferentially transported to the backing position on the automatic guided vehicle of the panel warehouse; When the automatic guided vehicle inside the production line delivers the first panel from the entrance of the target production line to the corresponding chain machine, the automatic guided vehicle controlling the panel warehouse transports the pad to the recycling area.

6. The control method for automatic plywood feeding and assembly according to claim 1, characterized in that: The controlling the robot to load the panels on each of the chain machines based on the recipe information includes: Based on the recipe information and the requirements of the robot feeding operation task, determine the scale of the robot, the initial position and speed of the robot; A fitness function is defined according to the optimization objective of the loading operation task, and based on the fitness function, an initial fitness value is calculated for each robot, and an initial global fitness value of all robots is calculated; Update the robot's speed and position according to the robot's current speed, individual optimal position and global optimal position; Based on the fitness function, calculate the current fitness value for each robot, and calculate the current global fitness value of all robots; Compare the current fitness value of each robot with the corresponding individual optimal fitness value. If the current fitness value is greater than the corresponding individual optimal fitness value, update the robot's individual optimal position and initial fitness value. Compare the current global fitness value of all robots with the optimal global fitness value. If the current global fitness value is greater than the optimal global fitness value, update the global optimal position and initial global fitness value of the robot. When the initial global fitness value reaches the optimal value, an optimal feeding operation plan is generated; Based on the optimal loading operation plan, the robot is controlled to perform loading operations on the panels on each of the chain machines.

7. The control method for automatic plywood feeding and assembly according to claim 1, characterized in that: The controlling the robot to load the panels on each of the chain machines based on the recipe information includes: Based on the recipe information, each robot is controlled to grab the plate on the corresponding chain machine, and the position and movement state of each robot is monitored in real time; Dynamically calculating the stopping point of each robot according to the position, motion state and geometric dimensions of each robot; According to the vector distance constraint between the current posture of each robot and the stop point, when controlling each robot to perform a loading operation on the grasped panel, avoidance measures are executed, and the avoidance measures include deceleration or pause.

8. The control method for automatic plywood feeding and assembly according to claim 1, characterized in that: The controlling the robot to load the panels on each of the chain machines based on the recipe information includes: Based on the recipe information, a plurality of feeding operation tasks for feeding the plates on each of the chain machines are generated, and based on a preset ant colony algorithm, each of the feeding operation tasks is arranged in order to form a near-field related task chain; Dividing the task chain into near-field subsets according to the task locations to obtain a plurality of task subsets, wherein the tasks in each task subset are geographically close and are collaboratively completed by the same robot or the same group of robots; Each of the task subsets is assigned to each robot, and each of the robots is controlled to execute the corresponding task subset.

9. The control method for automatic plywood feeding and assembly according to claim 1, characterized in that: Placing the captured multiple target panels at a preset position for assembly to obtain a target plywood comprises: Control each robot to place the captured multiple target panels to a preset position, and control the visual sensor and laser radar on the robot to start working to detect the edge position of each target panel; Inputting the detected edge position of each target plate into a preset particle swarm algorithm, optimizing the trajectory of each target plate, and obtaining the optimal adjustment trajectory of each target plate; According to the optimal adjustment trajectory of each target plate, the optimal motion trajectory is planned for each robot using a polynomial trajectory planning method; Each of the robots is controlled to adjust the edge position of the corresponding target panel according to the optimal motion trajectory, and the adjusted multiple target panels are assembled to obtain a target plywood.

10. A control system for automatic plywood feeding and assembly, characterized in that: It includes a chain machine, a robot and a control device, wherein the control device is connected to the chain machine and the robot respectively, wherein the control device includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the control method for automatic feeding and assembly of plywood as described in any one of claims 1 to 9.

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