An automobile body-in-white transfer hanging method and system

Abstract

The present invention provides a method and system for transferring and hanging an automotive body-in-white. The method includes: performing a full scan on the automotive body-in-white through a preset sensor array to detect in real time the target body parameters corresponding to the body-in-white; generating in real time a grasping control instruction corresponding to the automotive body-in-white based on preset rules according to the body parameters, and transmitting the grasping control instruction to a preset gripper system correspondingly to adjust the preset gripper system to the target grasping posture correspondingly; creating in real time a digital twin model corresponding to the automotive body-in-white and the preset gripper system through a preset program, and performing a corresponding virtual transfer and hanging experiment according to the digital twin model to generate in real time the optimal transfer and hanging path corresponding to the automotive body-in-white; completing the transfer and hanging of the automotive body-in-white through the preset gripper system based on the optimal transfer and hanging path according to the target grasping posture, and the target body parameters are unique. The present invention can eliminate the manual operation process and correspondingly improve the work efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of automobiles, and particularly relates to a method and system for transferring and hanging an automobile body-in-white. Background Art

[0002] With the progress of technology and the rapid development of productivity, automobiles have been popularized in people's daily lives, greatly improving people's travel efficiency and correspondingly facilitating people's lives.

[0003] Among them, in the actual production process of existing automobiles, it is necessary to first manufacture the body-in-white of the automobile and further perform painting treatment on the body-in-white. During this process, it is necessary to transfer and hang the body-in-white of the automobile to the painting production line correspondingly to complete the painting of the surface of the body-in-white, so as to complete the subsequent general assembly.

[0004] Furthermore, in the process of transferring and hanging the body-in-white of an automobile to the painting production line in the prior art, most of them arrange corresponding staff and corresponding semi-automatic equipment. During the actual transfer and hanging process, the transfer and hanging of the body-in-white of the automobile are mainly manually completed by the staff using the semi-automatic equipment. However, since there is no standard transfer and hanging route in this transfer and hanging method, the transfer and hanging of the body-in-white of the automobile mainly rely on the subjective experience of the staff to complete, which is prone to certain deviations, and thus is not conducive to subsequent production, correspondingly reducing the production efficiency of the automobile. Summary of the Invention

[0005] Based on this, the purpose of the present invention is to provide a method and system for transferring and hanging an automobile body-in-white to solve the problem that in the process of transferring and hanging the body-in-white of an automobile in the prior art, it mainly relies on the subjective experience of the staff to complete, resulting in easy deviation.

[0006] The first aspect of the embodiment of the present invention proposes:

[0007] A method for transferring and hanging an automobile body-in-white, wherein the method includes:

[0008] When it is detected in real time that the body-in-white of the automobile reaches the preset detection area, a full scan of the body-in-white of the automobile is performed through a preset sensor array to detect in real time the target body parameters corresponding to the body-in-white of the automobile;

[0009] Based on a preset rule, a grasping control instruction corresponding to the body-in-white of the automobile is generated in real time according to the target body parameters, and the grasping control instruction is correspondingly transmitted to a preset gripper system to adjust the preset gripper system to the target grasping posture;

[0010] Create a digital twin model corresponding to the automotive body-in-white and the preset gripper system in real time through a preset program, and conduct corresponding virtual transfer experiments based on the digital twin model to generate an optimal transfer path corresponding to the automotive body-in-white in real time;

[0011] Based on the optimal transfer path, complete the transfer of the automotive body-in-white by the preset gripper system according to the target grasping posture, and the target body parameters are unique.

[0012] The beneficial effects of the present invention are as follows: By comprehensively scanning the real-time detected automotive body-in-white, the target body parameters corresponding to the body-in-white can be detected in real time. Based on this, a grasping control instruction corresponding to the current automotive body-in-white can be generated in real time, and the grasping posture of the preset gripper system can be adjusted accordingly through the grasping control instruction. Based on this, finally, an optimal transfer path corresponding to the current automotive body-in-white can be simulated in real time through a preset program, and the current gripper system can complete the transfer of the automotive body-in-white according to the current optimal transfer path and the target grasping posture, thereby eliminating the manual operation process, corresponding eliminating deviations, and improving work efficiency at the same time.

[0013] Further, the step of generating a grasping control instruction corresponding to the automotive body-in-white in real time based on the preset rules according to the target body parameters includes:

[0014] When the target body parameters are obtained in real time, perform real-time parsing and processing on the target body parameters to extract the body size, body shape, and body structure corresponding to the automotive body-in-white in real time;

[0015] Create a corresponding body-in-white model in real time through a preset 3D software according to the body size, the body shape, and the body structure, and perform dynamic analysis on the body-in-white model to output the grasping parameters corresponding to the gripper system in real time;

[0016] Generate a grasping control instruction corresponding to the automotive body-in-white in real time according to the grasping parameters.

[0017] Further, the step of generating a grasping control instruction corresponding to the automotive body-in-white in real time according to the grasping parameters includes:

[0018] When the body-in-white model is obtained in real time, simulate the grasping posture between the gripper system and the body-in-white model in real time through the preset 3D software;

[0019] According to the grasping posture, several contact points and several contact surfaces corresponding between the gripper system and the body-in-white model are detected in real time, and the grasping force, grasping speed, and grasping torque generated by the gripper system are detected in real time at the several contact points and the several contact surfaces;

[0020] The grasping force, the grasping speed, and the grasping torque are integrated and processed to correspondingly generate the grasping parameters, and the grasping control instructions are generated according to the grasping parameters.

[0021] Further, the step of generating the grasping control instructions according to the grasping parameters includes:

[0022] When the grasping parameters are obtained in real time, a full scan is performed on the grasping parameters to detect in real time several target parameter values included therein;

[0023] The several target parameter values are classified and processed to correspondingly generate several parameter sets, and each parameter set is respectively converted into its corresponding local control code;

[0024] Each local control code is spliced to generate the corresponding target control code in real time, and the target control code is converted into the grasping control instructions in real time.

[0025] Further, the step of performing a corresponding virtual hanging experiment according to the digital twin model to generate an optimal hanging path corresponding to the automotive body-in-white in real time includes:

[0026] When the digital twin model is obtained in real time, an iterative grasping experiment is performed on the digital twin model through the preset program;

[0027] During the iterative grasping experiment of the digital twin model, the experimental hanging path generated after grasping by the digital twin model is collected in real time;

[0028] Each experimental hanging path is analyzed and processed to generate an optimal hanging path corresponding to the automotive body-in-white in real time.

[0029] Further, the step of analyzing and processing each experimental hanging path to generate an optimal hanging path corresponding to the automotive body-in-white in real time includes:

[0030] When each experimental hanging path is detected in real time, the real-time hanging end point corresponding to each experimental hanging path is detected in real time;

[0031] Calculate in real time the target difference between the real-time transfer end point and the preset standard transfer end point of each of the experimental transfer paths, and perform a ranking on each of the experimental transfer paths according to the magnitude of the target difference to generate a corresponding first ranking table in real time;

[0032] Screen out the optimal transfer path according to the first ranking table.

[0033] Further, the step of screening out the optimal transfer path according to the first ranking table includes:

[0034] When the first ranking table is obtained in real time, calculate in real time the transfer time corresponding to each of the experimental transfer paths;

[0035] Perform a secondary ranking on the rankings in the first ranking table according to the magnitude of the transfer time to generate a corresponding second ranking table in real time, and set the first place in the second ranking table as the optimal transfer path.

[0036] In the second aspect of the embodiments of the present invention, it is proposed that:

[0037] An automotive white body transfer system, wherein the system includes:

[0038] A detection module, configured to, when it is detected in real time that the automotive white body reaches a preset detection area, perform a full scan on the automotive white body through a preset sensor array to detect in real time the target body parameters corresponding to the automotive white body;

[0039] An adjustment module, configured to generate in real time a grasping control instruction corresponding to the automotive white body based on preset rules according to the target body parameters, and transmit the grasping control instruction to a preset gripper system correspondingly to adjust the preset gripper system to a target grasping posture;

[0040] A creation module, configured to create in real time a digital twin model corresponding to the automotive white body and the preset gripper system through a preset program, and perform a corresponding virtual transfer experiment according to the digital twin model to generate in real time the optimal transfer path corresponding to the automotive white body;

[0041] A processing module, configured to complete the transfer of the automotive white body through the preset gripper system according to the target grasping posture based on the optimal transfer path, and the target body parameters are unique.

[0042] Further, the adjustment module is specifically configured to:

[0043] When the target vehicle body parameters are obtained in real time, perform real-time parsing and processing on the target vehicle body parameters to extract in real time the vehicle body dimensions, vehicle body shape, and vehicle body structure corresponding to the automotive white body;

[0044] Use a preset 3D software to create a corresponding white body model in real time according to the vehicle body dimensions, the vehicle body shape, and the vehicle body structure, and perform dynamic analysis on the white body model to output in real time the grasping parameters corresponding to the gripper system;

[0045] Generate in real time a grasping control instruction corresponding to the automotive white body according to the grasping parameters.

[0046] Further, the adjustment module is specifically used for:

[0047] When the white body model is obtained in real time, use the preset 3D software to simulate in real time the grasping posture between the gripper system and the white body model;

[0048] According to the grasping posture, detect in real time a number of contact points and a number of contact surfaces generated between the gripper system and the white body model, and detect in real time the grasping force, grasping speed, and grasping torque generated by the gripper system at the number of contact points and the number of contact surfaces;

[0049] Integrate and process the grasping force, the grasping speed, and the grasping torque to correspondingly generate the grasping parameters, and generate the grasping control instruction according to the grasping parameters.

[0050] Further, the adjustment module is specifically used for:

[0051] When the grasping parameters are obtained in real time, perform a full scan on the grasping parameters to detect in real time a number of target parameter values included therein;

[0052] Classify the number of target parameter values to correspondingly generate a number of parameter sets, and convert each parameter set into its corresponding local control code;

[0053] Perform splicing processing on each local control code to generate in real time the corresponding target control code, and convert the target control code into the grasping control instruction in real time.

[0054] Further, the creation module is specifically used for:

[0055] When the digital twin model is obtained in real time, perform iterative grasping experiments on the digital twin model through the preset program;

[0056] During the iterative grasping experiment of the digital twin model, the experimental transfer path corresponding to the digital twin model after grasping is collected in real time;

[0057] Parse and process each of the experimental transfer paths to generate the optimal transfer path corresponding to the automotive body-in-white in real time.

[0058] Further, the creation module is specifically configured to:

[0059] When each of the experimental transfer paths is detected in real time, the real-time transfer end point corresponding to each of the experimental transfer paths is detected in real time;

[0060] Calculate in real time the target difference between the real-time transfer end point of each of the experimental transfer paths and the preset standard transfer end point, and sort each of the experimental transfer paths once according to the magnitude of the target difference to generate a corresponding first sorting table in real time;

[0061] Screen out the optimal transfer path according to the first sorting table.

[0062] Further, the creation module is specifically configured to:

[0063] When the first sorting table is obtained in real time, calculate in real time the transfer time corresponding to each of the experimental transfer paths;

[0064] Perform a secondary sorting on the rankings in the first sorting table according to the magnitude of the transfer time to generate a corresponding second sorting table in real time, and set the first place in the second sorting table as the optimal transfer path.

[0065] The third aspect of the embodiments of the present invention proposes:

[0066] A computer includes a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the automotive body-in-white transfer method as described above is implemented.

[0067] The fourth aspect of the embodiments of the present invention proposes:

[0068] A readable storage medium stores a computer program thereon. Wherein, when the program is executed by a processor, the automotive body-in-white transfer method as described above is implemented.

[0069] The additional aspects and advantages of the present invention will be partly given in the following description, partly will become obvious from the following description, or be understood through the practice of the present invention. Description of the Drawings

[0070] Figure 1The flowchart of the method for transferring and hanging the body-in-white of an automobile provided by the first embodiment of the present invention;

[0071] Figure 2 The structural block diagram of the system for transferring and hanging the body-in-white of an automobile provided by the third embodiment of the present invention.

[0072] The following specific embodiments will further illustrate the present invention in conjunction with the above-mentioned drawings. Specific Embodiments

[0073] To facilitate the understanding of the present invention, the present invention will be described more comprehensively below with reference to the relevant drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. On the contrary, these embodiments are provided to make the disclosure of the present invention more thorough and comprehensive.

[0074] It should be noted that when an element is referred to as being "fixed to" another element, it can be directly on the other element or there can also be an intermediate element. When an element is considered to be "connected" to another element, it can be directly connected to the other element or there may be an intermediate element at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0075] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0076] Please refer to Figure 1 , which shows the method for transferring and hanging the body-in-white of an automobile provided by the first embodiment of the present invention. The method for transferring and hanging the body-in-white of an automobile provided by this embodiment can eliminate the manual operation process, correspondingly eliminate the deviation, and improve the work efficiency at the same time.

[0077] Specifically, this embodiment provides:

[0078] A method for transferring and hanging the body-in-white of an automobile, specifically including the following steps:

[0079] Step S10, when it is detected in real time that the body-in-white of the automobile reaches the preset detection area, the body-in-white of the automobile is scanned in an all-round manner through a preset sensor array to detect in real time the target body parameters corresponding to the body-in-white of the automobile;

[0080] Step S20: Based on preset rules, generate in real time a grasping control instruction corresponding to the automotive body-in-white according to the target body parameters, and transmit the grasping control instruction to a preset gripper system correspondingly to adjust the preset gripper system to the target grasping posture correspondingly;

[0081] Step S30: Create in real time a digital twin model corresponding to the automotive body-in-white and the preset gripper system through a preset program, and conduct corresponding virtual transfer experiments according to the digital twin model to generate in real time an optimal transfer path corresponding to the automotive body-in-white;

[0082] Step S40: Based on the optimal transfer path, complete the transfer of the automotive body-in-white by the preset gripper system according to the target grasping posture. The target body parameters are unique.

[0083] Specifically, in this embodiment, it should be noted first that in order to quickly and effectively complete the transfer of the automotive body-in-white, it is necessary to accurately obtain the vehicle information related to the automotive body-in-white at this time. Based on this, the grasping posture and transfer path of the gripper system are adjusted specifically, so as to quickly and effectively complete the transfer of the automotive body-in-white without deviation. Specifically, in the actual application process, different vehicle models have different corresponding parameters such as body size and body shape. Based on this, in order to meet the requirements of different vehicle models at the same time, the present invention will preset a detection area for detecting the automotive body-in-white, and a corresponding sensor array will be arranged in advance inside the detection area. Based on this, when it is detected in real time that the body-in-white enters the detection area, the current sensor array will immediately conduct a full scan of the current automotive body-in-white, and can scan out in real time the target body parameters corresponding to the current automotive body-in-white. Based on this, in order to specifically complete the control of the gripper system, the present invention will immediately perform conversion processing on the current target body parameters according to the preset rules, and can correspondingly generate a grasping control instruction corresponding to the current automotive body-in-white, and can transmit the grasping control instruction to the inside of the preset gripper system in real time. Based on this, after the processor arranged inside the gripper system receives the grasping control instruction, it will correspondingly adjust the grasping posture of the current gripper system to the required target grasping posture. It should be noted that the target grasping posture can cooperate well with the current automotive body-in-white for subsequent processing.

[0084] Further, after adjusting the gripper system to the target grasping posture through the above steps, it is necessary to further determine the transfer hanging path corresponding to the current gripper system. Preferably, the present invention further creates a digital twin model corresponding to the current automotive body-in-white and the gripper system in real time through existing 3D programs such as ug or solidworks. It should be noted that the digital twin model is an equal-scale model corresponding to the physical object. Based on this, the corresponding virtual transfer hanging experiment can be carried out on the current digital twin model in real time inside the current 3D program, that is, iteratively simulate the transfer hanging action of the current gripper system. Based on this, the optimal transfer hanging path corresponding to the current automotive body-in-white can be finally generated. On this basis, the current gripper system can complete the transfer hanging of the automotive body-in-white according to the current optimal transfer hanging path in the above target grasping posture, thus eliminating the manual operation process, corresponding eliminating the deviation, and improving the work efficiency at the same time.

[0085] Second Embodiment

[0086] Further, the step of generating a grasping control instruction corresponding to the automotive body-in-white in real time according to the preset rule includes:

[0087] When the target body parameters are obtained in real time, perform real-time parsing processing on the target body parameters to extract in real time the body size, body shape, and body structure corresponding to the automotive body-in-white;

[0088] Create a corresponding body-in-white model in real time according to the body size, the body shape, and the body structure through a preset 3D software, and perform dynamic analysis on the body-in-white model to output in real time the grasping parameters corresponding to the gripper system;

[0089] Generate a grasping control instruction corresponding to the automotive body-in-white in real time according to the grasping parameters.

[0090] Further, the step of generating a grasping control instruction corresponding to the automotive body-in-white in real time according to the grasping parameters includes:

[0091] When the body-in-white model is obtained in real time, simulate in real time the grasping posture between the gripper system and the body-in-white model through the preset 3D software;

[0092] Detect in real time a plurality of contact points and a plurality of contact surfaces generated between the gripper system and the body-in-white model according to the grasping posture, and detect in real time the grasping force, grasping speed, and grasping torque generated by the gripper system at the plurality of contact points and the plurality of contact surfaces;

[0093] Integrate and process the grasping force, the grasping speed, and the grasping torque to correspondingly generate the grasping parameters, and generate the grasping control instructions according to the grasping parameters.

[0094] Further, the step of generating the grasping control instructions according to the grasping parameters includes:

[0095] When the grasping parameters are obtained in real time, perform a full scan of the grasping parameters to detect in real time a number of target parameter values included inside the grasping parameters;

[0096] Classify a number of the target parameter values to correspondingly generate a number of parameter sets, and convert each parameter set into its corresponding local control code respectively;

[0097] Perform splicing processing on each local control code to generate the corresponding target control code in real time, and convert the target control code into the grasping control instructions in real time.

[0098] Further, the step of performing a corresponding virtual transfer experiment according to the digital twin model to generate the optimal transfer path corresponding to the automotive body-in-white in real time includes:

[0099] When the digital twin model is obtained in real time, perform an iterative grasping experiment on the digital twin model through the preset program;

[0100] During the process of performing the iterative grasping experiment on the digital twin model, collect in real time the experimental transfer path generated after grasping by the digital twin model;

[0101] Perform parsing processing on each experimental transfer path to generate the optimal transfer path corresponding to the automotive body-in-white in real time.

[0102] Further, the step of performing parsing processing on each experimental transfer path to generate the optimal transfer path corresponding to the automotive body-in-white in real time includes:

[0103] When each experimental transfer path is detected in real time, detect in real time the real transfer end point corresponding to each experimental transfer path;

[0104] Calculate in real time the target difference between the real transfer end point of each experimental transfer path and the preset standard transfer end point, and perform a first sorting on each experimental transfer path according to the magnitude of the target difference to generate the corresponding first sorting table in real time;

[0105] Screen out the optimal transfer path according to the first sorting table.

[0106] Further, the step of corresponding screening out the optimal transfer hanging path according to the first sorting table includes:

[0107] When the first sorting table is obtained in real time, calculate in real time the transfer hanging time corresponding to each of the experimental transfer hanging paths;

[0108] Perform secondary sorting on the rankings in the first sorting table according to the magnitudes of the transfer hanging times, so as to generate a corresponding second sorting table in real time, and set the first place in the second sorting table as the optimal transfer hanging path.

[0109] In addition, in this embodiment, it should also be noted that after the required target body parameters are obtained in real time through the above steps, at this time, it is necessary to perform parsing processing on the current target body parameters in real time to generate the required grasping control instructions. Specifically, in the actual application process, since the current target body parameters contain a large number of different types of data, based on this, in order to shorten the data processing time, the present invention will extract in real time the required key parameters corresponding to the inside of the current target body parameters. Preferably, the present invention will extract in real time the body dimensions, body shapes, and body structures corresponding to the current automotive body-in-white from the inside of the current target body parameters. Based on this, the corresponding body-in-white model can be created in real time by existing 3D software such as ug or solidworks according to the current complete body dimensions, body shapes, and body structures. At the same time, in order to obtain the characteristics of the current body-in-white model, at this time, a dynamic analysis will be further performed on the current body-in-white model. Specifically, the present invention will simulate in real time the grasping postures between the current gripper system and the current body-in-white by existing 3D software. At the same time, a number of contact points and a number of contact surfaces corresponding to the current gripper system and the current body-in-white model can be detected synchronously. Among them, it should be pointed out that corresponding grasping parameters will be generated at the current contact points and contact surfaces. Based on this, the present invention can detect the grasping force, grasping speed, and grasping torque generated by the current gripper system at the positions of the current contact points and contact surfaces. Based on this, a comprehensive scan of the current several parameters will be performed to detect the several target parameter values corresponding to the inside of the current grasping parameters. At the same time, the current parameter values of each type will be integrally processed correspondingly, and a corresponding parameter set can be generated in real time. And the current parameter sets can be respectively converted through the existing DTW algorithm, and each of the current parameter sets can be respectively converted into corresponding local control codes. Then, the current local control codes are spliced into a whole correspondingly, and the required target control code can be generated, and the current target control code can be finally converted into the required grasping control instruction for subsequent processing.

[0110] Further, after obtaining the required grasping control instruction in real time through the above steps and adjusting the gripper system to the target grasping posture, it is necessary to further determine the corresponding optimal transfer path. Specifically, the present invention will first create a digital twin model corresponding to the current gripper system and the automotive white body. At the same time, the above three-dimensional software can be used to perform iterative grasping experiments on the current digital twin model. It should be noted that during the experiment, the present invention will record in real time the experimental transfer path generated after each grasping and transfer. At the same time, it will also record the real-time transfer end point corresponding to each current experimental transfer path. Based on this, it is necessary to calculate in real time the target difference generated between the real-time transfer end point of each current experimental transfer path and the preset standard transfer end point. Based on this, the current experimental transfer paths will be sorted once according to the magnitude of the current target difference, and a corresponding first list can be formed. On this basis, in order to comprehensively screen out the optimal transfer path, the present invention will also calculate in real time the transfer time generated after each current experimental transfer path is executed, and can perform a secondary sorting on the ranking in the current first list according to the magnitude of the current transfer time, so as to form a corresponding second list. Based on this, the present invention will finally set the first place in the current second list as the above optimal transfer path, so as to correspondingly improve the transfer efficiency of the gripper system, thereby eliminating the manual operation process and improving the production efficiency at the same time.

[0111] Please refer to Figure 2 , the third embodiment of the present invention provides:

[0112] An automotive white body transfer system, wherein the system includes:

[0113] A detection module, configured to, when it is detected in real time that the automotive white body reaches a preset detection area, perform a full scan on the automotive white body through a preset sensor array to detect in real time the target body parameters corresponding to the automotive white body;

[0114] An adjustment module, configured to generate a grasping control instruction corresponding to the automotive white body in real time based on a preset rule according to the target body parameters, and transmit the grasping control instruction to a preset gripper system correspondingly to adjust the preset gripper system to a target grasping posture;

[0115] A creation module, configured to create a digital twin model corresponding to the automotive white body and the preset gripper system in real time through a preset program, and perform a corresponding virtual transfer experiment according to the digital twin model to generate an optimal transfer path corresponding to the automotive white body in real time;

[0116] A processing module, configured to complete the transfer hanging of the automotive white body according to the target grasping posture through the preset gripper system based on the optimal transfer hanging path, where the target body parameters are unique.

[0117] Further, the adjustment module is specifically configured to:

[0118] When the target body parameters are obtained in real time, perform real-time parsing and processing on the target body parameters to extract in real time the body size, body shape, and body structure corresponding to the automotive white body;

[0119] Use a preset 3D software to create a corresponding white body model in real time according to the body size, the body shape, and the body structure, and perform dynamic analysis on the white body model to output in real time the grasping parameters corresponding to the gripper system;

[0120] Generate a grasping control instruction corresponding to the automotive white body in real time according to the grasping parameters.

[0121] Further, the adjustment module is specifically configured to:

[0122] When the white body model is obtained in real time, use the preset 3D software to simulate in real time the grasping posture between the gripper system and the white body model;

[0123] According to the grasping posture, detect in real time a number of contact points and a number of contact surfaces generated between the gripper system and the white body model, and detect in real time the grasping force, grasping speed, and grasping torque generated by the gripper system at the number of contact points and the number of contact surfaces;

[0124] Integrate and process the grasping force, the grasping speed, and the grasping torque to generate the grasping parameters correspondingly, and generate the grasping control instruction according to the grasping parameters.

[0125] Further, the adjustment module is specifically configured to:

[0126] When the grasping parameters are obtained in real time, perform a full scan on the grasping parameters to detect in real time a number of target parameter values included inside the grasping parameters;

[0127] Classify and process the number of target parameter values to generate a number of parameter sets correspondingly, and convert each parameter set into its corresponding local control code;

[0128] Perform splicing processing on each local control code to generate a corresponding target control code in real time, and convert the target control code into the grasping control instruction in real time.

[0129] Further, the creation module is specifically configured to:

[0130] When the digital twin model is obtained in real time, perform an iterative grasping experiment on the digital twin model through the preset program;

[0131] During the iterative grasping experiment of the digital twin model, collect in real time the experimental transfer path generated corresponding to the digital twin model after grasping;

[0132] Parse and process each experimental transfer path to generate in real time the optimal transfer path corresponding to the automotive body-in-white.

[0133] Further, the creation module is specifically configured to:

[0134] When each experimental transfer path is detected in real time, detect in real time the real transfer end point corresponding to each experimental transfer path;

[0135] Calculate in real time the target difference between the real transfer end point of each experimental transfer path and the preset standard transfer end point, and perform a first sorting on each experimental transfer path according to the magnitude of the target difference to generate a corresponding first sorting table in real time;

[0136] Screen out the optimal transfer path according to the first sorting table.

[0137] Further, the creation module is specifically configured to:

[0138] When the first sorting table is obtained in real time, calculate in real time the transfer time corresponding to each experimental transfer path;

[0139] Perform a second sorting on the rankings in the first sorting table according to the magnitude of the transfer time to generate a corresponding second sorting table in real time, and set the first place in the second sorting table as the optimal transfer path.

[0140] The fourth embodiment of the present invention provides a computer, including a memory, a processor, and a computer program stored on the memory and executable on the processor. Wherein, when the processor executes the computer program, the automotive body-in-white transfer method as described above is implemented.

[0141] The fifth embodiment of the present invention provides a readable storage medium, on which a computer program is stored. Wherein, when the program is executed by a processor, the automotive body-in-white transfer method as described above is implemented.

[0142] In summary, the method and system for transferring and hanging the automotive body-in-white provided in the above embodiments of the present invention can eliminate the manual operation process, correspondingly eliminate deviations, and improve work efficiency at the same time.

[0143] It should be noted that the above-mentioned respective modules can be functional modules or program modules, and can be implemented either by software or by hardware. For the modules implemented by hardware, the above-mentioned respective modules can be located in the same processor; or the above-mentioned respective modules can also be located in different processors in any combined form.

[0144] The logic and / or steps represented in the flowchart or described in other ways herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch instructions from the instruction execution system, apparatus, or device and execute the instructions), or in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.

[0145] More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection part (electronic device) having one or more wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0146] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0147] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0148] The above-described embodiments merely represent several implementation manners of the present invention. The descriptions are relatively specific and detailed, but should not be construed as a limitation on the scope of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the appended claims.

Claims

1. A method for transferring and hanging the white body of an automobile, characterized in that, The method includes: When it is detected in real time that the car body-in-white reaches the preset detection area, a full scan of the car body-in-white is performed through a preset sensor array to detect in real time the target body parameters corresponding to the car body-in-white; Based on preset rules, a grasping control instruction corresponding to the car body-in-white is generated in real time according to the target body parameters, and the grasping control instruction is transmitted correspondingly to a preset gripper system to adjust the preset gripper system correspondingly to the target grasping posture; A digital twin model corresponding to the car body-in-white and the preset gripper system is created in real time through a preset program, and a corresponding virtual transfer experiment is performed according to the digital twin model to generate in real time the optimal transfer path corresponding to the car body-in-white; Based on the optimal transfer path, the transfer of the car body-in-white is completed through the preset gripper system according to the target grasping posture, and the target body parameters are unique; The step of generating in real time a grasping control instruction corresponding to the car body-in-white based on preset rules according to the target body parameters includes: When the target body parameters are obtained in real time, real-time parsing processing is performed on the target body parameters to extract in real time the body size, body shape, and body structure corresponding to the car body-in-white; A corresponding body-in-white model is created in real time through a preset 3D software according to the body size, the body shape, and the body structure, and dynamic analysis is performed on the body-in-white model to output in real time the grasping parameters corresponding to the gripper system; A grasping control instruction corresponding to the car body-in-white is generated in real time according to the grasping parameters.

2. The method for transferring and hanging the body-in-white of an automobile according to claim 1, wherein: The step of generating in real time a grasping control instruction corresponding to the car body-in-white according to the grasping parameters includes: When the body-in-white model is obtained in real time, the grasping posture between the gripper system and the body-in-white model is simulated in real time through the preset 3D software; According to the grasping posture, a number of contact points and a number of contact surfaces generated between the gripper system and the body-in-white model are detected in real time, and the grasping force, grasping speed, and grasping torque generated by the gripper system are detected in real time at the number of contact points and the number of contact surfaces; The grasping force, the grasping speed, and the grasping torque are integrated to generate the grasping parameters correspondingly, and the grasping control instruction is generated correspondingly according to the grasping parameters.

3. The method for transferring and hanging the body-in-white of an automobile according to claim 2, characterized in that: The step of generating the grasping control instruction correspondingly according to the grasping parameters includes: When the grasping parameters are obtained in real time, a full scan of the grasping parameters is performed to detect in real time a number of target parameter values included inside the grasping parameters; The number of target parameter values is classified to generate a number of parameter sets correspondingly, and each parameter set is converted into its corresponding local control code respectively; The local control codes are spliced to generate a corresponding target control code in real time, and the target control code is converted into the grasping control instruction in real time.

4. The method for transferring and hanging the white body of an automobile according to claim 1, wherein: The steps of performing a corresponding virtual transfer experiment according to the digital twin model to generate an optimal transfer path corresponding to the automotive body-in-white in real time include: When the digital twin model is obtained in real time, perform an iterative grasping experiment on the digital twin model through the preset program; During the iterative grasping experiment of the digital twin model, collect in real time the experimental transfer paths generated after grasping by the digital twin model; Perform parsing processing on each of the experimental transfer paths to generate an optimal transfer path corresponding to the automotive body-in-white in real time.

5. The method for transferring and hanging the body-in-white of an automobile according to claim 4, wherein: The steps of performing parsing processing on each of the experimental transfer paths to generate an optimal transfer path corresponding to the automotive body-in-white in real time include: When each of the experimental transfer paths is detected in real time, detect in real time the real-time transfer end points corresponding to each of the experimental transfer paths; Calculate in real time the target differences between the real-time transfer end points of each of the experimental transfer paths and the preset standard transfer end points, and perform a first sorting on each of the experimental transfer paths according to the magnitudes of the target differences to generate a corresponding first sorting table in real time; Screen out the optimal transfer path according to the first sorting table.

6. The method for transferring and hanging the white body of an automobile according to claim 5, wherein: The steps of screening out the optimal transfer path according to the first sorting table include: When the first sorting table is obtained in real time, calculate in real time the transfer times corresponding to each of the experimental transfer paths; Perform a second sorting on the rankings in the first sorting table according to the magnitudes of the transfer times to generate a corresponding second sorting table in real time, and set the first place in the second sorting table as the optimal transfer path.

7. An automotive body-in-white transfer hanging system, characterized in that, A system for implementing the automotive body-in-white transfer method according to any one of claims 1 to 6, the system includes: A detection module, configured to, when it is detected in real time that the automotive body-in-white reaches a preset detection area, perform a full scan on the automotive body-in-white through a preset sensor array to detect in real time the target body parameters corresponding to the automotive body-in-white; An adjustment module, configured to generate a grasping control instruction corresponding to the automotive body-in-white in real time based on a preset rule according to the target body parameters, and transmit the grasping control instruction to a preset gripper system correspondingly to adjust the preset gripper system to a target grasping posture; A creation module, configured to create in real time a digital twin model corresponding to the automotive body-in-white and the preset gripper system through a preset program, and perform a corresponding virtual transfer experiment according to the digital twin model to generate an optimal transfer path corresponding to the automotive body-in-white in real time; A processing module, configured to complete the transfer of the automotive body-in-white through the preset gripper system based on the optimal transfer path according to the target grasping posture, and the target body parameters are unique.

8. A computer, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the automotive body-in-white transfer method according to any one of claims 1 to 6.

9. A readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the automotive body-in-white transfer method according to any one of claims 1 to 6.

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