Method and device for checking human-computer work, electronic equipment and readable storage medium

Abstract

The application discloses a man-machine working verification method and device, electronic equipment and a readable storage medium, and belongs to the technical field of man-machine working. The method comprises the following steps: acquiring human body parameters of a human body model from a database, and acquiring production equipment information; determining a limit motion range of the human body model according to the human body parameters and the production equipment information; simulating and verifying an operation process of the production equipment operated by the human body model based on the human body parameters and the production equipment information, and acquiring real-time joint parameters of the human body model in the simulation and verification process; comparing the real-time joint parameters with the limit motion range, and adjusting the simulation and verification process based on a comparison result of the real-time joint parameters and the limit motion range.

Description

Technical Field

[0001] This application belongs to the field of human-machine interface technology, and specifically relates to a verification method, device, electronic device and readable storage medium for human-machine interface. Background Technology

[0002] The automobile manufacturing process involves connecting various parts and subsystems to form a complete vehicle, characterized by its fast pace and high complexity. Any technological defects during the parts development process can be amplified during the manufacturing stage, affecting production rhythm and causing quality defects.

[0003] The manufacturing process of parts includes dimensions such as assembly path, tool space, human-machine interface, and cycle time. Among these, human-machine interface verification is an essential task. Without human-machine interface verification, it will lead to difficulties in operation for workers, low efficiency, and even physical injury to workers and product quality defects. Traditional human-machine interface verification methods are time-consuming and inconvenient to use. Summary of the Invention

[0004] The purpose of this application is to provide a human-machine operation verification method, device, electronic device, and readable storage medium, which can solve the problem of long processing time in traditional human-machine operation verification methods.

[0005] In a first aspect, embodiments of this application provide a method for verifying human-machine interaction, the method comprising:

[0006] Retrieve human body parameters from the human body model from the database, and obtain production equipment information;

[0007] Based on the human body parameters and the production equipment information, the limit range of motion of the human body model is determined;

[0008] Based on the human body parameters and the production equipment information, the operation process of the human body model operating the production equipment is simulated and verified, and the real-time joint parameters of the human body model are obtained during the simulation and verification process.

[0009] The real-time joint parameters are compared with the limit range of motion, and the simulation verification process is adjusted based on the comparison results.

[0010] Optionally, adjusting the simulation verification process based on the comparison results between the real-time joint parameters and the limit range of motion includes:

[0011] The simulation verification process is terminated when the real-time joint parameters exceed the limit range of motion.

[0012] The process of the operation is adjusted to obtain the adjusted process;

[0013] The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process.

[0014] Optionally, obtaining the human body parameters of the human body model from the database includes:

[0015] Obtain the geographical information of the production workshop;

[0016] Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database;

[0017] Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight.

[0018] Determining the limit range of motion of the human body model based on the human body parameters and the production equipment information includes:

[0019] The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model;

[0020] The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient;

[0021] Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

[0022] Optionally, the extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck.

[0023] The step of comparing the real-time joint parameters with the limit range of motion includes:

[0024] The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion.

[0025] Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

[0026] Secondly, embodiments of this application provide a verification device for human-machine interaction, the device comprising:

[0027] The acquisition module is used to retrieve human body parameters from the database for the human body model, as well as information on production equipment.

[0028] The determination module is used to determine the limit range of motion of the human body model based on the human body parameters and the production equipment information;

[0029] The simulation module is used to simulate and verify the operation process of the human body model operating the production equipment based on the human body parameters and the production equipment information, and to obtain the real-time joint parameters of the human body model during the simulation verification process.

[0030] The adjustment module is used to compare the real-time joint parameters with the limit range of motion, and adjust the simulation verification process based on the comparison results.

[0031] Optionally, the adjustment module is further configured to:

[0032] The simulation verification process is terminated when the real-time joint parameters exceed the limit range of motion.

[0033] The process of the operation is adjusted to obtain the adjusted process;

[0034] The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process.

[0035] Optionally, the acquisition module is further configured to:

[0036] Obtain the geographical information of the production workshop;

[0037] Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database;

[0038] Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight.

[0039] The determining module is also used for:

[0040] The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model;

[0041] The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient;

[0042] Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

[0043] Optionally, the extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck.

[0044] The adjustment module is also used for:

[0045] The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion.

[0046] Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

[0047] Thirdly, embodiments of this application provide an electronic device, which includes a processor and a memory. The memory stores programs or instructions that can run on the processor, and when the programs or instructions are executed by the processor, they implement the steps of the human-machine verification method as described in the first aspect.

[0048] Fourthly, embodiments of this application provide a readable storage medium storing a program or instructions that, when executed by a processor, implement the steps of the human-machine verification method as described in the first aspect.

[0049] The human-machine interface verification method provided in this application embodiment can be used to simulate human-machine interface operations of workers in a production workshop. It can compare the real-time joint parameters of the human body model with the set limit range of motion during simulation verification, and adjust the simulation verification process in a timely manner based on the comparison results. Furthermore, the simulation verification object is a human body model corresponding to representative human body parameters, eliminating the need to simulate all workers in the production workshop. This ensures the accuracy of the human-machine interface verification results while significantly reducing the time consumed in the verification process and improving verification efficiency. Attached Figure Description

[0050] Figure 1 A schematic diagram of the general angle of wrist rotation in the left-right direction provided for embodiments of this application;

[0051] Figure 2 A flowchart illustrating the human-machine interface verification method provided in this application embodiment;

[0052] Figure 3 A schematic diagram illustrating the limit range of wrist rotation in the left-right direction, provided in an embodiment of this application.

[0053] Figure 4 A schematic diagram of the general angle of wrist rotation in the up-down direction provided for embodiments of this application;

[0054] Figure 5 A schematic diagram illustrating the limit range of wrist rotation in the vertical direction, provided in an embodiment of this application.

[0055] Figure 6 A schematic diagram of all joints of the human body model provided in the embodiments of this application;

[0056] Figure 7 A schematic diagram of the structure of the human-machine verification device provided in the embodiments of this application;

[0057] Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0058] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0059] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0060] The verification method for human-machine interaction provided in this application will be described in detail below with reference to the accompanying drawings, through specific embodiments and application scenarios.

[0061] The human-machine operation verification method provided in this application embodiment can be used to simulate the process of workers operating production equipment to produce and assemble vehicle parts in a vehicle production workshop.

[0062] The process of workers operating production equipment to produce and assemble vehicle parts can be described in the following steps:

[0063] The operator retrieves screws and tools from the material bin;

[0064] The operator moves to the preset workstation;

[0065] The operator bent down and began driving in the bolts.

[0066] In the above steps, when operators pick up screws and tools, move around, and bend over to tighten bolts, they need to use parts of the body such as the elbows, knees, waist, head, shoulders, neck, and wrists. Figure 1 The diagram shown illustrates the general range of motion of the wrist. Figure 1 The image shows the state where the wrist angle is 0 when the wrist moves along the first degree of freedom (i.e., Figure 1The diagram shows 0deg-DOF1, where deg represents degrees and DOF represents degrees of freedom. The first degree of freedom represents the wrist's left-right rotation. Generally, the common range of wrist rotation in the left-right direction is 80 degrees (80deg) to -70 degrees (-70deg), that is, between 80 degrees to the left and 70 degrees to the right. It should be noted that although the wrist can rotate between 80 degrees and -70 degrees, this does not necessarily mean that the operator's posture is comfortable or suitable for work. The human-machine interface verification method provided in this application can verify the operator's operation process to determine whether the operator can work comfortably, thereby improving production efficiency.

[0067] like Figure 2 As shown in the embodiments of this application, the human-machine interaction verification method includes the following steps:

[0068] Step S1: Retrieve the human body parameters of the human body model from the database, and obtain the production equipment information.

[0069] The database contains physical data of all workers collected from the automobile factory, including names and corresponding information such as gender, age, height, and weight. The standards specified in CG10000-88 and CG / T1547-1992 can be used when collecting physical data.

[0070] The human body model is a digital model used in subsequent simulation verification processes, eliminating the need to construct a physical human body model structure. Based on the production equipment information, a corresponding production equipment model can be generated, also eliminating the need to construct physical production equipment, thereby reducing the cost of the human-machine interaction verification method in this embodiment.

[0071] The worker's anthropometric parameters include height, weight, age, and vision. Different anthropometric parameters result in different operating methods and levels of comfort when used to operate equipment. Similarly, the same anthropometric parameters will result in different operating methods and levels of comfort when used to operate production equipment models corresponding to different production equipment information.

[0072] It should be noted that the human body parameters obtained from the database represent representative human body parameters obtained from the database. The rationality of human-machine interaction is determined by simulating and verifying the operation process of the human body model corresponding to the representative human body parameters. This eliminates the need to simulate the operation process of each worker, reducing the time spent on human-machine interaction verification and improving efficiency.

[0073] Step S2: Based on the human body parameters and the production equipment information, determine the limit range of motion of the human body model.

[0074] Because the operation methods and comfort levels differ when human models with different human body parameters operate equipment, and even when human models with the same parameters operate production equipment models corresponding to different production equipment information, it is necessary to determine the extreme range of motion of the specific human body model for specific human body parameters and specific production equipment information to ensure the accuracy of the results in subsequent simulation verification processes.

[0075] The extreme range of motion of the human body model includes the range of motion of the wrist, elbow, knee, waist, and head. Each of these ranges of motion corresponds to a part of the human body model. When a part of the human body model moves within the range of motion of the corresponding part, it indicates that the movement of that part of the human body model is comfortable and that the human body model has high production efficiency when performing production operations.

[0076] Step S3: Based on the human body parameters and the production equipment information, simulate and verify the operation process of the human body model operating the production equipment, and obtain the real-time joint parameters of the human body model during the simulation and verification process.

[0077] Based on the human body model corresponding to the specific human body parameters and the specific production equipment information, the operation process of the human body model operating the production equipment can be simulated and verified. For example, the following operation process of the human body model is simulated:

[0078] The human body model corresponding to the human body parameters is taken from the screw model and tool model at the material box model;

[0079] The human body model corresponding to the human body parameters is moved to the front of the preset workstation model;

[0080] The human model corresponding to the specified human parameters bent over and began driving in the bolts.

[0081] During the above steps, real-time joint parameters of various parts of the human body model are acquired, such as the waist joint parameters and head joint parameters when the human body model is bent over, and the elbow joint parameters and wrist joint parameters when the human body model is tightening bolts.

[0082] Step S4: Compare the real-time joint parameters with the limit range of motion, and adjust the simulation verification process based on the comparison results of the real-time joint parameters and the limit range of motion.

[0083] During the simulation verification process, real-time joint parameters of the human body model are acquired and compared with the preset limit range of motion. If the real-time joint parameters are within the limit range, it indicates that the human body model's operation is comfortable and has high productivity. If the real-time joint parameters exceed the limit range, it indicates that the human body model's operation is uncomfortable and may even cause damage to the human body or equipment, requiring adjustments to the simulation verification process to change the human body model's operation. The human-machine work verification method provided in this application embodiment can be used to simulate human-machine work in production workshops. It can compare the real-time joint parameters of the human body model with the preset limit range of motion during simulation verification, and adjust the simulation verification process in a timely manner based on the comparison results. Moreover, the simulation verification object is a human body model corresponding to representative human body parameters, eliminating the need to simulate all workers in the production workshop. This ensures the accuracy of the human-machine work verification results while greatly reducing the time consumed in the verification process and improving verification efficiency.

[0084] Optionally, adjusting the simulation verification process based on the comparison results between the real-time joint parameters and the limit range of motion includes:

[0085] If the real-time joint parameters exceed the limit range of motion, the simulation verification process will be terminated.

[0086] During the simulation verification of the operation process of the human body model on the production equipment model corresponding to the production equipment information, the real-time joint parameters of the human body model are acquired in real time. At any moment, if the real-time joint parameters of any part of the human body model exceed the limit range of motion of the corresponding part, it indicates that the operation of the human body model at this time is not comfortable or efficient, and the simulation verification process is stopped to avoid wasting time.

[0087] The process of the operation is adjusted to obtain the adjusted process.

[0088] Specifically, when the real-time joint parameters of the human body model exceed the limit range of motion, the focus is on the problematic part of the human body model and the operation performed when the problem occurs. After analyzing the operation performed, adjustments are made, including changing the human body model's movements, operation angles, and positions. This also includes designing new workstation fixtures to change the human body model's movements, operation angles, and positions, thereby obtaining an adjustment process. The adjustment process is used to guide the operation process performed when the human body model is subsequently simulated and verified.

[0089] The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process.

[0090] During the simulation verification process, if any real-time joint parameters exceed the limit range of motion, the simulation verification process will be stopped, and the problematic operation will be adjusted. After adjustment, the simulation verification will restart. This process is repeated until the simulation verification of the operation process of the human model operating the production equipment model corresponding to the production equipment information does not result in any real-time joint parameters exceeding the limit range of motion. Under this condition, in the actual production process in the production workshop, the operators follow the adjusted procedure to operate the actual production equipment, thereby improving production efficiency.

[0091] It should be noted that if, before adjusting the operation process, the human body model does not exceed the limit range of motion in the simulation verification process of the corresponding production equipment model, it means that the human body model remains comfortable and efficient throughout the operation. Therefore, there is no need to adjust the original operation process, and the operator will follow the original operation process in the actual production process.

[0092] Optionally, obtaining the human body parameters of the human body model from the database includes:

[0093] Obtain the geographical information of the production workshop;

[0094] Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database;

[0095] Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight.

[0096] A car factory typically has multiple production workshops located in different areas, such as the south or the north. The physical characteristics of workers in these workshops will vary across regions, for example, in terms of average height. Therefore, retrieving worker anthropometric parameters from a database based on geographical location information can improve the accuracy and reliability of analyses conducted across different production workshops.

[0097] The human body parameters include mean height, mean weight, height variance, and weight variance. Height variance represents the degree of deviation between a random height data point and the mean height among multiple height data points. Similarly, weight variance represents the degree of deviation between a random weight data point and the mean weight among multiple weight data points. In subsequent processes, the degree of deviation between the mean and the random data is incorporated into the determination of the extreme range of motion, ensuring the rationality of the extreme range of motion.

[0098] like Figure 3 As shown, the wrist angle is 0 when the wrist rotates left and right (i.e., ... Figure 3 The range of motion of the wrist is defined as 0deg-DOF1 (where deg represents degrees and DOF represents degrees of freedom). Based on the above method, the limit range of motion of the wrist is redefined as 45 degrees to the left (45deg) to 45 degrees to the right (-45deg). When the worker performs the operation, the wrist moves within the above angle range, indicating that the operation is comfortable and efficient.

[0099] Please see further. Figure 4 and Figure 5 , Figure 4 This indicates the state where the wrist angle is 0 when the wrist moves along the second degree of freedom (i.e., Figure 4 The figure shows 0deg-DOF2 (deg represents degrees, DOF represents degrees of freedom), where the second degree of freedom is in the vertical direction of the wrist. Figure 4 The diagram shows that, prior to using the method of this embodiment, the range of wrist rotation angles in the vertical direction is between 20 degrees (20deg) upward rotation and 30 degrees (-30deg) downward rotation. Figure 5 This means that the maximum range of motion of the wrist in the vertical direction, determined after adopting the method of this embodiment, is between 20 degrees (20deg) upward rotation and 20 degrees (-20deg) downward rotation.

[0100] Further, determining the limit range of motion of the human body model based on the human body parameters and the production equipment information includes:

[0101] The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model.

[0102] It should be noted that in determining the limit range of motion for different parts of the human body model, the first and second coefficients are different for different parts.

[0103] The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient;

[0104] Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

[0105] In one embodiment, a first target value is determined based on the sum of the mean height and the variance of height; a second target value is determined based on the sum of the mean weight and the variance of weight; a third target value is determined based on the quotient of the first and second target values; the first parameter is determined based on the product of the third target value and a first coefficient; and the second parameter is determined based on the product of the third target value and a second coefficient. When determining the limit range of motion for different parts of the human body model, first and second coefficients corresponding to different parts are required. The first and second coefficients are determined based on GB10000-88, GB / T13547-1992, and anthropometric data from multiple countries.

[0106] Optionally, the extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck.

[0107] The step of comparing the real-time joint parameters with the limit range of motion includes:

[0108] The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion.

[0109] Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

[0110] like Figure 6 As shown, when the human body moves, multiple parts need to move in unison. During the simulation and verification of the operation of the human body model on the production equipment model, the real-time joint parameters of multiple parts of the human body model are monitored at the same time, and the real-time joint parameters of multiple parts are compared with the corresponding limit range of motion of multiple parts. This ensures that the linkage of multiple parts of the human body model is comfortable and efficient, thereby ensuring the comprehensiveness of the human-machine work verification method of this application embodiment.

[0111] The human-machine operation verification method provided in this application embodiment can be executed by a human-machine operation verification device. This application embodiment uses a human-machine operation verification device executing the human-machine operation verification method as an example, and combines it with the appendix... Figure 7 This application describes the implementation of the human-machine interface verification device 700. The human-machine interface verification device includes:

[0112] The acquisition module 701 is used to obtain human body parameters of the human body model from the database, as well as information on production equipment;

[0113] The determining module 702 is used to determine the limit range of motion of the human body model based on the human body parameters and the production equipment information;

[0114] The simulation module 703 is used to simulate and verify the operation process of the human body model operating the production equipment based on the human body parameters and the production equipment information, and to obtain the real-time joint parameters of the human body model during the simulation verification process.

[0115] The adjustment module 704 is used to compare the real-time joint parameters with the limit range of motion, and adjust the simulation verification process based on the comparison result of the real-time joint parameters and the limit range of motion.

[0116] Optionally, the adjustment module 704 is further configured to:

[0117] The simulation verification process is terminated when the real-time joint parameters exceed the limit range of motion.

[0118] The process of the operation is adjusted to obtain the adjusted process;

[0119] The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process.

[0120] Optionally, the acquisition module 701 is further configured to:

[0121] Obtain the geographical information of the production workshop;

[0122] Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database;

[0123] Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight.

[0124] The determining module 702 is further configured to:

[0125] The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model;

[0126] The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient;

[0127] Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

[0128] Optionally, the extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck.

[0129] The adjustment module 704 is also used for:

[0130] The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion.

[0131] Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

[0132] The human-machine operation verification device 700 provided in this application embodiment can simulate and verify the operation process of the human model operating the production equipment model corresponding to the production equipment information from the human body model in the database, and compare the real-time joint parameters in the simulation verification process with the set limit range of motion, and adjust the simulation verification process according to the comparison results.

[0133] It should be noted that the human-machine operation verification device provided in this application embodiment can realize all the technical processes of the above-mentioned human-machine operation verification method and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0134] The device in this application embodiment can be an electronic device or a component within an electronic device, such as an integrated circuit or a chip. The electronic device can be a terminal or other devices besides a terminal. For example, the electronic device can be a mobile phone, tablet computer, laptop computer, PDA, in-vehicle electronic device, mobile internet device (MID), augmented reality (AR) / virtual reality (VR) device, robot, wearable device, ultra-mobile personal computer (UMPC), netbook, or personal digital assistant (PDA), etc. Non-mobile electronic devices can also be servers, network attached storage (NAS), personal computers (PCs), televisions (TVs), ATMs, or self-service machines, etc. This application embodiment does not specifically limit the scope of the device.

[0135] Optionally, such as Figure 8 As shown, this application embodiment also provides an electronic device 800, including a processor 801 and a memory 802. The memory 802 stores a program or instructions that can run on the processor 801. When the program or instructions are executed by the processor 801, they implement the various steps of the above-described human-machine verification method embodiment and can achieve the same technical effect. To avoid repetition, they will not be described again here.

[0136] It should be noted that the electronic devices in the embodiments of this application include the mobile electronic devices and non-mobile electronic devices described above.

[0137] This application also provides a readable storage medium storing a program or instructions. When the program or instructions are executed by a processor, they implement the various processes of the above-described human-machine verification method embodiments and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0138] The processor is the processor in the electronic device described in the above embodiments. The readable storage medium includes computer-readable storage media, such as computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk.

[0139] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element. Furthermore, it should be noted that the scope of the methods and apparatuses in the embodiments of this application is not limited to performing functions in the order shown or discussed, but may also include performing functions substantially simultaneously or in the reverse order, depending on the functions involved. For example, the described methods may be performed in a different order than described, and various steps may be added, omitted, or combined. Additionally, features described with reference to certain examples may be combined in other examples.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0141] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for verifying human-machine interaction, characterized in that, The method includes: Retrieve human body parameters from the human body model from the database, and obtain production equipment information; Based on the human body parameters and the production equipment information, the limit range of motion of the human body model is determined; Based on the human body parameters and the production equipment information, the operation process of the human body model operating the production equipment is simulated and verified, and the real-time joint parameters of the human body model are obtained during the simulation and verification process. The real-time joint parameters are compared with the limit range of motion, and the simulation verification process is adjusted based on the comparison results. The process of adjusting the simulation verification based on the comparison results between the real-time joint parameters and the limit range of motion includes: The simulation verification process is terminated when the real-time joint parameters exceed the limit range of motion. The process of the operation is adjusted to obtain the adjusted process; The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process. The step of obtaining human body parameters from the database for the human body model includes: Obtain the geographical information of the production workshop; Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database; Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight. Determining the limit range of motion of the human body model based on the human body parameters and the production equipment information includes: The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model; The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient; Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

2. The human-machine operation verification method as described in claim 1, characterized in that, The extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck. The step of comparing the real-time joint parameters with the limit range of motion includes: The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion. Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

3. A human-machine verification device, characterized in that, The device includes: The acquisition module is used to retrieve human body parameters from the database for the human body model, as well as information on production equipment. The determination module is used to determine the limit range of motion of the human body model based on the human body parameters and the production equipment information; The simulation module is used to simulate and verify the operation process of the human body model operating the production equipment based on the human body parameters and the production equipment information, and to obtain the real-time joint parameters of the human body model during the simulation verification process. An adjustment module is used to compare the real-time joint parameters with the limit range of motion, and adjust the simulation verification process based on the comparison results of the real-time joint parameters and the limit range of motion. The adjustment module is further used for: The simulation verification process is terminated when the real-time joint parameters exceed the limit range of motion. The process of the operation is adjusted to obtain the adjusted process; The process of operating the production equipment according to the adjustment procedure of the human body model is simulated and verified so that the real-time joint parameters of the human body model are within the limit range of motion during the simulation and verification process. The acquisition module is also used for: Obtain the geographical information of the production workshop; Based on the geographical information of the production workshop, multiple pairs of height and weight data corresponding to the geographical information are obtained from the database; Based on the multiple pairs of height and weight data, the mean height, variance of height, mean weight, and variance of weight corresponding to the production workshop are determined. The human body parameters include the mean height, variance of height, mean weight, and variance of weight. The determining module is also used for: The first and second coefficients of the human body model are obtained from the database, wherein the first and second coefficients are used to characterize the degree of influence of the human body parameters on the extreme range of motion of the human body model; The first parameter is determined based on the mean height, the mean weight, the variance of height, the variance of weight, and the first coefficient; Based on the mean height, mean weight, variance of height, variance of weight, and the second coefficient, a second parameter is determined, wherein the first parameter is the minimum value of the extreme range of motion, and the second parameter is the maximum value of the extreme range of motion.

4. The human-machine operation verification device as described in claim 3, characterized in that, The extreme range of motion includes the range of motion of the elbow joint, the range of motion of the knee joint, the range of motion of the waist, the range of motion of the head, the range of motion of the shoulder, and the range of motion of the neck. The real-time joint parameters include real-time elbow joint parameters corresponding to the range of motion of the elbow joint, real-time knee joint parameters corresponding to the range of motion of the knee joint, real-time waist parameters corresponding to the range of motion of the waist, real-time head parameters corresponding to the range of motion of the head, real-time shoulder parameters corresponding to the range of motion of the shoulder, and real-time neck parameters corresponding to the range of motion of the neck. The adjustment module is also used for: The target joint parameters are compared with the corresponding target range of motion to determine whether the target joint parameters are within the target range of motion. Wherein, the target joint parameter is any one of the real-time elbow joint parameter, the real-time knee joint parameter, the real-time waist parameter, the real-time head parameter, the real-time shoulder parameter, and the real-time neck parameter, and the target range of motion is one of the elbow joint range of motion, knee joint range of motion, waist range of motion, head range of motion, shoulder range of motion, and neck range of motion that corresponds to the target joint parameter.

5. An electronic device, characterized in that, The electronic device includes a processor and a memory, the memory storing programs or instructions that can run on the processor, the programs or instructions being executed by the processor to implement the steps of the human-machine interface verification method as described in any one of claims 1 to 2.

6. A readable storage medium, characterized in that, The readable storage medium stores a program or instructions, which, when executed by a processor, implement the steps of the human-machine operation verification method as described in any one of claims 1 to 2.

Images