CN114330038B - Virtual reality based stability analysis material stacking method, system and equipment - Google Patents
Virtual reality based stability analysis material stacking method, system and equipment Download PDFInfo
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Abstract
The invention belongs to the field of material transfer stacking, and particularly relates to a virtual reality based stability analysis material stacking method, system and equipment, aiming at solving the problems of low material stacking stability and low material transfer efficiency of a flat plate trolley in the existing material transfer. The invention comprises the following steps: the VR glasses acquire a material stacking model group of a material sequence to be transferred, and calculate the gravity center of each material stacking model and the material staggered overlapping rate between two adjacent layers in the model; obtaining a stable value of a current material stacking model through a stability analysis network; traversing each material stacking model, and taking the material stacking model corresponding to the maximum stable value as the material stacking model of the material sequence to be transferred; and generating a material stacking flow by VR glasses, matching the current material to be stacked with the material stacking model in real time, and stacking the next material if the matching of the current material to be stacked is successful. The invention has high stacking stability of materials and high material transferring efficiency.
Description
Technical Field
The invention belongs to the field of material transferring and stacking, and particularly relates to a method, a system and equipment for stacking materials based on virtual reality stability analysis.
Background
In most production type enterprises, continuous transfer processes of materials are involved, including transportation of the materials from a storehouse to an assembly line in a production process, warehousing transportation of small materials, ex-warehouse transportation and the like. In the transfer process of materials, the logistics trolley is often used, so that the logistics trolley is continuously innovated and developed.
Adopt the most be exactly flat trolley to smallclothes goods and materials transmission in the commodity circulation shallow, nevertheless flat trolley carries out the goods and materials transportation and mostly is the manual work and carries out the goods and materials and pile up, stack when mixed and disorderly very easily cause rocking of goods and materials in the transportation because of the focus is unstable for the commodity circulation shallow drags the line inconveniently, the suitability is not strong, the goods and materials upset appears very easily, roll the circumstances such as fall, on the one hand, the efficiency of goods and materials transportation has been influenced greatly, on the other hand, also cause the damage to the goods and materials.
In order to solve the problems in the transportation of the flat car in the prior art, the logistics car is improved, for example, a guardrail is added to the flat car, the friction force of an object carrying surface of the flat car is increased, and the like. However, the increase of the guardrails can cause the loading capacity of the flat car to be greatly reduced, some materials with the volume exceeding the position of the guardrails cannot be loaded, and the increase of the friction force of the carrying surface of the flat car only greatly helps the stability of the materials directly contacting with the carrying surface, but has little help to the stability of the materials stacked on the upper layer.
Generally speaking, a method for realizing stable material stacking of a flat plate trolley in material transfer is urgently needed in the field, and the problems of unstable material and low efficiency in material transfer are solved, so that the material stacking stability and the transfer efficiency are improved.
Disclosure of Invention
In order to solve the problems in the prior art, namely the problems of low material stacking stability and low material transferring efficiency of a flat plate trolley in the existing material transferring process, the invention provides a material stacking method based on virtual reality stability analysis, which comprises the following steps:
step S10, VR glasses acquire a material stacking model group of a material sequence to be transferred, and calculate the gravity center of each material stacking model and the staggered overlapping rate of materials between two adjacent layers in the model;
step S20, acquiring a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
step S30, traversing each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
step S40, taking the material stacking model corresponding to the maximum stable value as the material stacking model of the material sequence to be transported, and generating a material stacking flow by VR glasses;
and step S50, matching the current materials to be stacked with the material stacking model by the VR glasses in real time, and stacking the next material if the matching of the current materials to be stacked is successful.
In some preferred embodiments, the matching between the currently stackable material and the material stacking model comprises:
step B10, matching the stacking position of the current materials to be stacked with the stacking position of the material stacking model by the VR glasses, and jumping to step B20 if the stacking position is incorrect; otherwise, jumping to step B30;
step B20, the VR glasses send out first alarm information, and strengthen the mark in the correct stacking position, guide the present materials to be stacked to stack in the correct stacking position;
step B30, matching the stacking direction of the materials to be stacked currently and the stacking model of the materials by the VR glasses, and if the stacking direction is incorrect, skipping to step B40; otherwise, jumping to step B50;
step B40, the VR glasses send out second alarm information, and generate a guide mark between the wrong stacking direction and the correct stacking direction, and guide the current materials to be stacked to be adjusted to the correct stacking direction;
and step B50, completing the matching of the materials to be stacked currently and the material stacking model.
In some preferred embodiments, the augmentation marker is:
and generating a three-dimensional virtual mark with the same size as the current material to be stacked at the correct stacking position, and dynamically changing the three-dimensional virtual mark to be used as a strengthening mark.
In some preferred embodiments, the guidance flag is:
a directional guide mark pointing from the wrong stacking direction to the correct stacking direction.
In some preferred embodiments, the stability analysis network is constructed based on a deep neural network, and the training method is as follows:
acquiring the gravity center of each material stacking model in the material stacking model group of the material sequence and the material staggered overlapping rate between two adjacent layers in the model as training samples;
performing dynamic analysis on the training sample under a set condition to obtain a stable value corresponding to the training sample and generate a sample label; the set conditions comprise a set movement direction, a set starting running acceleration, a set uniform speed running speed and a set stopping running deceleration;
inputting a training sample into the constructed stability analysis network, and calculating a loss value between the network output and a sample label;
and adjusting network parameters in the descending direction of the loss value and carrying out iterative training until a set training end condition is reached, thereby obtaining a trained stability analysis network.
In some preferred embodiments, the loss value between the network output and the sample label is expressed as:
wherein,
representing the loss function between the network output and the sample label,
the quantity of the material stacking models in the material stacking model group of the current material sequence,
is the probability distribution of the sample label corresponding to the material stacking model group of the current material sequence,
and the prediction probability distribution is output by the network corresponding to the material stacking model group of the current material sequence.
In some preferred embodiments, the gradient function of the drop in loss value is:
wherein,
as a function of the gradient of the drop in the loss value,
as a current parameter
Predicted probability distribution of network output under
Probability distribution with sample labels
The value of the loss in between is,
for a predetermined gradient descent acceleration function,
is an acceleration factor.
In another aspect of the present invention, a material stacking system based on virtual reality stability analysis is provided, which includes the following modules:
the center of gravity and staggered overlapping rate acquisition module is configured to acquire a material stacking model group of a material sequence to be transferred by VR glasses, and calculate the center of gravity of each material stacking model and the staggered overlapping rate of materials between two adjacent layers in the model;
the stability analysis module is configured to obtain a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
the traversing module is configured to traverse each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
the stacking flow generation module is configured to use a material stacking model corresponding to the maximum stable value as a material stacking model of the material sequence to be transferred, and generate a material stacking flow by VR glasses;
the matching and stacking module is configured to match the current materials to be stacked with the material stacking model of the VR glasses in real time, and if the matching of the current materials to be stacked is successful, the next material is stacked.
In a third aspect of the present invention, an electronic device is provided, including:
at least one processor; and
a memory communicatively coupled to at least one of the processors; wherein,
the memory stores instructions executable by the processor for execution by the processor to implement the above-described virtual reality-based stability analysis asset stacking method.
In a fourth aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for execution by the computer to implement the above-mentioned material stacking method based on virtual reality stability analysis.
The invention has the beneficial effects that:
(1) according to the material stacking method based on virtual reality stability analysis, the stacking models with different material sequences are obtained, the gravity center and the staggered stacking rate of each model are used as important factors of the stability of the models, the stability of the models is analyzed through the stability analysis network, the stacking model with the largest stable value is used as the stacking model for final transfer of the material sequences, the stability of material stacking is greatly improved on the basis of the original flat-plate trolley, and the efficiency of material transfer is effectively improved.
(2) According to the material stacking method based on virtual reality stability analysis, after an optimal material stacking model is obtained, the VR glasses guide the stacking of transported materials, meanwhile, the VR glasses match the stacked materials and the model in real time, the stacking process of the materials is supervised and restrained from the stacking position and the stacking direction, the material stacking efficiency and the accuracy are effectively improved, and the material stacking stability is guaranteed.
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Other features, objects and advantages of the present application will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:
FIG. 1 is a schematic flow chart of a material stacking method based on virtual reality stability analysis according to the present invention;
FIG. 2 is a schematic diagram of a stability analysis network training process according to an embodiment of the virtual reality-based stability analysis material stacking method of the present invention;
FIG. 3 is a schematic diagram illustrating a matching process of a currently stacked material and a material stacking model according to an embodiment of the virtual reality-based stability analysis-based material stacking method of the present invention;
FIG. 4 is a block diagram of a computer system of a server for implementing embodiments of the method, system, and apparatus of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The invention discloses a material stacking method based on virtual reality stability analysis, which comprises the following steps:
step S10, VR glasses acquire a material stacking model group of a material sequence to be transferred, and calculate the gravity center of each material stacking model and the staggered overlapping rate of materials between two adjacent layers in the model;
step S20, acquiring a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
step S30, traversing each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
step S40, taking the material stacking model corresponding to the maximum stable value as the material stacking model of the material sequence to be transported, and generating a material stacking flow by VR glasses;
and step S50, matching the current materials to be stacked with the material stacking model by the VR glasses in real time, and stacking the next material if the matching of the current materials to be stacked is successful.
In order to more clearly describe the material stacking method based on virtual reality stability analysis of the present invention, the following detailed description is made on the steps in the embodiment of the present invention with reference to fig. 1.
The material stacking method based on virtual reality stability analysis of the first embodiment of the invention comprises steps S10-S50, and the steps are described in detail as follows:
and step S10, the VR glasses acquire a material stacking model group of the material sequence to be transferred, and calculate the gravity center of each material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model.
The gravity center of each material is measured by the gravity center measuring device when the materials are put in storage, and the gravity center of each material and the volume, the shape and the like of each material are jointly used as the attributes of the materials to be stored, and when the materials are transported, the gravity center of each material can be obtained by reading the attributes in the materials.
After the barycenter of the materials to be transported is acquired, a model is stacked for each material, the geometric center of the material carrying surface of the material transporting flat trolley is used as an original point, the direction parallel to the long edge of the material carrying surface of the material transporting flat trolley is the X-axis direction, the direction parallel to the short edge of the material carrying surface of the material transporting flat trolley is the Y-axis direction, the direction perpendicular to the material carrying surface of the material transporting flat trolley is the Z-axis direction, a space coordinate system is established, the barycenter of each material of the material stacking model is expressed into a three-dimensional space coordinate system form, and the barycenter calculation of the whole material stacking model is carried out.
Taking the example of calculating the center of gravity of two material combinations, if the center of gravity of the first material is G1 and the center of gravity of the second material is G2, the combined center of gravity G12= (G1 + G2)/2, and the spatial coordinate corresponding to the midpoint of the line segment of G1 and G2 in the three-dimensional space is the coordinate of the combined center of gravity G12. By analogy, the gravity center of the material stacking model formed by a plurality of materials can be obtained.
The method for calculating the center of gravity of the material stacking model is only one preferred method of the invention, and other methods can be selected for calculating the center of gravity, which are not described in detail herein.
The staggered overlapping rate of the materials is an important attribute of stable transportation of the materials, the larger the staggered overlapping area of the materials is, the larger the gathering help of the materials on the upper layer to the materials on the lower layer is, and the more difficult the materials are to overturn and roll down.
And step S20, acquiring a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the material staggered overlapping rate between two adjacent layers in the model.
As shown in fig. 2, a schematic diagram of a stability analysis network training process according to an embodiment of the virtual reality-based stability analysis material stacking method of the present invention is shown, where the stability analysis network is constructed based on a deep neural network, and the training method includes:
the gravity center of each material stacking model in the material stacking model set of the material sequence and the material staggered overlapping rate between two adjacent layers in the model are obtained and used as training samples.
Performing dynamic analysis on the training sample under a set condition to obtain a stable value corresponding to the training sample and generate a sample label; the set conditions comprise a set moving direction, a set starting running acceleration, a set uniform running speed and a set stopping running deceleration.
In one embodiment of the present invention, the sample label is a soft label, and the calculation method is as shown in formula (1):
wherein,
a soft label representing the sample is provided,
for the stable values of the training samples output by the model,
and
respectively, a preset positive sample label threshold value and a preset negative sample label threshold value.
Inputting a training sample into the constructed stability analysis network, and calculating a loss value between the network output and a sample label, as shown in formula (2):
wherein,
representing the loss function between the network output and the sample label,
the quantity of the material stacking models in the material stacking model group of the current material sequence,
is the probability distribution of the sample label corresponding to the material stacking model group of the current material sequence,
and the prediction probability distribution is output by the network corresponding to the material stacking model group of the current material sequence.
And adjusting network parameters in the descending direction of the loss value and carrying out iterative training until a set training end condition is reached, thereby obtaining a trained stability analysis network.
The gradient function of the loss value decrease is shown in equation (3):
wherein,
as a function of the gradient of the drop in the loss value,
as a current parameter
Predicted probability distribution of network output under
Probability distribution with sample labels
The value of the loss in between is,
for a predetermined gradient descent acceleration function,
is an acceleration factor.
And step S30, traversing each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred.
And step S40, taking the material stacking model corresponding to the maximum stable value as the material stacking model of the material sequence to be transported, and generating a material stacking flow by VR glasses.
And step S50, matching the current materials to be stacked with the material stacking model by the VR glasses in real time, and stacking the next material if the matching of the current materials to be stacked is successful.
As shown in fig. 3, a schematic diagram of a matching process between a currently stacked material and a material stacking model according to an embodiment of the virtual reality-based stability analysis-based material stacking method of the present invention is shown, and the method includes:
step B10, matching the stacking position of the current materials to be stacked with the stacking position of the material stacking model by the VR glasses, and jumping to step B20 if the stacking position is incorrect; otherwise go to step B30.
And step B20, the VR glasses send out first alarm information, and strengthen marks are carried out at the correct stacking position, and the current materials to be stacked are guided to be stacked at the correct stacking position.
The reinforcement mark is:
and generating a three-dimensional virtual mark with the same size as the current material to be stacked at the correct stacking position, and dynamically changing the three-dimensional virtual mark to be used as a strengthening mark.
For example, a colored three-dimensional block with the same size as the material to be stacked at the right position is generated, and the three-dimensional block is flashed to prompt the right stacking position of the material.
Step B30, matching the stacking direction of the materials to be stacked currently and the stacking model of the materials by the VR glasses, and if the stacking direction is incorrect, skipping to step B40; otherwise it jumps to step B50.
And step B40, the VR glasses send out second alarm information, and generate a guide mark between the wrong stacking direction and the correct stacking direction to guide the current materials to be stacked to be adjusted to the correct stacking direction.
The boot flag is:
a directional guide mark pointing from the wrong stacking direction to the correct stacking direction.
For example, an arrow pointing from the wrong stacking direction to the correct stacking direction may likewise be flashed dynamically extended to indicate the correct stacking direction.
And step B50, completing the matching of the materials to be stacked currently and the material stacking model.
The strengthening mark of the stacking position and the guiding mark of the stacking direction can be set according to the requirement, and the invention is not described in detail herein.
Although the foregoing embodiments describe the steps in the above sequential order, those skilled in the art will understand that, in order to achieve the effect of the present embodiments, the steps may not be executed in such an order, and may be executed simultaneously (in parallel) or in an inverse order, and these simple variations are within the scope of the present invention.
The material stacking system based on the virtual reality stability analysis of the second embodiment of the invention comprises the following modules:
the gravity center and staggered overlapping rate acquisition module is configured to acquire a material stacking model group of a material sequence to be transferred by VR glasses, and calculate the gravity center of each material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
the stability analysis module is configured to obtain a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
the traversing module is configured to traverse each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
the stacking process generation module is configured to take a material stacking model corresponding to the maximum stable value as a material stacking model of the material sequence to be transported, and generate a material stacking process by VR glasses;
and the matching and stacking module is configured to match the materials to be stacked currently with the material stacking model in real time by the VR glasses, and stack the next material if the materials to be stacked are successfully matched currently.
It can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working process and related description of the system described above may refer to the corresponding process in the foregoing method embodiment, and details are not described herein again.
It should be noted that, the material stacking system based on virtual reality stability analysis provided in the foregoing embodiment is only illustrated by the division of the functional modules, and in practical applications, the functions may be allocated to different functional modules according to needs, that is, the modules or steps in the embodiment of the present invention are further decomposed or combined, for example, the modules in the foregoing embodiment may be combined into one module, or may be further split into multiple sub-modules, so as to complete all or part of the functions described above. The names of the modules and steps involved in the embodiments of the present invention are only for distinguishing the modules or steps, and are not to be construed as unduly limiting the present invention.
An electronic apparatus according to a third embodiment of the present invention includes:
at least one processor; and
a memory communicatively coupled to at least one of the processors; wherein,
the memory stores instructions executable by the processor for execution by the processor to implement the above-described virtual reality-based stability analysis asset stacking method.
A computer-readable storage medium of a fourth embodiment of the present invention stores computer instructions for execution by the computer to implement the above-described material stacking method based on virtual reality stability analysis.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes and related descriptions of the storage device and the processing device described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
Referring now to FIG. 4, therein is shown a block diagram of a computer system of a server that may be used to implement embodiments of the method, system, and apparatus of the present application. The server shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 4, the computer system includes a Central Processing Unit (CPU)601, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for system operation are also stored. The CPU 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An Input/Output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output section 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a Network interface card such as a LAN (Local Area Network) card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 as necessary.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611. The computer program performs the above-described functions defined in the method of the present application when executed by a Central Processing Unit (CPU) 601. It should be noted that the computer readable medium mentioned above in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The terms "first," "second," and the like are used for distinguishing between similar elements and not necessarily for describing or implying a particular order or sequence.
The terms "comprises," "comprising," or any other similar term are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
So far, the technical solutions of the present invention have been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of the present invention is obviously not limited to these specific embodiments. Equivalent changes or substitutions of related technical features can be made by those skilled in the art without departing from the principle of the invention, and the technical scheme after the changes or substitutions can be within the protection scope of the invention.
Claims (9)
1. A material stacking method based on virtual reality stability analysis is characterized by comprising the following steps:
step S10, VR glasses acquire a material stacking model group of a material sequence to be transferred, and calculate the gravity center of each material stacking model and the staggered overlapping rate of materials between two adjacent layers in the model;
step S20, acquiring a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
step S30, traversing each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
step S40, taking the material stacking model corresponding to the maximum stable value as the material stacking model of the material sequence to be transported, and generating a material stacking flow by VR glasses;
step S50, matching the current materials to be stacked with the material stacking model by the VR glasses in real time, and stacking the next material if the matching of the current materials to be stacked is successful;
the stability analysis network is constructed based on a deep neural network, and the training method comprises the following steps:
acquiring the gravity center of each material stacking model in a material stacking model group of a material sequence and the material staggered overlapping rate between two adjacent layers in the model as training samples;
performing dynamic analysis on the training sample under a set condition to obtain a stable value corresponding to the training sample and generate a sample label; the set conditions comprise a set movement direction, a set starting running acceleration, a set uniform speed running speed and a set stopping running deceleration;
inputting a training sample into the constructed stability analysis network, and calculating a loss value between the network output and a sample label;
and adjusting network parameters in the descending direction of the loss value and carrying out iterative training until a set training end condition is reached, thereby obtaining a trained stability analysis network.
2. The virtual reality-based material stacking method for stability analysis according to claim 1, wherein the matching between the currently stacked material and the material stacking model comprises:
step B10, matching the stacking position of the current materials to be stacked with the stacking position of the material stacking model by the VR glasses, and jumping to step B20 if the stacking position is incorrect; otherwise, jumping to step B30;
step B20, the VR glasses send out first alarm information, and strengthen the mark in the correct stacking position, guide the present materials to be stacked to stack in the correct stacking position;
step B30, matching the stacking direction of the materials to be stacked currently and the stacking model of the materials by the VR glasses, and if the stacking direction is incorrect, skipping to step B40; otherwise, jumping to the step B50;
step B40, the VR glasses send out second alarm information, and generate a guide mark between the wrong stacking direction and the correct stacking direction, and guide the current materials to be stacked to be adjusted to the correct stacking direction;
and step B50, completing the matching of the materials to be stacked currently and the material stacking model.
3. The virtual reality based stability analysis asset stacking method of claim 2, wherein the augmentation marker is:
and generating a three-dimensional virtual mark with the same size as the current material to be stacked at the correct stacking position, and dynamically changing the three-dimensional virtual mark to be used as a strengthening mark.
4. The virtual reality based stability analysis materials stacking method of claim 2, wherein the guidance mark is:
a directional guide mark pointing from the wrong stacking direction to the correct stacking direction.
5. The virtual reality based stability analysis asset stacking method of claim 1, wherein a loss value between the network output and a sample tag is expressed as:
the loss function between the network output and the sample label is represented, the number of the material stacking models in the material stacking model group of the current material sequence is represented, the probability distribution of the sample label corresponding to the material stacking model group of the current material sequence is represented, and the predicted probability distribution of the network output corresponding to the material stacking model group of the current material sequence is represented.
6. The virtual reality-based stability analysis materials stacking method of claim 5, wherein the gradient function of the loss value decrease is:
wherein, the gradient function of loss value decrease is the current parameter
The loss value between the predicted probability distribution of the lower network output and the probability distribution of the sample label is a preset gradient descent acceleration function and is an acceleration factor.
7. A virtual reality based stability analysis material stacking system, comprising:
the gravity center and staggered overlapping rate acquisition module is configured to acquire a material stacking model group of a material sequence to be transferred by VR glasses, and calculate the gravity center of each material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
the stability analysis module is configured to obtain a stable value of the current material stacking model through a stability analysis network based on the gravity center of the material stacking model and the staggered overlapping rate of the materials between two adjacent layers in the model;
the traversing module is configured to traverse each material stacking model of the material stacking model group to obtain a stable value of each material stacking model of the material sequence to be transferred;
the stacking flow generation module is configured to use a material stacking model corresponding to the maximum stable value as a material stacking model of the material sequence to be transferred, and generate a material stacking flow by VR glasses;
the matching and stacking module is configured to match the materials to be stacked currently with the material stacking model in real time by the VR glasses, and stack the next material if the materials to be stacked currently are successfully matched;
the stability analysis network is constructed based on a deep neural network, and the training method comprises the following steps:
acquiring the gravity center of each material stacking model in a material stacking model group of a material sequence and the material staggered overlapping rate between two adjacent layers in the model as training samples;
performing dynamic analysis on the training samples under a set condition to obtain stable values corresponding to the training samples and generate sample labels; the set conditions comprise a set movement direction, a set starting running acceleration, a set uniform speed running speed and a set stopping running deceleration;
inputting a training sample into the constructed stability analysis network, and calculating a loss value between the network output and a sample label;
and adjusting network parameters in the descending direction of the loss value and carrying out iterative training until a set training end condition is reached, thereby obtaining a trained stability analysis network.
8. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to at least one of the processors; wherein,
the memory stores instructions executable by the processor for execution by the processor to implement the method of stacking materials for virtual reality based stability analysis of any of claims 1-6.
9. A computer-readable storage medium storing computer instructions for execution by the computer to implement the method for stacking materials for virtual reality-based stability analysis of any one of claims 1-6.
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