A method of assembling a modular integrated building

Abstract

This application relates to the field of intelligent construction technology, providing a modular integrated building assembly method. The method includes: dividing the building plan into assembly units, dividing the building plan into peripheral modules located in the outer perimeter area and embedded modules located in the inner perimeter area; assembling the equipment inside the peripheral modules and the equipment inside the embedded modules in a factory according to the building plan, and transporting the peripheral modules and embedded modules to predetermined locations on the construction site according to a preset transportation route; assembling the peripheral modules in the outer perimeter area of ​​the building using a hoisting assembly method; sequentially sliding and positioning the embedded modules to the inner perimeter area using an automatic sliding vehicle according to a preset assembly sequence, and updating and displaying the assembly progress status in real time; and fixing the embedded modules and peripheral modules together to form a complete building. This application not only effectively improves construction progress but also ensures building safety.

Description

Technical Field

[0001] This application relates to the field of intelligent construction technology, and in particular to an assembly method for modular integrated buildings. Background Technology

[0002] With the deepening of a new round of technological revolution and industrial transformation, traditional construction methods in the construction industry have been significantly impacted, making it imperative to vigorously develop the intelligent construction industry to lead and drive the transformation and upgrading of the construction industry. Against this backdrop, taking new-type building industrialization as the path, we should vigorously develop MiC (Modular Integrated Construction), the core technology of the prefabricated building 4.0 era, to inject new momentum into the high-quality development of the construction industry.

[0003] The MiC modular integrated building system breaks down buildings into modular units during the design phase. All construction processes, including structure, decoration, water and electricity, equipment pipelines, and bathroom facilities, are completed efficiently in the factory. On-site, the modules are quickly assembled into a whole building through reliable connection technology, realizing "building houses like building cars". It is currently a green construction method with a high degree of industrialization in the building industry.

[0004] However, existing modular integrated buildings all use hoisting assembly. But some MIC modules located inside the building, such as consultation rooms, restrooms, and changing rooms, will shake during hoisting assembly, making it difficult to accurately assemble them into the predetermined installation position. This not only affects the construction progress but also the building's safety. Summary of the Invention

[0005] This application provides an assembly method for modular integrated buildings to solve the above-mentioned technical problems.

[0006] To achieve the above technical objectives, embodiments of this application provide an assembly method for modular integrated buildings, comprising:

[0007] The architectural drawings are divided into assembly units, namely, peripheral modules located in the outer area and embedded modules located in the inner area;

[0008] According to the architectural drawings, the assembly of each piece of equipment inside the peripheral module and the internal equipment inside the embedded module are completed in the factory. Then, according to the preset transportation route, the peripheral module and the embedded module are transported to the predetermined location on the construction site.

[0009] The peripheral modules are assembled on the exterior of the building using a hoisting and assembly method;

[0010] According to the preset assembly sequence, the embedded modules are slid and positioned sequentially to the embedded area by an automatic sliding tractor, and the assembly progress status is updated and displayed in real time.

[0011] The embedded modules are fixedly connected to the peripheral modules to form a complete building.

[0012] Furthermore, the step of dividing the architectural drawing into assembly units, dividing the architectural drawing into peripheral modules located in the outer area and embedded modules located in the inner area, includes:

[0013] The optimal assembly unit partitioning scheme is obtained through a cloning algorithm. The architectural drawing is then partitioned into assembly units based on the optimal assembly unit partitioning scheme, dividing the architectural drawing into peripheral modules located in the outer area and embedded modules located in the inner area.

[0014] Furthermore, the step of dividing the architectural drawing into assembly units, dividing the architectural drawing into peripheral modules located in the outer area and embedded modules located in the inner area, includes:

[0015] Step 21: Determine the initial population size of the assembly unit partitioning scheme;

[0016] Step 22: Generate an initial population using a random method and define a memory set, wherein the size threshold of the memory set is smaller than the size of the initial population;

[0017] Step 23: In the kth generation, evaluate the current assembly unit partitioning scheme and calculate the antigen affinity, antibody affinity and antibody reproduction rate of each scheme in the current assembly unit partitioning scheme population.

[0018] Step 24: If the current assembly unit partitioning scheme population contains the optimal assembly unit partitioning scheme, or the maximum number of iterations has been reached, then output the optimal assembly unit partitioning scheme and exit; otherwise, perform a memory operation and proceed to the next step.

[0019] Step 25: Select a predetermined number of high antigen affinity assembly unit partitioning schemes from the current assembly unit partitioning scheme population and add them to the memory set. When the number of assembly unit partitioning schemes in the memory set exceeds the memory set size threshold, use the exclusion algorithm to delete redundant schemes to obtain a high antigen affinity scheme group.

[0020] Step 26: Perform cloning operations on the current assembly unit population according to the antibody reproduction rate to generate a clone population;

[0021] Step 27: Perform crossover and mutation operations on the cloned population according to the crossover probability and mutation probability, respectively, to obtain a new population;

[0022] Step 28: Use the high antigen affinity scheme group in the memory set described in step 25 to replace the low antigen affinity scheme in the new population to generate a new assembly unit partitioning scheme population, and then jump to step 22.

[0023] Furthermore, determining the initial population size for the assembly unit partitioning scheme includes:

[0024] The assembly unit partitioning scheme is represented by a two-dimensional coding method, as shown in the following formula:

[0025]

[0026] In the above formula, n is the number of modules participating in the partitioning, and m is the maximum number of clusters; each row of the matrix represents an assembly unit, and the value of each cell indicates whether the module corresponding to the cell belongs to its corresponding assembly unit; a binary clustering coding matrix corresponds to an antibody. The initial population is set using a random method. For each column vector of the matrix, one element is randomly selected and set to 1, and the other elements of the column vector are set to 0 to form an initial antibody; this process is repeated until the pre-set population size is reached.

[0027] Furthermore, according to the preset assembly sequence, the embedded modules are sequentially slid and positioned into the embedded area by an automatic sliding vehicle, and the assembly progress status is updated and displayed in real time. The preset assembly algorithm includes the following steps:

[0028] Extract the assembly relationship matrix from the architectural drawings and initialize the directed graph to establish a hierarchical architectural structure. Perform path planning on the embedded areas in the building to fill the embedded areas layer by layer in combination with the path.

[0029] Based on the relationship between embedded regions at different levels, priority constraints between embedded modules are added to generate a high-level directed graph, that is, a relatively complete directed graph.

[0030] The optimal assembly sequence is obtained by heuristically searching the topological sorting of the high-level directed graph using the particle swarm optimization algorithm.

[0031] Furthermore, according to a preset assembly sequence, the embedded modules are sequentially slid and positioned into the embedded area by an automatic sliding vehicle, and the assembly progress status is updated and displayed in real time.

[0032] A reader and four antennas are installed on the automatic sliding vehicle, and a tag is placed in the embedded area. The vehicle is then positioned to the embedded area by sliding distance measurement.

[0033] Furthermore, the method of installing a reader and four antennas on the automatic sliding vehicle, placing a tag in the embedded area, and locating the embedded area by sliding distance measurement includes:

[0034] The reader is controlled sequentially to transmit RFID signals at frequencies f1 and f2 through four connected antennas;

[0035] The reader reads the carrier phases θ1 and θ2 and the incident angle α of the tag reflected signals at frequencies f1 and f2 in real time;

[0036] When the reader antenna transmits two RFID signals of different frequencies to the tag, and after traveling the same distance, receives two different phase values, the distance d between the reader and the target tag is calculated. i (i = 1, 2, 3, 4);

[0037] Construct a ranging triangle and calculate the distance from the label to the reader;

[0038] Calculate the final ranging result value D, and perform navigation and positioning based on the ranging result value.

[0039] Furthermore, according to the preset assembly sequence, the embedded modules are sequentially slid and positioned into the embedded area by an automatic sliding vehicle, and the assembly progress status is updated and displayed in real time. Specifically, updating and displaying the assembly progress status in real time includes:

[0040] When the distance between the label in the embedded area and the reader is zero, the assembly progress status will be updated in real time to show that the current embedded area is assembled.

[0041] As can be seen from the above, this application divides the building into an outer area and an inner area, assembling the outer module in the outer area using a hoisting assembly method and the inner module in the inner area using a sliding assembly method. Therefore, it effectively avoids the module shaking that occurs when assembling MIC modules located inside the building using a hoisting method. Furthermore, the sliding assembly method can accurately assemble the inner module to the predetermined installation position, which not only effectively improves the construction progress but also ensures the safety of the building. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating an assembly method for a modular integrated building provided in an embodiment of this application. Detailed Implementation

[0044] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0045] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0046] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0047] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0048] In addition, it should be noted that the sequence number of each step in this embodiment does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of this application embodiment.

[0049] To illustrate the technical solution described in this application, specific embodiments are provided below.

[0050] See Figure 1 , Figure 1 This is a flowchart illustrating an assembly method for a modular integrated building provided in an embodiment of this application. Figure 1 As shown, a method for assembling a modular integrated building includes the following steps:

[0051] Step 1: Design architectural drawings based on the Design for Manufacture and Assembly (DfMA) methodology;

[0052] Step 2: Divide the architectural drawing into assembly units, dividing it into peripheral modules located in the outer area and embedded modules located in the inner area;

[0053] Step 3: According to the architectural drawings, assemble the equipment inside the peripheral modules and the equipment inside the embedded modules in the factory, and transport the peripheral modules and embedded modules to the predetermined location on the construction site according to the preset transportation route.

[0054] Step 4: Assemble the peripheral modules on the outer perimeter of the building using a hoisting and assembly method;

[0055] Step 5: According to the preset assembly sequence, the embedded modules are slid and positioned sequentially to the embedded area by an automatic sliding trolley, and the assembly progress status is updated and displayed in real time;

[0056] Step 6: Securely connect the embedded module to the outer module to form a complete building.

[0057] Since the entire building is constructed by modular integration and assembly of the modules, it is necessary to consider the assembly process, sequence, and sub-modules of each module. This is the original intention of dividing the assembly unit.

[0058] At the same time, since two methods are to be used to assemble the building, namely, the outer area of ​​the building is assembled by hoisting and the inner area is assembled by sliding, the outer area and the inner area need to be separated. However, only one area is separated, and this area must carry the physical building. That is, the outer area carries the outer module and the inner area carries the inner module.

[0059] Based on this, architectural drawings can be divided into multiple assembly units. The outer modules of architectural drawings can be divided into one or more assembly units, and the embedded modules of architectural drawings can be divided into one or more assembly units.

[0060] The outer perimeter area carries the outer perimeter modules, which refer to the building's exterior walls and components that can be integrated with them. Correspondingly, the inner perimeter area is located inside the outer perimeter area and carries the inner perimeter modules (e.g., meeting rooms, restrooms, etc.).

[0061] Obviously, by dividing the building into an outer area and an inner area, and assembling the outer module in the outer area using a hoisting assembly method, and assembling the inner module in the inner area using a sliding assembly method, this application effectively avoids the module swaying that occurs when assembling MIC modules located inside the building using a hoisting method. Furthermore, the sliding assembly method can accurately assemble the inner module to the predetermined installation position, which not only effectively improves the construction progress but also ensures the safety of the building.

[0062] In this embodiment of the application, step 2, dividing the building drawing into assembly units, dividing the building drawing into peripheral modules located in the outer area and embedded modules located in the inner area, includes the following steps: Step 21, determining the initial population size, crossover probability, mutation probability, termination condition, encoding method, etc. of the assembly unit division scheme;

[0063] Step 22: Generate an initial population using a random method and define a memory set, with the memory set size threshold being smaller than the initial population size;

[0064] Step 23: In the kth generation, where k is greater than 3, evaluate the current assembly unit partitioning scheme and calculate the antigen affinity, antibody affinity, and antibody reproduction rate of each scheme in the current assembly unit partitioning scheme population.

[0065] Among them, antigen affinity represents the degree to which the antibody recognizes the antigen, reflecting the quality of the assembly unit partitioning scheme described by the antibody. Partitioning scheme a i The antigen affinity can be expressed as:

[0066]

[0067] In the above formula, F i For scheme a i The objective function value; F min To find the minimum objective function in the population for the partitioning scheme, F max To maximize the objective function in the population partitioning scheme;

[0068] Antibody affinity refers to the degree of similarity between antibodies. Since antibody populations use binary encoding, the Hamming distance between antibodies is used to calculate antibody affinity. Two arbitrary partitioning schemes (a, b, c) are chosen from the population. p and a q The corresponding clustering encoding matrices can be represented as follows: as well as

[0069] The number of assembly units corresponding to each partitioning scheme is not necessarily equal, i.e., m p With m q The values ​​of m are not necessarily equal. To facilitate the calculation of the Hamming distance between the schemes, without loss of generality, when m p >m q When, add matrix C q The number of rows is m p Since all the added matrix elements are 0, the result is transformed into the following formula:

[0070]

[0071] The Hamming distance between antibodies p and q can be expressed by the following formula:

[0072]

[0073] Considering that the Hamming distance between two identical partitioning schemes is 0, the antibody affinity between the schemes can be expressed as:

[0074]

[0075] It can be seen that aff pq∈(0,1],aff pq The larger the value of aff, the higher the similarity between the two schemes. pq When the value is 1, it means that the solutions are exactly the same;

[0076] In addition, partitioning scheme a i The antibody proliferation rate can be expressed as:

[0077]

[0078] In the above formula, AC i For partitioning scheme a i antibody concentration;

[0079] Step 24: If the current assembly unit partitioning scheme population contains the optimal assembly unit partitioning scheme, or the maximum number of iterations has been reached, output the optimal assembly unit partitioning scheme and exit; otherwise, perform a memory operation and proceed to the next step.

[0080] Step 25: Select a predetermined number of assembly unit partitioning schemes with high antigen affinity from the assembly unit partitioning scheme population and add them to the memory set. When the number of assembly unit partitioning schemes in the memory set exceeds the memory set size threshold, use the exclusion algorithm to delete redundant schemes. The exclusion algorithm can be an existing exclusion algorithm.

[0081] Step 26: Perform cloning operations on the current assembly unit population according to the antibody reproduction rate to generate a clone population;

[0082] Step 27: Perform crossover and mutation operations on the cloned population according to the crossover probability and mutation probability, respectively, to obtain a new population;

[0083] Step 28: Replace the low antigen affinity scheme in the new population with the high antigen affinity scheme from the memory set in Step 25 to generate a new population with a new partitioning scheme, and then jump to Step 22.

[0084] Obviously, the embodiments of this application can obtain the optimal assembly unit division scheme through the cloning algorithm, thereby making the division of the outer and inner areas of the building more reasonable and facilitating efficient and reliable assembly.

[0085] The assembly unit partitioning scheme can be represented using a two-dimensional coding method, for example, it can be represented by the following formula:

[0086]

[0087] In the above formula, n is the number of modules participating in the partitioning, and m is the maximum number of clusters; each row of the matrix represents an assembly unit (cluster), and the value of each cell indicates whether the module corresponding to the cell belongs to its corresponding assembly unit; a binary clustering coding matrix corresponds to an antibody. The initial population is set using a random method. For each column vector of the matrix, one element is randomly selected and set to 1, and the other elements of the column vector are set to 0 to form an initial antibody; this process is repeated until the pre-set population size is reached.

[0088] Clearly, by using a two-dimensional encoding method to represent the assembly unit partitioning scheme, the algorithm process can be simplified, and the optimal assembly unit partitioning scheme can be calculated quickly.

[0089] In this embodiment of the application, step 5 involves using an automatic sliding vehicle to sequentially slide and position the embedded modules to the embedded area according to a preset assembly sequence, and updating and displaying the assembly progress status in real time. The preset assembly algorithm may include the following steps:

[0090] Extract the assembly relationship matrix from the architectural drawings and initialize the directed graph to establish a hierarchical architectural structure. Perform path planning on the embedded areas in the building to fill the embedded areas layer by layer in combination with the path.

[0091] Based on the relationship between embedded regions at different levels, priority constraints between embedded modules are added to generate a high-level directed graph, that is, a relatively complete directed graph.

[0092] The optimal assembly sequence is obtained by heuristically searching the topological sorting of the high-level directed graph using the particle swarm optimization algorithm.

[0093] Clearly, since the sequences generated by directed graph topological sorting are of high quality, using particle swarm optimization to heuristically search these sequences reduces the search space compared to traditional methods, thus enabling the faster identification of optimal assembly sequences.

[0094] The process involves using an automated sliding vehicle to sequentially slide and position the embedded modules to the embedded area. This can be achieved by mounting a reader and four antennas on the automated sliding vehicle, placing a tag in the embedded area, and using sliding ranging to locate the modules within the embedded area. Specifically, this includes:

[0095] The reader is controlled sequentially to transmit RFID signals at frequencies f1 and f2 through four connected antennas;

[0096] The reader reads the carrier phases θ1 and θ2 and the incident angle α of the tag reflected signals at frequencies f1 and f2 in real time;

[0097] When the reader antenna transmits two RFID signals of different frequencies to the tag, and after traveling the same distance, receives two different phase values, the distance d between the reader and the target tag is calculated.i (i = 1, 2, 3, 4);

[0098] Construct a ranging triangle and calculate the distance D between the label and the reader using a first preset formula. i (i = 1, 2, 3, 4);

[0099] The final distance measurement result value D is calculated using the second preset formula, and navigation and positioning are performed based on the distance measurement result value.

[0100] The first preset formula can be expressed by the following equation:

[0101]

[0102] In the above formula, d0 is the distance between the antenna and the reader.

[0103] The second preset formula can be expressed as follows:

[0104]

[0105] The real-time updating and display of assembly progress status can include:

[0106] When the distance between the label in the embedded area and the reader is zero, the assembly progress status will be updated in real time to show that the current embedded area is assembled. For example, the red mark when it is not assembled can be updated to a green mark to indicate that the current embedded area is assembled.

[0107] Clearly, by unifying the updates of RFID tags with events during the assembly process, the assembly execution status can be reflected through the status of the RFID tags, thus facilitating real-time monitoring of the assembly progress.

[0108] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0109] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0110] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0111] The methods described in this application can be implemented in whole or in part by a computer program product. When the computer program product is run on a terminal, the terminal executes the steps in the various method embodiments described above.

[0112] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method of assembling a modular integrated building, characterized in that, include: The architectural drawing is divided into assembly units, namely, peripheral modules located in the outer area and embedded modules located in the inner area; According to the architectural drawings, the assembly of each device inside the peripheral module and the assembly of each device inside the embedded module are completed in the factory, and the peripheral module and the embedded module are transported to the predetermined location on the construction site according to the preset transportation route. The peripheral modules are assembled into the peripheral area using a hoisting and assembly method. According to the preset assembly sequence, the embedded modules are sequentially slid and positioned to the embedded area by an automatic sliding vehicle, including: setting a reader and four antennas on the automatic sliding vehicle, setting a tag in the embedded area, positioning the embedded modules to the embedded area by sliding distance measurement; and updating and displaying the assembly progress status in real time. The embedded module and the peripheral module are fixedly connected to form a complete building; The step of dividing the architectural drawing into assembly units, which involves dividing the architectural drawing into peripheral modules located in the outer area and embedded modules located in the inner area, includes: An optimal assembly unit partitioning scheme is obtained through a cloning algorithm. Based on this scheme, the architectural drawing is divided into assembly units, resulting in peripheral modules located in the outer perimeter area and embedded modules located in the inner perimeter area. The peripheral modules refer to the building's exterior walls, and the embedded modules include meeting rooms and restrooms. According to a preset assembly sequence, an automatic sliding vehicle sequentially slides and positions the embedded modules to the inner perimeter area, updating and displaying the assembly progress status in real time. This process also includes obtaining the optimal preset assembly sequence based on a preset assembly algorithm, specifically: The assembly relationship matrix is ​​extracted from the architectural drawings and a directed graph is initialized. A hierarchical architectural structure is established, and path planning is performed on the embedded areas to fill the embedded areas layer by layer in combination with the paths. The priority constraints between the embedded modules are supplemented based on the relationships between the embedded regions at different levels, thereby generating a high-level directed graph; The optimal preset assembly sequence is obtained by performing a heuristic search on the topological sorting of the high-level directed graph using the particle swarm optimization algorithm.

2. The method of claim 1, wherein The process of obtaining the optimal assembly unit partitioning scheme through the cloning algorithm includes: Step 21: Determine the initial population size of the assembly unit partitioning scheme; Step 22: Generate an initial population using a random method and define a memory set, wherein the size threshold of the memory set is smaller than the size of the initial population; Step 23: In the kth generation, evaluate the current assembly unit partitioning scheme and calculate the antigen affinity, antibody affinity and antibody reproduction rate of each scheme in the current assembly unit partitioning scheme population. Step 24: If the current assembly unit partitioning scheme population contains the optimal assembly unit partitioning scheme, or the maximum number of iterations has been reached, then output the optimal assembly unit partitioning scheme and exit; otherwise, perform a memory operation and proceed to the next step. Step 25: Select a predetermined number of high antigen affinity assembly unit partitioning schemes from the current assembly unit partitioning scheme population and add them to the memory set. When the number of assembly unit partitioning schemes in the memory set exceeds the memory set size threshold, use an exclusion algorithm to delete redundant schemes. Step 26: Perform cloning operations on the current assembly unit population according to the antibody reproduction rate to generate a clone population; Step 27: Perform crossover and mutation operations on the cloned population according to the crossover probability and mutation probability, respectively, to obtain a new population; Step 28: Replace the low antigen affinity scheme in the new population with a predetermined number of high antigen affinity assembly unit partitioning schemes from the memory set described in step 25 to generate a new assembly unit partitioning scheme population, and then jump to step 22.

3. The method according to claim 2, characterized in that, The determination of the initial population size for the assembly unit partitioning scheme includes: The assembly unit partitioning scheme is represented by a two-dimensional coding method, as shown in the following formula: In the above formula, The number of modules participating in the partitioning. The maximum number of clusters is defined as follows: each row of the matrix represents an assembly unit, and the value of each cell indicates whether the module corresponding to that cell belongs to its corresponding assembly unit; a binary clustering coding matrix corresponds to one antibody. The initial population is set using a random method. For each column vector of the matrix, one element is randomly selected and set to 1, while the other elements of the column vector are set to 0, forming an initial antibody. This process is repeated until the pre-set initial population size is reached.

4. The method according to claim 1, characterized in that, The process of installing a reader and four antennas on the automated guided vehicle, placing a tag in the embedded area, and positioning the embedded module to the embedded area via sliding ranging includes: The reader is sequentially controlled to transmit at frequencies via four connected antennas. and RFID signals; The reader's real-time reading frequency is and The carrier phase of the reflected signal of the tag below and and angle of incidence ; When the reader controls the antenna to transmit two RFID signals of different frequencies to the tag, and after traveling the same distance, receives two different phase values, the first distance between the reader and the tag is calculated. ; Construct a ranging triangle, and calculate a second distance between the tag and the reader based on the first distance; The final ranging result value D is calculated based on the second distance, and navigation and positioning are performed based on the ranging result value D.

5. The method according to claim 4, characterized in that, The process involves using an automated sliding vehicle to sequentially slide and position the embedded modules to the embedded area according to a preset assembly sequence, and updating and displaying the assembly progress status in real time. Specifically, updating and displaying the assembly progress status in real time includes: When the distance between the label and the reader is zero, the assembly progress status will be updated in real time to show that the current embedded area is assembled.

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