Management method for point cloud data and three-dimensional model data of underground pipeline channel

Abstract

The invention relates to the technical field of data processing, and particularly discloses a method for managing point cloud data and three-dimensional model data of an underground pipeline channel, comprising the following steps: determining each pipeline channel node of the underground pipeline channel; scanning each pipeline channel node through static three-dimensional laser scanning equipment to obtain point cloud data corresponding to each pipeline channel node; performing three-dimensional modeling based on the point cloud data under the coordinate system of the static three-dimensional laser scanning equipment to obtain three-dimensional model data corresponding to each pipeline channel node; and determining registration parameters corresponding to the point cloud data of each pipeline channel node, and merging and displaying the three-dimensional model data of all the pipeline channel nodes. Therefore, modeling after complete registration of the point cloud data is not needed, the three-dimensional model data and the registration parameters can be adjusted independently and flexibly, the defect that only the whole model can be deleted if the registration parameters are wrong is avoided, and the flexibility of three-dimensional modeling and data application is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data management, and in particular to a method for managing point cloud data and three-dimensional model data of an underground pipeline channel. Background Art

[0002] Underground pipeline channels, especially urban underground pipeline channels, are mainly composed of underground working wells and inter-well connecting parts (such as Figure 1 As shown). Among them, the underground working well is an underground limited space with a specific spatial form (length, width, height) and connected to the ground through the well neck; the connecting parts between the wells are of types such as drainage pipes, trenches and tunnels. The spacing distances between working wells are different for different types of pipeline channels. For example: when the pipe diameter is greater than or equal to 200mm, the distance between underground working wells such as inspection wells should not be greater than 30m; the distance between inspection wells on municipal drainage pipes should not be greater than 50m; when laying cable drainage pipes, the distance between two underground working wells in the straight section should not be greater than 150m.

[0003] Use a 3D laser scanner (such as a static station 3D laser scanner or a portable laser scanner) to scan underground pipeline channels and capture point cloud data of channel sections, pipeline equipment and other details. The laser scanner obtains high-precision spatial position data by emitting laser beams and calculating the reflection time, forming a large number of dense 3D coordinate points, namely point cloud data. Point cloud data can "replicate" the on-site situation in real life and accurately and objectively reflect the actual situation of underground pipeline channels. It is more efficient and accurate than traditional measurement methods. A 3D model can be generated through point cloud data, such as using 3D modeling tool software (such as Revit, 3DMAX, MeshLab, Blender, etc.) or custom-developed modeling software to convert point cloud data into a mesh model or vector model. Based on the constructed 3D model, visualization analysis and application of underground channel resources can be carried out to support work such as construction planning, asset management, and safety protection, which can provide basic data support for the construction of smart cities.

[0004] Typically, point cloud data is collected from different perspectives or positions by a scanner. Especially in larger scenes or complex environments such as underground pipelines, a single scan may not cover the entire area or details (of course, for smaller scenes, a single scan can also cover the entire area and details). The point cloud data generated at each scanning position is only local information. There are differences in spatial position, direction, etc. between the point cloud data obtained at different scanning positions, and they cannot be directly combined together. For 3D modeling based on point cloud data, it is usually necessary to first align and splice the point cloud to ensure that the data obtained from multiple scans can be accurately docked and merged, eliminate the spatial errors between the scan data, and finally obtain a complete and accurate 3D point cloud.

[0005] Point cloud registration refers to aligning point cloud data obtained from different perspectives or positions into the same coordinate system (generally the actual geographic coordinate system according to the needs of later display and utilization) by solving the coordinate transformation relationship to ensure that they correspond correctly in space. Point cloud stitching usually refers to merging multiple different, overlapping station point clouds into a complete point cloud.

[0006] When performing static 3D laser scanning on underground pipeline channels, for reasons of operational safety, scanning equipment such as the scanning distance of a single station of the scanner, point cloud registration, and stitching accuracy, when the manhole cover can be opened, the scanner is inverted and lowered into the well for scanning; when there is no manhole cover on the ground but personnel and equipment can enter the channel, a static scan is performed every 20-30m in the channel, and encrypted scanning is performed at key nodes of the channel (such as turning points or bifurcation points) to obtain point cloud data.

[0007] In the prior art, when performing 3D modeling of underground pipeline channels, a common practice is to first align all point cloud data to the same coordinate system (i.e., the actual geographic coordinate system) to form the overall point cloud data of the channel, and then model the overall channel based on the overall point cloud data. In this case, when the registration and splicing of the overall point cloud data of the channel are inaccurate, it will be passed to the 3D modeling link, causing errors in the channel model. Even if it is discovered later, it cannot be improved. The only option is to delete the overall model and then re-model it with the correctly registered overall point cloud data. Summary of the invention

[0008] In view of this, an object of the present invention is to provide a method for managing point cloud data and three-dimensional model data of an underground pipeline channel, so as to overcome the problem of poor flexibility in the current modeling of underground pipeline channels.

[0009] To achieve the above objectives, the present invention adopts the following technical solutions: The present application provides a method for managing point cloud data and three-dimensional model data of an underground pipeline channel, including: Determine each pipeline channel node of the underground pipeline channel; Scan each of the pipeline channel nodes respectively by a static three-dimensional laser scanning device to obtain point cloud data corresponding to each of the pipeline channel nodes; wherein one pipeline channel node corresponds to at least one point cloud data, and one point cloud data corresponds to only one pipeline channel node; Performing three-dimensional modeling based on the point cloud data in the coordinate system of the static three-dimensional laser scanning device itself to obtain three-dimensional model data corresponding to each of the pipeline channel nodes; The registration parameters corresponding to the point cloud data of each pipeline channel node are determined, and the three-dimensional model data of all the pipeline channel nodes are combined and displayed based on the registration parameters.

[0010] Furthermore, in some embodiments of the present application, the step of determining each pipeline channel node of the underground pipeline channel includes: Determining the node interval based on the spatial form of the underground pipeline channel, the distribution of pipeline equipment in the channel, and the scanning range of the static three-dimensional laser scanning device; Based on the node intervals, each pipeline channel node of the underground pipeline channel is determined.

[0011] Furthermore, in some embodiments of the present application, the registration parameters are used to locate key points in the point cloud data and the three-dimensional model data, and to orient the initial directions of the point cloud data and the three-dimensional model data.

[0012] Further, in some embodiments of the present application, for a pipeline channel node corresponding to a point cloud data, determining the registration parameters corresponding to the point cloud data of each pipeline channel node includes: The registration parameters corresponding to each point cloud data are calculated respectively through external equipment.

[0013] Furthermore, in some embodiments of the present application, for a pipeline channel node corresponding to at least two point cloud data, it also includes: Determine reference point cloud data from a plurality of point cloud data corresponding to the pipeline channel node; splice point cloud data other than the reference point cloud data from the plurality of point cloud data corresponding to the pipeline channel node onto the reference point cloud data to form overall point cloud data of the pipeline channel node; For pipeline channel nodes corresponding to at least two point cloud data, determining the registration parameters corresponding to the point cloud data of each pipeline channel node includes: calculating the registration parameters corresponding to the reference point cloud data through an external device.

[0014] Further, in some embodiments of the present application, the merging and displaying of the three-dimensional model data of all the pipeline channel nodes based on the registration parameters includes: The sections in the three-dimensional model data of adjacent pipeline channel nodes are connected to form a three-dimensional model between the pipeline channel nodes.

[0015] Furthermore, in some embodiments of the present application, it also includes: When an error occurs in merging and displaying the three-dimensional model data of the plurality of pipeline channel nodes, the alignment parameters are recalculated and updated, and based on the updated alignment parameters, the three-dimensional model data are merged and displayed again.

[0016] Furthermore, in some embodiments of the present application, it also includes: When the geographic coordinate system is to be changed for merging and displaying the three-dimensional model data, the alignment parameters are updated, and based on the updated alignment parameters, the three-dimensional model data are merged and displayed again.

[0017] The present invention relates to the field of data processing technology, and specifically discloses a method for managing point cloud data and three-dimensional model data of an underground pipeline channel, including: determining each pipeline channel node of the underground pipeline channel; scanning each pipeline channel node separately by a static three-dimensional laser scanning device to obtain point cloud data corresponding to each pipeline channel node; performing three-dimensional modeling based on the point cloud data in the coordinate system of the static three-dimensional laser scanning device itself to obtain three-dimensional model data corresponding to each pipeline channel node; determining the alignment parameters corresponding to the point cloud data of each pipeline channel node, and merging and displaying the three-dimensional model data of all pipeline channel nodes. In this way, it is not necessary to model the point cloud data after complete alignment, and the three-dimensional model data and alignment parameters can be adjusted separately and flexibly, avoiding the disadvantage that the entire model can only be deleted if the alignment parameters are wrong, and improving the flexibility of three-dimensional modeling and data application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a schematic diagram of an underground pipeline channel in the prior art; Figure 2 It is a flow chart of a method for managing point cloud data and three-dimensional model data of an underground pipeline channel provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0020] To make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other implementation methods obtained by ordinary technicians in this field without creative work belong to the scope of protection of the present invention.

[0021] Figure 2 This is a flow chart of a method for managing point cloud data and three-dimensional model data of underground pipeline channels provided by an embodiment of the present invention. Figure 2 , this embodiment may include the following steps: S101. Determine each pipeline channel node of the underground pipeline channel.

[0022] Specifically, it should be noted that, in the present application, each pipeline channel node of the underground pipeline channel is determined as a channel portion for the underground pipeline channel, that is, Figure 1 The underground working well shown in the figure is carried out. The interval between pipeline channel nodes, i.e., the node interval, can be determined based on the spatial form of the underground pipeline channel, the distribution of pipeline equipment in the channel, and the scanning range of the static three-dimensional laser scanning device that scans and obtains point cloud data, and then the pipeline channel nodes of the underground pipeline channel are determined based on the node interval. On this basis, in some embodiments of the present application, key channel nodes such as inflection points and bifurcation points can also be used to improve the determination of each pipeline channel node.

[0023] S102, scanning each pipeline channel node respectively by using a static three-dimensional laser scanning device to obtain point cloud data corresponding to each pipeline channel node.

[0024] Specifically, each pipeline channel node can be scanned multiple times by one or more static 3D laser scanning devices or by one static 3D laser scanning device to obtain point cloud data. Each static 3D laser scan can be regarded as a measuring station, and the point cloud data obtained by a measuring station is called a point cloud data.

[0025] Based on the above settings, it can be understood that the point cloud data finally obtained by scanning all correspond to the pipeline channel nodes and the static three-dimensional laser scanning equipment, wherein each pipeline channel node corresponds to the point cloud data of at least one measuring station. Of course, at some pipeline channel nodes, when multiple point cloud data of the pipeline channel node are obtained by scanning multiple measuring stations, the pipeline channel node corresponds to multiple point cloud data.

[0026] S103, performing three-dimensional modeling based on the point cloud data in the coordinate system of the static three-dimensional laser scanning device itself, and obtaining three-dimensional model data corresponding to each pipeline channel node.

[0027] In this application, when performing 3D modeling, only one 3D model data is generated based on one pipeline channel node, regardless of whether the point cloud data of this pipeline channel node is composed of one measuring station or multiple measuring stations. In other words, in this application, regardless of how many point cloud data a pipeline channel node corresponds to, a pipeline channel node ultimately generates only one 3D model data using the point cloud data corresponding to it.

[0028] In practical applications, for a pipeline channel node corresponding to at least two point cloud data, the reference point cloud data can be first determined from the multiple point cloud data corresponding to the pipeline channel node; then the point cloud data other than the reference point cloud data in the multiple point cloud data corresponding to the pipeline channel node can be spliced ​​onto the reference point cloud data to form the overall point cloud data of the pipeline channel node, and then the overall point cloud data of the pipeline channel node can be used for modeling to obtain the three-dimensional modeling data of the pipeline channel node.

[0029] It should be noted that due to the rigid body properties of the point cloud data obtained by the static 3D laser scanning equipment, the registration of the point cloud data or 3D model data can only be done by translating and rotating the point cloud data or 3D model data (because the rigid body cannot be scaled). Among them, the core of the registration is to determine the 3D coordinates of key points in the point cloud data of each measuring station, such as the scanning center, and to orient the initial direction of the point cloud data. Among them, it should be noted that after the point cloud data is registered, the registration of the corresponding 3D model data can be automatically achieved through the preset software, that is, the 3D coordinates of key points in the 3D model data, such as the center, are located, and the initial direction of the 3D model data is oriented. Therefore, different registration results can be obtained by registering the same point cloud data or 3D model data with different registration parameters.

[0030] In practical applications, point cloud data that has not been registered with registration parameters is based on the coordinate system of a scanning device such as a scanner itself. In this application, the corresponding point cloud data is three-dimensionally modeled through the coordinates of the static three-dimensional laser scanning device itself, thereby obtaining three-dimensional model data corresponding to each pipeline channel node.

[0031] It should be noted that when a pipeline channel node corresponds to only one point cloud data, the point cloud data is directly used to generate the three-dimensional modeling data corresponding to the pipeline channel node, and when the pipeline channel node corresponds to at least two point cloud data, the spliced ​​overall point cloud data is used to generate the three-dimensional modeling data corresponding to the pipeline channel node.

[0032] S104: determining the registration parameters corresponding to the point cloud data of each pipeline channel node, and merging and displaying the three-dimensional model data of all pipeline channel nodes based on the registration parameters.

[0033] Specifically, after determining the registration parameters corresponding to the point cloud data of each pipeline channel node (as mentioned below, when a pipeline channel node corresponds to at least two point cloud data, only the registration parameters of the reference point cloud data need to be determined), the three-dimensional model data corresponding to all the above pipeline channel nodes are merged and displayed based on their respective registration parameters, thereby obtaining and displaying the overall model of the underground pipeline channel.

[0034] It can be understood that in the present application, because only the point cloud data corresponding to the node is used when modeling the pipeline channel node, and no alignment parameters are required, the solution of the present application can also improve the immediacy and flexibility of modeling to a certain extent for the modeling link.

[0035] The management method of point cloud data and three-dimensional model data of underground pipeline channels provided by the present application reasonably decomposes the overall modeling of underground pipeline channels into independent modeling of each pipeline channel node, so that the quality of node modeling is not affected by the registration parameters, and modeling can be performed without waiting until the point cloud data of all nodes are fully registered, thereby improving the flexibility of three-dimensional modeling and data application. At the same time, the registration error of the point cloud data of the pipeline channel node can be corrected by updating the registration parameters of the point cloud data of the individual node, avoiding the risk of having to delete and rebuild the overall model when there is a registration error in the point cloud data of an individual node.

[0036] In addition, in order to ensure that all 3D model data can be efficiently combined and displayed, in the embodiment of the present application, it can be stipulated that when selecting the point cloud data of the pipeline channel node for modeling, the point cloud data selected by each pipeline channel node cannot overlap with the point cloud data of other nodes, thereby ensuring that the 3D model data does not overlap when combined and displayed, and then the 3D model data is combined and displayed by connecting the sections mentioned later. In practical applications, point cloud data can be selected for all or specific nodes based on the scanning range of a static 3D laser scanning device. For example, the scanning range of a static 3D laser scanning device is 50m, and when modeling the point cloud data of the pipeline channel node, only 30m is selected for modeling.

[0037] Furthermore, in the present application, determining the registration parameters corresponding to the point cloud data of each pipeline channel node can be achieved by the following method: First, for the pipeline channel node corresponding to a point cloud data, the registration parameters corresponding to the point cloud data of all pipeline channel nodes can be directly calculated by external equipment. For example, the point cloud data can be absolutely positioned and oriented by using external equipment to determine the registration parameters corresponding to the point cloud data of each pipeline channel node. In addition, for the pipeline channel node corresponding to at least two point cloud data, it is only necessary to determine the registration parameters of the reference point cloud data. In practical applications, because for the pipeline channel node corresponding to at least two point cloud data, its non-reference point cloud data (point cloud data other than the reference point cloud data in the multiple point cloud data corresponding to the pipeline channel node) is spliced ​​on the reference point cloud data, therefore, when the registration parameters of the reference point cloud data are determined, there is no need to determine the registration parameters of the non-reference point cloud data.

[0038] In the present application, when the three-dimensional model data of all nodes are combined and displayed based on the registration parameters, each pipeline channel node has an independent modeling result under a scanning device such as a scanner coordinate system, namely the three-dimensional model data of the node, and the registration parameters of the target coordinate system for display (in actual applications, the geographic coordinate system in reality) corresponding to the point cloud data under the node. At this time, the three-dimensional model data of each node can be called and used as a separate model, and combined and displayed based on their respective registration parameters to form the final overall model of the underground pipeline channel. Among them, when merging, the sections in the three-dimensional model data of adjacent pipeline channel nodes can be connected to form a connection between pipeline channel nodes (i.e. Figure 1 A three-dimensional model of the well connection part in the pipeline.

[0039] It should be noted that in the present application, in the overall model, the above-mentioned connected parts are composed of direct connections between corresponding sections of the three-dimensional model data of adjacent nodes, so when the alignment parameters change, the model of the corresponding connected parts will also change accordingly, thereby ensuring the tightness of the overall model.

[0040] Furthermore, the management method of point cloud data and three-dimensional model data of underground pipeline channels provided in the present application also includes: when an error occurs in the merging of three-dimensional model data of multiple nodes (such as the positions cannot be merged together, etc.), recalculating and updating the alignment parameters, and re-merging and displaying the three-dimensional model data based on the updated alignment parameters.

[0041] Specifically, when the registration parameters of the point cloud data of a certain node are inaccurate, it may cause the merging of the 3D model data of multiple nodes to fail. In this case, the registration parameters can be updated only for the point cloud data with inaccurate registration parameters, and then merged and displayed again. And when the geographic coordinate system is changed for merging and displaying the 3D model data, the registration parameters of all point cloud data can be updated to orient and locate the corresponding 3D model data, and then merged and displayed again.

[0042] The management method of point cloud data and three-dimensional model data of underground pipeline channels provided by the present application, when performing three-dimensional modeling of underground pipeline channels, firstly independently modeling is performed for each pipeline channel node based on the point cloud data of the scanning device such as the scanner's own coordinate system to obtain three-dimensional model data, and then the independent three-dimensional model data of each node is merged and displayed in the same coordinate system through the registration parameters of the point cloud data of each pipeline channel node to obtain the overall model of the underground pipeline channel. Among them, for the connection part of the three-dimensional model of each node, the corresponding sections of the three-dimensional model data of the adjacent nodes are connected to form a three-dimensional model of the connected part. In this way, the point cloud data of each pipeline channel node can be positioned and oriented with their own separate registration parameters. Even if the registration parameters of the point cloud data of some nodes are inaccurate, they can be adjusted by updating the registration parameters separately, thereby avoiding the need to delete and rebuild the overall model due to problems with the registration of the point cloud data of a certain node, greatly improving the flexibility of three-dimensional modeling and data application of underground pipeline channels, and avoiding error transmission and spread due to initial data errors.

[0043] In addition, in the present application, each of the above steps can be performed at different ends. For example, the generation of node three-dimensional model data, the merging of the overall model, and the subsequent display and utilization of the overall model can be performed by different relevant personnel at different ends. Through the above technical solution, not only the operating difficulty of personnel at each end can be reduced, but also the confidentiality of process results can be achieved and data security can be guaranteed.

[0044] Specifically, for example, modelers who generate 3D model data of pipeline channel nodes do not need to understand the registration parameters and related operations, which can reduce their work difficulty and achieve data confidentiality for the registration parameters. In addition, the registration parameters can be set with the same constant at the scanning center of the registration parameters of the relevant measuring stations for overall offset, and unified corrections can be made after the overall modeling is completed, thereby achieving full data confidentiality of 3D modeling.

[0045] It can be understood that the same or similar parts of the above embodiments can be referenced to each other, and the contents not described in detail in some embodiments can refer to the same or similar contents in other embodiments.

[0046] It should be noted that, in the description of the present invention, the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, the meaning of "plurality" refers to at least two.

[0047] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code that includes one or more executable instructions for implementing the steps of a specific logical function or process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention belong.

[0048] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0049] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0050] In addition, each functional unit in each embodiment of the present invention may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0051] The storage medium mentioned above can be a read-only memory, a magnetic disk or an optical disk, etc.

[0052] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0053] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A method for managing point cloud data and three-dimensional model data of an underground pipeline channel, characterized in that: include: Determine each pipeline channel node of the underground pipeline channel; Scan each of the pipeline channel nodes respectively by a static three-dimensional laser scanning device to obtain point cloud data corresponding to each of the pipeline channel nodes; wherein one pipeline channel node corresponds to at least one point cloud data, and one point cloud data corresponds to only one pipeline channel node; Performing three-dimensional modeling based on the point cloud data in the coordinate system of the static three-dimensional laser scanning device itself to obtain three-dimensional model data corresponding to each of the pipeline channel nodes; The registration parameters corresponding to the point cloud data of each pipeline channel node are determined, and the three-dimensional model data of all the pipeline channel nodes are combined and displayed based on the registration parameters.

2. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: The step of determining each pipeline channel node of the underground pipeline channel includes: Determining the node interval based on the spatial form of the underground pipeline channel, the distribution of pipeline equipment in the channel, and the scanning range of the static three-dimensional laser scanning device; Based on the node intervals, each pipeline channel node of the underground pipeline channel is determined.

3. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: The registration parameters are used to locate key points in the point cloud data and the three-dimensional model data, and to orient the initial directions of the point cloud data and the three-dimensional model data.

4. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: For a pipeline channel node corresponding to a point cloud data, determining the registration parameters corresponding to the point cloud data of each pipeline channel node includes: The registration parameters corresponding to each point cloud data are calculated respectively through external equipment.

5. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: For the pipeline channel node corresponding to at least two point cloud data, it also includes: Determine reference point cloud data from a plurality of point cloud data corresponding to the pipeline channel node; splice point cloud data other than the reference point cloud data from the plurality of point cloud data corresponding to the pipeline channel node onto the reference point cloud data to form overall point cloud data of the pipeline channel node; For pipeline channel nodes corresponding to at least two point cloud data, determining the registration parameters corresponding to the point cloud data of each pipeline channel node includes: calculating the registration parameters corresponding to the reference point cloud data through an external device.

6. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: The merging and displaying of the three-dimensional model data of all the pipeline channel nodes based on the registration parameters includes: The sections in the three-dimensional model data of adjacent pipeline channel nodes are connected to form a three-dimensional model between the pipeline channel nodes.

7. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: Also includes: When an error occurs in merging and displaying the three-dimensional model data of the plurality of pipeline channel nodes, the alignment parameters are recalculated and updated, and based on the updated alignment parameters, the three-dimensional model data are merged and displayed again.

8. The method for managing point cloud data and three-dimensional model data of underground pipeline channels according to claim 1, characterized in that: Also includes: When the geographic coordinate system is to be changed for merging and displaying the three-dimensional model data, the alignment parameters are updated, and based on the updated alignment parameters, the three-dimensional model data are merged and displayed again.

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