Indoor map construction method and system based on BIM and laser radar

Abstract

The invention discloses a BIM and laser radar indoor map construction method and system. The method comprises the steps that an engineer interaction control interface sends an indoor map construction signal to a BIM and laser radar multi-modal data monitoring and collecting platform; after the BIM and laser radar multi-modal data monitoring and collecting platform receives an indoor map building signal, a plurality of data collecting sensors collect a plurality of radar setting parameters and BIM setting parameters of the BIM and the laser radar in each unit time and data processing and fusion parameters of working states of the BIM and the laser radar in each unit time; the collected data are stored and sent to the engineer interaction control interface; the engineer interaction control interface judges whether the multiple radar setting parameters, the BIM setting parameters and the data processing and fusion parameters are within a preset error allowable threshold; and the result is fed back to the BIM and laser radar room scanning point calibration check algorithm unit. According to the invention, BIM and laser radar to-be-optimized prompt signals can be sent in time, and the indoor map construction efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of indoor map construction, and in particular to a method and system for indoor map construction using BIM and laser radar. Background Art

[0002] The combination of BIM (Building Information Modeling) and LiDAR technology provides an efficient and accurate solution for indoor map construction. LiDAR can quickly acquire high-density 3D point cloud data to capture the geometric features of buildings, while BIM provides a comprehensive view of buildings by integrating building information and data management. This combination can not only improve modeling efficiency, but also provide data support for subsequent building maintenance and management.

[0003] However, existing methods still face challenges in data processing and model fusion. The point cloud data generated by LiDAR often contains noise and inconsistency, requiring complex registration and filtering steps to improve data quality. In addition, the fusion process of point cloud and BIM model may be restricted by the efficiency of the algorithm, resulting in long calculation time and difficulty in achieving real-time application.

[0004] In addition, current methods often rely on traditional geometric processing techniques and lack a deep understanding of the complex structures and features in point clouds. This limits their application capabilities in complex environments and makes it impossible to effectively process point cloud data of different scales and densities, which in turn affects the accuracy and practicality of indoor maps. Therefore, seeking new algorithms and technical means to improve processing accuracy and efficiency is a key direction for future development.

[0005] To solve the above problems, this application proposes a method and system for constructing an indoor map using BIM and lidar. Summary of the invention

[0006] In order to overcome the shortcomings and deficiencies of the prior art, the present invention provides a method and system for constructing an indoor map using BIM and laser radar.

[0007] The embodiment of the present invention provides a method for constructing an indoor map using BIM and laser radar, which includes: The engineer's interactive control interface sends indoor map construction signals to the BIM and LiDAR multimodal data monitoring platform; After the BIM and LiDAR multimodal data monitoring and acquisition platform receives the indoor map building signal, multiple data acquisition sensors collect multiple radar setting parameters and BIM setting parameters of the BIM and LiDAR at each unit time, data processing and fusion parameters of the BIM and LiDAR working status at each unit time, and store and send the collected data to the engineer interactive control interface; The engineer interactive control interface determines whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and lidar optimization prompt signal is generated and fed back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

[0008] Furthermore, the various radar setting parameters and BIM setting parameters include: scanning frequency, scanning range, point cloud resolution, data acquisition rate, geometric data, attribute information, hierarchical structure, and time information.

[0009] Furthermore, the data processing and fusion parameters include: registration algorithm, data filtering, feature extraction, and model generation.

[0010] Furthermore, it also includes: pre-setting a map construction model data cloud in the engineer interactive control interface, and storing the information of the plurality of radar setting parameters and BIM setting parameters, the error allowable range of data processing and fusion parameters, and the map construction type in the map construction model data cloud.

[0011] Furthermore, if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and LiDAR optimization prompt signal is generated and fed back to the BIM and LiDAR room scanning point calibration inspection algorithm unit through the edge computing gateway, including: The engineer interactive control interface evaluates the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters and the map construction type in the map construction model data cloud; The engineer interactive control interface sends corresponding BIM and lidar optimization prompt signals to the edge computing gateway based on the evaluation results.

[0012] Furthermore, if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and laser radar optimization prompt signal is generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway, further comprising: The engineer interactive control interface sends software program run / interrupt or hardware electrical parts run / interrupt signals to the BIM and lidar mainboard according to the evaluation results to control the operation steps of the BIM and lidar per unit time.

[0013] Further, the feedback to the BIM and LiDAR room scanning point calibration and verification algorithm unit through the edge computing gateway includes: the edge computing gateway feeds back the BIM and LiDAR optimization prompt signal to the BIM and LiDAR room scanning point calibration and verification algorithm unit through special encoding.

[0014] The embodiment of the present invention also provides a BIM and laser radar indoor map construction system, including a BIM and laser radar control server, multiple BIM and laser radar room scanning points, an edge computing gateway and a BIM and laser radar room scanning point calibration and inspection algorithm unit, the BIM and laser radar control server is provided with an engineer interactive control interface, and the multiple BIM and laser radar room scanning points are all provided with a BIM and laser radar multimodal data monitoring and acquisition platform; The engineer interactive control interface is used to send indoor map construction signals to the BIM and LiDAR multimodal data monitoring platform; The BIM and LiDAR multimodal data monitoring and acquisition platform is used to, after receiving the indoor map construction signal, use multiple data acquisition sensors to collect multiple radar setting parameters and BIM setting parameters of the BIM and LiDAR at each unit time, data processing and fusion parameters of the BIM and LiDAR working status at each unit time, and store and send the collected data to the engineer interactive control interface; The engineer interactive control interface is also used to determine whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and lidar optimization prompt signal is generated and fed back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

[0015] Furthermore, the edge computing gateway is used to feed back the BIM and LiDAR optimization prompt signals to the BIM and LiDAR room scanning point calibration verification algorithm unit through special encoding.

[0016] Furthermore, the engineer interactive control interface is used to evaluate the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters, and map construction types in the map construction model data cloud; and according to the evaluation results, send corresponding BIM and lidar optimization prompt signals to the edge computing gateway.

[0017] Beneficial effects: The present invention provides a method and system for building an indoor map of BIM and laser radar, which can timely send out prompt signals for optimization of BIM and laser radar, improve the efficiency of indoor map construction, and reduce costs. The method for building an indoor map of BIM and laser radar provided by the embodiment of the present invention is mainly executed on the engineer interactive control interface and the BIM and laser radar multimodal data monitoring platform, and has a fast response speed. The present invention combines BIM and laser radar to use a graph neural network to perform room scanning point calibration inspection. The graph neural network can effectively capture the complex relationship between points in the point cloud data, and through deep learning of node features, it can achieve accurate correction of inaccurate scanning points. In addition, the graph structure of the graph neural network can process non-Euclidean spatial data, improve the robustness and flexibility of the model on irregular data sets, thereby significantly improving the accuracy and efficiency of room scanning, and providing a more reliable foundation for intelligent building management. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0019] Figure 1 A schematic diagram of a method for constructing an indoor map using BIM and laser radar provided in an embodiment of the present invention; Figure 2 This is a structural diagram of the indoor map construction system of BIM and LiDAR provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application may be combined with each other. The present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0021] See also Figure 1 , a flow chart of a method for constructing an indoor map using BIM and laser radar provided in an embodiment of the present invention, the method comprising: Step 101, the engineer interactive control interface sends an indoor map construction signal to the BIM and LiDAR multimodal data monitoring platform; Step 102: After the BIM and laser radar multimodal data monitoring and acquisition platform receives the indoor map building signal, multiple data acquisition sensors collect multiple radar setting parameters and BIM setting parameters of the BIM and laser radar at each unit time, data processing and fusion parameters of the working status of the BIM and laser radar at each unit time, and store and send the collected data to the engineer interactive control interface; Step 103, the engineer interactive control interface determines whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and lidar optimization prompt signal is generated and fed back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

[0022] In the embodiment of the present invention, the BIM and laser radar room scanning point calibration verification algorithm unit uses a graph neural network to perform room scanning point calibration verification, including: Graph construction: For point cloud data , each node , where i = 1, 2, ..., n, with eigenvector , where i=1, 2, …, n; Node features: , T is the matrix transpose operation, Edge Features: Edge With Node , Connections, edge characteristics are defined as their Euclidean distance : , Graph neural network layer: Each layer of the graph neural network updates the node features through graph convolution. Assume that The node characteristics of the +1 layer are , then the update formula is: , in: Is a node The set of neighbor nodes of is the normalization factor, It is The weight matrix of the layer, yes Layer bias term, is the activation function. After passing through multiple layers of GNN, the output layer obtains Final representation of layer nodes , through a fully connected layer for the final classification or regression task: , in, Is a node The prediction results, It is +1 layer weight matrix, It is +1 layer node features, yes Layer bias term; Loss function: The loss function is used to measure the difference between the predicted result and the true label. The expression is: , in, is the mean square error of the loss function, is the true label; Optimization process: Use the back-propagation algorithm to update the model parameters. Assuming the stochastic gradient descent optimizer is used, the parameter update rule is: , in, is the learning rate; Calibration test: After training, use the model for calibration test. For new scanning points, input the model, obtain the calibration value, and compare it with the BIM model to evaluate the calibration effect.

[0023] In the embodiment of the present invention, the engineer interactive control interface can send an indoor map construction signal to the BIM and laser radar multimodal data monitoring platform. The BIM and laser radar multimodal data monitoring platform can control the collection of multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters according to the indoor map construction signal and feedback to the engineer interactive control interface. In this way, the engineer interactive control interface can determine whether the multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters are within the error allowable threshold. If not, a BIM and laser radar to be optimized prompt signal is automatically generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway. The management personnel can timely understand the map construction information of BIM and laser radar per unit time, and process the map construction in time to prevent damage to BIM and laser radar per unit time. The method provided in the embodiment of the present invention can automatically perform inspections, and can timely send BIM and laser radar to be optimized prompt signals, improve the efficiency of indoor map construction, and reduce costs. The indoor map construction method of BIM and laser radar provided in the embodiment of the present invention is mainly executed on the engineer interactive control interface and the BIM and laser radar multimodal data monitoring platform, and has a fast response speed.

[0024] Specifically, in step 101, the engineer interactive control interface can send the indoor map construction signal to the BIM and lidar multimodal data monitoring platform in different ways, for example, sending the indoor map construction signal in a timed manner, that is, sending the indoor map construction signal once every same period of time, which can be the default duration of the device or a custom duration.

[0025] In addition, the indoor map building signal can be sent irregularly, that is, the indoor map building signal is sent every different time intervals. In this way, it can be manually started by the management personnel, that is, the management personnel can evaluate whether it is necessary to send the indoor map building signal based on their own experience or actual working status. It is also possible to divide each cycle into several different time periods in advance, and set a time interval for different time periods, so that within a time period, the indoor map building signal is sent regularly according to the corresponding time interval. This method is actually a scheduled inspection, but the time interval is different in different time periods. The advantage of setting different time periods is that the sampling frequency can be set in a targeted manner.

[0026] In step 102, the multiple data acquisition sensors are started, and multiple radar setting parameters and BIM setting parameters of the BIM and the lidar at each unit time, and data processing and fusion parameters of the working status of the BIM and the lidar at each unit time are collected according to the type of each sensor in the sensor group.

[0027] The various radar setting parameters and BIM setting parameters include: scanning frequency, scanning range, point cloud resolution, data acquisition rate, geometric data, attribute information, hierarchy, and time information. The data processing and fusion parameters include: registration algorithm, data filtering, feature extraction, and model generation.

[0028] Scanning frequency: affects the density and accuracy of the point cloud. Scanning range: the distance and angle that the LiDAR can cover. Point cloud resolution: the number and accuracy of points generated by each scan. Data acquisition rate: the amount of data that can be collected per unit time. Geometric data: the shape, size, layout, etc. of the building. Attribute information: material, structure, equipment information, etc. Hierarchy: the hierarchical relationship between the various parts of the building. Time information: data on the construction progress or the life cycle of the building.

[0029] Registration algorithm: Align point cloud data collected at different times or angles.

[0030] Data filtering: Remove noise and unnecessary data points to improve point cloud quality.

[0031] Feature extraction: Extract feature information of buildings, such as walls, doors and windows, from point clouds.

[0032] Model generation: Convert point cloud data into a BIM model, usually involving geometric modeling and attribute association.

[0033] The above data can be collected by corresponding sensors. The combination of sensors can be collectively referred to as a sensor group. A sensor group can be set on each unit time BIM and laser radar to collect various radar setting parameters and BIM setting parameters of each unit time BIM and laser radar, and data processing and fusion parameters of each unit time BIM and laser radar working status, so as to realize the remote construction function of each unit time BIM and laser radar.

[0034] The above-mentioned various radar setting parameters, BIM setting parameters and data processing and fusion parameters have different functions. For example, various radar setting parameters and BIM setting parameters can directly reflect the current status of BIM and laser radar per unit time, and can determine whether BIM and laser radar have constructed a map per unit time. The data processing and fusion parameters of the working status of BIM and laser radar per unit time can directly reflect the current working status of BIM and laser radar per unit time, such as whether the working status of BIM and laser radar per unit time has changed significantly, or whether the working status has deteriorated, etc. In this way, it can be predicted whether the BIM and laser radar will construct a map per unit time, so as to handle it in time.

[0035] The BIM and LiDAR multimodal data monitoring and acquisition platform can store the data collected by the sensor group and eventually send it to the engineer's interactive control interface.

[0036] In step 103, after receiving the multiple radar setting parameters, BIM setting parameters, and data processing and fusion parameters, the engineer interactive control interface can determine whether the multiple radar setting parameters, BIM setting parameters, and data processing and fusion parameters are within a preset error tolerance threshold.

[0037] If the multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, that is, the multiple radar setting parameters and BIM setting parameters are not within the preset error tolerance threshold, and the data processing and fusion parameters are not within the preset error tolerance threshold, then it is necessary to generate a BIM and lidar optimization prompt signal and feed it back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

[0038] The BIM and laser radar room scanning point calibration and verification algorithm unit can be the BIM and laser radar room scanning point calibration and verification algorithm unit of the maintenance personnel, so that the maintenance personnel can promptly process the map construction that is occurring or is about to occur by BIM and laser radar per unit time. The BIM and laser radar room scanning point calibration and verification algorithm unit can also be the BIM and laser radar room scanning point calibration and verification algorithm unit of the management personnel, so that the management personnel can arrange personnel to process according to the area to which the BIM and laser radar belong per unit time.

[0039] Calibration verification algorithms for BIM and LiDAR room scan points are often used to ensure that the geometric characteristics of BIM and LiDAR or physical prototypes meet the design requirements during the manufacturing process. The main goal of such algorithms is to calibrate the measurement data, correct errors, and perform accurate construction accuracy assessment. A typical calibration verification algorithm process may include the following steps: Using multiple data acquisition sensors to collect multiple radar setting parameters and BIM setting parameters of BIM and LiDAR at each unit time, data processing and fusion parameters of BIM and LiDAR working status at each unit time, the calibration inspection algorithm can ensure the consistency and accuracy of BIM and LiDAR in the manufacturing process, and help to timely detect deviations or equipment abnormalities in production. Depending on the specific production environment and sensor type, the algorithm may be different.

[0040] In order to better analyze the map construction of BIM and laser radar per unit time, the embodiment of the present invention preferably simultaneously collects multiple radar setting parameters and BIM setting parameters of the BIM and laser radar per unit time and data processing and fusion parameters of the working status of BIM and laser radar per unit time, and analyzes the map construction based on these two types of information. When the multiple radar setting parameters, BIM setting parameters and data processing and fusion parameters are all within the preset error tolerance threshold, the BIM and laser radar optimization prompt signal is not generated. When any of the multiple radar setting parameters, BIM setting parameters and data processing and fusion parameters is not within the preset error tolerance threshold, the BIM and laser radar optimization prompt signal is generated. This ensures that the map construction is discovered in a timely manner and the map construction is processed.

[0041] In one embodiment, the method for constructing an indoor map using BIM and laser radar further includes: A map construction model data cloud is set in advance in the engineer interactive control interface, and the information of the various radar setting parameters and BIM setting parameters, the error tolerance range of data processing and fusion parameters, and the map construction type is stored in the map construction model data cloud.

[0042] In this embodiment, the error tolerance ranges of various radar setting parameters, BIM setting parameters, data processing and fusion parameters can be stored in advance in the map construction model data cloud, so that the engineer interactive control interface can call up the corresponding error tolerance range at any time and perform evaluation when performing map construction analysis. At the same time, the information of the map construction type can also be stored in the map construction model data cloud, so that the type of map construction can be determined, which is convenient for maintenance personnel to perform map construction processing.

[0043] In one embodiment, if the multiple radar setting parameters, BIM setting parameters, and data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and laser radar optimization prompt signal is generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway, including: The engineer interactive control interface evaluates the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters and the map construction type in the map construction model data cloud; The engineer interactive control interface sends corresponding BIM and lidar optimization prompt signals to the edge computing gateway based on the evaluation results.

[0044] After determining that the various radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance range, the various radar setting parameters, BIM setting parameters, data processing and fusion parameters and the map construction type in the map construction model data cloud can be evaluated. Then, the BIM and LiDAR optimization prompt signal is sent to the edge computing gateway, and the edge computing gateway is used to feedback to the BIM and LiDAR room scanning point calibration inspection algorithm unit. In this way, not only can the information of BIM and LiDAR map construction or map construction in unit time be obtained, but also the information of what map construction has occurred in BIM and LiDAR per unit time can be obtained, so as to facilitate targeted processing.

[0045] In one embodiment, the feedback to the BIM and laser radar room scanning point calibration verification algorithm unit through the edge computing gateway includes: The edge computing gateway feeds back the BIM and LiDAR optimization prompt signals to the BIM and LiDAR room scanning point calibration inspection algorithm unit in a special coding manner. The edge computing gateway can feed back the BIM and LiDAR optimization prompt signal to the BIM and LiDAR room scanning point calibration verification algorithm unit via email or a signal pop-up window. Of course, it can also be constructed in other ways, such as WeChat, mini-programs, dedicated apps, etc. for reminders.

[0046] In one embodiment, if the multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and laser radar optimization prompt signal is generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway, further comprising: The engineer interactive control interface sends software program run / interrupt or hardware electrical parts run / interrupt signals to the BIM and lidar mainboard according to the evaluation results to control the operation steps of the BIM and lidar per unit time.

[0047] In this embodiment, when it is determined that the multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold and a BIM and laser radar optimization prompt signal is generated and sent to the BIM and laser radar room scanning point calibration inspection algorithm unit, the maintenance personnel can handle it in time. In the embodiment of the present invention, the engineer interactive control interface can also send a software program run / interrupt signal or a hardware electrical parts run / interrupt signal to the BIM and laser radar mainboard to control the operation steps of the BIM and laser radar per unit time. For example, when it is detected that the BIM setting parameters of the BIM and laser radar working status per unit time are too high, a software program run / interrupt signal can be sent to the relay in the BIM and laser radar mainboard.

[0048] In other embodiments, a neural network model may be used to predict the collected data, so as to understand the upcoming map construction information in advance, which is helpful to avoid the risk of unbalanced BIM and LiDAR data collection per unit time.

[0049] Generally speaking, if a certain state of BIM and laser radar continues to change or certain parameters in the working state continue to deviate from normal values ​​during use, the risk of damage to the BIM and laser radar per unit time is relatively high. Therefore, the embodiment of the present invention can collect historical map construction data, which includes the type of map construction that occurred and various radar setting parameters and BIM setting parameters and data processing and fusion parameters before the map construction occurred.

[0050] Then, the historical map construction data is preprocessed, and the preprocessing content may include normalization, etc., so that each type of data is classified into the same dimension, and then the historical map construction data is divided into a sample set and a test set. Then, the neural network model is used to train the sample set of the historical map construction data, and then the trained neural network model is tested using the test set, and finally the preset accuracy requirements are met.

[0051] See also Figure 2, an embodiment of the present invention also provides a BIM and laser radar indoor map construction system, which includes a BIM and laser radar control server, multiple BIM and laser radar room scanning points, an edge computing gateway and a BIM and laser radar room scanning point calibration and inspection algorithm unit, the BIM and laser radar control server is provided with an engineer interactive control interface, and the multiple BIM and laser radar room scanning points are all provided with a BIM and laser radar multimodal data monitoring and acquisition platform; The engineer interactive control interface is used to send indoor map construction signals to the BIM and LiDAR multimodal data monitoring platform; The BIM and LiDAR multimodal data monitoring and acquisition platform is used to, after receiving the indoor map construction signal, use multiple data acquisition sensors to collect multiple radar setting parameters and BIM setting parameters of the BIM and LiDAR at each unit time, data processing and fusion parameters of the BIM and LiDAR working status at each unit time, and store and send the collected data to the engineer interactive control interface; The engineer interactive control interface is also used to determine whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and lidar optimization prompt signal is generated and fed back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

[0052] In one embodiment, the edge computing gateway is used to feed back the BIM and LiDAR optimization prompt signals to the BIM and LiDAR room scanning point calibration verification algorithm unit through special encoding.

[0053] In one embodiment, the engineer interactive control interface is used to evaluate the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters, and map construction types in the map construction model data cloud; and based on the evaluation results, send corresponding BIM and lidar optimization prompt signals to the edge computing gateway.

[0054] The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the various embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, several improvements and modifications can be made to the present invention, and these improvements and modifications also fall within the protection threshold of the claims of the present invention.

Claims

1. A method for constructing an indoor map using BIM and laser radar, characterized in that: The method includes: Step 101: The engineer interactive control interface sends an indoor map construction signal to the BIM and LiDAR multimodal data monitoring platform; Step 102: After the BIM and laser radar multimodal data monitoring and acquisition platform receives the indoor map building signal, multiple data acquisition sensors collect multiple radar setting parameters and BIM setting parameters of the BIM and laser radar at each unit time, data processing and fusion parameters of the working status of the BIM and laser radar at each unit time, and store and send the collected data to the engineer interactive control interface; Step 103: The engineer interactive control interface determines whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and laser radar optimization prompt signal is generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway; The BIM and LiDAR room scanning point calibration verification algorithm unit uses a graph neural network to perform room scanning point calibration verification, including: Graph construction: For point cloud data , each node , where i = 1, 2, ..., n, with eigenvector , where i=1, 2, …, n; Node features: , T is the matrix transpose operation; Edge Features: Edge With Node , Connections, edge characteristics are defined as their Euclidean distance : ， Graph neural network layer: Each layer of the graph neural network updates the node features through graph convolution. Assume that The node characteristics of the +1 layer are , then the update formula is: ， in: Is a node The set of neighbor nodes of is the normalization factor, It is The weight matrix of the layer, yes Layer bias term, is the activation function. After passing through multiple layers of GNN, the output layer obtains Final representation of layer nodes , through a fully connected layer for the final classification or regression task: ， in, Is a node The prediction results, It is +1 layer weight matrix, It is +1 layer node features, yes Layer bias term; Loss function: The loss function is used to measure the difference between the predicted result and the true label. The expression is: ， in, is the mean square error of the loss function, is the true label; Optimization process: Use the back-propagation algorithm to update the model parameters. Assuming the stochastic gradient descent optimizer is used, the parameter update rule is: ， in, is the learning rate; Calibration test: After training, use the model for calibration test. For new scanning points, input the model, obtain the calibration value, and compare it with the BIM model to evaluate the calibration effect.

2. The method for constructing an indoor map using BIM and laser radar according to claim 1, characterized in that: The various radar setting parameters and BIM setting parameters include: scanning frequency, scanning range, point cloud resolution, data acquisition rate, geometric data, attribute information, hierarchical structure, and time information.

3. The method for constructing an indoor map using BIM and laser radar according to claim 1, characterized in that: The data processing and fusion parameters include: registration algorithm, data filtering, feature extraction, and model generation; The registration algorithm aligns point cloud data collected at different times or angles; The data filtering is used to remove noise and unnecessary data points to improve the quality of the point cloud; The feature extraction extracts feature information of the building from the point cloud; The model generation converts point cloud data into a BIM model, including geometric modeling and attribute association.

4. The method for constructing an indoor map using BIM and laser radar according to claim 1, characterized in that: Also includes: A map construction model data cloud is set in advance in the engineer interactive control interface, and the information of the various radar setting parameters and BIM setting parameters, the error tolerance range of data processing and fusion parameters, and the map construction type is stored in the map construction model data cloud.

5. The method for constructing an indoor map using BIM and laser radar according to claim 4, characterized in that: If the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and LiDAR optimization prompt signal is generated and fed back to the BIM and LiDAR room scanning point calibration inspection algorithm unit through the edge computing gateway, including: The engineer interactive control interface evaluates the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters and the map construction type in the map construction model data cloud; The engineer interactive control interface sends corresponding BIM and lidar optimization prompt signals to the edge computing gateway based on the evaluation results.

6. The method for constructing an indoor map using BIM and laser radar according to claim 5, characterized in that: If the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and laser radar optimization prompt signal is generated and fed back to the BIM and laser radar room scanning point calibration inspection algorithm unit through the edge computing gateway, and also includes: The engineer interactive control interface sends software program run / interrupt or hardware electrical parts run / interrupt signals to the BIM and lidar mainboard according to the evaluation results to control the operation steps of the BIM and lidar per unit time.

7. The method for constructing an indoor map using BIM and laser radar according to claim 1, characterized in that: The feedback to the BIM and LiDAR room scanning point calibration verification algorithm unit through the edge computing gateway includes: The edge computing gateway feeds back the BIM and LiDAR optimization prompt signals to the BIM and LiDAR room scanning point calibration inspection algorithm unit through special coding.

8. The indoor map construction system of BIM and laser radar is characterized by: It includes a control BIM and LiDAR control server, multiple BIM and LiDAR room scanning points, an edge computing gateway, and a BIM and LiDAR room scanning point calibration and verification algorithm unit; The control BIM and laser radar control server is provided with an engineer interactive control interface, and the multiple BIM and laser radar room scanning points are provided with a BIM and laser radar multimodal data monitoring platform; The engineer interactive control interface is used to send indoor map construction signals to the BIM and LiDAR multimodal data monitoring platform; The BIM and LiDAR multimodal data monitoring and acquisition platform is used to, after receiving the indoor map construction signal, use multiple data acquisition sensors to collect multiple radar setting parameters and BIM setting parameters of the BIM and LiDAR at each unit time, data processing and fusion parameters of the BIM and LiDAR working status at each unit time, and store and send the collected data to the engineer interactive control interface; The engineer interactive control interface is also used to determine whether the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are within the preset error tolerance threshold; if the multiple radar setting parameters, BIM setting parameters, data processing and fusion parameters are not within the preset error tolerance threshold, a BIM and lidar optimization prompt signal is generated and fed back to the BIM and lidar room scanning point calibration inspection algorithm unit through the edge computing gateway.

9. The indoor map construction system of BIM and laser radar according to claim 8, characterized in that: The edge computing gateway is used to feed back the BIM and LiDAR optimization prompt signals to be optimized to the BIM and LiDAR room scanning point calibration inspection algorithm unit in a special coding manner; The engineer interactive control interface is used to evaluate the received multiple radar setting parameters and BIM setting parameters, data processing and fusion parameters and the map construction type in the map construction model data cloud; And based on the evaluation results, the corresponding BIM and LiDAR optimization prompt signals are sent to the edge computing gateway.

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