A measurement point planning method and system based on intelligent recognition of architectural drawings

Abstract

The present invention discloses a method and system for planning measurement points based on intelligent recognition of architectural drawings. The method first obtains and processes the original map to identify the corresponding parts of walls, doors, and windows on the map. Next, the processed map is differentiated to determine the measurement objects contained in each room outline on the map. Finally, the corresponding measurement points are planned based on the measured items to be measured and the determined measured objects. The solution provided by the present invention fully automatically plans measurement points based on intelligent recognition. Compared to existing solutions based on manual measurement point setup, it can achieve automatic planning for multiple rooms and multiple measurement items, greatly improving the efficiency of measurement point planning.

Description

Technical Field

[0001] The present invention relates to the technical field of building measurement, and in particular to a planning scheme for measurement points. Background Art

[0002] In existing building surveying projects, the planning of measurement points often relies on manual setup. Based on architectural drawings, each room with a measuring tool must be measured manually. After obtaining the corresponding measurement data, the corresponding measurement object is selected and calibrated based on the measurement items. Finally, calculations are performed to determine the corresponding measurement points for the determined measurement object.

[0003] The entire planning work basically relies on manual work, which has low measurement efficiency and greatly affects the progress of the project. Summary of the Invention

[0004] Aiming at the problem of low efficiency in the existing building surveying projects based on manual setting of measurement points, the purpose of the present invention is to provide a measurement point planning method based on intelligent recognition of building drawings, which can fully automatically plan measurement points based on intelligent recognition and greatly improve efficiency.

[0005] In order to achieve the above-mentioned object, the present invention provides a measurement point planning method based on intelligent recognition of architectural drawings, comprising:

[0006] (1) Obtaining the original map, processing the original map, and marking the corresponding parts of walls, doors, and windows on the map;

[0007] (2) performing differentiation processing on the map obtained by step (1) to determine the measurement objects contained in each room outline on the map;

[0008] (3) According to the measurement items to be measured, corresponding measurement points are planned based on the measured objects divided and determined in step (2).

[0009] In some examples of the present invention, the original map is processed in step (1) to convert the original map into a PNG format bitmap, and the parts corresponding to walls, doors, and windows are marked on the bitmap.

[0010] In some embodiments of the present invention, step (2) includes the following sub-steps:

[0011] (2.1) Divide the processed map into several sub-regions, each of which corresponds to a room outline;

[0012] (2.2) For each sub-region segmented in step (2.1), traverse the outline of each sub-region and identify the components corresponding to the wall, door, window, and corner in each sub-region;

[0013] (2.3) Divide the outline of each sub-area according to the components corresponding to the wall, door, window, and corner identified in step (2.2) to form a corresponding measurement object.

[0014] In some examples of the present invention, the step (2.3) performs sorting on the formed measurement objects.

[0015] In some examples of the present invention, step (3) includes planning measurement points for the verticality and flatness of the wall and the detection of embedded wall parts. First, based on the coordinates and size information of the wall segment measurement object identified in step (2), two extreme points are marked on both sides of the wall segment, and the field of view of the measuring device just covers the boundary; then, for the area in the middle of the wall segment, a number of points are generated at equal intervals according to the principle of full coverage of the field of view of the measuring device.

[0016] In some examples of the present invention, step (3) includes planning the measurement points of the internal and external corners. First, based on the relevant information when identifying each corner in step (2), the coordinate information of each corner is determined, and a measurement point is generated for each internal and external corner based on the coordinate information of each corner.

[0017] In some embodiments of the present invention, the step (3) includes planning measurement points for the cross-sectional dimensions of columns and narrow walls. First, based on the measurement objects corresponding to the wall segments identified in step (2), and according to the coordinate information and / or dimension information of the measurement objects corresponding to the wall segments, a wall segment measurement object having a width less than a threshold is identified and determined to be a column or a narrow wall.

[0018] Next, for the measurement object determined to be a column or narrow wall, a measurement point is pre-planned based on the wall measurement point planning method;

[0019] Next, for the pre-planned measurement points, offset adjustments are made based on the overall size of the measurement equipment, and the offset distance is adjusted to obtain the final measurement points.

[0020] In some examples of the present invention, step (3) includes planning measurement points for door and window sizes. First, based on the measurement objects corresponding to the door and window sections identified in step (2), and according to the coordinate information and size information of the measurement objects corresponding to the door and window sections, a median perpendicular to the door and window sections is constructed; then, for the constructed median, a measurement point is determined on the median based on the distance of the measuring device from the wall.

[0021] In some examples of the present invention, step (3) includes planning measurement points for wall spacing. First, based on the coordinates and size information of the wall segment measurement objects, door segment measurement objects, and window segment measurement objects contained in each sub-region identified in step (2), the region in the sub-region whose ends on both sides in the horizontal and vertical directions are wall segments is determined; then, the region is used as a measurement point planning region, and a measurement point is determined in the region.

[0022] In order to achieve the above-mentioned object, the present invention provides a measurement point planning system based on intelligent recognition of architectural drawings, which includes a map preprocessing module, a measurement object division module, and a measurement point planning module;

[0023] The map preprocessing module is used to obtain the original map corresponding to the building map, and process it to identify the parts corresponding to the walls, doors and windows on the map;

[0024] The measurement object division module interacts with the map preprocessing module to perform differentiation processing on the map obtained by the map preprocessing module and determine the measurement objects contained in each room outline on the map;

[0025] The measurement point planning module exchanges data with the measurement object division module, and is used to plan corresponding measurement points according to the measurement items to be measured and based on the objects to be measured determined by the measurement object division module.

[0026] The solution provided by the present invention performs fully automatic planning of measurement points based on intelligent recognition. Compared with the existing solution based on manual setting of measurement points, it can realize automatic planning of multiple rooms and multiple measurement items, greatly improving the efficiency of measurement point planning. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further described below with reference to the accompanying drawings and specific embodiments.

[0028] Figure 1 This is an example diagram of obtaining the original map in the solution of the present invention;

[0029] Figure 2 This is an example diagram of a measurement object obtained by dividing the sub-areas in the solution of the present invention;

[0030] Figure 3 This is an example diagram of measurement points planned for the wall in the solution of the present invention;

[0031] Figure 4a This is an example diagram of measurement points for planning the external corners in the solution of the present invention;

[0032] Figure 4b This is an example diagram of measurement points for planning internal corners in the solution of the present invention;

[0033] Figure 5 This is an example diagram of measurement points planned for short walls in the solution of the present invention;

[0034] Figure 6 This is an example diagram of measurement points for planning doors and windows in the solution of the present invention;

[0035] Figure 7 This is an example diagram of measurement points planned for a rectangular room in the solution of the present invention;

[0036] Figure 8 This is an example diagram of the measurement points for needle-wall spacing planning in the solution of the present invention;

[0037] Figure 9 This is an example diagram of the composition of the measurement point planning system based on intelligent recognition of architectural drawings in the solution of the present invention. DETAILED DESCRIPTION

[0038] In order to make the technical means, creative features, objectives and effects achieved by the present invention easier to understand, the present invention is further described below with reference to specific illustrations.

[0039] The solution of the present invention innovatively introduces intelligent recognition technology, which effectively realizes the automatic planning of measurement points by intelligently identifying architectural drawings.

[0040] Specifically, the implementation process of the present invention for measuring point planning based on intelligent recognition of architectural drawings mainly includes:

[0041] (1) Obtain the original map and process it.

[0042] In some implementations of this solution, in this step, first, an original map is obtained according to the image address, and the original map corresponds to the architectural drawing of the building to be measured, such as Figure 1 shown.

[0043] Next, the obtained original map is processed and the corresponding positions of doors and windows on the original map are marked.

[0044] As an example, in this step, the obtained original map is processed to obtain a PNG format bitmap; the parts corresponding to doors and windows on the PNG format bitmap are marked for subsequent processing.

[0045] Here, a black background is preferably used for the PNG format bitmap, which is convenient for subsequent processing; at the same time, there is no limitation on the marking method, and it is preferred to mark by color, such as marking the part corresponding to the wall in green, the part corresponding to the door in yellow, and the part corresponding to the window in blue.

[0046] The specific form of the mark is not limited to this, and other forms can be used as needed.

[0047] (2) The map obtained by step (1) is divided into blocks to determine the measurement objects contained in each room outline on the map.

[0048] This step, when implemented, includes the following sub-steps:

[0049] (2.1) Divide the map obtained by step (1) into several sub-regions, each of which corresponds to a room outline.

[0050] In some implementations of the present solution, when this step is specifically implemented, the map formed in step (1) is segmented based on a region segmentation algorithm to obtain several sub-regions, each of which corresponds to a room outline.

[0051] As an example, the region segmentation algorithm used here is the findContours function of the OpenCV library, but it is not limited to this. Other region segmentation methods can also be used as needed.

[0052] (2.2) For each sub-region obtained by segmentation in step (2.1), traverse the outline of each sub-region respectively, filter out the components of walls, doors, and windows, and read their coordinates.

[0053] In some implementations of the present solution, when this step is specifically implemented, the positions corresponding to doors and windows are marked on the original map in step (1) to filter out the wall, door, and window components.

[0054] Continuing with the example in step (1), in this step, the three objects can be distinguished based on color information, and the coordinates of the wall, door, and window parts, that is, the location information on the map, can be read, and the corresponding size information can be obtained at the same time.

[0055] (2.3) For each sub-region, identify the location corresponding to the corner of the room.

[0056] In some implementations of this solution, this step is implemented by traversing each pixel of each room outline (i.e., each sub-region outline) and obtaining the distribution of the eight pixels surrounding the pixel to determine whether the current pixel is a corner. The coordinate information of the corner, i.e., its location on the map, is also obtained. This allows for rapid and accurate identification of the corresponding room corner.

[0057] (2.4) The contour of each sub-region is divided to form a corresponding measurement object.

[0058] In some implementations of the present solution, when this step is specifically implemented, for each wall portion in each sub-area, the wall portion is divided using the wall corner portion determined in step (2.3) and the door and window boundary portions determined in step (2.2) as segmentation points to obtain corresponding wall segments, door segments, and window segments, which are used as the corresponding measurement objects contained in the sub-area.

[0059] See also Figure 2 , the sub-area shown is divided into 6 wall segments, 1 door segment, and 1 window segment. Thus, the sub-area will have 6 wall segment measurement objects, 1 door segment measurement object, and 1 window segment measurement object.

[0060] (2.5) Sort the measurement objects (such as corresponding wall segments, door segments, and window segments) that have been segmented in step (2.4) to ensure that the measurement points generated subsequently are also in order.

[0061] There is no limitation on the specific sorting method, and the sorting can be performed clockwise or counterclockwise.

[0062] (3) Plan measurement points for the object to be measured based on the measurement items to be measured.

[0063] This step, when implemented, includes the following sub-steps:

[0064] (3.1) Planning of measurement points for wall verticality, flatness, and embedded parts inspection.

[0065] If the measurement items are wall verticality, flatness, or embedded wall parts, the measurement object is determined to be the wall, and the measurement points are planned as a series of points at a certain distance from the wall.

[0066] See also Figure 3 , which shows an example diagram of planned measurement points for a wall as the measurement object in this example.

[0067] Based on the diagram, l is the length of the wall being measured, d is the distance from the wall, r is the single-sided field of view of the measuring device, and a is the distance between the points in the middle section.

[0068] Based on this, when planning the measurement points, first identify the coordinates and size information of the wall segment measurement object based on step (2), mark two extreme points on both sides of the wall segment, and just make the field of view of the measuring device cover the boundary; then, for the area in the middle of the wall segment, generate several points at equal intervals according to the principle of full coverage of the field of view of the measuring device.

[0069] The calculation formula for the equidistant distance a (i.e. the distance between the middle points) is as follows:

[0070]

[0071] Where l is the length of the wall to be measured, d is the distance from the wall, r is the single-sided field of view of the measuring device, and a is the distance between the points in the middle section.

[0072] (3.2) Planning of measurement points for the inner and outer corners.

[0073] If the measurement item is a Yin-Yang angle, make sure the measurement object is a wall corner.

[0074] In this step, based on the relevant information when identifying each corner in step (2), the coordinate information of each corner is determined, and a measurement point is generated for each yin and yang corner based on the coordinate information of each corner.

[0075] See also Figure 4a and Figure 4b , which shows an example diagram of measurement point planning for the Yin-Yang corners in this example.

[0076] For each corner, obtain the coordinate information of the corner, and construct a corresponding square based on the corner point with the distance d from the wall as the side length, and use the vertex on the constructed square that is diagonally distributed with the corner point as the measurement point.

[0077] like Figure 4a If the corner 41 is a positive corner, the coordinate information of the corner is obtained, and the two wall sections 42 and 43 adjacent to the corner are respectively extended outward by a distance d. The two extension sections cooperate with the corner 41 to construct a square with a side length of d from the wall, and the vertex 44 of the constructed square that is diagonally distributed with the corner point 41 is used as the measurement point.

[0078] like Figure 4b If the corner 45 is a concave corner, the coordinate information of the corner is obtained, and with the corner 45 as the starting point, a length d is directly selected on the two wall parts 46 and 47 adjacent to the corner. The two selected sections are combined with the corner 45 to construct a square with a side length of d from the wall, and the vertex 48 of the constructed square that is diagonally distributed with the corner point is used as the measurement point.

[0079] This allows the measuring point of the internal and external corners to be precisely determined, and allows the measuring device to be oriented towards the corner.

[0080] (3.3) Planning of measurement points for column and narrow wall cross-section dimensions.

[0081] If the measurement item is the cross-sectional dimensions of a column or narrow wall, make sure the measurement object is the wall with the shorter width.

[0082] In this step, based on the measurement objects corresponding to the wall segments identified in step (2), and according to the coordinate information and / or size information of the measurement objects corresponding to the wall segments, the wall segment measurement objects with a length less than a threshold are identified and determined to be columns or narrow walls.

[0083] For the measurement object determined to be a column or a narrow wall, a measurement point 51 is pre-planned based on the wall measurement point planning method (i.e., step 3.1);

[0084] Because columns or narrow walls are smaller than regular wall segments, using the same measurement point rule for the wall will result in measurement point 51 being outside the room. To address this, this step also performs an offset adjustment for pre-planned measurement point 51 based on the overall dimensions of the measurement equipment. This adjustment adjusts the offset distance f to obtain the final measurement point 52.

[0085] On this basis, this step further calculates the corresponding rotation adjustment angle according to the offset distance f, the overall size of the measuring device, and the single-sided field of view angle, so that the measuring device can face the corresponding column or narrow wall.

[0086] It should be noted here that the specific implementation method for determining the offset distance f based on the overall size of the measuring device is not limited here and can be determined according to actual needs.

[0087] Furthermore, the specific implementation method for determining the rotation adjustment angle is not limited here and can be determined according to actual needs.

[0088] (3.4) Planning of measurement points for door and window dimensions.

[0089] If the measurement item is the door and window size, make sure the measurement object is the door and window section.

[0090] See also Figure 6 In this step, when planning the measurement points of door and window dimensions, a measurement point is planned for each door and window segment. First, based on the measurement objects corresponding to the door and window segments identified in step (2), and according to the coordinate information and dimension information (such as the door and window width l) of the measurement objects corresponding to the door and window segments, a median perpendicular to the door and window segments is constructed; for the constructed median perpendicular, a measurement point 61 is determined on the median based on the distance d between the measuring device and the wall.

[0091] (3.5) Surface flatness, slope, top plate surface flatness, and floor height measurement point planning of ground works.

[0092] The four measurement items of surface flatness and slope of floor engineering, surface flatness of ceiling, and floor height are applicable to rectangular rooms.

[0093] See also Figure 7 In this step, first, based on the wall segment measurement objects, door segment measurement objects, and window segment measurement objects contained in each sub-region identified in step (2), and according to their coordinate information and size information, it is calculated and determined whether the room outline corresponding to the sub-region is a rectangle;

[0094] If it is a rectangle, five measurement points are generated at the center and around the corners of the area.

[0095] For example, the position of the central measurement point is calculated based on the area size, and the measurement points of the four surrounding corner points are determined based on the distance d from the wall.

[0096] (3.6) Planning of measurement points for wall spacing.

[0097] For the wall distance measurement item, it is applicable to the situation where there are walls at both ends in the horizontal and vertical directions.

[0098] See also Figure 8 This step first determines the area 81 in the sub-area where both ends in the horizontal and vertical directions are wall segments based on the coordinates and size information of the wall segment measurement objects, door segment measurement objects, and window segment measurement objects contained in each sub-area identified in step (2), and excludes the area 82 corresponding to the door segment or window segment.

[0099] Next, an area is planned using area 81 as a measurement point, and a measurement point 83 is determined in the area.

[0100] As an example, the measurement point is determined based on the principle of being located near the center of the area.

[0101] The solution provided by the present invention is further described below through specific examples.

[0102] In this example, the measurement point planning method based on intelligent architectural drawing recognition provided by the present invention is implemented as a corresponding software program, forming a corresponding measurement point planning system based on intelligent architectural drawing recognition. When executed, this software program executes the aforementioned measurement point planning method based on intelligent architectural drawing recognition and is stored in a corresponding storage medium for access and execution by a processor.

[0103] See also Figure 9 When implemented, the measurement point planning system 100 based on intelligent recognition of architectural drawings mainly includes a map preprocessing module 110, a measurement object division module 120, a measurement point planning module 130 and a database 140.

[0104] The database 140 in this system is used to store basic data of the system operation and various data generated by the operation, such as imported architectural drawings, corresponding measurement items, measurement requirements, etc.

[0105] The specific structure of the database is not limited here and can be determined according to actual needs.

[0106] The map pre-processing module 110 in this system is used to obtain the original map corresponding to the building map, and process it to identify the parts on the map corresponding to walls, doors, and windows.

[0107] For example, the map pre-processing module 110 processes the original map into a PNG format bitmap, and marks the parts corresponding to walls, doors, and windows on the bitmap with different colors.

[0108] The measurement object segmentation module 120 in the system interacts with the map pre-processing module 110 to perform segmentation processing on the map processed by the map pre-processing module 110 and determine the measurement objects contained in each room outline on the map.

[0109] Specifically, the measurement object division module 120 mainly protects the area division module 121 , the identification module 122 , and the measurement object determination module 123 , which cooperate with each other.

[0110] The region division module 121 obtains the map processed by the map pre-processing module 110 and performs region division to obtain a plurality of sub-regions, each of which corresponds to a room outline.

[0111] As an example, the region division module 121 may be implemented by the solution described in the above step (2.1).

[0112] The identification module 122 exchanges data with the area division module 121 , and traverses the outline of each sub-area divided by the area division module 121 to identify the components corresponding to the wall, door, window, and corner in each sub-area.

[0113] For example, the identification module 122 can be implemented by the solutions described in the above steps (2.2) and (2.3).

[0114] The measurement object determination module 123 exchanges data with the identification module 122 , and divides the outline of each sub-region according to the components corresponding to the wall, door, window, and corner identified by the identification module 122 to form a corresponding measurement object.

[0115] As an example, the measurement object determination module 123 can be implemented by the solutions described in the above steps (2.3) and (2.4).

[0116] The measurement point planning module 130 in the system interacts with the measurement object division module 120 and the database 140 to plan corresponding measurement points according to the measurement items to be measured and the measured objects determined by the measurement object division module 120 .

[0117] The measurement point planning module 130 first determines the corresponding measurement object according to different measurement items; then, automatically plans the corresponding measurement points according to the structural characteristics, coordinate information, size information, etc. of the corresponding measurement object.

[0118] As an example, the measurement point planning module 130 can be implemented by the solution described in step (3) above.

[0119] The measurement point planning system based on intelligent recognition of architectural drawings formed by the present invention, when implemented, first obtains the original map corresponding to the building map by the map preprocessing module 110, and processes it to identify the parts on the map corresponding to walls, doors, and windows.

[0120] Next, the measurement object segmentation module 120 performs segmentation processing on the map obtained by the map pre-processing module 110 to determine the measurement objects contained in each room outline on the map.

[0121] Next, the measurement point planning module 130 in this system plans corresponding measurement points based on the measurement items to be measured and the objects to be measured determined by the measurement object classification module 120. The measurement point planning module 130 first determines the corresponding measurement objects based on the different measurement items; then, it automatically plans the corresponding measurement points based on the structural characteristics, coordinate information, and size information of the corresponding measurement objects.

[0122] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A measurement point planning method based on intelligent recognition of architectural drawings, characterized in that: include: (1) Obtain the original map, process it, and identify the corresponding parts of walls, doors, and windows on the map; (2) Divide the map obtained by step (1) into blocks and determine the measurement objects contained in each room outline on the map; (3) According to the measurement items to be measured, the corresponding measurement points are planned based on the measured objects divided and determined in step (2), including: For the planning of measurement points for wall verticality, flatness, and embedded wall parts detection, first, based on the coordinates and size information of the wall segment measurement object identified in step (2), two extreme points are marked on both sides of the wall segment, and the field of view of the measuring device just covers the boundary; then, for the area in the middle of the wall segment, several points are generated at equal distances according to the principle of full coverage of the field of view of the measuring device; The measurement point planning for the cross-sectional dimensions of columns and narrow walls is first based on the measurement objects corresponding to the wall segments identified in step (2), and according to the coordinate information and / or size information of the measurement objects corresponding to the wall segments, the wall segment measurement objects with a width less than a threshold are identified and determined to be columns or narrow walls; Next, for the measurement object determined to be a column or narrow wall, a measurement point is pre-planned based on the wall measurement point planning method; Next, for the pre-planned measurement points, offset adjustments are made based on the overall size of the measurement equipment, and the offset distance is adjusted to obtain the final measurement points.

2. The measurement point planning method based on intelligent recognition of architectural drawings according to claim 1 is characterized in that: In the step (1), the original map is processed into a PNG format bitmap, and the corresponding parts of the walls, doors and windows are marked on the bitmap.

3. The measurement point planning method based on intelligent recognition of architectural drawings according to claim 1 is characterized in that: The step (2) includes the following sub-steps: (2.1) Divide the processed map into several sub-regions, each of which corresponds to a room outline; (2.2) For each sub-region segmented in step (2.1), traverse the outline of each sub-region and identify the components corresponding to the wall, door, window, and corner in each sub-region; (2.3) Divide the outline of each sub-area according to the components corresponding to the wall, door, window, and corner identified in step (2.2) to form corresponding measurement objects.

4. The method for planning measurement points based on intelligent recognition of architectural drawings according to claim 3, characterized in that: The step (2.3) is to sort the formed measurement objects.

5. The measurement point planning method based on intelligent recognition of architectural drawings according to claim 1 is characterized in that: The step (3) includes planning the measurement points of the internal and external corners. First, based on the relevant information when identifying each corner in step (2), the coordinate information of each corner is determined, and a measurement point is generated for each internal and external corner based on the coordinate information of each corner.

6. The method for planning measurement points based on intelligent recognition of architectural drawings according to claim 1, characterized in that: The step (3) includes planning the measurement points for the door and window sizes. First, based on the measurement objects corresponding to the door and window sections identified in step (2), and according to the coordinate information and size information of the measurement objects corresponding to the door and window sections, a median perpendicular to the door and window sections is constructed; then, for the constructed median perpendicular, a measurement point is determined on the median based on the distance of the measuring device from the wall.

7. The method for planning measurement points based on intelligent recognition of architectural drawings according to claim 1, characterized in that: The step (3) includes planning the measurement points of the wall spacing. First, based on the coordinates and size information of the wall segment measurement objects, door segment measurement objects, and window segment measurement objects contained in each sub-region identified in step (2), the region in the sub-region where both ends in the horizontal and vertical directions are wall segments is determined; then, the region is used as the measurement point planning region, and a measurement point is determined in the region.

8. The measurement point planning system based on intelligent recognition of architectural drawings is characterized by: The system includes a map preprocessing module, a measurement object division module, and a measurement point planning module; The map preprocessing module is used to obtain the original map corresponding to the building map, and process it to identify the parts corresponding to the walls, doors and windows on the map; The measurement object division module interacts with the map preprocessing module to divide the map processed by the map preprocessing module into blocks and determine the measurement objects contained in each room outline on the map; The measurement point planning module interacts with the measurement object division module to plan corresponding measurement points according to the measurement items to be measured and the objects to be measured determined by the measurement object division module; The measurement point planning module can plan measurement points for wall verticality, flatness, and embedded wall parts inspection. First, based on the coordinates and size information of the wall segment measurement object identified in the measurement object division module, two extreme points are marked on both sides of the wall segment, just enough to ensure that the measurement device's field of view covers the boundary. Then, a number of points are generated at equal intervals in the area in the middle of the wall segment based on the principle of full coverage of the measurement device's field of view. The measurement point planning module is capable of planning measurement points for the cross-sectional dimensions of columns and narrow walls. First, based on the measurement objects corresponding to wall segments identified in the measurement object division module and according to the coordinate information and / or size information of the measurement objects corresponding to the wall segments, the module identifies the wall segment measurement objects with a width less than a threshold value and determines them as columns or narrow walls. Next, for the measurement object determined to be a column or narrow wall, a measurement point is pre-planned based on the wall measurement point planning method; Next, for the pre-planned measurement points, offset adjustments are made based on the overall size of the measurement equipment, and the offset distance is adjusted to obtain the final measurement points.

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