CN117470106A - Narrow space point cloud absolute data acquisition method and model building equipment - Google Patents

Abstract

The invention discloses a narrow space point cloud absolute data acquisition method and model building equipment, wherein the narrow space point cloud absolute data acquisition method comprises the following steps: starting from the requirement of a tunnel construction profile surface, aiming at the problems of precision requirement and scanning view angle limitation of a three-dimensional laser scanner, the two kinds of point cloud data are registered and spliced with high precision through the cooperation of a total station scanning device capable of acquiring high precision and absolute position coordinates and a flexible small handheld SLAM device, so that the point cloud absolute data of the construction profile surface at narrow spaces such as a small space (a micro-step upper-stage excavation surface), a large depression angle (an inverted arch excavation surface) and the like are realized. The invention can effectively control the problems of tunnel construction over-excavation and the like, provides high-precision data support, realizes the digital management of tunnel construction, and has positive benefits on the progress and quality of construction.

Description

Narrow space point cloud absolute data collection method and model building equipment

Technical field

The invention belongs to the field of engineering surveying, especially for scenes in tunnel engineering construction where it is difficult to set up a large-scale three-dimensional laser scanner for scanning in narrow spaces such as steps or inverts. It relates to a point cloud absolute data collection method and model establishment in a narrow space. equipment.

Background technique

The geological conditions of the tunnel are harsh, the construction environment is complex, and there are many inconveniences in construction management and control. As a result, the over-excavation problem during the construction process has become an important factor affecting the cost of tunnel construction. Therefore, effectively controlling the degree of over-excavation in tunnel construction and promptly and accurately grasping tunnel construction profile data information have become the key to solving the problem.

Currently, tunnel construction profiles are mainly obtained through cross-section measurement. The main instruments used are section meters and total stations. These methods are inefficient and require a lot of time and manpower. Compared with traditional measurement methods, 3D laser scanning technology provides a faster, safer, and more effective method of investigation, measurement, and monitoring. The 3D laser scanner can work in extremely complex spatial scenes. By carefully scanning the space, a large amount of 3D laser point cloud data is collected into the computer, and then the software can quickly detect various non-standard and irregular shapes. 3D model construction of large entities. However, the tunnel is a long and narrow structure, and the 3D laser scanner itself has accuracy requirements and scanning viewing angle limitations.

Therefore, the data acquisition problem is a key issue in applying 3D laser scanning technology to tunnel engineering. Especially when excavating with the micro-step method, the viewing angle of the upper excavation surface space is small, and the three-dimensional scanning measuring instrument cannot be placed in a small space. The three-dimensional scanning measuring instrument for the inverted arch excavation surface is affected by the blind area of depression angle measurement. Precise scanning measurement is difficulty.

Contents of the invention

One object of the present invention is to provide a point cloud absolute data acquisition method in a small space to solve the problem of difficulty in accurately collecting cloud data of construction contour surface points during the step method construction tunnel excavation proposed in the above background technology.

In order to achieve the above objects, the present invention adopts the following technical solutions:

A method for absolute data collection of point clouds in a small space, including the following steps:

Arrange control points in the tunnel construction section;

Set up the first scanner at the control point, establish a measuring station in the global coordinate system of tunnel construction, and scan to obtain global point cloud data of the construction contour surface;

Preprocess the global point cloud data obtained by the full-station scanner, compare it with the actual contour surface, and obtain the vacant areas where the contour surface point cloud data cannot be obtained;

Use the second scanner to move to obtain SLAM point cloud data including the point cloud data of the contour surface of the vacant area;

The SLAM point cloud data and the global point cloud data are registered, and the SLAM point cloud data is integrated into the global point cloud data to fill in the point cloud data of the vacant area, and the absolute point cloud of the full contour surface of the tunnel construction section is obtained. data.

As a preferred aspect, the narrow space point cloud absolute data collection method also includes the step of establishing a three-dimensional model of the tunnel construction contour surface using the point cloud absolute data of the tunnel construction section.

As a preferred aspect, the first scanner is a full-station scanner, and the point cloud coordinates obtained are absolute data in the global coordinate system of tunnel construction; the second scanner is a handheld SLAM device, and the point cloud coordinates obtained are It is relative data under the point cloud space coordinate system centered on the SLAM device. Each frame point cloud has a local coordinate system. After registering each frame data, the SLAM point cloud global space is formed. The coordinate system of this space is the SLAM point. Cloud global coordinate system.

As a preferred aspect, the step of registering SLAM point cloud data and global point cloud data is specifically implemented as:

Project the point cloud data obtained by the handheld SLAM device from the local coordinate system of each frame to the global coordinate system of the SLAM point cloud, and then complete positioning and splicing;

The global point cloud data of the full-station scanner and the spliced SLAM point cloud data are registered to realize the projection conversion from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

As a preferred aspect, the step of registering the global point cloud data of the full-station scanner and the spliced SLAM point cloud data to realize the projection conversion from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system is specifically implemented. As follows: first, the matching correspondence between point clouds is constructed through the morphological characteristics of the measured part itself, and then the AO algorithm based on point SHOT features is used to estimate the projection transformation relationship.

As a preferred aspect, the step of fusing the SLAM point cloud data filling into the global point cloud data to fill the point cloud data in the vacant area is specifically implemented as:

According to the projection conversion relationship, the spliced SLAM point cloud data is converted to the tunnel construction global coordinate system, and the converted SLAM data is filled into the global point cloud data.

As a preferred aspect, the projection transformation relationship between the local coordinate system of each frame and the global coordinate system of the SLAM point cloud is:

Among them, x ₁ , y ₁ , z ₁ are the spatial coordinates in the local coordinate system of a certain frame of SLAM point cloud data; x ₂ , y ₂ , z ₂ are the spatial coordinates in the global coordinate system of the SLAM point cloud; x ₀ , y ₀ , z ₀ is the offset of the origin of the local coordinate system of a certain frame of SLAM point cloud data relative to the origin of the global coordinate system of the SLAM point cloud; It is the rotation angle parameter of each coordinate axis converted from the local coordinate system of a certain frame of SLAM point cloud data to the global coordinate system of SLAM point cloud.

As a preferred aspect, the projection transformation relationship between the SLAM point cloud global coordinate system and the tunnel construction global coordinate system includes the following formula:

Among them, X, Y, Z are arbitrary spatial coordinates in the tunnel construction global coordinate system; x, y, z are spatial coordinates in the SLAM point cloud global coordinate system; X ₀ , Y ₀ , Z ₀ are the SLAM point cloud global coordinates The offset of the system origin relative to the origin of the tunnel construction global coordinate system; It is the rotation angle parameter of each coordinate axis converted from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system; It is the scale factor for converting the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

As a preferred aspect, the handheld SLAM device includes visual SLAM and/or laser SLAM;

The steps to obtain SLAM point cloud data are as follows:

The handheld SLAM device moves to acquire contour surface point cloud data, and acquires multiple point cloud data at the same location from different angles and different frames.

A narrow space point cloud absolute data collection and model building equipment, including:

Control point arrangement unit, used to arrange control points in the tunnel construction section;

The global point cloud data acquisition unit is used to set up the first scanner at the control point, establish a measuring station in the global coordinate system of tunnel construction, and scan and obtain the global point cloud data of the construction contour surface;

The vacant area acquisition unit is used to preprocess the global point cloud data obtained by the full-station scanner, compare it with the actual contour surface, and obtain the vacant area where the contour surface point cloud data cannot be obtained;

The SLAM point cloud data acquisition unit uses the second scanner to move to acquire SLAM point cloud data including the point cloud data of the contour surface of the vacant area;

The point cloud absolute data calculation unit is used to register the SLAM point cloud data and the global point cloud data, fill in the blank area contour surface point cloud data into the global point cloud data, and obtain the point cloud absolute data of the tunnel construction section. .

The model building unit is used to establish a three-dimensional model of the tunnel construction contour surface using absolute point cloud data of the tunnel construction section.

Compared with the prior art, the beneficial effects of the present invention are:

This invention uses full station scanning to obtain partial point cloud data of the tunnel construction contour surface in an open area of a narrow space such as a tunnel, and then uses a small handheld SLAM device to conduct mobile measurements to obtain local point cloud data of the upper excavation surface, inverts, etc. Through further registration and splicing, absolute data collection of point clouds in a small space was achieved, and the current contour surface information during tunnel construction was obtained in a timely, comprehensive and accurate manner. It provided high-precision data support for effectively controlling over-excavation and other issues in tunnel construction, and achieved Digital management of tunnel construction can have positive benefits on the progress and quality of construction.

Referring to the following description and drawings, specific embodiments of the invention are disclosed in detail and the manner in which the principles of the invention may be employed is indicated. It should be understood that embodiments of the invention are not thereby limited in scope.

Features described and/or illustrated with respect to one embodiment may be used in the same or similar manner in one or more other embodiments, in combination with features in other embodiments, or in place of features in other embodiments .

It should be emphasized that the term "comprising" when used herein refers to the presence of features, integers, steps or components but does not exclude the presence or addition of one or more other features, integers, steps or components.

Description of the drawings

In order to explain the embodiments of the present invention or the technical solutions in the prior art more clearly, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings in the following description are only These are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without exerting any creative effort.

Figure 1 is a schematic diagram of the method steps of a narrow space point cloud absolute data acquisition method provided by an embodiment of the present invention;

Figure 2 is a schematic diagram of a device module provided by an embodiment of the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of protection of the present invention.

It should be noted that when an element is referred to as being "disposed on" another element, it can be directly on the other element or the other element may be interveningly present. When an element is said to be "connected" to another element, it can be directly connected to the other element or it may be present between the other element. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation manner.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which the invention belongs. The terminology used herein in the description of the invention is for the purpose of describing specific embodiments only and is not intended to limit the invention. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed items.

Please refer to Figure 1. One embodiment of the present invention provides a point cloud absolute data acquisition method in a small space, which includes the following steps:

S1. Arrange control points in the tunnel construction section;

S2. Set up the first scanner at the control point, establish a measuring station in the global coordinate system of tunnel construction, and scan to obtain the global point cloud data of the construction contour surface;

S3. Preprocess the global point cloud data obtained by the full-station scanner, compare it with the actual contour surface, and obtain the vacant areas where the point cloud data of the contour surface cannot be obtained;

S4. Use the second scanner to move to obtain SLAM point cloud data including the point cloud data of the contour surface of the vacant area;

S5. Register the SLAM point cloud data and the global point cloud data, fill and fuse the SLAM point cloud data into the global point cloud data to fill the point cloud data in the vacant area, and obtain the point cloud absolute data of the tunnel construction section;

S6. Use the point cloud absolute data of the tunnel construction section to establish a three-dimensional model of the tunnel construction contour surface.

In step S1, the engineering control network is introduced into the tunnel construction excavation section through wire measurement, and control points are arranged. Among them, the control points are mainly used to set up scanning instruments and obtain the absolute coordinate values of the point cloud in the tunnel construction coordinate system. The control point is generally in the center of the tunnel, making it easy to set up a full-station scanner. The field of view is wide and the construction contour can be observed to the greatest extent possible.

The first scanner is a full-station scanner. The global point cloud data obtained in step S2 is the point cloud data in the tunnel construction global coordinate system (absolute coordinate system). In step S3, the actual contour surface is the current tunnel contour surface in reality. Through manual comparison, unobserved areas are found, such as cavity areas in the point cloud such as the upper platform excavation surface and inverted arches. This vacant area is mainly an area that the full-station scanner cannot scan due to viewing angle and other issues.

The second scanner is a handheld SLAM device. The handheld SLAM device includes visual SLAM and/or laser SLAM. The step S4 is implemented as follows: the handheld SLAM device moves to acquire contour surface point cloud data, and acquires multiple (SLAM) point cloud data at the same position from different angles and different frames. The handheld SLAM device performs multi-frame shooting and scanning at multiple locations and angles in the tunnel, with particular emphasis on measuring the (SLAM) point cloud data of the vacant areas obtained in S3. Handheld SLAM has low accuracy, but its equipment is flexible in movement, but it cannot directly obtain the absolute coordinates of the point cloud. Therefore, the SLAM point cloud data can cover the vacant areas that cannot be scanned by the full-station scanner, thereby converting the SLAM point cloud data into The relevant data in can be filled into the full-site cloud data to obtain absolute point cloud data of the entire tunnel construction section.

In this embodiment, the step of registering SLAM point cloud data and global point cloud data is specifically implemented as the following sub-steps:

S51. Project the SLAM point cloud data of the handheld SLAM device from the local coordinate system of each frame to the global coordinate system of the SLAM point cloud space, and then complete the positioning splicing;

S52. Register the global point cloud data of the full-station scanner and the spliced SLAM point cloud data to realize the projection conversion from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

The specific implementation of step S52 is as follows: first, the matching correspondence between point clouds is constructed based on the morphological characteristics of the measured part itself, and then the AO algorithm based on point SHOT features is used to estimate and obtain the projection conversion relationship. Among them, the registration process can be continuously iterated, evolving from coarse registration to fine registration, and finally stopped through judgment criteria.

In step S51, the projection transformation relationship between the local coordinate system of each frame and the global coordinate system of the SLAM point cloud is:

Among them, x ₁ , y ₁ , z ₁ are the spatial coordinates in the local coordinate system of a certain frame of SLAM point cloud data; x ₂ , y ₂ , z ₂ are the spatial coordinates in the global coordinate system of the SLAM point cloud; x ₀ , y ₀ , z ₀ is the offset of the origin of the local coordinate system of a certain frame of SLAM point cloud data relative to the origin of the global coordinate system of the SLAM point cloud; It is the rotation angle parameter of each coordinate axis converted from the local coordinate system of a certain frame of SLAM point cloud data to the global coordinate system of SLAM point cloud.

In step S52, the projection transformation relationship between the SLAM point cloud global coordinate system and the tunnel construction global coordinate system includes the following formula:

Among them, X, Y, Z are arbitrary spatial coordinates in the tunnel construction global coordinate system; x, y, z are spatial coordinates in the SLAM point cloud global coordinate system; X ₀ , Y ₀ , Z ₀ are the SLAM point cloud global coordinates The offset of the system origin relative to the origin of the tunnel construction global coordinate system; It is the rotation angle parameter of each coordinate axis converted from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system; It is the scale factor for converting the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

Further, the specific implementation of step S5 of fusing the SLAM point cloud data filling into the global point cloud data to fill the point cloud data in the vacant area is: converting the spliced SLAM point cloud data to Tunnel construction global coordinate system, and fill the converted SLAM data into the global point cloud data.

In this step, the station scan data (global point cloud data) is used as the benchmark, and the SLAM point cloud data is integrated into it to realize the conversion of the SLAM point cloud data from relative coordinates to absolute coordinates, and then integrate it into the global point cloud data. The point cloud absolute data of the overall tunnel construction section is formed.

In order to improve the accuracy of point cloud registration, it also includes the following steps: first arrange a certain number of targets (two or more) on site, and then use the global point cloud data and the same-name feature points of the targets in the SLAM point cloud data for registration. allow. Correspondingly, in step S51, the same-named feature points of the target can be used to determine the offset of the origin of the local coordinate system of the SLAM point cloud data of different frames relative to the origin of the global coordinate system of the SLAM point cloud space, and in step S52, The same-named feature points of the target can be used to determine the offset of the origin of the global coordinate system of the SLAM point cloud space relative to the origin of the global coordinate system of the tunnel construction.

Furthermore, for targets with known size and shape characteristics, the target's feature points can be accurately extracted through the algorithm, and then the target's feature points of the same name between full-station scanning and SLAM point clouds are used for registration, which can effectively improve the accuracy of the alignment. Accuracy.

As shown in Figure 2, one embodiment of the present invention also provides a narrow space point cloud absolute data collection and model establishment device, including:

Control point arrangement unit, used to arrange control points in the tunnel construction section;

The global point cloud data acquisition unit is used to set up the first scanner at the control point, establish a measuring station in the global coordinate system of tunnel construction, and scan and obtain the global point cloud data of the construction contour surface;

The vacant area acquisition unit is used to preprocess the global point cloud data obtained by the full-station scanner, compare it with the actual contour surface, and obtain the vacant area where the contour surface point cloud data cannot be obtained;

The SLAM point cloud data acquisition unit uses the second scanner to move to acquire SLAM point cloud data including the point cloud data of the contour surface of the vacant area;

The point cloud absolute data calculation unit is used to register the SLAM point cloud data and the global point cloud data, fill in the blank area contour surface point cloud data into the global point cloud data, and obtain the point cloud absolute data of the tunnel construction section. ;

The model building unit is used to establish a three-dimensional model of the tunnel construction contour surface using absolute point cloud data of the tunnel construction section.

Multiple elements, components, components or steps can be provided by a single integrated element, component, component or step. Alternatively, a single integrated element, component, component or step may be divided into separate multiple elements, components, components or steps. The word "a" or "an" used to describe an element, component, component or step is not intended to exclude other elements, components, components or steps.

It should be understood that the above description is for purposes of illustration rather than limitation. Many embodiments and many applications beyond the examples provided will be apparent to those skilled in the art from reading the above description. The scope of the present teachings, therefore, should be determined, not with reference to the foregoing description, but rather with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. For purposes of comprehensiveness, the disclosures of all articles and references, including patent applications and publications, are hereby incorporated by reference. The omission of any aspect of the subject matter disclosed herein from the preceding claims is not intended to be a disclaimer of that subject matter, nor should it be deemed that the inventors failed to consider such subject matter to be part of the disclosed inventive subject matter.

Claims (10)

1. The method for acquiring the absolute data of the point cloud in the narrow space is characterized by comprising the following steps of:

arranging control points in a tunnel construction section;

erecting a first scanner at a control point, establishing a measuring station under a tunnel construction global coordinate system, and scanning to obtain global point cloud data of a construction contour surface;

preprocessing global point cloud data acquired by a total station scanner, and comparing the global point cloud data with an actual contour surface to acquire a vacant area in which the contour surface point cloud data cannot be acquired;

moving and acquiring SLAM point cloud data comprising the point cloud data of the outline surface of the vacant area by using a second scanner;

registering SLAM point cloud data and global point cloud data, filling and fusing the SLAM point cloud data into the point cloud data of the gap area filled in the global point cloud data, and obtaining point cloud absolute data of the full-contour surface of the tunnel construction section.

2. The method for collecting absolute data of a point cloud in a small space according to claim 1, further comprising the steps of: and establishing a three-dimensional model of the tunnel construction profile by using the absolute data of the point cloud of the tunnel construction section.

3. The method for acquiring absolute data of a point cloud in a small space according to claim 1, wherein the first scanner is a total station scanner; the second scanner is a handheld SLAM device.

4. The method for acquiring the absolute data of the small-space point cloud as claimed in claim 3, wherein the step of registering SLAM point cloud data and global point cloud data is implemented as follows:

carrying out projection of each frame of local coordinate system on SLAM point cloud data of the handheld SLAM equipment to an SLAM point cloud global coordinate system, and then completing positioning and splicing;

and registering the global point cloud data of the total station scanner and the spliced SLAM point cloud data to realize projection conversion from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

5. The method for collecting absolute data of point clouds in a narrow space according to claim 4, wherein the step of registering global point cloud data of a total station scanner and spliced SLAM point cloud data to realize projection conversion from a SLAM point cloud global coordinate system to a tunnel construction global coordinate system is specifically implemented as follows: firstly, matching correspondence among point clouds is constructed through morphological characteristics of the measured part, and then, the projection conversion relation is estimated by adopting an AO algorithm based on point SHOT characteristics.

6. The method for collecting absolute data of point cloud in small space according to claim 5, wherein the step of filling and fusing SLAM point cloud data into the global point cloud data to fill the point cloud data of the vacant area is implemented as follows:

and converting the spliced SLAM point cloud data into a tunnel construction global coordinate system according to the projection conversion relation, and filling the converted SLAM data into the global point cloud data.

7. The method for collecting absolute data of point cloud in small space according to claim 4, wherein the projection conversion relation between the local coordinate system of each frame and the global coordinate system of SLAM point cloud is:

wherein x is ₁ 、y ₁ 、z ₁ Space coordinates in a local coordinate system of a certain frame of SLAM point cloud data; x is x ₂ 、y ₂ 、z ₂ The space coordinates in the SLAM point cloud global coordinate system are obtained; x is x ₀ 、y ₀ 、z ₀ The method comprises the steps that the offset of a local coordinate system origin of a certain frame of SLAM point cloud data relative to a global coordinate system origin of SLAM point cloud is performed; />And the rotation angle parameters of all coordinate axes converted from a local coordinate system of a certain frame of SLAM point cloud data to a SLAM point cloud global coordinate system are obtained.

8. The method for collecting absolute data of point cloud in small space according to claim 6, wherein the projection conversion relation from the SLAM point cloud global coordinate system to the tunnel construction global coordinate system comprises the following formula:

x, Y, Z is any space coordinate in a tunnel construction global coordinate system; x, y and z are space coordinates in the SLAM point cloud global coordinate system; x is X ₀ 、Y ₀ 、Z ₀ Offset of the SLAM point cloud global coordinate system origin relative to the tunnel construction global coordinate system origin;applying to tunnels for SLAM point cloud global coordinate systemRotation angle parameters of all coordinate axes converted by the industrial global coordinate system; />And converting the scale factors for the SLAM point cloud global coordinate system to the tunnel construction global coordinate system.

9. The small space point cloud absolute data collection method of claim 3, wherein the handheld SLAM device comprises a visual SLAM and/or a laser SLAM;

the step of acquiring SLAM point cloud data is implemented as:

the handheld SLAM equipment moves to acquire the contour face point cloud data, and acquires a plurality of point cloud data of the same position from different angles and different frames.

10. The utility model provides a narrow and small space point cloud absolute data collection and model establishment equipment which characterized in that includes:

a control point arrangement unit for arranging control points at the tunnel construction section;

the global point cloud data acquisition unit is used for erecting a first scanner at the control point, establishing a station under a tunnel construction global coordinate system, and scanning to acquire global point cloud data of a construction contour surface;

the vacant area acquisition unit is used for preprocessing global point cloud data acquired by the total station scanner, comparing the actual profile surface and acquiring vacant areas without acquiring the profile surface point cloud data;

a SLAM point cloud data acquisition unit for acquiring SLAM point cloud data including the outline surface point cloud data of the vacant area by using the second scanner;

the point cloud absolute data computing unit is used for registering SLAM point cloud data and global point cloud data, filling and fusing the point cloud data of the outline surface of the vacant area into the global point cloud data, and obtaining tunnel construction point cloud absolute data;

the model building unit is used for building a three-dimensional model of the tunnel construction profile by utilizing the absolute data of the point cloud of the tunnel construction section.