Tunnel three-dimensional deformation monitoring robot and working method thereof

Abstract

This invention discloses a tunnel 3D deformation monitoring robot and its working method, comprising: a robot body, and a 3D laser scanner, a total station, and a processing module mounted on the robot body; the 3D laser scanner is used to perform a comprehensive scan of various parts of the tunnel to obtain tunnel point cloud data; the processing module receives the tunnel point cloud data and is configured to obtain rough positioning points of deformation within the tunnel based on the tunnel point cloud data, and feed back the coordinates of the rough positioning points to the total station; the total station receives the coordinates and is used to perform single-point deformation monitoring of each rough positioning point. By integrating a 3D laser scanner and a total station into one unit, it balances accuracy and breadth, solving the problems of low measurement accuracy of the 3D laser scanner and the single-point measurement limitation of the total station in tunnel 3D deformation monitoring.

Description

Technical Field

[0001] This invention relates to the field of tunnel monitoring and measurement technology, and in particular to a tunnel three-dimensional deformation monitoring robot and its working method. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Current tunnel monitoring and measurement methods cannot simultaneously achieve both accuracy and breadth, and the monitoring and measurement are point-based, resulting in blind spots. When using 3D laser scanning for monitoring and measurement, the 3D laser scanner can monitor the entire area, but the accuracy is low and cannot meet the monitoring requirements of the specifications. When using a total station for monitoring and measurement, the total station has higher accuracy but can only monitor single points. Moreover, when monitoring tunnels, the points monitored by the total station are laid out according to a uniform layout map, and they are basically all in the same position, without taking into account the actual deformation characteristics of the tunnel. Furthermore, after the 3D laser scanner finds a point, it cannot effectively transmit the position to the total station, and the coarse data scanned by the 3D laser scanner cannot be well integrated with the data from the total station. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes a tunnel three-dimensional deformation monitoring robot and its working method, integrating a three-dimensional laser scanner and a total station into one unit, balancing accuracy and breadth, and solving the problems of low measurement accuracy of the three-dimensional laser scanner and the total station's limitation to single-point measurement in the tunnel three-dimensional deformation monitoring process.

[0005] To achieve the above objectives, the present invention adopts the following technical solution:

[0006] In a first aspect, the present invention provides a tunnel three-dimensional deformation monitoring robot, comprising: a robot body, and a three-dimensional laser scanner, a total station and a processing module mounted on the robot body;

[0007] The three-dimensional laser scanner is used to scan all parts of the tunnel to obtain tunnel point cloud data;

[0008] The processing module receives tunnel point cloud data and is configured to obtain a rough location point of the deformation inside the tunnel based on the tunnel point cloud data, and feed back the coordinates of the rough location point to the total station.

[0009] The total station receives coordinates and is used to monitor the deformation of each coarsely located point.

[0010] As an alternative implementation, the 3D laser scanner and the total station use the same set of coordinate axes and have the same coordinate system.

[0011] As an alternative implementation, the three-dimensional laser scanner is used to perform multiple overall scans of various parts of the tunnel at different time periods, thereby obtaining multiple tunnel point cloud data at different time periods.

[0012] As an alternative implementation, the processor finds a rough location point where the deformation exceeds a threshold by analyzing changes in the tunnel point cloud data.

[0013] As an alternative implementation, the robot body includes a vehicle travel module, on which a platform equipped with a 3D laser scanner, a total station and a processing module is mounted. The platform is also equipped with a video image sensing device for receiving the coordinates of a coarse positioning point.

[0014] As an alternative implementation, the video image sensing device is used to lay out within the tunnel based on the coordinates of a rough positioning point, so as to provide a target monitoring point for the total station, enabling the total station to determine the monitoring position and perform deformation monitoring at a single point.

[0015] As an alternative implementation, the total station is also used to store the coordinates of coarse positioning points.

[0016] As an alternative implementation method, after the first deformation monitoring is completed, when deformation monitoring is performed again, the total station continues to perform single-point deformation monitoring based on the coordinates of the stored coarse positioning points, while the three-dimensional laser scanner performs an overall scan. If the coarse positioning points obtained from the second overall scan remain unchanged, the original monitoring scheme is maintained. If changes occur, the coordinates of the new coarse positioning points are fed back to the total station.

[0017] As an alternative implementation, the processing module is also used to integrate the coordinates of the coarse positioning points into the point cloud model, add texture to the point cloud model to generate a three-dimensional model, map the three-dimensional model to the ground station, realize automated point finding through the three-dimensional model, and combine it with prism-free measuring points to aim at the target, ultimately realizing automated monitoring.

[0018] In a second aspect, the present invention provides a method for operating the tunnel three-dimensional deformation monitoring robot described in the first aspect, comprising:

[0019] A 3D laser scanner was used to perform a comprehensive scan of all parts of the tunnel to obtain tunnel point cloud data.

[0020] Based on the tunnel point cloud data, the rough location points of the deformation inside the tunnel are obtained, and the coordinates of the rough location points are fed back to the total station.

[0021] A total station was used to monitor the deformation at each coarsely located point.

[0022] The coordinates of the rough positioning points are integrated into the point cloud model. After adding texture to the point cloud model, a 3D model is generated. The 3D model is then mapped to the ground station. Automated point finding is achieved through the 3D model. Combined with prism-free measuring points to aim at the target, automated monitoring is finally realized.

[0023] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0024] This invention proposes a tunnel three-dimensional deformation monitoring robot and its working method, which integrates a three-dimensional laser scanner and a total station. On the one hand, it makes up for the problem of insufficient accuracy of the laser scanner, and on the other hand, it solves the problem that the total station does not know which point to monitor and cannot accurately perform single-point monitoring. It solves the disadvantages of low measurement accuracy of three-dimensional laser scanner and single-point measurement of total station in the process of tunnel three-dimensional deformation monitoring, and balances accuracy and breadth, so as to achieve more intelligent and efficient monitoring and measurement of tunnels.

[0025] This invention proposes a tunnel three-dimensional deformation monitoring robot and its working method. The three-dimensional laser scanner and the total station use the same set of coordinate axes and have the same coordinate system. Therefore, after unifying the coordinate system, the total station measurement point data and the three-dimensional laser scanner data can be fused to achieve data sharing.

[0026] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0027] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0028] Figure 1 This is a schematic diagram of a tunnel three-dimensional deformation monitoring robot provided in Embodiment 1 of the present invention;

[0029] Figure 2 This is a flowchart of the working method of the tunnel three-dimensional deformation monitoring robot provided in Embodiment 2 of the present invention. Detailed Implementation

[0030] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0031] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0032] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the exemplary embodiments of the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. Furthermore, it should be understood that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0034] Example 1

[0035] This embodiment provides a tunnel 3D deformation monitoring robot that integrates a 3D laser scanner and a total station. On the one hand, it makes up for the lack of accuracy of the 3D laser scanner, and on the other hand, it solves the problem that the total station does not know which point to monitor and cannot accurately perform single-point monitoring. It balances accuracy and breadth, and realizes more intelligent and efficient monitoring and measurement of tunnels.

[0036] like Figure 1 As shown, it includes:

[0037] The robot body, and the 3D laser scanner, total station and processing module mounted on the robot body;

[0038] The three-dimensional laser scanner is used to scan all parts of the tunnel to obtain tunnel point cloud data;

[0039] The processing module receives tunnel point cloud data and is configured to obtain a rough location point of the deformation inside the tunnel based on the tunnel point cloud data, and feed back the coordinates of the rough location point to the total station.

[0040] The total station receives coordinates and is used to monitor the deformation of each coarsely located point.

[0041] In this embodiment, the 3D laser scanner and the total station use the same set of coordinate axes and have the same coordinate system. Therefore, after unifying the coordinate system, the total station measurement data and the 3D laser scanner scanning data can be fused to achieve data sharing.

[0042] In this embodiment, the three-dimensional laser scanner is used to perform multiple overall scans of various parts of the tunnel at different time periods, thereby obtaining multiple tunnel point cloud data at different time periods.

[0043] After receiving the tunnel point cloud data, the processing module processes it and finds a rough location point where the deformation exceeds a threshold by analyzing the changes in the tunnel point cloud data. The coordinates of this point are then fed back to the total station to achieve rough positioning using a 3D laser scanner.

[0044] Understandably, conventional techniques can be used to process tunnel point cloud data, such as using PACT software, which will not be elaborated here.

[0045] In this embodiment, after rough positioning, the coordinates of the rough positioning point can be fed back to the total station and the position coordinates of the point can be recorded. Then, within a small area of ​​the rough positioning point, the point can be accurately located through single-point deformation monitoring.

[0046] As an alternative implementation, the robot body includes a vehicle travel module, on which a platform equipped with a 3D laser scanner, a total station, and a processing module is mounted, as well as a video image sensing device. After obtaining a rough positioning point, the coordinates are fed back to the video image sensing device. The video image sensing device is used to lay out the tunnel, which can be used to provide a target monitoring point for the total station, so that the total station can determine the monitoring position and monitor the displacement change of that point.

[0047] As is understandable, the vehicle movement module and video image sensing device are existing technologies and will not be described in detail here.

[0048] In this embodiment, after the first deformation monitoring is completed, when the deformation monitoring is carried out for the second or subsequent time, the total station can continue to monitor the deformation of the point based on the coordinates of the recorded rough positioning point. At the same time, the three-dimensional laser scanner continues to monitor a large area within the region. If the point is still the point of maximum deformation, the original monitoring scheme is maintained. If not, the new coordinates can be fed back to the total station, and the next monitoring will also be carried out.

[0049] In this embodiment, the tunnel 3D deformation monitoring robot can also achieve automated monitoring. After obtaining a rough positioning point, the xyz coordinates of the point are integrated into the point cloud model, and texture is added to the point cloud model to generate a 3D model. This model is then integrated into the robot's field of view and mapped to the ground station. By clicking on the model's location, the robot can turn its head to find the point. Combined with prism-free measuring points aiming at the target, automated monitoring is finally achieved.

[0050] The tunnel 3D deformation monitoring robot proposed in this embodiment not only makes up for the lack of accuracy of laser scanners, but also solves the problem that total stations do not know which point to monitor and therefore cannot accurately perform single-point monitoring.

[0051] Example 2

[0052] This embodiment provides a working method for the tunnel three-dimensional deformation monitoring robot described in Embodiment 1, such as... Figure 2 As shown, it includes the following steps:

[0053] A 3D laser scanner was used to scan all parts of the tunnel to obtain tunnel point cloud data, which was used to roughly locate the tunnel within a wide field of view.

[0054] Based on the tunnel point cloud data, the rough location points of the deformation inside the tunnel are obtained, and the coordinates of the rough location points are fed back to the total station.

[0055] A total station was used to monitor the deformation of each coarse positioning point in order to achieve precise aiming within a small area.

[0056] The xyz coordinates of the rough positioning points are integrated into the point cloud model, and textures are added to the point cloud model to generate a 3D model. This model is then integrated into the robot's field of view and mapped to the ground station. This allows the robot to turn its head to find the point by clicking on the model's location. Combined with prism-free measurement points to aim at the target, automated monitoring is ultimately achieved.

[0057] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A tunnel three-dimensional deformation monitoring robot, characterized in that, include: The robot body, and the 3D laser scanner, total station and processing module mounted on the robot body; The three-dimensional laser scanner is used to scan all parts of the tunnel to obtain tunnel point cloud data; The processing module receives tunnel point cloud data and is configured to obtain a rough location point of the deformation inside the tunnel based on the tunnel point cloud data, and feed back the coordinates of the rough location point to the total station. The total station receives coordinates and is used to monitor the deformation of each coarsely located point. The robot body includes a vehicle travel module, on which a platform equipped with a 3D laser scanner, a total station and a processing module is mounted. The platform is also equipped with a video image sensing device, which is used to receive the coordinates of a coarse positioning point. The video image sensing device is used to lay out the tunnel according to the coordinates of the rough positioning point, so as to provide the total station with the target monitoring point, so that the total station can determine the monitoring position and perform deformation monitoring at a single point. The processing module is also used to integrate the coordinates of the rough positioning points into the point cloud model, add texture to the point cloud model to generate a three-dimensional model, map the three-dimensional model to the ground station, realize automated point finding through the three-dimensional model, and combine it with prism-free measuring points to aim at the target, ultimately realizing automated monitoring.

2. The tunnel three-dimensional deformation monitoring robot according to claim 1, wherein The 3D laser scanner and total station use the same set of coordinate axes and have the same coordinate system.

3. The tunnel three-dimensional deformation monitoring robot according to claim 1, wherein The 3D laser scanner is used to perform multiple overall scans of various parts of the tunnel at different time periods, thereby obtaining multiple tunnel point cloud data at different time periods.

4. The tunnel three-dimensional deformation monitoring robot according to claim 1, wherein The processor finds a rough location point where the deformation exceeds a threshold by analyzing changes in the tunnel point cloud data.

5. The tunnel three-dimensional deformation monitoring robot as described in claim 1, characterized in that, The total station is also used to store the coordinates of rough positioning points.

6. The tunnel three-dimensional deformation monitoring robot as described in claim 5, characterized in that, After the initial deformation monitoring is completed, when deformation monitoring is performed again, the total station continues to monitor the deformation of a single point based on the coordinates of the stored coarse positioning point. At the same time, the 3D laser scanner performs an overall scan. If the coarse positioning point obtained from the second overall scan remains unchanged, the original monitoring scheme is maintained. If there is a change, the coordinates of the new coarse positioning point are fed back to the total station.

7. A working method for a tunnel three-dimensional deformation monitoring robot, characterized in that, The tunnel three-dimensional deformation monitoring robot according to any one of claims 1-6 includes: A 3D laser scanner was used to perform a comprehensive scan of all parts of the tunnel to obtain tunnel point cloud data. Based on the tunnel point cloud data, the rough location points of the deformation inside the tunnel are obtained, and the coordinates of the rough location points are fed back to the total station. A total station was used to monitor the deformation at each coarsely located point. The coordinates of the rough positioning points are integrated into the point cloud model. After adding texture to the point cloud model, a 3D model is generated. The 3D model is then mapped to the ground station. Automated point finding is achieved through the 3D model. Combined with prism-free measuring points to aim at the target, automated monitoring is finally realized.

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