Positioning method, device and equipment of tunnel construction equipment and storage medium

Abstract

The invention provides a positioning method and device of tunnel construction equipment, equipment and a storage medium, and relates to the field of tunnel positioning. Comprising the following steps: acquiring three-dimensional coordinate information of a plurality of corner reflectors in an area where to-be-positioned tunnel construction equipment is located; obtaining dynamic pixel coordinate information of the corner reflector through a visual module of the tunnel construction equipment to be positioned; determining a conversion relation between a millimeter wave radar coordinate system and an image pixel coordinate system according to the three-dimensional coordinate information and the dynamic pixel coordinate information; determining a radar observation equation of the corner reflector and the millimeter-wave radar module according to a conversion relation between the millimeter-wave radar coordinate system and the image pixel coordinate system; and determining the pose of the tunnel construction equipment to be positioned according to the radar observation equation. The technical problems that the accuracy of an existing tunnel positioning technology is less affected by the dust environment, laser is seriously scattered in the high-dust environment, the effective distance is shortened, and the positioning efficiency of tunnel construction equipment is reduced are solved.

Description

Technical Field

[0001] This application relates to the field of tunnel positioning, and more particularly to a positioning method, device, equipment, and storage medium for tunnel construction equipment. Background Technology

[0002] During tunnel construction, precise navigation and positioning of construction equipment are essential to ensure project quality and construction safety. However, the tunnel construction environment is complex, with problems such as dust, water mist, and uneven lighting. Traditional total station positioning is the main technical means for positioning in construction tunnels, but it is still greatly affected by dust and lighting, often resulting in low positioning accuracy, significant influence from environmental factors, poor real-time performance, and reliance on manual station relocation.

[0003] With the development of computer vision technology, visual positioning technology has been gradually introduced into tunnel construction environments. To address the problem that relying solely on camera positioning may not be effective in low light or high dust conditions, a "semantic segmentation view mapping model" that combines 2D maps with semantic segmentation of front views is currently used to reduce reliance on high-precision textures, and infrared supplementary lighting is employed.

[0004] However, the accuracy of existing tunnel positioning technology is reduced by dusty environments, and lasers are severely scattered in high-dust environments, shortening their effective distance and reducing the positioning efficiency of tunnel construction equipment. Summary of the Invention

[0005] This application provides a positioning method, device, equipment, and storage medium for tunnel construction equipment, which solves the problem that existing synchronous pushing and assembling technology ignores the impact of sudden changes in hydraulic cylinder thrust in the assembly area, resulting in low positioning efficiency of tunnel construction equipment.

[0006] Firstly, this application provides a method for positioning tunnel construction equipment, comprising:

[0007] Obtain the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located;

[0008] The dynamic pixel coordinate information of the corner reflector is obtained through the vision module of the tunnel construction equipment to be located; the vision module of the tunnel construction equipment is set up on the tunnel construction equipment to be located in conjunction with the millimeter-wave radar module.

[0009] Based on the three-dimensional coordinate information and dynamic pixel coordinate information, the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system is determined;

[0010] Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined.

[0011] The position and orientation of the tunnel construction equipment to be located are determined based on the radar observation equations.

[0012] In one possible design, based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined, including:

[0013] Determine the physical measurement information of the millimeter-wave radar module; the physical measurement information includes the radial distance, horizontal azimuth angle, and elevation angle of the acquired corner reflector;

[0014] Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, as well as physical measurement information, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined.

[0015] In one possible design, the pose of the tunnel construction equipment to be located is determined according to the radar observation equations, including:

[0016] Acquire the physical measurement values ​​of multiple corner reflectors corresponding to the millimeter-wave radar module;

[0017] The position and orientation of the tunnel construction equipment to be located are calculated based on the collected physical measurement information and the radar observation equation.

[0018] One possible design also includes:

[0019] If the tunnel construction equipment to be located is stationary, the static pixel coordinate information of multiple corner reflectors is obtained through the vision module.

[0020] Based on the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module are determined.

[0021] In one possible design, after determining the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module based on static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the design further includes:

[0022] Obtain the third static three-dimensional coordinate information of all corner reflectors in the area;

[0023] The positioning posture of the vision module is determined based on the third static three-dimensional coordinate information.

[0024] Based on the positioning posture of the vision module and the second static three-dimensional coordinate information, the fourth static three-dimensional coordinate information of the newly added corner reflector is identified.

[0025] In one possible design, after identifying the fourth static three-dimensional coordinate information of the newly added corner reflector based on the positioning pose of the vision module and the second static three-dimensional coordinate information, the following steps are also included:

[0026] Based on the millimeter-wave radar module, obtain the distance information of the newly added corner reflector and the corner reflectors in the area;

[0027] Based on the distance information, the third static three-dimensional coordinate information, and the fourth static three-dimensional coordinate information, update the radar observation equations for the corner reflector and the millimeter-wave radar module.

[0028] In one possible design, before obtaining the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located, the following steps are also included:

[0029] Obtain the layout information of the data sources for the tunnel construction equipment to be located; the data sources include corner reflectors, vision modules, and millimeter-wave radar modules.

[0030] Secondly, this application provides a positioning device for tunnel construction equipment, the device comprising:

[0031] The first acquisition module is used to acquire the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located;

[0032] The second acquisition module is used to acquire the dynamic pixel coordinate information of the corner reflector through the vision module of the tunnel construction equipment to be located; wherein, the tunnel construction equipment vision module and the millimeter-wave radar module are set on the tunnel construction equipment to be located.

[0033] The first determining module is used to determine the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system based on the three-dimensional coordinate information and the dynamic pixel coordinate information.

[0034] The second determining module is used to determine the radar observation equations of the corner reflector and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system.

[0035] The third determination module is used to determine the pose of the tunnel construction equipment to be located based on the radar observation equations.

[0036] Thirdly, this application provides a positioning device for tunnel construction equipment, comprising:

[0037] At least one processor;

[0038] and memory that is communicatively connected to at least one processor;

[0039] The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform a positioning method for tunnel construction equipment as described in the first aspect of the invention.

[0040] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement a positioning method for tunnel construction equipment as described in the first aspect of the invention.

[0041] Fifthly, this application provides a computer program product, including a computer program, which, when executed by a processor, is used to implement a positioning method for tunnel construction equipment as described in the first aspect of the invention.

[0042] This application provides a positioning method, device, equipment, and storage medium for tunnel construction equipment, comprising: acquiring the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be positioned is located; acquiring the dynamic pixel coordinate information of the corner reflectors through the vision module of the tunnel construction equipment to be positioned; determining the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system based on the three-dimensional coordinate information and the dynamic pixel coordinate information; determining the radar observation equation of the corner reflectors and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system; and determining the pose of the tunnel construction equipment to be positioned based on the radar observation equation. Compared to existing tunnel positioning technologies, this application addresses the technical problem that the accuracy of tunnel construction equipment is reduced by dusty environments, and laser light is severely scattered in high-dust environments, shortening its effective range and thus reducing the positioning efficiency. Based on the anti-dust / water mist interference of millimeter-wave radar and high-resolution scene perception through visual fusion, combined with multiple data sources, including corner reflectors, vision modules, and millimeter-wave radar modules, this application achieves improved robustness and accuracy through multi-source data fusion, thereby improving the positioning efficiency of tunnel construction equipment. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 A schematic diagram of a positioning system architecture for tunnel construction equipment provided in an embodiment of this application;

[0045] Figure 2 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 1 ;

[0046] Figure 3 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 2 ;

[0047] Figure 4 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 3 ;

[0048] Figure 5 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 4 ;

[0049] Figure 6 A schematic diagram of the positioning device for tunnel construction equipment provided in this application embodiment;

[0050] Figure 7 This is a structural schematic diagram of a positioning device for tunnel construction equipment provided in an embodiment of this application;

[0051] Figure 8 A schematic diagram of the hardware layout structure of the tunnel construction equipment navigation and positioning device system provided in the embodiments of this application. Detailed Implementation

[0052] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0053] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, nor do they necessarily imply difference. It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0054] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the positioning method for tunnel construction equipment provided in the embodiments of this application is merely an example; the positioning method for tunnel construction equipment may also include more or fewer elements.

[0055] During tunnel construction, construction equipment requires precise navigation and positioning to ensure project quality and construction safety. The tunnel construction environment is complex, with problems such as dust, water mist, and uneven lighting.

[0056] In current positioning technologies, traditional total station positioning methods are greatly affected by dust and light, often resulting in problems such as low positioning accuracy, susceptibility to environmental factors, poor real-time performance, and the need for manual station relocation.

[0057] Optionally, in enclosed environments such as tunnels, the signals of the Global Navigation Satellite System (GNSS) can be easily blocked, rendering satellite navigation unusable.

[0058] Alternatively, laser positioning systems can provide a certain level of positioning accuracy within tunnels, but they are highly dependent on environmental reflectivity and obstacles, and are easily affected by dust and other factors, thus limiting their effectiveness.

[0059] Optionally, inertial navigation systems may accumulate errors due to sensor malfunctions during prolonged use, which can affect positioning accuracy.

[0060] Optionally, with the development of computer vision technology, visual positioning technology has been gradually introduced into the tunnel construction environment. However, cameras in the tunnel environment may be affected by factors such as lighting conditions and dust, which can affect image quality and positioning accuracy.

[0061] Relying solely on camera positioning may yield poor results in low light or high dust conditions. For example, the "semantic segmentation view mapping model" proposed by Qiteng Robotics combines 2D maps with frontal view semantic segmentation to reduce reliance on high-precision textures, but the accuracy of semantic segmentation is still affected in dusty environments. Infrared supplementary lighting can be used, but laser scattering is severe in high dust, shortening the effective range.

[0062] Optionally, current research on millimeter-wave radar mainly focuses on fields such as weaponry and autonomous driving. Research on its use for navigation and positioning in tunnels is still in its early stages. Millimeter-wave radar is mainly used for personnel positioning in tunnels. However, using millimeter-wave radar for positioning may not be accurate enough in some situations. It is mainly used to track the trajectories of engineering vehicles, equipment, and personnel in construction tunnels to prevent mechanical collisions or boundary violations.

[0063] To address the aforementioned problems, the inventors, during their research on the positioning of tunnel construction equipment using synchronous push-and-assemble technology, discovered that the accuracy of existing tunnel positioning technologies is reduced by dusty environments, and that laser scattering is severe in high-dust environments, shortening its effective range and thus reducing the positioning efficiency of tunnel construction equipment. Based on this, the inventors considered a positioning scheme based on millimeter-wave radar's resistance to dust / water mist interference and high-resolution scene perception through visual fusion, combined with multiple data sources, including corner reflectors, visual modules, and millimeter-wave radar modules, to improve robustness and accuracy through multi-source data fusion. Based on this, embodiments of this application provide a positioning method, apparatus, device, and storage medium for tunnel construction equipment, applicable to the field of tunnel positioning, aiming to solve the aforementioned technical problems of the prior art and further effectively improve the positioning efficiency of tunnel construction equipment.

[0064] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0065] Figure 1 This is a schematic diagram of a positioning system architecture for tunnel construction equipment provided in an embodiment of this application. The positioning system for this tunnel construction equipment is a computer device. Figure 1 In the above architecture, at least one of data acquisition device 101, processing device 102 and display device 103 is included.

[0066] It is understood that the structures illustrated in the embodiments of this application do not constitute a specific limitation on the positioning system architecture of tunnel construction equipment. In other feasible embodiments of this application, the above architecture may include more or fewer components than illustrated, or combine some components, or divide some components, or arrange different components, which can be determined according to the actual application scenario and is not limited here. Figure 1 The components shown can be implemented in hardware, software, or a combination of both.

[0067] In the specific implementation process, the data acquisition device 101 may include an input / output interface or a communication interface, and the data acquisition device 101 can be connected to the processing device through the input / output interface or the communication interface.

[0068] The processing device 102 can process the acquired information and determine the position and orientation of the tunnel construction equipment to be located through radar observation equations.

[0069] The display device 103 can also be a touch screen or the screen of a terminal device, used to receive user commands while displaying the above-mentioned content, so as to realize interaction with the user.

[0070] It should be understood that the aforementioned processing device can be implemented by a processor reading instructions from memory and executing those instructions, or it can be implemented by a chip circuit.

[0071] Furthermore, the network architecture and business scenarios described in the embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network architecture and the emergence of new business scenarios, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0072] The technical solution of this application will be described in detail below with reference to specific embodiments:

[0073] Figure 2 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 1 ,like Figure 2 As shown, the method includes:

[0074] S201. Obtain the data source layout information of the tunnel construction equipment to be located.

[0075] The data sources include corner reflectors, vision modules, and millimeter-wave radar modules.

[0076] In one possible embodiment, Figure 8 This is a schematic diagram of the hardware layout structure of the tunnel construction equipment navigation and positioning device system provided in the embodiments of this application, as shown below. Figure 8 As shown, the positioning system mainly includes: millimeter-wave radar 1, camera 2, corner reflector 3, computer 4, cab 5, and trolley 6.

[0077] Optionally, the millimeter-wave radar module - millimeter-wave radar 1 (data source 1) can be installed on the top of the trolley 6 to cover a 120° fan-shaped area on the side and rear, ensuring that it can cover the key area around the construction equipment while avoiding interference from the construction equipment itself.

[0078] Specifically, the millimeter-wave radar module is directly fixed to the trolley 6 or the equipment vehicle structure to ensure a rigid connection with the vehicle body. Its antenna points towards the pre-set array of corner reflectors 3 on the tunnel sidewall or arch, and is responsible for transmitting millimeter waves and receiving strong reflected signals.

[0079] Optionally, the vision module - camera 2 (data source 2) is installed in a position where clear images can be obtained. Considering the lighting conditions and construction environment inside the tunnel, a wide-angle lens and a supplementary light are provided to acquire environmental red-green-blue three-channel images (RGB).

[0080] Specifically, the vision module, also known as the industrial camera module, is mounted on a gimbal or fixed bracket and is rigidly connected to the millimeter-wave radar module or its precise relative pose is determined through calibration.

[0081] Optionally, corner reflectors 3 (together with the millimeter-wave radar module, jointly acquiring data from data source 1 and data source 2) are arranged at suitable locations within the tunnel, with a group (3-4) arranged every 20m along the tunnel axis, ensuring that at least 3 are visible and in fixed positions, and that they are in line of sight with millimeter-wave radar 1 and camera 2.

[0082] In addition, the data acquisition unit has a built-in high-precision clock source to strictly synchronize the data acquisition of millimeter-wave radar 1 and the exposure time of camera 2, ensuring that radar distance / angle data and camera images are acquired at the same time.

[0083] Optionally, the computer 4-control module can be installed in the control room or operating room of the construction equipment for easy monitoring and adjustment by operators.

[0084] S202. Obtain the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located.

[0085] For example, three-dimensional coordinate measurement: using a total station to perform three-dimensional coordinate measurement on each corner reflector, recording its x, y, and z coordinate values, denoted as P. i .

[0086] S203. Obtain the dynamic pixel coordinate information of the corner reflector through the vision module of the tunnel construction equipment to be located.

[0087] The tunnel construction equipment's vision module and millimeter-wave radar module are installed together on the tunnel construction equipment to be located.

[0088] For example, to obtain pixel coordinates: use a camera to photograph these corner reflectors and record their pixel positions (u, v) in the image:

[0089]

[0090] Where u is the horizontal pixel coordinate of the corner reflector in the image, representing the position information of the corner reflector from left to right.

[0091] Where v is the vertical pixel coordinate of the corner reflector in the image, representing the position information of the corner reflector from top to bottom.

[0092] Where i is the corner reflector number, used to distinguish and identify different corner reflectors in the image, and each corner reflector has a unique number.

[0093] S204. Based on the three-dimensional coordinate information and dynamic pixel coordinate information, determine the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system.

[0094] In this embodiment, by measuring the positions of multiple corner reflectors, a transformation matrix between sensors is calculated and established, including rotation and translation components, to calibrate the intrinsic and extrinsic parameters of the camera and establish the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system.

[0095] First, using rotation and translation operations, points in 3D space are transformed from the world coordinate system to the camera coordinate system:

[0096]

[0097] Here, R is the rotation matrix from the world coordinate system to the camera coordinate system.

[0098] Specifically, the rotation matrix is: R = R(z) * R(y) * R(x).

[0099] More specifically, the rotation matrix is ​​determined according to the rotation direction specified by the camera's external parameter timing, and is a 3×3 matrix.

[0100] Where t is the translation matrix from the origin of the world coordinate system to the origin of the camera coordinate system, which is a 3×1 matrix.

[0101] Secondly, a transformation from the camera coordinate system to the image coordinate system is performed. This transformation involves perspective projection, and the conversion from 3D to 2D requires satisfying the similarity theorem of triangles, based on proportional relationships:

[0102]

[0103] Where f represents the focal length.

[0104] Furthermore, this can be written in matrix form as follows:

[0105]

[0106] Secondly, the transformation from the image coordinate system to the pixel coordinate system involves no rotation transformation, only scaling and translation transformations. The coordinate transformation equations are:

[0107]

[0108] Where, d x d yThe scaling factor is represented by u0 and v0, which represent the positions of the origin of the image coordinate system in the pixel coordinate system.

[0109] Furthermore, convert it to matrix form to complete the transformation from the image coordinate system to the pixel coordinate system:

[0110]

[0111] Finally, the relationship between pixel coordinates and the world coordinate system is shown below:

[0112]

[0113] Where f represents the focal length; d x = Sensor lateral dimension / resolution w, unit is mm / pixel; d y = Sensor longitudinal dimension resolution / resolution h.

[0114] Specifically, based on the world coordinates of four known points and the camera's intrinsic parameters, the camera's exterior orientation elements, i.e., the camera pose, can be determined.

[0115] S205. Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, determine the radar observation equations for the corner reflector and the millimeter-wave radar module.

[0116] Specifically, determine the physical measurement information of the millimeter-wave radar module.

[0117] The physical measurement information includes the radial distance, horizontal azimuth, and pitch angle of the collected corner reflector.

[0118] Specifically, based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, as well as physical measurement information, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined.

[0119] It should be noted that combining the precise distance measurement of radar with visual information from images improves the accuracy of target detection, especially in low light or adverse weather conditions. Coordinate system transformation enables data alignment between radar and cameras, supporting functions such as environmental perception and path planning in autonomous driving, and achieving multi-sensor collaboration. The strong echo characteristics of corner reflectors enhance target recognizability, reduce false alarms and missed detections, and improve system reliability and anti-interference capabilities.

[0120] S206. Determine the position and orientation of the tunnel construction equipment to be located based on the radar observation equation.

[0121] This embodiment provides a positioning method for tunnel construction equipment, comprising: acquiring the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be positioned is located; acquiring the dynamic pixel coordinate information of the corner reflectors through the vision module of the tunnel construction equipment to be positioned; determining the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system based on the three-dimensional coordinate information and the dynamic pixel coordinate information; determining the radar observation equation of the corner reflectors and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system; and determining the pose of the tunnel construction equipment to be positioned based on the radar observation equation. Compared to existing tunnel positioning technologies, this method addresses the technical problem that the accuracy of tunnel construction equipment is reduced by dusty environments, and laser light is severely scattered in high-dust environments, shortening its effective range and thus reducing the positioning efficiency. This application is based on a positioning scheme that combines millimeter-wave radar's anti-dust / water mist interference and high-resolution scene perception through visual fusion with multiple data sources, including corner reflectors, vision modules, and millimeter-wave radar modules. This achieves improved robustness and accuracy through multi-source data fusion, thereby improving the positioning efficiency of tunnel construction equipment.

[0122] Figure 3 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 2 ,like Figure 3 As shown, the specific implementation steps of S206 above include:

[0123] S301. Acquire the physical measurement information collected from multiple corner reflectors corresponding to the millimeter-wave radar module.

[0124] S302. Based on the collected physical measurement information and radar observation equations, the position and orientation of the tunnel construction equipment to be located are calculated.

[0125] For example, a radar observation equation can be established between each corner reflector and the millimeter-wave radar. Therefore, when the radar observes i targets simultaneously, i radar observation equations can be established. When the number of observed targets i ≥ 3, the position of the millimeter-wave radar can be calculated using the resection algorithm. The three-dimensional position of the millimeter-wave radar is calculated, thereby obtaining the vehicle's pose.

[0126] Furthermore, suppose we have multiple corner reflectors, and the position of each corner reflector is known as P. i =(x i ,y i ,z i The location of the millimeter-wave radar is R = (x r ,y r ,z r According to the distance measurement formula, the distance d i It can be represented as:

[0127] Furthermore, assume the approximate coordinates of the millimeter-wave radar are (x... r0 ,y r0 ,z r0 The coordinates of the i-th corner reflector are (x... i ,y i ,z i ), and in (x r0 ,y r0 ,z r0 Expanding the first-order Taylor series at position ) gives:

[0128]

[0129] Among them, V x V y V z These are the coordinate increments in the x, y, and z directions, respectively.

[0130] Specifically, when the radar observes i targets simultaneously, i observation equations can be derived from the above formula. Based on the least squares principle, the three-dimensional position of the millimeter-wave radar can be calculated.

[0131] It should be noted that combining measurements from multiple corner reflectors enhances positioning accuracy through redundant data, performing exceptionally well, especially in complex geometric layouts. The millimeter-wave radar operates stably in harsh environments such as low light and dust, and the strong echo characteristics of the corner reflectors ensure data reliability and improve anti-interference capabilities. Filtering algorithms suppress measurement noise, reducing the impact of single-point failures and improving overall system stability. Real-time pose feedback supports automated construction, reducing manual intervention and shortening the construction period.

[0132] In this embodiment, the pose of the tunnel construction equipment to be located is calculated based on the collected physical measurement information and radar observation equations. By combining a polygonal reflector with an advanced filtering algorithm, high-precision and robust positioning of the tunnel construction equipment is achieved, effectively solving the problem of GPS failure in underground environments. This improves positioning accuracy, environmental adaptability, and engineering practicality, thereby increasing the positioning efficiency of the tunnel construction equipment.

[0133] Figure 4 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 3 ,like Figure 4 As shown, after step S206 above, the following steps are also included:

[0134] S401. If the tunnel construction equipment to be positioned is stopped.

[0135] S402. Based on the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, determine the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module.

[0136] Specifically, when the trolley is stationary and dust levels are low, the camera takes real-time photos of the corner reflectors. Coordinate transformation is then used to determine the coordinates of the camera and the trolley. If a new corner reflector needs to be added, the camera's positioning attitude is obtained using information from other corner reflectors with known coordinates. Finally, the spatial coordinates of the newly deployed corner reflector are calculated using the camera's positioning information.

[0137] For example, assuming the camera's position and orientation are known, the position of the new corner reflector can be calculated through coordinate transformation. Let the position of the new corner reflector in the local coordinate system be P. new x′ = (x′, y′, z′), transform to global coordinate system: P new =R+TP new ′.

[0138] Where T is a rotation matrix composed of Euler angles.

[0139] It should be noted that high-precision positioning is achieved by eliminating single-sensor errors through multi-sensor data fusion. In a stationary state, there is no need to process dynamic noise, simplifying the algorithm and improving computational efficiency. Specifically, the vision module provides high-resolution pixel coordinates, suitable for fine-grained close-range positioning. The millimeter-wave radar operates stably in harsh environments (such as dust and low light), providing long-range, wide-area distance and angle information. The data from both modules complement each other, enhancing system robustness.

[0140] In this embodiment, based on the stationary state, the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module are determined according to the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system. By fusing the static pixel coordinate information with the millimeter-wave radar data, high-precision and robust static positioning of the tunnel construction equipment is achieved. This improves positioning accuracy, environmental adaptability, and engineering practicality, thereby increasing the positioning efficiency of the tunnel construction equipment.

[0141] Figure 5 A flowchart illustrating a positioning method for tunnel construction equipment provided in this application embodiment. Figure 4 ,like Figure 5 As shown, the procedure following step S402 includes:

[0142] S501. Obtain the third static three-dimensional coordinate information of all corner reflectors in the area.

[0143] S502. Determine the positioning posture of the vision module based on the third static three-dimensional coordinate information.

[0144] S503. Based on the positioning posture of the vision module and the second static three-dimensional coordinate information, identify the fourth static three-dimensional coordinate information of the newly added corner reflector.

[0145] S504. Based on the millimeter-wave radar module, obtain the distance information of the newly added corner reflector and the corner reflectors in the area.

[0146] S505. Based on the distance information, the third static three-dimensional coordinate information, and the fourth static three-dimensional coordinate information, update the radar observation equations of the corner reflector and the millimeter-wave radar module.

[0147] For example, the radar measures the distances to the new and existing corner reflectors. Based on the corner reflector coordinates, the radar coordinates can be obtained in real time. The pose is then optimized using the Perspective-n-Point Algorithm (PnP) to calculate the coordinates of the new corner reflector. Finally, an Extended Kalman Filter (EKF) is used to fuse the millimeter-wave radar and visual data. The specific fusion process is as follows:

[0148] First, the dynamic operation phase is integrated.

[0149] Optional, radar-dominated, real-time measurement of the change in corner reflector distance (Δd) by millimeter-wave radar.

[0150] Optional, visual aids, low-frequency visual feature points (such as blurred outlines of corner reflectors), are used for anomaly detection.

[0151] Furthermore, the motion model is constructed based on radar Δd data, and an extended Kalman filter (EKF) is used to build the trolley motion model to predict the pose at the next moment (state vector: position x, y, z, yaw angle θ).

[0152] If the radar experiences a sudden change in Δd for N consecutive frames (e.g., exceeding the 3σ statistical range), it is identified as radar noise and its weight is temporarily reduced.

[0153] If the radar does not have consecutive N frames of Δd abrupt change, the radar motion model is corrected in reverse by the visual offset, and the EKF observation matrix is ​​updated.

[0154] Then, the static phase merges.

[0155] Optional, vision-driven: The camera calculates high-precision pose (position error ±1cm, attitude angle error ±0.5°) using the PnP algorithm.

[0156] Optional, radar-assisted: the reference value for radar ranging in a stationary state.

[0157] Furthermore, the initial visual pose solution is as follows: based on the known 3D coordinates of the corner reflector and the 2D pixel coordinates of the image, the EPnP algorithm is used to solve the camera pose (outputting 6DoF parameters).

[0158] Furthermore, radar range constraints: The current absolute distance of the corner reflector measured by the radar (calibration reference value ± Δd) is used as the range constraint condition to construct a constrained least squares optimization problem.

[0159] Furthermore, the visual pose calculation results are optimized by spatially clustering the radar point cloud (distance information) and visual feature points (coordinate information) to remove outliers (such as dynamic obstacles).

[0160] It should be noted that the fusion of visual and radar data eliminates single-sensor errors, achieving high-precision positioning. Even when visual sensors fail in low light, radar can still provide reliable data, ensuring continuous system operation. New corner reflectors are quickly identified via visual sensors, and seamless expansion is achieved by integrating them with the existing coordinate system. New equipment is calibrated using known reflector coordinates to avoid misidentification and improve system flexibility. The observation equations are continuously optimized using radar ranging data to correct parameter drift and maintain model accuracy. The least squares method ensures that the coordinates of new reflectors are consistent with measurements, reducing long-term operational errors.

[0161] In this embodiment, multi-sensor fusion improves robust positioning, significantly enhancing the positioning capability and environmental adaptability of tunnel construction equipment. It also improves accuracy, reliability, efficiency, and cost, further increasing the positioning efficiency of the tunnel construction equipment.

[0162] This application also provides a possible embodiment, which provides an in-vehicle integrated sensing terminal device that integrates modules such as a millimeter-wave radar sensing unit, a high-resolution visual sensing unit, and a data processing core unit.

[0163] The millimeter-wave radar module is directly fixed to the trolley or equipment vehicle structure to ensure a rigid connection with the vehicle body. Its antenna points towards the pre-set corner reflector array on the tunnel sidewall or arch, and is responsible for transmitting millimeter waves and receiving strong reflected signals.

[0164] The industrial camera module is mounted on a gimbal or fixed bracket and is rigidly connected to the millimeter-wave radar module or its precise relative pose is determined through calibration.

[0165] The data acquisition unit has a built-in high-precision clock source to strictly synchronize the data acquisition of the millimeter-wave radar with the exposure time of the camera, ensuring that radar distance / angle data and camera images are acquired at the same time.

[0166] Specifically, the operation process of this vehicle-mounted integrated sensing terminal device is not described below:

[0167] First, perform sensor spatial calibration. Before the equipment leaves the factory, complete the spatial calibration of multi-source sensors and establish the transformation relationship between the millimeter-wave radar coordinate system, the camera coordinate system and the vehicle body.

[0168] Specifically, the coordinates of multiple target points, cameras, and radar installed on the trolley are accurately measured using a total station; the camera is simultaneously triggered to capture images to obtain the pixel coordinates of the target points, while radar ranging data is collected at the same time; and a kinematic mapping model of the sensor-trolley system is established by combining coordinate system transformation algorithms.

[0169] Secondly, on-site positioning and implementation were carried out.

[0170] Specifically, millimeter-wave radar positioning: by scanning the corner reflectors pre-set at the construction site in real time, the radar body is located based on the resection algorithm, and the distance change from the radar to the corner reflectors during the tunneling process is continuously monitored to establish a dynamic displacement trajectory.

[0171] Specifically, visual positioning: when the equipment stops and the dust concentration decreases, the camera is triggered to capture environmental images. The known corner reflector pixel coordinates are identified through feature matching technology. Combined with real-time distance change information provided by millimeter-wave radar, the improved PnP algorithm is used to calculate the camera pose.

[0172] More specifically, in this process, the change in radar distance is used as a constraint condition and substituted into the pose calculation equation to reduce the distance error in visual calculation.

[0173] Specifically, dynamic coordinate updates: when the equipment is in operation, millimeter-wave radar is used to locate the vehicle's coordinates in high-dust environments; when the equipment stops, the vehicle's coordinates are determined based on the camera's pose.

[0174] More specifically, for newly added corner reflectors during construction, the two-dimensional image coordinates captured by the camera are used, combined with the radar ranging reference value and dynamic changes, and the three-dimensional coordinates of the target are reconstructed through an inverse perspective transformation fusion algorithm to achieve dynamic expansion of the new positioning reference.

[0175] Finally, multi-source data fusion is performed to construct a spatiotemporal registration framework to achieve the fusion of millimeter-wave radar and visual data. During dynamic operations, the motion model is constructed based on the change in radar distance, while in the static state, the visual pose calculation is the core. The sensor weights are dynamically allocated through a Kalman filter, and an adaptive weighted fusion algorithm is adopted to improve positioning accuracy.

[0176] In this embodiment, innovative technologies such as multi-sensor deep fusion, dynamic positioning switching, and adaptive calibration are used to achieve high-precision and robust positioning of tunnel construction equipment in harsh environments. This improves positioning accuracy, environmental adaptability, system scalability, and construction efficiency in multiple dimensions.

[0177] Figure 6 This is a schematic diagram of the positioning device for tunnel construction equipment provided in the embodiments of this application, as shown below. Figure 6 As shown, the device includes: a first acquisition module 61, a second acquisition module 62, a first determination module 63, a second determination module 64, and a third determination module 65.

[0178] The first acquisition module 61 is used to acquire the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located;

[0179] The second acquisition module 62 is used to acquire the dynamic pixel coordinate information of the corner reflector through the vision module of the tunnel construction equipment to be located; wherein, the tunnel construction equipment vision module and the millimeter-wave radar module are set on the tunnel construction equipment to be located in conjunction.

[0180] The first determining module 63 is used to determine the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system based on the three-dimensional coordinate information and the dynamic pixel coordinate information.

[0181] The second determining module 64 is used to determine the radar observation equations of the corner reflector and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system.

[0182] The third determining module 65 is used to determine the position and orientation of the tunnel construction equipment to be located based on the radar observation equation.

[0183] In one possible design, based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined, including:

[0184] The second determining module 64 is also used to determine the physical measurement information of the millimeter-wave radar module; wherein, the physical measurement information includes the radial distance, horizontal azimuth angle and elevation angle of the acquired corner reflector;

[0185] Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, as well as physical measurement information, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined.

[0186] In one possible design, the pose of the tunnel construction equipment to be located is determined according to the radar observation equations, including:

[0187] The third determining module 65 is also used to acquire the collected values ​​of physical measurement information of multiple corner reflectors corresponding to the millimeter-wave radar module;

[0188] The position and orientation of the tunnel construction equipment to be located are calculated based on the collected physical measurement information and the radar observation equation.

[0189] One possible design also includes:

[0190] If the tunnel construction equipment to be located is stationary, the static pixel coordinate information of multiple corner reflectors is obtained through the vision module.

[0191] Based on the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module are determined.

[0192] In one possible design, after determining the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module based on static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the design further includes:

[0193] Obtain the third static three-dimensional coordinate information of all corner reflectors in the area;

[0194] The positioning posture of the vision module is determined based on the third static three-dimensional coordinate information.

[0195] Based on the positioning posture of the vision module and the second static three-dimensional coordinate information, the fourth static three-dimensional coordinate information of the newly added corner reflector is identified.

[0196] In one possible design, after identifying the fourth static three-dimensional coordinate information of the newly added corner reflector based on the positioning pose of the vision module and the second static three-dimensional coordinate information, the following steps are also included:

[0197] Based on the millimeter-wave radar module, obtain the distance information of the newly added corner reflector and the corner reflectors in the area;

[0198] Based on the distance information, the third static three-dimensional coordinate information, and the fourth static three-dimensional coordinate information, update the radar observation equations for the corner reflector and the millimeter-wave radar module.

[0199] In one possible design, before obtaining the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located, the following steps are also included:

[0200] Obtain the layout information of the data sources for the tunnel construction equipment to be located; the data sources include corner reflectors, vision modules, and millimeter-wave radar modules.

[0201] The positioning device for tunnel construction equipment provided in this embodiment can perform the positioning method for tunnel construction equipment in the above embodiment. Its implementation principle and technical effect are similar, and will not be described again here.

[0202] In the specific implementation of the aforementioned positioning method for tunnel construction equipment, each module can be implemented as a processor. The processor can execute computer execution instructions stored in the memory, thereby enabling the processor to execute the aforementioned positioning method for tunnel construction equipment.

[0203] Figure 7 This is a structural schematic diagram of a positioning device for tunnel construction equipment provided in an embodiment of this application. Figure 7 As shown, the positioning device 70 of the tunnel construction equipment includes at least one processor 71 and a memory 72. The positioning device 70 of the tunnel construction equipment also includes a communication component 73. The processor 71, the memory 72, and the communication component 73 are connected via a second bus 74.

[0204] In the specific implementation process, at least one processor 71 executes computer execution instructions stored in memory 72, causing at least one processor 71 to execute a positioning method for tunnel construction equipment as described above.

[0205] The specific implementation process of processor 71 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0206] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0207] The memory may include high-speed RAM, and may also include non-volatile storage (NVM), such as at least one disk storage.

[0208] The second bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0209] The above description of the functions implemented by the positioning device and main control device of tunnel construction equipment illustrates the solution provided by the embodiments of the present invention. It is understood that, in order to achieve the above functions, the positioning device or main control device of the tunnel construction equipment includes hardware structures and / or software modules corresponding to the execution of each function. By combining the units and algorithm steps of the various examples described in the embodiments of the present invention, the embodiments of the present invention can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the technical solution of the embodiments of the present invention.

[0210] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the positioning method for tunnel construction equipment described above.

[0211] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0212] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Alternatively, the readable storage medium can be an integral part of the processor. The processor and the readable storage medium can reside in application-specific integrated circuits (ASICs). Alternatively, the processor and the readable storage medium can exist as discrete components in the positioning device or main control device of tunnel construction equipment.

[0213] This application also provides a computer program product, comprising: a computer program stored in a readable storage medium, wherein at least one processor of the positioning device of the tunnel construction equipment can read the computer program from the readable storage medium, and the at least one processor executes the computer program to cause the positioning device of the tunnel construction equipment to perform the scheme provided in any of the above embodiments.

[0214] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disk, or optical disk.

[0215] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A positioning method for tunnel construction equipment, characterized in that, include: Obtain the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located; The dynamic pixel coordinate information of the corner reflector is obtained through the vision module of the tunnel construction equipment to be located; wherein, the vision module of the tunnel construction equipment is set on the tunnel construction equipment to be located in cooperation with the millimeter-wave radar module. Based on the three-dimensional coordinate information and the dynamic pixel coordinate information, the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system is determined; Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined. The position and orientation of the tunnel construction equipment to be located are determined based on the radar observation equation.

2. The method according to claim 1, characterized in that, The step of determining the radar observation equations for the corner reflector and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system includes: Determine the physical measurement information of the millimeter-wave radar module; wherein, the physical measurement information includes the radial distance, horizontal azimuth angle, and elevation angle of the corner reflector; Based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, as well as the physical measurement information, the radar observation equations for the corner reflector and the millimeter-wave radar module are determined.

3. The method according to claim 2, characterized in that, Determining the pose of the tunnel construction equipment to be located based on the radar observation equation includes: Acquire the collected values ​​of the physical measurement information of the multiple corner reflectors corresponding to the millimeter-wave radar module; The position and orientation of the tunnel construction equipment to be located are calculated based on the collected physical measurement information and the radar observation equation.

4. The method according to any one of claims 1 to 3, characterized in that, Also includes: If the tunnel construction equipment to be located is in a stopped state, the static pixel coordinate information of the multiple corner reflectors is obtained through the vision module. Based on the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module are determined.

5. The method according to claim 4, characterized in that, After determining the first static three-dimensional coordinate information of the tunnel construction equipment to be located and the second static three-dimensional coordinate information of the vision module based on the static pixel coordinate information and the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system, the method further includes: Obtain the third static three-dimensional coordinate information of all corner reflectors in the area; The positioning posture of the vision module is determined based on the third static three-dimensional coordinate information. Based on the positioning posture of the vision module and the second static three-dimensional coordinate information, the fourth static three-dimensional coordinate information of the newly added corner reflector is identified.

6. The method according to claim 5, characterized in that, After identifying the fourth static three-dimensional coordinate information of the newly added corner reflector based on the positioning posture of the vision module and the second static three-dimensional coordinate information, the method further includes: Based on the millimeter-wave radar module, the distance information between the newly added corner reflector and the corner reflector in the area is obtained; The radar observation equations of the corner reflector and the millimeter-wave radar module are updated based on the distance information, the third static three-dimensional coordinate information, and the fourth static three-dimensional coordinate information.

7. The method according to any one of claims 1 to 3, characterized in that, Before obtaining the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located, the method further includes: The layout information of the data source of the tunnel construction equipment to be located is obtained; wherein, the data source includes a corner reflector, a vision module and a millimeter-wave radar module.

8. A positioning device for tunnel construction equipment, characterized in that, The device includes: The first acquisition module is used to acquire the three-dimensional coordinate information of multiple corner reflectors in the area where the tunnel construction equipment to be located is located; The second acquisition module is used to acquire the dynamic pixel coordinate information of the corner reflector through the vision module of the tunnel construction equipment to be located; wherein, the tunnel construction equipment vision module and the millimeter-wave radar module are installed on the tunnel construction equipment to be located. The first determining module is used to determine the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system based on the three-dimensional coordinate information and the dynamic pixel coordinate information. The second determining module is used to determine the radar observation equations of the corner reflector and the millimeter-wave radar module based on the transformation relationship between the millimeter-wave radar coordinate system and the image pixel coordinate system. The third determining module is used to determine the pose of the tunnel construction equipment to be located based on the radar observation equation.

9. A positioning device for tunnel construction equipment, characterized in that, include: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores instructions that can be executed by the at least one processor, which are executed by the at least one processor to enable the at least one processor to perform the positioning method of the tunnel construction equipment as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the positioning method for tunnel construction equipment as described in any one of claims 1 to 7.

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