Method and system for realizing intelligent positioning of tools in three-dimensional space based on two-dimensional images

Abstract

This invention relates to a method and system for intelligent positioning of tools in three-dimensional space based on two-dimensional images. The specific steps include: attaching a uniquely identifiable barcode to a prominent position on the front of each tool; installing several cameras at different angles in a tool storage room, each facing a wall where the tools are placed, and acquiring real-time images of the tool storage room through the cameras; selecting each tool in the real-time images and simultaneously recording the set of planar coordinate points of each tool in each two-dimensional image; extracting feature data and feature points from the surface of each tool in the two-dimensional images using a preset algorithm, and binding the feature data, coordinate point set, and feature points of each tool with the uniquely identified barcode of the corresponding tool; and, when searching for a tool, performing three-dimensional reconstruction of the target tool based on its feature points, coordinate point set, feature data, and the calibration parameters of the corresponding angle camera on the wall.

Description

Technical Field

[0001] This invention relates to the field of power system safety equipment management technology, specifically to a method and system for intelligent positioning of tools in three-dimensional space based on two-dimensional images. Background Technology

[0002] Safety tools and equipment are essential for the lives of power system workers; therefore, their storage and management are of paramount importance. Traditional methods of managing safety tools and equipment have numerous problems.

[0003] Traditional warehouse management typically requires manual inventory checks, which is time-consuming and prone to errors.

[0004] Unclear locations of tools and equipment can make accurate tracking difficult, especially in large warehouses. These issues not only impact work efficiency but also pose potential safety hazards to power production. To address these problems, the positional relationships of multiple cameras and the tool's location information in two-dimensional images are used. Through triangulation or other three-dimensional reconstruction methods, the precise location of each tool in three-dimensional space is calculated, allowing users to quickly retrieve and return the tools.

[0005] Currently, safety tools and equipment are managed using RFID tagging, which is mainly used for the management of all safety tools and equipment entering and leaving the warehouse. RFID tags are affixed to the safety tools and equipment to determine whether they are in the warehouse.

[0006] The existing technology CN112036532A, "An Intelligent Power Safety Tool Management System and Method," discloses a method that transmits radio frequency signals to RFID tags via shelf antennas and access control antennas. The distance between the RFID tag and the shelf antenna and access control antenna is obtained based on the wireless signal strength value fed back by the RFID tag. This distance is then used to determine the registration status of the borrowing or returning of tools, thus accurately determining the entry and exit status of tools. However, while this existing technology uses RFID tags for managing the entry and exit of safety tools, the actual location within the warehouse is not precise, affecting work efficiency and posing potential safety hazards to power production. Summary of the Invention

[0007] To address the problems existing in the prior art, this invention proposes a method and system for intelligent positioning of tools in three-dimensional space using two-dimensional images.

[0008] The technical solution of the present invention is as follows:

[0009] On the one hand, this invention proposes a method for intelligent positioning of tools in three-dimensional space based on two-dimensional images, the specific steps of which include:

[0010] A unique, identifiable barcode is attached to a prominent location on the front of each tool.

[0011] Several cameras at different angles are installed in the tool and equipment warehouse, facing each wall where the tools and equipment are placed. The cameras capture real-time images of the tool and equipment warehouse, and each tool and equipment in the real-time images is selected. At the same time, the set of planar coordinate points of each tool and equipment in each two-dimensional image is recorded.

[0012] The feature data and feature points of each tool surface in the two-dimensional image are extracted using a preset algorithm, and the feature data, coordinate point set and feature points of each tool are bound to the unique identification barcode of the corresponding tool.

[0013] When locating tools, the target tools are reconstructed in three dimensions based on their feature points, coordinate point set, feature data, and the calibration parameters of the corresponding angle camera on the wall surface. The three-dimensional point cloud data of the target tools is then obtained to determine their precise location in three-dimensional space.

[0014] When returning tools and equipment, the camera on the wall where the target tool or equipment is located scans the barcode on the surface of all tools and equipment on the wall, reads all the feature points, and compares them with the feature points of the target tool or equipment to confirm whether the tool or equipment has been returned.

[0015] In a preferred embodiment, the feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

[0016] In a preferred embodiment, the step of performing three-dimensional reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface is specifically as follows:

[0017] First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows:

[0018] [[u, v] = P[X, Y, Z]]

[0019] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix;

[0020] After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

[0021] In a preferred embodiment, the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm involves constructing a mathematical model using the preset algorithm. Specifically, this mathematical model is as follows:

[0022]

[0023] In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

[0024] On the other hand, this invention proposes a system for intelligent positioning of tools in three-dimensional space based on two-dimensional images, comprising:

[0025] The tool coding module adds a unique, identifiable barcode to a prominent position on the front of each tool.

[0026] The tool and equipment plane coordinate extraction module installs several cameras at different angles in the tool and equipment warehouse, which are respectively facing the walls of the warehouse where the tools and equipment are placed. The module obtains real-time images of the tool and equipment warehouse through the cameras, selects each tool and equipment in the real-time images, and records the set of plane coordinate points of each tool and equipment in each two-dimensional image.

[0027] The tool feature binding module uses a preset algorithm to extract feature data and feature points from the surface of each tool in the two-dimensional image, and binds the feature data, coordinate point set and feature points of each tool with the unique identification barcode of the corresponding tool.

[0028] The tool and equipment outbound positioning module, when searching for tools and equipment, performs three-dimensional reconstruction of the target tools and equipment based on the feature points, coordinate point set, feature data, and calibration parameters of the corresponding angle camera on the wall surface where the target tools and equipment are located, and obtains the three-dimensional point cloud data of the target tools and equipment to determine the precise position of the target tools and equipment in three-dimensional space.

[0029] The tool and equipment warehousing module scans the barcodes on the surfaces of all tools and equipment on the wall corresponding to the target tool and equipment when the tool and equipment are returned. It reads all the feature points and compares them with the feature points of the target tool and equipment to confirm whether the tool and equipment has been returned.

[0030] In a preferred embodiment, the feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

[0031] In a preferred embodiment, the step of performing three-dimensional reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface is specifically as follows:

[0032] First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows:

[0033] [[u, v] = P[X, Y, Z]]

[0034] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix;

[0035] After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

[0036] In a preferred embodiment, the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm involves constructing a mathematical model using the preset algorithm. Specifically, this mathematical model is as follows:

[0037]

[0038] In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

[0039] On the other hand, the present invention proposes an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method for intelligent positioning of tools in three-dimensional space based on two-dimensional images as described in any embodiment of the present invention.

[0040] On the other hand, the present invention proposes a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for intelligent positioning of tools in three-dimensional space based on two-dimensional images as described in any embodiment of the present invention.

[0041] The present invention has the following beneficial effects:

[0042] 1. This invention, through the positional relationship of multiple cameras and a three-dimensional reconstruction method, enables accurate position estimation of tools in three-dimensional space, thereby improving the accuracy of position positioning and tracking efficiency.

[0043] 2. By extracting the feature data of each tool in the warehouse, the present invention can accurately construct the model of the tool, realize the identification and positioning of the tool, thereby improving the efficiency and accuracy of warehouse management.

[0044] 3. Compared with traditional methods, the present invention can quickly and accurately locate tools and equipment, reducing the time required for inventory and searching for tools and equipment, and improving work efficiency.

[0045] 4. This invention, through effective tool management and tracking, can provide better safety guarantees for power system workers and reduce work risks. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the steps of the present invention. Detailed Implementation

[0047] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0048] It should be understood that the step numbers used in the text are for ease of description only and are not intended to limit the order in which the steps are performed.

[0049] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0050] The terms “comprising” and “including” indicate the presence of the described feature, whole, step, operation, element and / or component, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or collections thereof.

[0051] The term “and / or” refers to any combination of one or more of the associated listed items, as well as all possible combinations, and includes these combinations.

[0052] Example 1:

[0053] See Figure 1 A method for intelligent positioning of tools in three-dimensional space based on two-dimensional images, the specific steps of which include:

[0054] Step 1: Attach a unique, identifiable barcode to a prominent location on the front of each tool.

[0055] In this embodiment, the identification barcode is attached to a prominent position on each tool and implement without obscuring the main structure of the tool and implement.

[0056] Step 2: Install several cameras at different angles in the tool and equipment warehouse, facing each wall where the tools and equipment are placed. Use the cameras to capture real-time images of the tool and equipment warehouse, select each tool and equipment in the real-time images, and record the set of planar coordinate points of each tool and equipment in each two-dimensional image.

[0057] In this embodiment, multiple cameras are used to identify different tools on each wall, and each tool in the image is manually selected to ensure that there is no overlap. Then, the coordinate points of the outline of each tool in the two-dimensional image are recorded.

[0058] Step 3: Use a preset algorithm to extract feature data and feature points from the surface of each tool in the 2D image, and bind the feature data, coordinate point set and feature points of each tool with the unique identification barcode of the corresponding tool.

[0059] In this embodiment, feature data is extracted according to the following algorithm:

[0060] Edge detection algorithms: Edge detection is a commonly used image processing technique used to detect the contours of objects. Commonly used edge detection algorithms include the Sobel operator and Canny edge detection.

[0061] Color space conversion: Converting an image from the RGB color space to other color spaces (such as HSV, Lab, etc.) can improve the extraction of color information. For example, thresholding techniques can be used to extract the color information of objects in a color space.

[0062] Texture feature extraction: Texture describes the spatial arrangement and color variation of pixels in an image. Commonly used texture feature extraction methods include Gray-Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP).

[0063] Feature matching algorithms are used to find similar regions or feature points in an image. Commonly used feature matching algorithms include SIFT, SURF, and ORB.

[0064] Deep learning methods: Using deep learning techniques, such as convolutional neural networks (CNNs), image features, including contours, colors, and textures, can be learned end-to-end.

[0065] By combining the above algorithms and techniques, feature data of the surfaces of various tools in a two-dimensional image can be extracted and used for subsequent analysis and processing.

[0066] Step 4: When searching for tools, based on the feature points, coordinate point set, feature data, and calibration parameters of the corresponding angle camera on the wall surface where the target tool is located, perform 3D reconstruction of the target tool and obtain the 3D point cloud data of the target tool to determine the precise position of the target tool in 3D space.

[0067] In this embodiment, the three-dimensional coordinates of the target tool's feature points can be determined based on the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall. Then, based on the three-dimensional coordinates, combined with the feature data and planar coordinates of the target tool, the model of the target tool in three-dimensional space is reconstructed, thereby determining the accurate location of the target tool in the warehouse.

[0068] Step 5: When returning the tools, scan the barcodes on the surfaces of all tools on the wall corresponding to the target tool using the camera, read all feature points, and compare them with the feature points of the target tool to confirm whether the tool has been returned.

[0069] In this embodiment, when tools are put back into storage after use, the system can confirm whether tools that have been taken out of the warehouse have been returned simply by using a camera to identify the barcodes of all tools in the warehouse.

[0070] In a preferred embodiment of this invention, the feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

[0071] In this embodiment, in addition to the outline, texture, color, and size of the tools mentioned above, all other data that can represent the surface features of the tools can also be used as feature data.

[0072] In a preferred embodiment of this invention, the step of performing three-dimensional reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface is as follows:

[0073] First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows:

[0074] [[u, v] = P[X, Y, z]]

[0075] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix;

[0076] After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

[0077] In a preferred embodiment of this invention, the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm involves constructing a mathematical model using the preset algorithm. This mathematical model is specifically as follows:

[0078]

[0079] In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

[0080] Example 2:

[0081] A system for intelligent positioning of tools in three-dimensional space based on two-dimensional images includes:

[0082] The tool coding module attaches a unique, identifiable barcode to a prominent position on the front of each tool; this module is used to implement the function of step one in embodiment one, and will not be described in detail here.

[0083] The tool and equipment plane coordinate extraction module is installed in the tool and equipment warehouse with several cameras at different angles facing the walls where the tools and equipment are placed. The camera captures real-time images of the tool and equipment warehouse, selects each tool and equipment in the real-time images, and records the set of plane coordinate points of each tool and equipment in each two-dimensional image. This module is used to implement the function of step two in embodiment one, and will not be described in detail here.

[0084] The tool feature binding module uses a preset algorithm to extract feature data and feature points from the surface of each tool in the two-dimensional image, and binds the feature data, coordinate point set, and feature points of each tool with the unique identification barcode of the corresponding tool; this module is used to implement the function of step three in embodiment one, and will not be described in detail here;

[0085] The tool and equipment outbound positioning module, when searching for tools and equipment, performs three-dimensional reconstruction of the target tools and equipment based on the feature points, coordinate point set, feature data, and calibration parameters of the corresponding angle camera on the wall surface where the target tools and equipment are located, and obtains the three-dimensional point cloud data of the target tools and equipment to determine the precise position of the target tools and equipment in three-dimensional space; this module is used to implement the function of step four in embodiment one, and will not be described in detail here.

[0086] The tool and equipment storage module, when returning tools and equipment, scans the identification barcodes on the surfaces of all tools and equipment on the wall corresponding to the target tool and equipment, reads all feature points, and compares them with the feature points of the target tool and equipment to confirm whether the tool and equipment has been returned; this module is used to implement the function of step five in embodiment one, and will not be described in detail here.

[0087] In a preferred embodiment of this invention, the feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

[0088] In a preferred embodiment of this invention, the step of performing three-dimensional reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface is as follows:

[0089] First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows:

[0090] [[u, v] = P[X, Y, z]]

[0091] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix;

[0092] After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

[0093] In a preferred embodiment of this invention, the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm involves constructing a mathematical model using the preset algorithm. This mathematical model is specifically as follows:

[0094]

[0095] In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

[0096] Example 3:

[0097] This embodiment discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method for intelligent positioning of tools in three-dimensional space based on two-dimensional images, as described in any embodiment of the present invention.

[0098] Example 4:

[0099] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for intelligent positioning of tools in three-dimensional space based on a two-dimensional image, as described in any embodiment of the present invention.

[0100] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for intelligent positioning of tools in three-dimensional space based on two-dimensional images, characterized in that, The specific steps include: A unique, identifiable barcode is attached to a prominent location on the front of each tool. Several cameras at different angles are installed in the tool and equipment warehouse, facing each wall where the tools and equipment are placed. The cameras capture real-time images of the tool and equipment warehouse, and each tool and equipment in the real-time images is selected. At the same time, the set of planar coordinate points of each tool and equipment in each two-dimensional image is recorded. The feature data and feature points of each tool surface in the two-dimensional image are extracted using a preset algorithm, and the feature data, coordinate point set and feature points of each tool are bound to the unique identification barcode of the corresponding tool. When locating tools, the target tools are reconstructed in three dimensions based on their feature points, coordinate point set, feature data, and the calibration parameters of the corresponding angle camera on the wall surface. The three-dimensional point cloud data of the target tools is then obtained to determine their precise location in three-dimensional space. When returning tools and equipment, the camera on the wall where the target tool or equipment is located scans the barcode on the surface of all tools and equipment on the wall, reads all the feature points, and compares them with the feature points of the target tool or equipment to confirm whether the tool or equipment has been returned.

2. The method for intelligent positioning of tools in three-dimensional space based on two-dimensional images according to claim 1, characterized in that, The feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

3. The method for intelligent positioning of tools in three-dimensional space based on two-dimensional images according to claim 2, characterized in that, The specific steps for performing 3D reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface are as follows: First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows: [u, v] = P[X, Y, Z] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix; After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

4. The method for intelligent positioning of tools in three-dimensional space based on two-dimensional images according to claim 1, characterized in that, In the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm, a mathematical model is constructed using the preset algorithm. Specifically, this mathematical model is as follows: In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

5. A system for intelligent positioning of tools in three-dimensional space based on two-dimensional images, characterized in that, include: The tool coding module adds a unique, identifiable barcode to a prominent position on the front of each tool. The tool and equipment plane coordinate extraction module installs several cameras at different angles in the tool and equipment warehouse, which are respectively facing the walls of the warehouse where the tools and equipment are placed. The module obtains real-time images of the tool and equipment warehouse through the cameras, selects each tool and equipment in the real-time images, and records the set of plane coordinate points of each tool and equipment in each two-dimensional image. The tool feature binding module uses a preset algorithm to extract feature data and feature points from the surface of each tool in the two-dimensional image, and binds the feature data, coordinate point set and feature points of each tool with the unique identification barcode of the corresponding tool. The tool and equipment outbound positioning module, when searching for tools and equipment, performs three-dimensional reconstruction of the target tools and equipment based on the feature points, coordinate point set, feature data, and calibration parameters of the corresponding angle camera on the wall surface where the target tools and equipment are located, and obtains the three-dimensional point cloud data of the target tools and equipment to determine the precise position of the target tools and equipment in three-dimensional space. The tool and equipment warehousing module scans the barcodes on the surfaces of all tools and equipment on the wall corresponding to the target tool and equipment when the tool and equipment are returned. It reads all the feature points and compares them with the feature points of the target tool and equipment to confirm whether the tool and equipment has been returned.

6. The intelligent positioning system for tools in three-dimensional space based on two-dimensional images according to claim 5, characterized in that, The feature data includes the outline of the tool, the texture of the tool, the color of the tool, and the size of the tool.

7. The intelligent positioning system for tools in three-dimensional space based on two-dimensional images according to claim 6, characterized in that, The specific steps for performing 3D reconstruction of the target tool based on its feature points, coordinate point set, feature data, and calibration parameters of the camera at the corresponding angle on the wall surface are as follows: First, by using the feature points of the target tool and the calibration parameters of the corresponding angle camera on the wall surface, the specific coordinates of the target tool in three-dimensional space are determined. The specific formula is as follows: [u, v] = P[X, Y, Z] In the formula, u and v are the corresponding pixel coordinates under the camera's view, and P is the camera's projection matrix; After determining the three-dimensional spatial coordinates of the target tool, the three-dimensional model of the target tool is reconstructed by combining the feature data of the surface of the target tool and the set of planar coordinate points, thus completing the three-dimensional reconstruction of the target tool.

8. The intelligent positioning system for tools in three-dimensional space based on two-dimensional images according to claim 5, characterized in that, In the step of extracting feature points of each tool in a two-dimensional image using a preset algorithm, a mathematical model is constructed using the preset algorithm. Specifically, this mathematical model is as follows: In the formula, x and y represent the horizontal and vertical coordinates of the feature point, and σ represents the angle of the feature point. and Let L and Y represent the second-order partial derivatives of the image grayscale value L with respect to the horizontal x-direction and the vertical y-direction, respectively.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for intelligent positioning of tools in three-dimensional space based on a two-dimensional screen as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the method for intelligent positioning of tools in three-dimensional space based on a two-dimensional image, as described in any one of claims 1 to 4.

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