Drill jumbo control method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a drill jumbo control method and device, electronic equipment and a storage medium. An excavation face is scanned and modeled through a laser radar, and a first point cloud model for the current cycle of the excavation face is generated; when it is judged that the drill jumbo does not work on the excavation face for the first time, registration is conducted on the first point cloud model and a second point cloud model generated in the last cycle of work, and a first target point cloud model is generated; converting the first target point cloud model into a first engineering coordinate parameter, and determining the first engineering coordinate parameter as first spatial position information of the drill jumbo; obtaining first tunnel face point cloud data based on the first target point cloud model; determining a first tunnel face projection through the first tunnel face point cloud data; the drill jumbo is controlled through the first spatial position information and the first tunnel face projection, automatic operation of the drill jumbo on tunnel excavation engineering is achieved, and engineering efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rock drilling trolley control, and in particular to a rock drilling trolley control method, a rock drilling trolley control device, an electronic device, a computer-readable storage medium and a rock drilling trolley. Background Art

[0002] The tunnel blasting excavation method first drills holes in the tunnel face according to the design requirements, and then charges and blasts to achieve tunnel excavation progress. Rock drilling rigs are often used for tunnel blasting excavation drilling. Before drilling, the relevant technology requires surveyors to lay out the tunnel excavation face, that is, to determine and mark the location of the drill hole on the excavation face, and then the rock drilling rig operator drills according to the drill hole location, which leads to low construction efficiency. Summary of the invention

[0003] An embodiment of the present invention provides a drilling rig control method, device, drilling rig, electronic device and computer-readable storage medium to overcome the above problems or at least partially solve the above problems.

[0004] The embodiment of the present invention discloses a method for controlling a rock drilling trolley, wherein the rock drilling trolley control is configured with a laser radar, comprising:

[0005] Scanning and modeling the excavation surface by using the laser radar to generate a first point cloud model of the excavation surface in this cycle;

[0006] When it is determined that the drilling rig is not operating the excavation surface for the first time, the first point cloud model is aligned with the second point cloud model generated in the previous cycle operation to generate a first target point cloud model;

[0007] Converting the first target point cloud model into first engineering coordinate parameters, and determining the first engineering coordinate parameters as first spatial position information of the drilling rig;

[0008] Acquiring first tunnel face point cloud data based on the first target point cloud model;

[0009] Determining a first tunnel face projection through the first tunnel face point cloud data;

[0010] The drilling rig is controlled by using the first spatial position information and the first tunnel face projection.

[0011] Optionally, the drilling rig control configuration is equipped with a corresponding surveying and mapping device, and further comprises:

[0012] When it is determined that the drilling rig is operating the excavation surface for the first time, or the registration error is greater than a preset threshold, controlling the surveying and mapping device to obtain the coordinate information of the calibration points, and constructing a reference model based on the coordinate information of the calibration points;

[0013] Using the first point cloud model and the reference model for registration to generate a second target point cloud model;

[0014] Converting the second target point cloud model into second engineering coordinate parameters, and determining the second engineering coordinate parameters as second spatial position information of the drilling rig;

[0015] Acquiring second tunnel face point cloud data based on the second target point cloud model;

[0016] Determining a second tunnel face projection through the second tunnel face point cloud data;

[0017] The drilling rig is controlled by using the second spatial position information and the second tunnel face projection.

[0018] Optionally, before the step of scanning and modeling the excavation surface by the laser radar to generate a first point cloud model of the current cycle for the excavation surface, the step further includes:

[0019] Acquire and calibrate the spatial position data of the drilling rig in a relative coordinate system centered at the laser radar;

[0020] generating an initial position movement control signal based on the spatial position data;

[0021] The drilling rig is controlled to reach a waiting operation position based on the initial position movement control signal.

[0022] Optionally, it also includes:

[0023] Determining noise points, abnormal points and outliers of the first point cloud model;

[0024] The noise points, abnormal points and outliers are removed.

[0025] Optionally, the step of acquiring the first tunnel face point cloud data by using the point cloud model based on the first target includes:

[0026] Determine the normal vector of the tunnel axis and each point of the first target point cloud model;

[0027] Determining a tunnel angle using the tunnel axis and the normal vector;

[0028] The tunnel face target points whose tunnel angle is less than a preset angle threshold are screened out, and the first tunnel face point cloud data are generated by using the tunnel face target points.

[0029] Optionally, the step of determining the first tunnel face projection by using the first tunnel face point cloud data includes:

[0030] Creating a plane based on the first tunnel face point cloud data; the normal vectors of the points on the plane are perpendicular to the tunnel axis;

[0031] The position of the plane on the tunnel axis is determined by the least square method to determine the first tunnel face projection.

[0032] Optionally, it also includes:

[0033] When the drilling rig is operating, if a specific target is detected within a preset safety range, the drilling rig is controlled to stop and an alarm message is generated.

[0034] The embodiment of the present invention further discloses a rock drilling trolley control device, wherein the rock drilling trolley control device is equipped with a laser radar, and comprises:

[0035] A first point cloud model generating module, configured to scan and model the excavation surface by using the laser radar, and generate a first point cloud model of the excavation surface in this cycle;

[0036] A first target point cloud model generating module is used to generate a first target point cloud model by aligning the first point cloud model with the second point cloud model generated in the previous cycle operation when it is determined that the drilling rig is not operating the excavation surface for the first time;

[0037] A first spatial position information determination module, configured to convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drilling rig;

[0038] A first tunnel face point cloud data acquisition module, used for acquiring first tunnel face point cloud data based on the first target point cloud model;

[0039] A first palm face projection determination module, configured to determine a first palm face projection through the first palm face point cloud data;

[0040] A drilling rig control module is used to control the drilling rig through the first spatial position information and the first tunnel face projection.

[0041] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0042] The memory is used to store computer programs;

[0043] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0044] The embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, enables the processors to execute the method described in the embodiment of the present invention.

[0045] A rock drilling rig, comprising:

[0046] one or more processors;

[0047] and one or more machine-readable media having instructions stored thereon, which, when executed by the one or more processors, cause the drilling rig to perform one or more of the methods described above.

[0048] The embodiments of the present invention include the following advantages:

[0049] In an embodiment of the present invention, the laser radar is used to scan and model the excavation face, and a first point cloud model of the current cycle for the excavation face is generated; when it is determined that the drilling rig is not operating the excavation face for the first time, the first point cloud model and the second point cloud model generated in the previous cycle are aligned to generate a first target point cloud model; the first target point cloud model is converted into a first engineering coordinate parameter, and the first engineering coordinate parameter is determined as the first spatial position information of the drilling rig; the first face point cloud data is obtained based on the first target point cloud model; the first face projection is determined through the first face point cloud data; the drilling rig is controlled through the first spatial position information and the first face projection, so that the drilling rig can automatically perform operations on the tunnel excavation project, thereby improving the project efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is a flowchart of a method for controlling a rock drilling rig provided in an embodiment of the present invention;

[0051] Figure 2 is a structural schematic diagram of a point cloud model registration provided in an embodiment of the present invention;

[0052] Figure 3 It is a structural schematic diagram of a rock drilling rig provided in an embodiment of the present invention, which is positioned based on a surveying and mapping device;

[0053] Figure 4 is a flowchart of another method for controlling a rock drilling rig provided in an embodiment of the present invention;

[0054] Figure 5 It is a schematic diagram of the spatial state structure of a rock drilling trolley provided in an embodiment of the present invention;

[0055] Figure 6 is a structural block diagram of a rock drilling trolley control device provided in an embodiment of the present invention;

[0056] Figure 7 is a hardware structure block diagram of an electronic device provided in an embodiment of the present invention;

[0057] Figure 8 is a schematic diagram of a computer-readable medium provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0059] Reference Figure 1 , shows a flowchart of a rock drilling trolley control method provided in an embodiment of the present invention, which may specifically include the following steps:

[0060] Step 101, scanning and modeling the excavation surface by the laser radar to generate a first point cloud model of the excavation surface in this cycle;

[0061] In a specific implementation, the drilling rig control of the embodiment of the present invention is configured with a laser radar.

[0062] LiDAR is a sensor that emits laser light and receives reflected signals to measure the distance and angle of objects. Through LiDAR, vehicles can obtain three-dimensional point cloud data of the surrounding environment, including information such as the location and shape of obstacles. This information is crucial for the automatic control of operating vehicles.

[0063] In the automatic control system of the working vehicle, the lidar data is usually integrated with other sensor data, such as the global positioning system GPS, inertial measurement unit IMU, etc., to obtain more accurate environmental perception information. Then, the automatic control system will plan the movement trajectory of the vehicle based on this information and control the vehicle's actuators, such as steering and braking, to ultimately achieve automatic operation of the vehicle.

[0064] Excavation face and heading face are both terms in tunnel construction, and there is a close connection between them.

[0065] The excavation face refers to the surrounding rock interface formed after tunnel excavation.

[0066] The face refers to the excavated tunnel working face during the tunnel excavation process. The face is the starting position of tunnel excavation and the starting position of tunnel support. During the tunnel excavation process, the face will continue to move forward.

[0067] The main differences between the excavation face and the tunnel face are:

[0068] Different locations: the excavation face is located in the surrounding rock of the tunnel that has not yet been excavated, while the heading face is located in the working face of the tunnel that has already been excavated.

[0069] Different states: the excavation face is the unexcavated rock mass, while the heading face is the excavated rock mass.

[0070] Different functions: the excavation face is the potential space for tunnel excavation, while the heading face is the actual working face of tunnel excavation.

[0071] The relationship between the excavation face and the tunnel face is as follows:

[0072] The excavation face is the predecessor of the heading face.

[0073] The heading face is the follow-up to the excavation face.

[0074] As the tunnel is continuously excavated, the excavation face will gradually become the heading face and then disappear.

[0075] In tunnel construction, both excavation face and tunnel face are important concepts. For the excavation face, geological survey and assessment are required to determine the tunnel excavation plan; for the tunnel face, support and monitoring are required to ensure the safe construction of the tunnel.

[0076] In an embodiment of the present invention, the excavation surface can be scanned and modeled by a laser radar to generate a first point cloud model of the current cycle for the excavation surface. In a tunnel excavation project, multiple rounds of cyclic excavation are required, and the first point cloud model is the point cloud model of the current cycle.

[0077] Step 102, when it is determined that the drilling rig is not operating the excavation surface for the first time, the first point cloud model is aligned with the second point cloud model generated in the previous cycle operation to generate a first target point cloud model;

[0078] The point cloud model collected this time is registered with the point cloud model of the previous cycle. The purpose is to make the two point cloud models as consistent as possible, so as to better reflect the changes of the target object.

[0079] Commonly used point cloud registration algorithms include:

[0080] Iterative Closest Point (ICP) algorithm: This algorithm achieves registration by iteratively minimizing the point-to-point distance between two point cloud models. The ICP algorithm is a classic point cloud registration algorithm with the advantages of strong robustness and high computational efficiency.

[0081] Normal Distribution Transformation (NDT) algorithm: This algorithm represents the point cloud model as a normal distribution and achieves registration by minimizing the difference between two normal distributions. The NDT algorithm is robust to noise and local distortion, but its computational efficiency is slightly lower than that of the ICP algorithm.

[0082] Feature matching algorithm: This algorithm first extracts the features of the point cloud model, and then calculates the registration transformation based on the matching relationship between the features. The feature matching algorithm has high computational efficiency, but has high requirements for feature extraction and matching algorithms.

[0083] The specific steps are as follows:

[0084] 1. Select the registration algorithm

[0085] Select an appropriate registration algorithm based on the characteristics of the point cloud model and the requirements of the registration task. For example, if the point cloud model has noise or local distortion, you can choose the NDT algorithm; if high computational efficiency is required, you can choose the ICP algorithm.

[0086] 2. Parameter settings

[0087] Set appropriate parameters for the selected registration algorithm. For example, for the ICP algorithm, you need to set parameters such as the maximum number of iterations and the distance threshold; for the NDT algorithm, you need to set parameters such as the voxel size and the search radius.

[0088] 3. Perform registration

[0089] The two,point cloud models are registered using the selected registration algorithm.

[0090] 4. Evaluate the results

[0091] The registration results are evaluated to ensure their accuracy and correctness. Common evaluation methods include:

[0092] Visual inspection: Observe whether the two registered point cloud models overlap.

[0093] Distance error calculation: Calculate the point-to-point distance between the two registered point cloud models.

[0094] Application testing: Apply the registration results to actual tasks to evaluate their performance.

[0095] The accuracy of point cloud registration has a great impact on subsequent point cloud processing tasks. Therefore, when performing point cloud registration, it is necessary to carefully select the registration algorithm and parameters and evaluate the results.

[0096] In addition to the general registration algorithms mentioned above, there are also some point cloud registration algorithms for specific applications, such as point cloud registration algorithms for outdoor scenes, point cloud registration algorithms for industrial scenes, etc.

[0097] refer to Figure 2 , Figure 2 is a structural schematic diagram of a point cloud model registration provided in an embodiment of the present invention;

[0098] According to an embodiment of the present invention, when it is not the first drilling operation and there is no need to calibrate the automatic positioning accuracy of the drilling rig, the first point cloud model and the second point cloud model generated in the previous cycle operation can be aligned to generate a first target point cloud model.

[0099] Step 103, converting the first target point cloud model into first engineering coordinate parameters, and determining the first engineering coordinate parameters as first spatial position information of the drilling rig;

[0100] In addition to determining the tunnel face projection, it is also necessary to convert the registered point cloud model into engineering coordinates for the following reasons:

[0101] 1. The face projection is usually local information, while the engineering coordinates are global information.

[0102] The tunnel face projection only reflects the excavation face information of this round of construction, while the engineering coordinates are the spatial position information of the entire tunnel. By converting the point cloud model into engineering coordinates, the excavation face of this round of construction can be associated with the entire tunnel, thereby better managing the construction progress and monitoring safety.

[0103] 2. Project coordinates can be used for other construction tasks.

[0104] In tunnel construction, in addition to excavation, other construction tasks are also required, such as support, measurement, grouting, etc. These tasks all require engineering coordinates. Therefore, converting the point cloud model into engineering coordinates can provide basic data for subsequent construction tasks.

[0105] 3. Converting engineering coordinates can improve data accuracy.

[0106] The coordinate system of the point cloud model is usually a relative coordinate system, while the engineering coordinates are absolute coordinate systems. Converting the point cloud model into engineering coordinates can eliminate the error between the relative coordinate systems and improve the accuracy of the data.

[0107] Determining the tunnel face projection is the premise of excavation construction, and converting the point cloud model into engineering coordinates is the basis of excavation construction. The two are interrelated and mutually reinforcing.

[0108] To convert a point cloud model into engineering coordinates, a coordinate transformation method is usually required. Common coordinate transformation methods include translation transformation, rotation transformation, and scaling transformation.

[0109] In practical applications, the relative coordinate system of the point cloud model refers to the coordinate system centered on the lidar, and the spatial position information refers to the position and posture information of the vehicle in the lidar coordinate system.

[0110] Therefore, in the embodiment of the present invention, the first target point cloud model can be converted into first engineering coordinate parameters, and the first engineering coordinate parameters can be determined as the first spatial position information of the drilling rig.

[0111] Step 104, acquiring first tunnel face point cloud data based on the first target point cloud model;

[0112] Step 105, determining a first tunnel face projection through the first tunnel face point cloud data;

[0113] To determine the face projection plane for this round of construction, the following steps need to be followed:

[0114] 1. Data preparation

[0115] Make sure that the point cloud model of the excavation surface of the current round of construction and the point cloud model of the excavation surface of the previous round of construction have been obtained.

[0116] The two sets of point cloud models need to be preprocessed, such as filtering and denoising, to ensure the quality of the data.

[0117] 2. Point cloud registration

[0118] The excavation surface point cloud model of this round of construction is aligned with the excavation surface point cloud model of the previous round of construction.

[0119] The purpose of registration is to make the two point cloud models as consistent as possible so that the position and shape of the wheel face can be accurately calculated.

[0120] Commonly used point cloud registration algorithms include ICP algorithm, NDT algorithm, etc.

[0121] 3. Extraction of the palm face

[0122] Based on the registered point cloud model, the point cloud data of the current round of tunnel face is extracted.

[0123] There are many methods for tunnel face extraction, such as threshold-based segmentation and region growing-based segmentation.

[0124] The appropriate tunnel face extraction method can be selected based on the specific point cloud data characteristics and application requirements.

[0125] 4. Projection calculation

[0126] Projection calculation is performed on the extracted point cloud data of the current round of tunnel face to obtain the projection plane of the current round of tunnel face.

[0127] There are many methods for projection calculation, such as plane fitting, least squares method, etc.

[0128] The appropriate projection calculation method can be selected according to the specific point cloud data characteristics and application requirements.

[0129] 5. Result evaluation

[0130] The obtained projection plane of the current wheel face is evaluated to ensure its accuracy and correctness.

[0131] Evaluation methods may include visual inspection, distance error calculation, etc.

[0132] If the evaluation result is not satisfactory, you need to repeat the previous steps until you get a satisfactory result.

[0133] For example:

[0134] When performing point cloud registration, you can choose to use the ICP algorithm or the NDT algorithm. The ICP algorithm is more robust, but the computational efficiency is lower; the NDT algorithm is more efficient, but is sensitive to noise and local distortion.

[0135] When extracting the tunnel face, you can choose to use a threshold-based segmentation method or a region growing-based segmentation method. The threshold-based segmentation method is simple and easy to use, but it is sensitive to the choice of threshold; the region growing-based segmentation method is more robust.

[0136] When performing projection calculations, you can choose to use the plane fitting method or the least squares method. The plane fitting method is simple and easy, but it has high requirements on the quality of point cloud data; the least squares method is more robust.

[0137] Step 106: Control the drilling rig by using the first spatial position information and the first tunnel face projection.

[0138] Exemplarily, the specific steps are as follows:

[0139] 1. Delineation of excavation area

[0140] The excavation area of ​​this round is delineated according to the shape and size of the projection plane of the tunnel face of this round. The excavation area should be slightly larger than the area of ​​the projection plane of the tunnel face to leave a certain safety margin.

[0141] 2. Mining parameter settings

[0142] According to the specific conditions of the excavation area, the excavation parameters of the rock drilling rig are set, including excavation depth, excavation angle, excavation speed, etc. The setting of excavation parameters should ensure a balance between excavation efficiency and safety.

[0143] 3. Positioning of drilling rig

[0144] The drilling rig is positioned at the excavation area based on the first engineering coordinate parameters (X, Y, Z), as well as the azimuth angle α, pitch angle β, and roll angle θ of the drilling rig.

[0145] 4. Excavation construction

[0146] The drilling rig autonomously determines the position of the borehole in the face point cloud model according to the drilling design parameters, and controls the drilling robot arm to reach the drilling position to carry out the drilling operation based on the first spatial position information. During the excavation process, the operation of the drilling rig should be closely observed, and the excavation parameters should be adjusted in a timely manner. At the same time, safety precautions should also be taken to prevent accidents. Optionally, the drilling rig can monitor whether there are specific targets (such as construction personnel) within a preset safety range through a laser radar. When a specific target is detected within the preset safety range, the drilling rig is controlled to stop and an alarm message is generated.

[0147] 5. Palm face inspection

[0148] After the excavation is completed, the drilling rig can be controlled to obtain the face point cloud model of the current round through the drilling rig, and the face point cloud model of the current round can be converted into engineering coordinates and then checked to ensure that the shape and size of the face meet the design requirements. If any problems are found, they should be dealt with in a timely manner.

[0149] In an embodiment of the present invention, the laser radar is used to scan and model the excavation face, and a first point cloud model of the current cycle for the excavation face is generated; when it is determined that the drilling rig is not operating the excavation face for the first time, the first point cloud model and the second point cloud model generated in the previous cycle are aligned to generate a first target point cloud model; the first target point cloud model is converted into a first engineering coordinate parameter, and the first engineering coordinate parameter is determined as the first spatial position information of the drilling rig; the first face point cloud data is obtained based on the first target point cloud model; the first face projection is determined through the first face point cloud data; the drilling rig is controlled through the first spatial position information and the first face projection, so that the drilling rig can automatically perform operations on the tunnel excavation project, thereby improving the project efficiency.

[0150] Based on the above embodiment, a variant embodiment of the above embodiment is proposed. It should be noted that in order to make the description concise, only the differences from the above embodiment are described in the variant embodiment.

[0151] refer to Figure 3 , Figure 3 It is a structural schematic diagram of a rock drilling rig provided in an embodiment of the present invention, which is positioned based on a surveying and mapping device;

[0152] In an optional embodiment of the present invention, the drilling rig control configuration is equipped with a corresponding surveying and mapping device, and further comprises:

[0153] When it is determined that the drilling rig is operating the excavation surface for the first time, or the registration error is greater than a preset threshold, controlling the surveying and mapping device to obtain calibration point coordinate information, and constructing a reference model based on the calibration point coordinate information;

[0154] Using the first point cloud model and the reference model for registration to generate a second target point cloud model;

[0155] Converting the second target point cloud model into second engineering coordinate parameters, and determining the second engineering coordinate parameters as second spatial position information of the drilling rig;

[0156] Acquiring second tunnel face point cloud data based on the second target point cloud model;

[0157] Determining a second tunnel face projection through the second tunnel face point cloud data;

[0158] The drilling rig is controlled by using the second spatial position information and the second tunnel face projection.

[0159] During the first drilling operation, point cloud model registration and tunnel face projection generation are crucial steps, which lay the foundation for subsequent accurate drilling and safe construction.

[0160] Optionally, it also includes:

[0161] Determining noise points, abnormal points and outliers of the first point cloud model;

[0162] Eliminate the noise,points, the abnormal points and the outliers.

[0163] In practical applications, there are two situations where the first point cloud model needs to be registered with the surveying and mapping data obtained by the total station. The first situation is the first excavation. The second situation is that after multiple rounds of excavation, the registration result is not enough to meet the accuracy requirements. After the first point cloud model and the second point cloud model generated in the previous cycle are registered, the registration error can be obtained, and the registration error is greater than the preset threshold, which indicates that the registration result is not enough to meet the accuracy requirements. The third situation is that the number of excavation rounds is greater than the preset threshold.

[0164] In the specific implementation, since the first excavation is not aligned with the point cloud model of the previous round, when it is determined that the drilling rig is operating on the excavation surface for the first time, or the alignment error is greater than the preset threshold, the surveying and mapping device is controlled to obtain the calibration point coordinate information. At the same time, a reference model is constructed through the tunnel design data and the calibration point coordinate information of the total station.

[0165] The first point cloud model is converted into engineering coordinate parameters. The first point cloud model and the reference model are aligned by comparing the calibration point coordinate information of the total station and the engineering coordinate parameters generated by the conversion of the first point cloud model to generate a second target point cloud model. It can be seen from the above that the second target point cloud model is the target point cloud model for the first round of excavation or when the automatic positioning accuracy of the trolley needs to be corrected after multiple rounds of excavation. The second target point cloud model is converted into second engineering coordinate parameters, and the second engineering coordinate parameters are determined as the second spatial position information of the drilling trolley; the second face point cloud data is obtained based on the second target point cloud model; the second face projection is determined by the second face point cloud data; and the drilling trolley is controlled by the second spatial position information and the second face projection.

[0166] It should be noted that the specific execution method of the above-mentioned alignment process, target point cloud model generation process, engineering coordinate parameter conversion process, spatial position information determination process, face point cloud data acquisition process, face projection determination process, and drilling rig control process can be aligned with the first point cloud model and the second point cloud model generated in the previous cycle operation to generate a first target point cloud model; convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as the first spatial position information of the drilling rig; obtain the first face point cloud data based on the first target point cloud model; determine the first face projection through the first face point cloud data; and control the drilling rig through the first spatial position information and the first face projection in the same manner.

[0167] For example:

[0168] 1. Get point cloud data:

[0169] Use a LiDAR scanner or other 3D scanning equipment to scan the tunnel space and obtain raw point cloud data.

[0170] Ensure that the point cloud data is of good quality and contains sufficient information and accuracy.

[0171] 2. Perform point cloud preprocessing:

[0172] The original point cloud data (first point cloud model) is cleaned to remove noise, abnormal points and outliers.

[0173] Filter, simplify and stitch the point cloud data as needed to obtain a high-quality point cloud model.

[0174] 3. Tunnel space registration:

[0175] The reference model of the tunnel space can be established by combining known tunnel design drawings with coordinate information of calibration points obtained by surveying and mapping devices such as total stations to establish a tunnel space model.

[0176] The first point cloud data acquired is registered with the reference model to make the two as consistent as possible. Common registration methods include iterative closest point (ICP) algorithm, point feature matching, etc.

[0177] 4. Palm face extraction:

[0178] The point cloud of the tunnel face in the current excavation cycle is extracted by using the registered second target point cloud model. Commonly used methods include normal calculation and curvature analysis.

[0179] The face point cloud should accurately reflect the tunnel surface area that currently needs to be excavated.

[0180] 5. Palm face projection generation:

[0181] The second tunnel face point cloud data is obtained based on the second target point cloud model; the second tunnel face projection is determined by the second tunnel face point cloud data. The projection can be a plane projection or a curved surface projection, depending on the requirements of the drilling operation.

[0182] The tunnel face projection should clearly and accurately show the shape and size of the tunnel face to provide a reference for drilling operations.

[0183] 6. Visualization and quality control:

[0184] Visualize the point cloud model, tunnel face point cloud, and tunnel face projection to check whether the registration and extraction results are as expected.

[0185] Perform quality control to ensure the accuracy and reliability of point cloud data and projection results.

[0186] Note:

[0187] Since there is no ready-made tunnel face reference for the first drilling operation, special attention needs to be paid to the accuracy of point cloud model registration.

[0188] The selection of face extraction and projection methods should be based on the specific tunnel structure and construction requirements.

[0189] Point cloud data and projection results should be checked regularly to ensure that their data quality meets construction needs.

[0190] In addition, existing drilling data or other auxiliary information can be used to assist in point cloud model registration and tunnel face extraction.

[0191] For tunnels with complex shapes, more advanced registration algorithms and point cloud processing techniques can be used.

[0192] Professional point cloud processing software can be used to perform the above operations, which can improve efficiency and accuracy.

[0193] In an optional embodiment of the present invention, before the step of scanning and modeling the excavation surface by the laser radar to generate the first point cloud model of the current cycle for the excavation surface, the step further includes:

[0194] Acquire and calibrate the spatial position data of the drilling rig in a relative coordinate system centered at the laser radar;

[0195] generating an initial position movement control signal based on the spatial position data;

[0196] The drilling rig is controlled to reach a waiting operation position based on the initial position movement control signal.

[0197] In the field of automatic control of work vehicles, when the vehicle reaches the vicinity of the target position, it will use the on-board laser radar to perceive the surrounding environment and perform automatic control based on the spatial position data of the vehicle in the laser radar coordinate system obtained by the laser radar.

[0198] The embodiments of the present invention can enable the vehicle to be equipped with a laser radar with a ranging error of millimeter level and an angular accuracy of 0.009°. Before operation, the spatial position data of the drilling rig in a relative coordinate system centered on the laser radar can be calibrated. After obtaining the calibrated spatial position data of the drilling rig in the relative coordinate system centered on the laser radar, an initial position movement control signal is generated based on the spatial position data, and the drilling rig is controlled to reach the position to be operated based on the initial position movement control signal, thereby improving operation efficiency.

[0199] In an optional embodiment of the present invention, the step of acquiring first tunnel face point cloud data based on the first target point cloud model includes:

[0200] Determine the normal vector of the tunnel axis and each point of the first target point cloud model;

[0201] Determining a tunnel angle using the tunnel axis and the normal vector;

[0202] The tunnel face target points whose tunnel angle is less than a preset angle threshold are screened out, and the first tunnel face point cloud data are generated by using the tunnel face target points.

[0203] For example, the tunnel axis can be determined by the design data of the tunnel, for example:

[0204] Method based on cylinder fitting: The basic principle of this method is to fit the point cloud data to a cylinder and then take the central axis of the cylinder as the tunnel axis.

[0205] Straight line fitting based on the RANSA method: The basic principle of this method is to randomly extract three groups of points from the point cloud data using the RANSA method, then calculate the straight lines determined by the three groups of points, and select the straight line with the maximum support as the tunnel axis.

[0206] In addition to using the point neighborhood based normal calculation method, other methods can be used to calculate normals, such as:

[0207] Normal calculation method based on surface fitting: The basic principle of this method is to fit the point cloud data onto a surface and then calculate the normal vector of the surface at each point.

[0208] Normal calculation method based on deep learning: This method can use the deep learning model to directly predict the normal vector of each point cloud point.

[0209] After the tunnel angle is determined by using the tunnel axis and the normal vector, the tunnel face target points whose tunnel angle is less than the preset angle threshold are screened out, and the tunnel face target points are used to generate the first tunnel face point cloud data. For example, the normal information of the point cloud in the calculation model is used. When the tunnel angle between the normal and the tunnel axis is less than 25°, the point is considered to be the tunnel face target point. The tunnel face target point is used to generate the first tunnel face point cloud data, thereby improving the validity and reliability of the first tunnel face point cloud data.

[0210] In an optional embodiment of the present invention, the step of determining the first tunnel face projection by using the first tunnel face point cloud data comprises:

[0211] Creating a plane based on the first tunnel face point cloud data; the normal vectors of the points on the plane are perpendicular to the tunnel axis;

[0212] The position of the plane on the tunnel axis is determined by the least square method to determine the first tunnel face projection.

[0213] In a specific implementation, an embodiment of the present invention can construct a plane perpendicular to the tunnel axis, and use the least squares method to determine the position of the plane on the tunnel axis so that the distance from the face point to the plane reaches the minimum value, thereby obtaining the face projection plane parameters of the first face projection, thereby determining the first face projection.

[0214] In order to enable those skilled in the art to better understand the embodiment of the present invention, an example is used below to illustrate the embodiment of the present invention.

[0215] refer to Figure 4 , Figure 4 is a flowchart of another method for controlling a rock drilling rig provided in an embodiment of the present invention;

[0216] (1) The drilling rig arrives near the tunnel excavation face and prepares for drilling operations. The laser radar installed on the rig has been calibrated, that is, the spatial position data of the rig in a relative coordinate system centered on the laser radar has been calibrated.

[0217] (2) The trolley-mounted 3D laser radar performs scanning and modeling to collect the point cloud model of the tunnel near the excavation surface.

[0218] refer to Figure 5 , Figure 5 It is a schematic diagram of the spatial state structure of a rock drilling trolley provided in an embodiment of the present invention;

[0219] (3) When the drilling operation is performed for the first time or when the automatic positioning accuracy of the drilling rig needs to be corrected, a total station is used to measure the coordinates of the calibration points of the drilling rig, determine the spatial position information of the drilling rig, and convert the three-dimensional laser point cloud model into the engineering coordinate system.

[0220] (4) When it is not the first drilling operation or the trolley automatic positioning accuracy does not need to be corrected, the point cloud model collected this time is aligned with the point cloud model of the previous cycle (which has been converted to the engineering coordinate system). Since the two point clouds are collected at different excavation locations, the extra parts of the point cloud model can be removed after the first alignment, and then the second alignment can be performed to further reduce the model alignment error.

[0221] (5) Determine the spatial position information of the drilling rig based on the point cloud model registration parameters.

[0222] (6) Extract the tunnel face point cloud and establish a projection plane perpendicular to the tunnel axis. The least squares method or other methods can be used to calculate the tunnel face projection plane parameters.

[0223] (7) Autonomously determine the location of the drill hole in the face point cloud model based on the design parameters.

[0224] (8) The drilling rig has the function of automatic control of the drilling robot arm, which controls the drilling robot arm to reach the drilling position and carry out drilling operations based on its own spatial information.

[0225] Through the above method, the following beneficial effects are achieved:

[0226] (1) Auxiliary measurement and positioning only need to be performed when positioning and correcting for the first drilling or after multiple drilling operations, avoiding measurement and layout for each drilling operation and greatly reducing the measurement workload.

[0227] (2) The drilling position is determined based on the high-precision 3D point cloud model of the tunnel face, and the drilling positioning accuracy is higher.

[0228] (3) It is possible to realize autonomous positioning of the rock drilling rig, and the positioning method is simple. There is no need to set up auxiliary targets in the environment, and there is no need to set up various angle sensors on the body of the rock drilling rig.

[0229] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0230] Reference Figure 6 , shows a structural block diagram of a rock drilling trolley control device provided in an embodiment of the present invention, which may specifically include the following modules:

[0231] A first point cloud model generating module 601 is used to scan and model the excavation surface by using the laser radar to generate a first point cloud model of the excavation surface in this cycle;

[0232] A first target point cloud model generating module 602 is used to generate a first target point cloud model by aligning the first point cloud model with the second point cloud model generated in the previous cycle operation when it is determined that the drilling rig is not operating the excavation surface for the first time;

[0233] A first spatial position information determination module 603, configured to transform the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drilling rig;

[0234] A first tunnel face point cloud data acquisition module 604 is used to acquire first tunnel face point cloud data based on the first target point cloud model;

[0235] A first palm face projection determination module 605 is used to determine a first palm face projection through the first palm face point cloud data;

[0236] The drilling rig control module 606 is configured to control the drilling rig according to the first spatial position information and the first tunnel face projection.

[0237] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0238] In addition, an embodiment of the present invention further provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned rock drilling rig control method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0239] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned rock drilling trolley control method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0240] Figure 7 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0241] The electronic device 700 includes but is not limited to: a radio frequency unit 701, a network module 702, an audio output unit 703, an input unit 704, a sensor 705, a display unit 706, a user input unit 707, an interface unit 708, a memory 709, a processor 710, and a power supply 711. Those skilled in the art will appreciate that Figure 7 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and the electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. In the embodiments of the present invention, the electronic device includes but is not limited to a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted terminal, a wearable device, and a pedometer.

[0242] It should be understood that in the embodiment of the present invention, the radio frequency unit 701 can be used for receiving and sending signals during information transmission or communication. Specifically, after receiving downlink data from the base station, it is sent to the processor 710 for processing; in addition, uplink data is sent to the base station. Generally, the radio frequency unit 701 includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the radio frequency unit 701 can also communicate with the network and other devices through a wireless communication system.

[0243] The electronic device provides users with wireless broadband Internet access through the network module 702, such as helping users to send and receive emails, browse web pages, and access streaming media.

[0244] The audio output unit 703 can convert the audio data received by the RF unit 701 or the network module 702 or stored in the memory 709 into an audio signal and output it as sound. Moreover, the audio output unit 703 can also provide audio output related to a specific function performed by the electronic device 700 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 703 includes a speaker, a buzzer, a receiver, etc.

[0245] The input unit 704 is used to receive audio or video signals. The input unit 704 may include a graphics processor (GPU) 7041 and a microphone 7042, and the graphics processor 7041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 706. The image frame processed by the graphics processor 7041 can be stored in the memory 709 (or other storage medium) or sent via the radio frequency unit 701 or the network module 702. The microphone 7042 can receive sound and can process such sound into audio data. The processed audio data can be converted into a format output that can be sent to a mobile communication base station via the radio frequency unit 701 in the case of a telephone call mode.

[0246] The electronic device 700 also includes at least one sensor 705, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 7061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 7061 and / or the backlight when the electronic device 700 is moved to the ear. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary, which can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; the sensor 705 can also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be repeated here.

[0247] The display unit 706 is used to display information input by the user or information provided to the user. The display unit 706 may include a display panel 7061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0248] The user input unit 707 can be used to receive input digital or character information, and to generate key signal input related to user settings and function control of the electronic device. Specifically, the user input unit 707 includes a touch panel 7071 and other input devices 7072. The touch panel 7071, also known as a touch screen, can collect the user's touch operation on or near it (such as the user's operation on the touch panel 7071 or near the touch panel 7071 using any suitable object or accessory such as a finger, stylus, etc.). The touch panel 7071 may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the contact point coordinates, and then sends it to the processor 710, receives the command sent by the processor 710 and executes it. In addition, the touch panel 7071 can be implemented using multiple types such as resistive, capacitive, infrared and surface acoustic waves. In addition to the touch panel 7071, the user input unit 707 may also include other input devices 7072. Specifically, other input devices 7072 may include but are not limited to a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail here.

[0249] Furthermore, the touch panel 7071 may be overlaid on the display panel 7061. When the touch panel 7071 detects a touch operation on or near it, it transmits the information to the processor 710 to determine the type of the touch event. Then, the processor 710 provides a corresponding visual output on the display panel 7061 according to the type of the touch event. Figure 7 In the figure, the touch panel 7071 and the display panel 7061 are used as two independent components to realize the input and output functions of the electronic device. However, in some embodiments, the touch panel 7071 and the display panel 7061 can be integrated to realize the input and output functions of the electronic device, which is not limited here.

[0250] The interface unit 708 is an interface for connecting an external device to the electronic device 700. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, etc. The interface unit 708 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic device 700 or may be used to transmit data between the electronic device 700 and an external device.

[0251] The memory 709 can be used to store software programs and various data. The memory 709 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 709 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0252] The processor 710 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 709, and calling data stored in the memory 709, so as to monitor the electronic device as a whole. The processor 710 may include one or more processing units; preferably, the processor 710 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 710.

[0253] The electronic device 700 may also include a power supply 711 (such as a battery) for supplying power to each component. Preferably, the power supply 711 may be logically connected to the processor 710 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system.

[0254] In addition, the electronic device 700 includes some functional modules not shown, which will not be described in detail here.

[0255] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0256] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0257] like Figure 8 As shown, in another embodiment provided by the present invention, a computer-readable storage medium 801 is also provided, in which instructions are stored. When the computer-readable storage medium is run on a computer, the computer executes the rock drilling rig control method described in the above embodiment.

[0258] The embodiment of the present invention further discloses a rock drilling trolley, comprising:

[0259] one or more processors;

[0260] and one or more machine-readable media having instructions stored thereon, which, when executed by the one or more processors, cause the drilling rig to perform one or more of the methods described above.

[0261] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

[0262] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0263] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0264] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0265] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0266] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0267] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0268] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for controlling a rock drilling rig, characterized in that: The drilling rig control is configured with a laser radar, including: Scanning and modeling the excavation surface by using the laser radar to generate a first point cloud model of the excavation surface in this cycle; When it is determined that the drilling rig is not operating the excavation surface for the first time, the first point cloud model is aligned with the second point cloud model generated in the previous cycle operation to generate a first target point cloud model; Converting the first target point cloud model into first engineering coordinate parameters, and determining the first engineering coordinate parameters as first spatial position information of the drilling rig; Acquiring first tunnel face point cloud data based on the first target point cloud model; Determining a first tunnel face projection through the first tunnel face point cloud data; The drilling rig is controlled by using the first spatial position information and the first tunnel face projection.

2. The method according to claim 1, characterized in that The rock drilling rig control configuration is equipped with a corresponding surveying and mapping device, and also includes: When it is determined that the drilling rig is operating the excavation surface for the first time, or the registration error is greater than a preset threshold, controlling the surveying and mapping device to obtain the coordinate information of the calibration points, and constructing a reference model based on the coordinate information of the calibration points; Using the first point cloud model and the reference model for registration to generate a second target point cloud model; Converting the second target point cloud model into second engineering coordinate parameters, and determining the second engineering coordinate parameters as second spatial position information of the drilling rig; Acquiring second tunnel face point cloud data based on the second target point cloud model; Determining a second tunnel face projection through the second tunnel face point cloud data; The drilling rig is controlled by using the second spatial position information and the second tunnel face projection.

3. The method according to claim 2, characterized in that Before the step of scanning and modeling the excavation surface by the laser radar to generate the first point cloud model of the current cycle for the excavation surface, the method further includes: Acquire and calibrate the spatial position data of the drilling rig in a relative coordinate system centered at the laser radar; generating an initial position movement control signal based on the spatial position data; The drilling rig is controlled to reach a waiting operation position based on the initial position movement control signal.

4. The method according to claim 2, characterized in that: Also includes: Determining noise points, abnormal points and outliers of the first point cloud model; The noise points, abnormal points and outliers are removed.

5. The method according to claim 1, characterized in that The step of obtaining the first tunnel face point cloud data using the point cloud model based on the first target includes: Determine the normal vector of the tunnel axis and each point of the first target point cloud model; Determining a tunnel angle using the tunnel axis and the normal vector; The tunnel face target points whose tunnel angle is less than a preset angle threshold are screened out, and the first tunnel face point cloud data are generated by using the tunnel face target points.

6. The method according to claim 5, characterized in that The step of determining the first tunnel face projection by using the first tunnel face point cloud data comprises: Creating a plane based on the first tunnel face point cloud data; the normal vectors of the points on the plane are perpendicular to the tunnel axis; The position of the plane on the tunnel axis is determined by the least square method to determine the first tunnel face projection.

7. The method according to claim 1, characterized in that Also includes: When the drilling rig is operating, if a specific target is detected within a preset safety range, the drilling rig is controlled to stop and an alarm message is generated.

8. A rock drilling trolley control device, characterized in that: The drilling rig control is configured with a laser radar, including: A first point cloud model generating module, configured to scan and model the excavation surface by using the laser radar, and generate a first point cloud model of the excavation surface in this cycle; A first target point cloud model generating module is used to generate a first target point cloud model by aligning the first point cloud model with the second point cloud model generated in the previous cycle operation when it is determined that the drilling rig is not operating the excavation surface for the first time; A first spatial position information determination module, configured to convert the first target point cloud model into first engineering coordinate parameters, and determine the first engineering coordinate parameters as first spatial position information of the drilling rig; A first tunnel face point cloud data acquisition module, used for acquiring first tunnel face point cloud data based on the first target point cloud model; A first palm face projection determination module, configured to determine a first palm face projection through the first palm face point cloud data; A drilling rig control module is used to control the drilling rig through the first spatial position information and the first tunnel face projection.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

11. A rock drilling rig, characterized in that: include: one or more processors; and One or more machine-readable media having instructions stored thereon, when executed by the one or more processors, cause the drilling rig to perform the method of any one of claims 1-7.

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