Positioning Method and Device for Movable Equipment Underground in Mine

Abstract

The present disclosure provides a positioning method and device for movable equipment underground in a mine. Among them, the method includes: obtaining first point cloud information underground in the mine; determining first pose information of the movable equipment in the body coordinate system at a target moment and second point cloud information corresponding to the target moment based on the radar signal of the movable equipment; performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain second pose information at a second sampling frequency of the movable equipment in the point cloud coordinate system at the target moment; converting the sampling frequency of the second pose information according to the first pose information to obtain target pose information at a first sampling frequency of the movable equipment in the point cloud coordinate system. Thus, precise positioning of the movable equipment underground in the mine can be achieved. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the movable equipment underground in the mine.

Description

Technical Field

[0001] The present disclosure relates to the technical field of positioning of movable devices, and in particular, to a positioning method and device for movable devices underground in a mine. Background Art

[0002] Movable devices (such as, drones) have increasingly wide application scenarios because of their high efficiency, low cost, and reusable characteristics.

[0003] However, due to the narrow roadway and limited space in a mine (such as, underground in a coal mine), the situation of being affected by noise interference and signal shielding is relatively serious, and the Global Positioning System (GPS) cannot obtain effective positioning signals, making it difficult to apply GPS to the autonomous navigation of movable devices underground in a mine. Therefore, how to achieve precise positioning of movable devices underground in a mine to realize the autonomous navigation of movable devices underground in a mine has become an urgent problem to be solved. Summary of the Invention

[0004] The present disclosure aims to solve at least one of the technical problems in the above technologies to some extent.

[0005] To this end, the first object of the present disclosure is to propose a positioning method for a movable device underground in a mine, so as to accurately determine the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system by downsampling the first point cloud information and the second point cloud information and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information. Furthermore, by converting the second pose information at the second sampling frequency according to the first pose information at the first sampling frequency, the target pose information at the first sampling frequency in the point cloud coordinate system can be accurately obtained. Thus, precise positioning of the movable device underground in a mine can be achieved according to the target pose information at the first sampling frequency in the point cloud coordinate system. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the movable device underground in a mine.

[0006] The second object of the present disclosure is to propose a positioning device for a movable device underground in a mine.

[0007] The third object of the present disclosure is to propose an electronic device.

[0008] The fourth object of the present disclosure is to propose a non-transitory computer-readable storage medium.

[0009] The fifth object of the present disclosure is to propose a computer program product.

[0010] To achieve the above object, an embodiment of the first aspect of the present disclosure provides a positioning method for a movable device underground in a mine, including: obtaining first point cloud information underground in the mine; using a lidar mounted on the movable device to detect the underground in the mine at a first sampling frequency to obtain radar signals; predicting the pose of the movable device at a target time based on the radar signals to obtain first pose information of the movable device in the body coordinate system at the target time; determining second point cloud information corresponding to the movable device at the target time based on the radar signals; downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target time; and converting the sampling frequency of the second pose information according to the first pose information to obtain target pose information of the movable device at the first sampling frequency in the point cloud coordinate system.

[0011] In the positioning method for a movable device underground in the mine according to the embodiment of the present disclosure, by obtaining first point cloud information underground in the mine; using a lidar mounted on the movable device to detect the underground in the mine at a first sampling frequency to obtain radar signals; predicting the pose of the movable device at a target time based on the radar signals to obtain first pose information of the movable device in the body coordinate system at the target time; determining second point cloud information corresponding to the movable device at the target time based on the radar signals; downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target time; and converting the sampling frequency of the second pose information according to the first pose information to obtain target pose information of the movable device at the first sampling frequency in the point cloud coordinate system. Thus, by downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information, the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target time can be accurately determined. Furthermore, by converting the second pose information at the second sampling frequency according to the first pose information at the first sampling frequency, the target pose information at the first sampling frequency in the point cloud coordinate system can be accurately obtained, so that the precise positioning of the movable device underground in the mine can be realized according to the pose information at the first sampling frequency in the point cloud coordinate system. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the movable device underground in the mine.

[0012] To achieve the above object, an embodiment of the second aspect of the present disclosure provides a positioning device for a movable device underground in a mine, including: an acquisition module configured to acquire first point cloud information underground in the mine; a detection module configured to detect the underground in the mine by using a lidar mounted on the movable device at a first sampling frequency to obtain radar signals; a prediction module configured to predict the pose of the movable device at a target time based on the radar signals to obtain first pose information of the movable device in a body coordinate system at the target time; a first determination module configured to determine second point cloud information corresponding to the movable device at the target time based on the radar signals; a second determination module configured to downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain second pose information at a second sampling frequency of the movable device in a point cloud coordinate system at the target time; and a conversion module configured to convert the sampling frequency of the second pose information according to the first pose information to obtain target pose information of the movable device at the first sampling frequency in the point cloud coordinate system.

[0013] To achieve the above object, an embodiment of the third aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the method described in the embodiment of the first aspect of the present disclosure.

[0014] To achieve the above object, an embodiment of the fourth aspect of the present disclosure provides a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in the embodiment of the first aspect of the present disclosure is implemented.

[0015] To achieve the above object, an embodiment of the fifth aspect of the present disclosure provides a computer program product, including a computer program, and when the computer program is executed by a processor, the method described in the embodiment of the first aspect of the present disclosure is implemented.

[0016] The additional aspects and advantages of the present disclosure will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present disclosure. Description of the Drawings

[0017] The above and / or additional aspects and advantages of the present disclosure will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0018] Figure 1 It is a schematic flowchart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0019] Figure 2 Schematic flow chart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0020] Figure 3 Schematic flow chart of the cutting of the first point cloud information provided by an embodiment of the present disclosure;

[0021] Figure 4 Schematic flow chart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0022] Figure 5 Schematic flow chart of the matching of the second point cloud information and the point cloud sub - information provided by an embodiment of the present disclosure;

[0023] Figure 6 Schematic flow chart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0024] Figure 7 Schematic flow chart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0025] Figure 8 Schematic flow chart of a positioning method for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0026] Figure 9 Schematic structural diagram of a positioning device for a movable device underground in a mine provided by an embodiment of the present disclosure;

[0027] Figure 10 Structural block diagram of an electronic device provided according to an embodiment of the present disclosure. Detailed implementation manners

[0028] The embodiments of the present disclosure are described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, and should not be construed as a limitation to the present disclosure.

[0029] Due to characteristics such as high efficiency, low cost, and convenient use, movable devices have been widely used in more and more scenarios. However, the underground mine roadway is narrow, the space is limited, and there is no GPS signal, so it is difficult to obtain the position information under the GPS coordinates, and thus it is difficult to achieve precise positioning underground in the mine.

[0030] In the related art, in a mine, an Ultra Wide Band (UWB) radar or a Simultaneous Localization and Mapping (SLAM) technology is used to achieve precise positioning of a movable device.

[0031] Among them, UWB positioning mainly measures the current first real-time position data of the movable device through inertial navigation, detects the second real-time position data of the movable device through a UWB positioning algorithm, and obtains the current absolute position coordinates of the movable device after fusing the two position data through Kalman filtering. When the movable device hovers at the target position, two-dimensional point cloud data can be obtained through a single-line lidar, and then precise three-dimensional position information of the movable device can be obtained through laser SLAM, and the hovering accuracy can be optimized.

[0032] Among them, SLAM can achieve precise positioning of the movable device by obtaining the three-dimensional position and attitude information of the movable device through a laser odometry calculation method. Furthermore, key point cloud frames can be extracted based on the three-dimensional pose information, and the key point cloud frames can be described based on the feature histogram of the viewpoints, and the similarity of the key point cloud of the key frames can be calculated to obtain the three-dimensional position information of the movable device. For example, when the similarity is greater than a preset threshold, it proves that the positions of the two key frames are close, and the true relative transformation between the two key frames is calculated through a point cloud matching algorithm. Furthermore, based on the pose transformation of the key frames and the historical coordinate positions, each pose data is corrected to obtain the three-dimensional position information of the movable device.

[0033] However, in the UWB positioning method, UWB is used to obtain absolute coordinates. The UWB positioning accuracy is similar to the GPS positioning accuracy, and the error can reach the meter level. Moreover, the positioning accuracy depends on the base station position calibration and the base station signal, and the equipment is complicated. In addition, due to the narrow space in the mine, the signal is easily blocked, so the UWB technology is not suitable for the positioning of movable devices in the mine. In addition, although a two-dimensional lidar can be used to reduce the UWB positioning error in the UWB positioning method, a single-line lidar can only obtain two-dimensional position information and cannot obtain the three-dimensional position information of the movable device in the mine. When the movable device hovers, it can continuously adjust its attitude to correct its current position. When the attitude of the movable device changes, the positioning obtained by the SLAM algorithm based on the single-line lidar may deviate, resulting in a decrease in the positioning accuracy of the movable device.

[0034] In the UWB positioning method, when using laser SLAM to achieve precise positioning of the movable device, the trajectory optimization of laser SLAM can be realized through the loop detection method based on the factor graph, the relative error of SLAM can be eliminated, and the positioning accuracy can be improved. However, since the relative position coordinates obtained are still relative to the starting point of operation, the relative position coordinates cannot be used for navigation and autonomous operation.

[0035] In addition, at present, many mobile devices use the Global Navigation Satellite System (GNSS) to achieve positioning. However, since the mine is an enclosed space, GNSS signals cannot be received, so it is not applicable to mobile devices in the mine. Many mobile devices are equipped with multi-camera for visual SLAM positioning. However, the visual SLAM positioning method is greatly affected by light. The lighting in the mine environment (such as fully mechanized mining face and main haulage belt roadway) is uneven. Machine vision can ensure the positioning accuracy when the mobile device hovers, but cannot ensure the positioning accuracy when the mobile device is operating normally. Moreover, SLAM can only obtain the relative pose information of the mobile device relative to the starting position of the operation, and cannot meet the needs of autonomous operation and navigation of mobile devices in the mine.

[0036] Therefore, in view of the above problems, the present disclosure proposes a positioning method and device for a mobile device in a mine.

[0037] The following describes the positioning method and device for a mobile device in a mine according to an embodiment of the present disclosure with reference to the accompanying drawings.

[0038] Figure 1 FIG. is a schematic flow chart of a positioning method for a mobile device in a mine provided by an embodiment of the present disclosure.

[0039] As shown in Figure 1 the positioning method for the mobile device in the mine may include:

[0040] Step 101, obtain first point cloud information in the mine.

[0041] In an embodiment of the present disclosure, the first point cloud information in the mine may be obtained in advance. As an example, a point cloud device may be used to obtain multiple point cloud sub-information at multiple spatial positions in the mine in advance. Then, SLAM is used to construct point cloud information from the multiple point cloud sub-information, and the first point cloud information can be obtained.

[0042] Step 102, use the lidar mounted on the mobile device to detect the mine at a first sampling frequency to obtain radar signals.

[0043] As an example, use the lidar mounted on the mobile device to detect the mine at a first sampling frequency to obtain radar signals. For example, when the mobile device is in the mine, the lidar emits signals (laser beams) for detection, so that radar signals reflected from the target can be received. Among them, the mobile device may be, for example, a wheeled robot, a robotic dog, a handheld device, etc.

[0044] Step 103: Predict the pose of the movable device at the target moment based on the radar signal to obtain the first pose information of the movable device in the body coordinate system at the target moment.

[0045] To improve the positioning accuracy of the movable device, as a possible implementation of the embodiments of the present disclosure, underground in a mine, the movable device can use a multi-line lidar or a solid-state lidar to emit signals (laser beams) to detect the X, Y, and Z axes. Thus, the movable device can receive the reflected radar signals and send the emitted signals and the reflected radar signals to the control system of the movable device. The control system of the movable device can compare and process the received reflected radar signals with the emitted signals, and can obtain the position and attitude of the movable device on the X, Y, and Z axes, and use the position and attitude of the movable device on the X, Y, and Z axes as the first pose information of the movable device in the body coordinate system. For example, the control system of the movable device can use laser SLAM to compare and process the received reflected radar signals with the emitted signals to obtain the three-dimensional coordinates and attitude of the movable device, or, according to the SLAM method of fusing lidar and IMU, obtain the three-dimensional pose information of the movable device. It should be noted that the first pose information can be the pose information relative to the starting working position of the movable device.

[0046] In the embodiments of the present disclosure, the first pose information can be the current pose information T of the movable device b_i , T b_i can include q b_i =(q b_i_w , q b_i_x , q b_i_y , q b_i_z ) and t b_i =(x b_i , y b_i , z b_i ), where q b_i =(q b_i_w , q b_i_x , q b_i_y , q b_i_z ) is the rotation matrix from the body coordinate system where the movable device is located at the initial moment to the current body coordinate system of the movable device, and t b_i =(x b_i , y b_i , z b_i ) is the position of the center of the current body coordinate system of the movable device in the body coordinate system where the movable device was located at the initial moment.

[0047] Step 104: Determine the second point cloud information corresponding to the movable device at the target moment based on the radar signal.

[0048] In an embodiment of the present disclosure, three-dimensional point cloud data of a mobile device in a body coordinate system at a target moment can be obtained according to transmitted signals emitted by a multi-line lidar or a single-line lidar and reflected radar signals. Furthermore, according to the mapping relationship between the body coordinate system of the mobile device at the target moment and a point cloud coordinate system, point cloud information of the three-dimensional point cloud data in the body coordinate system in the point cloud coordinate system is determined, and the point cloud information in the point cloud coordinate system is used as the second point cloud information corresponding to the mobile device at the target moment.

[0049] Step 105: Downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment.

[0050] Furthermore, in order to reduce the computational complexity of point cloud data matching, as an example, the first point cloud information and the second point cloud information can be downsampled respectively, and then the downsampled first point cloud information and the downsampled second point cloud information are subjected to point cloud matching to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment. For example, the first point cloud information can be cut to obtain point cloud sub-information, and filters with different grid sizes are used to downsample the second point cloud information and the point cloud sub-information respectively. Then, the downsampled second point cloud information and the downsampled point cloud sub-information are subjected to point cloud matching to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment.

[0051] Step 106: Convert the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the mobile device in the point cloud coordinate system.

[0052] In an embodiment of the present disclosure, in order to achieve precise positioning of the mobile device and meet the navigation requirements of the mobile device, the sampling frequency of the second pose information can be converted according to the first pose information, and the pose information at the second sampling frequency in the point cloud coordinate system can be accurately obtained. Among them, the second sampling frequency is greater than the first sampling frequency.

[0053] In summary, by obtaining the first point cloud information in the mine; using the lidar mounted on the mobile device to detect the mine at the first sampling frequency to obtain radar signals; predicting the pose of the mobile device at the target moment based on the radar signals to obtain the first pose information of the mobile device in the body coordinate system at the target moment; determining the second point cloud information corresponding to the mobile device at the target moment based on the radar signals; downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment; converting the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the mobile device in the point cloud coordinate system. Thus, by downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information, the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment can be accurately determined. Furthermore, by converting the second pose information at the second sampling frequency according to the first pose information at the first sampling frequency, the target pose information at the first sampling frequency in the point cloud coordinate system can be accurately obtained, so that the precise positioning of the mobile device can be realized according to the target pose information at the first sampling frequency in the point cloud coordinate system. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the mobile device.

[0054] To clearly illustrate how the first point cloud information and the second point cloud information are downsampled, and the downsampled first point cloud information and the downsampled second point cloud information are subjected to point cloud matching to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment in the above embodiments, the present disclosure proposes another positioning method for a mobile device in a mine.

[0055] Figure 2 It is a flowchart showing a positioning method for a mobile device in a mine provided by an embodiment of the present disclosure.

[0056] As Figure 2 shown, the positioning method for the mobile device in the mine may include:

[0057] Step 201, obtain the first point cloud information in the mine.

[0058] Step 202, use the lidar mounted on the mobile device to detect the mine at the first sampling frequency to obtain radar signals.

[0059] Step 203: Predict the pose of the movable device at the target moment based on the radar signal to obtain the first pose information of the movable device in the body coordinate system at the target moment.

[0060] Step 204: Determine the second point cloud information corresponding to the movable device at the target moment based on the radar signal.

[0061] Step 205: Determine the point cloud sub-information corresponding to the movable device at the target moment from the first point cloud information.

[0062] In order to reduce the data volume of point cloud matching, in the embodiments of the present disclosure, the first point cloud information may be cut according to the position information of the movable device at the target moment to obtain the point cloud sub-information.

[0063] As an example, determine the position information of the movable device at the target moment according to the second point cloud information; determine the cutting range of the first point cloud information according to the detection range of the lidar; cut the first point cloud information according to the cutting range and the position information to obtain the point cloud sub-information.

[0064] For example, as Figure 3 shown, the horizontal field of view of the multi-line lidar is 360°, and the farthest detectable distance is l. The cutting range of the first point cloud information is a circular range with the current position of the movable device as the center and a radius of at least d, where d > l.

[0065] It should be noted that when the detection range of the lidar of the moving movable device exceeds the range of the current point cloud sub-information, the first point cloud information is re-cut according to the detection range of the movable device.

[0066] Step 206: Downsample the second point cloud information and the point cloud sub-information, and perform point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub-information to obtain the second pose information.

[0067] In order to improve the accuracy of point cloud matching, in the embodiments of the present disclosure, the second point cloud information and the point cloud sub-information may be downsampled, and the downsampled second point cloud information and the downsampled point cloud sub-information may be subjected to point cloud matching to obtain the second pose information in the point cloud coordinate system.

[0068] Step 207: Convert the sampling frequency of the second pose information according to the first pose information to obtain the target pose information of the first sampling frequency of the movable device in the point cloud coordinate system.

[0069] It should be noted that the execution processes of steps 201 to 204 and step 207 may be implemented in any one of the embodiments of the present disclosure respectively. The embodiments of the present disclosure do not make any limitations in this regard and will not be elaborated further.

[0070] In summary, by determining the point cloud sub - information corresponding to the mobile device at the target moment from the first point cloud information, downsampling the second point cloud information and the point cloud sub - information, and performing point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub - information to obtain the second pose information. Thus, through point cloud matching of the second point cloud information and the point cloud sub - information, the second pose information of the mobile device in the point cloud coordinate system can be accurately determined, and the data volume of point cloud matching is reduced.

[0071] To clearly illustrate how the above - mentioned embodiment downsamples the second point cloud information and the point cloud sub - information, and performs point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub - information to obtain the second pose information of the mobile device in the point cloud coordinate system at the target moment, the present disclosure proposes another positioning method for mobile devices underground in mines.

[0072] Figure 4 It is a schematic flowchart of a positioning method for a mobile device underground in mines provided by an embodiment of the present disclosure.

[0073] As Figure 4 shown, the positioning method for the mobile device underground in mines may include:

[0074] Step 401, obtain the first point cloud information underground in the mine.

[0075] Step 402, use the lidar carried on the mobile device to detect underground in the mine at the first sampling frequency to obtain radar signals.

[0076] Step 403, predict the pose of the mobile device at the target moment based on the radar signals to obtain the first pose information of the mobile device in the body coordinate system at the target moment.

[0077] Step 404, determine the second point cloud information corresponding to the mobile device at the target moment based on the radar signals.

[0078] Step 405, determine the point cloud sub - information corresponding to the mobile device at the target moment from the first point cloud information.

[0079] Step 406, use the grid filter with the first grid size to downsample the second point cloud information and the point cloud sub - information respectively to obtain the third point cloud information and the first point cloud sub - information.

[0080] To improve the efficiency and accuracy of point cloud matching, in the embodiment of the present disclosure, the grid filter with the first grid size (for example, the voxel side length is r1) can be used to downsample the second point cloud information and the point cloud sub - information respectively to obtain the third point cloud information and the first point cloud sub - information.

[0081] Step 407: Use a grid filter with a second grid size to downsample the second point cloud information and the point cloud sub-information respectively, so as to obtain a fourth point cloud information and a second point cloud sub-information.

[0082] Wherein, the first grid size is greater than the second grid size.

[0083] Similarly, use a grid filter with a second grid size (for example, the voxel side length is r2, r2 < r1, and r1 is the voxel side length of the first grid size) to downsample the second point cloud information and the point cloud sub-information respectively, so as to obtain a fourth point cloud information and a second point cloud sub-information.

[0084] Step 408: Perform point cloud matching on the third point cloud information and the first point cloud sub-information to obtain the reference pose information of the movable device in the point cloud coordinate system at the target moment.

[0085] In the embodiments of the present disclosure, a point cloud matching algorithm can be used to perform point cloud matching (coarse matching) on the third point cloud information and the first point cloud sub-information to obtain the reference pose information of the movable device in the point cloud coordinate system at the target moment. It should be noted that the point cloud matching algorithm can include, but is not limited to: data registration method (Iterative Closest Point, abbreviated as ICP), Normal Distribution Transformation (abbreviated as NDT), etc.

[0086] Step 409: Based on the reference pose information, perform point cloud matching on the fourth point cloud information and the second point cloud sub-information to obtain a second pose information.

[0087] Furthermore, using the reference pose information as the initial value of point cloud matching, use a point cloud matching algorithm to perform point cloud matching (fine matching) on the fourth point cloud information and the second point cloud sub-information to obtain a second pose information.

[0088] For example, as Figure 5 shown, Figure 5 is a schematic flow chart of the matching of the second point cloud information and the point cloud sub-information in the embodiments of the present disclosure. In Figure 5 taking the movable device as a drone as an example, the steps of the matching of the second point cloud information and the point cloud sub-information can be as follows:

[0089] 1. Obtain the current point cloud sub-information (point cloud sub-information);

[0090] 2. Determine whether the field of view range of the lidar on the drone exceeds the current point cloud sub-information;

[0091] 3. When the field of view of the airborne lidar of the drone exceeds the current point cloud sub-information, re-cut the first point cloud information according to the field of view of the airborne lidar of the drone to obtain the point cloud sub-information, and execute step 5;

[0092] 4. When the field of view of the airborne lidar of the drone does not exceed the current point cloud sub-information, execute step 5;

[0093] 5. Coarsely match the data after voxel downsampling of the point cloud sub-information and the drone environmental point cloud (target point cloud information) to obtain the coarse pose information (reference pose information);

[0094] For example, voxel downsampling filtering is performed on the point cloud sub-information p M_i and the point cloud information p b at the current position of the movable device, with the voxel side length being r1, to obtain the filtered sub-map point cloud p' M_i and the filtered current environmental point cloud p b '. Then, point cloud matching is performed on the two groups of point clouds p' M_i and p b ' to obtain the coarse pose information (reference pose information);

[0095] 6. Using the coarse pose information as the initial value, finely match the data after voxel downsampling of the point cloud sub-information and the drone environmental point cloud to obtain the absolute pose data (second pose information) of the current position of the drone.

[0096] For example, voxel downsampling filtering is performed on the point cloud sub-information p M_i and the point cloud information p b at the current position of the drone, with the voxel side length being r2, where r2 < r1, to obtain the filtered sub-map point cloud p″ M_i and the filtered current environmental point cloud p″ b ″. Using the pose information obtained from the coarse matching as the initial pose, point cloud matching is performed on the two groups of point clouds p″ M_i and p″ b to obtain the absolute pose of the drone currently underground in the coordinate system of the point cloud information

[0097] Step 410. According to the first pose information, convert the sampling frequency of the second pose information to obtain the target pose information at the first sampling frequency of the movable device in the point cloud coordinate system.

[0098] It should be noted that the execution processes of steps 401 to 405 and step 410 can be implemented in any one of the embodiments of the present disclosure respectively. The embodiments of the present disclosure do not make any limitations in this regard and will not be elaborated further.

[0099] In summary, by using a grid filter with a first grid size to downsample the second point cloud information and the point cloud sub-information respectively to obtain the third point cloud information and the first point cloud sub-information; using a grid filter with a second grid size to downsample the second point cloud information and the point cloud sub-information respectively to obtain the fourth point cloud information and the second point cloud sub-information; performing point cloud matching on the third point cloud information and the first point cloud sub-information to obtain the reference pose information of the mobile device in the point cloud coordinate system at the target moment; based on the reference pose information, performing point cloud matching on the fourth point cloud information and the second point cloud sub-information to obtain the second pose information. Thus, by using grid filters with different grid sizes to downsample the second point cloud information and the point cloud sub-information respectively, and performing point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub-information, the efficiency and accuracy of point cloud matching are improved.

[0100] To clearly illustrate how the above embodiments determine the second point cloud information corresponding to the mobile device at the target moment based on the radar signal, the present disclosure proposes another positioning method for the mobile device in the mine.

[0101] Figure 6 It is a schematic flowchart of a positioning method for a mobile device in a mine provided by an embodiment of the present disclosure.

[0102] As Figure 6 shown, the positioning method for the mobile device in the mine may include:

[0103] Step 601, obtain the first point cloud information in the mine.

[0104] Step 602, use the lidar mounted on the mobile device to detect the mine at the first sampling frequency to obtain the radar signal.

[0105] Step 603, predict the pose of the mobile device at the target moment based on the radar signal to obtain the first pose information of the mobile device in the body coordinate system at the target moment.

[0106] Step 604, determine the fifth point cloud information of the mobile device in the body coordinate system at the target moment based on the radar signal.

[0107] In the embodiment of the present disclosure, the three-dimensional point cloud data of the mobile device in the body coordinate system at the target moment can be obtained according to the emission signal and the reflected radar signal emitted by the multi-line lidar or the solid-state lidar, and the three-dimensional point cloud data of the mobile device in the body coordinate system at the target moment is used as the fifth point cloud information.

[0108] Step 605, determine the first mapping relationship between the body coordinate system and the point cloud coordinate system at the target moment according to the set pose data of the mobile device in the point cloud coordinate system at the target moment.

[0109] In an embodiment of the present disclosure, the set pose data of the mobile device at the target moment in the point cloud coordinate system may be the pose information of the mobile device at the previous moment of the target moment in the point cloud coordinate system, and the pose information of the mobile device at the initial moment in the point cloud coordinate system may be the set pose information.

[0110] Furthermore, according to the pose information of the mobile device at the previous moment of the target moment in the point cloud coordinate system and the pose information of the mobile device in the body coordinate system, the mapping relationship between the body coordinate system and the point cloud coordinate system at the target moment is determined, and this mapping relationship is used as the first mapping relationship.

[0111] Step 606: Determine the sixth point cloud information corresponding to the fifth point cloud information in the point cloud coordinate system according to the first mapping relationship.

[0112] Furthermore, according to this first mapping relationship, the sixth point cloud information corresponding to the fifth point cloud information in the point cloud coordinate system can be determined.

[0113] Step 607: Use the sixth point cloud information as the second point cloud information corresponding to the mobile device at the target moment.

[0114] In an embodiment of the present disclosure, the sixth point cloud information can be used as the second point cloud information corresponding to the mobile device at the target moment.

[0115] Step 608: Downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment.

[0116] Step 609: Convert the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the mobile device in the point cloud coordinate system.

[0117] It should be noted that the execution processes of steps 601 to 603 and step 609 can be implemented in any one of the embodiments of the present disclosure respectively. The embodiments of the present disclosure do not make any limitations on this and will not be elaborated further.

[0118] In summary, based on the radar signal, the fifth point cloud information of the mobile device in the body coordinate system at the target moment is determined; according to the set pose data of the mobile device in the point cloud coordinate system at the target moment, the first mapping relationship between the body coordinate system and the point cloud coordinate system at the target moment is determined; according to the first mapping relationship, the sixth point cloud information corresponding to the fifth point cloud information in the point cloud coordinate system is determined; the sixth point cloud information is used as the second point cloud information corresponding to the mobile device at the target moment. Thus, according to the mapping relationship between the body coordinate system and the point cloud coordinate system, the point cloud information of the mobile device in the body coordinate system at the target moment can be mapped to the point cloud coordinate system.

[0119] To clearly illustrate how the above embodiment converts the sampling frequency of the second pose information according to the first pose information to obtain the target pose information with the first sampling frequency of the mobile device in the point cloud coordinate system, the present disclosure proposes another positioning method for the mobile device in the mine.

[0120] Figure 7 It is a schematic flowchart of a positioning method for a mobile device in a mine provided by an embodiment of the present disclosure.

[0121] As Figure 7 shown, the positioning method for the mobile device in the mine may include:

[0122] Step 701, obtain the first point cloud information in the mine.

[0123] Step 702, use the lidar mounted on the mobile device to detect the mine at the first sampling frequency to obtain radar signals.

[0124] Step 703, predict the pose of the mobile device at the target moment based on the radar signal to obtain the first pose information of the mobile device in the body coordinate system at the target moment.

[0125] Step 704, determine the second point cloud information corresponding to the mobile device at the target moment based on the radar signal.

[0126] Step 705, downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information with the second sampling frequency of the mobile device in the point cloud coordinate system at the target moment.

[0127] Step 706, determine the second mapping relationship between the body coordinate system and the point cloud coordinate system at the initial moment according to the second pose information and the first pose information.

[0128] Wherein, the initial moment is used to indicate that the mobile device switches from a stationary state to a start operation state.

[0129] In an embodiment of the present disclosure, based on the second pose information, an inverse transformation of the first pose information is performed to obtain the pose transformation relationship from the body coordinate system of the mobile device to the point cloud coordinate system at the initial moment, and the pose transformation relationship from the body coordinate system of the mobile device to the point cloud coordinate system at the initial moment is used as the second mapping relationship.

[0130] For example, taking the second pose information as and the first pose information as T b_j as an example, the second mapping relationship

[0131] Step 707: Multiply the mapping relationship between the body coordinate system and the point cloud coordinate system at the initial moment by the first pose information, and use the result as the target pose information of the mobile device at the first sampling frequency in the point cloud coordinate system.

[0132] Furthermore, according to the second mapping, a relative pose transformation between coordinate systems is performed on the first pose information to obtain the target pose information of the mobile device at the first sampling frequency in the point cloud coordinate system.

[0133] For example, taking the second mapping relationship as and the first pose information as T b_j , the target pose information

[0134] It should be noted that the execution processes of steps 701 to 705 can be implemented in any one of the embodiments of the present disclosure. The embodiments of the present disclosure do not make any limitations in this regard and will not be elaborated further.

[0135] In summary, by determining the second mapping relationship between the body coordinate system and the point cloud coordinate system at the initial moment according to the second pose information and the first pose information; multiplying the mapping relationship between the body coordinate system and the point cloud coordinate system at the initial moment by the first pose information, and using the result as the target pose information of the mobile device at the first sampling frequency in the point cloud coordinate system. Thus, according to the second pose information and the first pose information, the mapping relationship between the body coordinate system and the point cloud coordinate system when the mobile device starts to operate can be determined. Furthermore, according to this mapping relationship and the first pose information, the pose information at a relatively high sampling frequency can be effectively determined.

[0136] To illustrate the above embodiments more clearly, examples are given below for illustration.

[0137] For example, as Figure 8 shown, Figure 8 is a flowchart of a positioning method for a mobile device in a mine in an embodiment of the present disclosure. In Figure 8Among them, taking a mobile device as an example of a drone, the positioning method of the mobile device in the mine can specifically include the following steps:

[0138] 1. Use laser SLAM to determine the relative pose of the drone with respect to the take-off position;

[0139] 2. Obtain the environmental point cloud information (the second point cloud information) of the current position of the drone according to the on-board lidar, and perform point cloud matching between the environmental point cloud information and the point cloud sub-information (the point cloud sub-information under the first point cloud information) to obtain the absolute pose of the drone at the second sampling frequency in the current mine;

[0140] 3. Use the absolute pose data of the drone at the second sampling frequency in the mine and the current relative pose of the drone to determine the relative transformation between the relative coordinate system (the body coordinate system at take-off) of the drone and the absolute coordinate system in the mine (the point cloud coordinate system);

[0141] 4. Fuse the relative pose of the drone and the relative pose change between the coordinate systems to obtain the absolute pose data of the drone in the mine at the first sampling frequency, where the first sampling frequency can be greater than the second sampling frequency;

[0142] 5. Use the absolute pose data of the drone in the mine at the first sampling frequency at the current moment to determine the second point cloud information of the drone in the point cloud coordinate system at the next moment.

[0143] The positioning method for the movable device underground in the embodiments of the present disclosure includes: obtaining the first point cloud information underground in the mine; using the lidar mounted on the movable device to detect underground in the mine at the first sampling frequency to obtain radar signals; predicting the pose of the movable device at the target moment based on the radar signals to obtain the first pose information of the movable device in the body coordinate system at the target moment; determining the second point cloud information corresponding to the movable device at the target moment based on the radar signals; downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment; converting the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the movable device in the point cloud coordinate system. Thus, by downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information, the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment can be accurately determined. Furthermore, by converting the second pose information at the second sampling frequency according to the first pose information at the first sampling frequency, the pose information at the first sampling frequency in the point cloud coordinate system can be accurately obtained. Therefore, the precise positioning of the movable device underground in the mine can be realized according to the pose information at the first sampling frequency in the point cloud coordinate system. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the movable device underground in the mine.

[0144] To implement the above embodiments, the present disclosure also proposes a positioning device for a movable device underground in a mine.

[0145] Figure 9 The following is a schematic structural diagram of a positioning device for a movable device underground in a mine provided by an embodiment of the present disclosure.

[0146] As Figure 9 shown, the positioning device 900 for the movable device underground in the mine includes: an acquisition module 9, a detection module 920, a prediction module 930, a first determination module 940, a second determination module 950, and a conversion module 960.

[0147] Among them, an acquisition module 910 is configured to acquire first point cloud information underground in a mine; a detection module 920 is configured to detect underground in the mine by using a lidar mounted on a movable device at a first sampling frequency to obtain radar signals; a prediction module 930 is configured to predict the pose of the movable device at a target moment based on the radar signals to obtain first pose information of the movable device in a body coordinate system at the target moment; a first determination module 940 is configured to determine second point cloud information corresponding to the movable device at the target moment based on the radar signals; a second determination module 950 is configured to downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain second pose information at the second sampling frequency of the movable device in a point cloud coordinate system at the target moment; a conversion module 960 is configured to convert the sampling frequency of the second pose information according to the first pose information to obtain target pose information at the first sampling frequency of the movable device in the point cloud coordinate system.

[0148] As a possible implementation manner of an embodiment of the present disclosure, the second determination module 950 is configured to: determine point cloud sub-information corresponding to the movable device at the target moment from the three-dimensional point cloud information; downsample the target point cloud information and the point cloud sub-information, and perform point cloud matching on the downsampled target point cloud information and the downsampled point cloud sub-information to obtain the second pose information.

[0149] As a possible implementation manner of an embodiment of the present disclosure, the second determination module 950 is further configured to: respectively downsample the second point cloud information and the point cloud sub-information by using a grid filter with a first grid size to obtain third point cloud information and first point cloud sub-information; respectively downsample the second point cloud information and the point cloud sub-information by using a grid filter with a second grid size to obtain fourth point cloud information and second point cloud sub-information, where the first grid size is greater than the second grid size; perform point cloud matching on the third point cloud information and the first point cloud sub-information to obtain reference pose information of the movable device in a point cloud coordinate system at the target moment; based on the reference pose information, perform point cloud matching on the fourth point cloud information and the second point cloud sub-information to obtain the second pose information.

[0150] As a possible implementation manner of an embodiment of the present disclosure, the second determination module 950 is further configured to: determine the position information of the movable device at the target moment according to the second point cloud information; determine the cutting range of the first point cloud information according to the detection range of the lidar; cut the first point cloud information according to the cutting range and the position information to obtain the point cloud sub-information.

[0151] As a possible implementation manner of an embodiment of the present disclosure, a first determination module 940 is configured to determine fifth point cloud information of the movable device in the body coordinate system based on a radar signal; determine a first mapping relationship between the body coordinate system and the point cloud coordinate system at a target moment according to the set pose data of the movable device in the point cloud coordinate system at the target moment; determine sixth point cloud information corresponding to the fifth point cloud information in the point cloud coordinate system according to the first mapping relationship; and use the fifth point cloud information as the second point cloud information corresponding to the movable device at the target moment.

[0152] As a possible implementation manner of an embodiment of the present disclosure, a conversion module 950 is configured to: determine a second mapping relationship between the body coordinate system and the point cloud coordinate system at an initial moment according to the second pose information and the first pose information, where the initial moment is used to indicate that the movable device switches from a stationary state to a start operation state; and use the product of the second mapping relationship and the first pose information as the target pose information of the first sampling frequency of the movable device in the point cloud coordinate system.

[0153] As a possible implementation manner of an embodiment of the present disclosure, an acquisition module 910 is configured to acquire a plurality of third point cloud sub-information at a plurality of spatial positions in a mine; and perform point cloud information construction on the plurality of third point cloud sub-information by using simultaneous localization and mapping (SLAM) to obtain first point cloud information.

[0154] The positioning device for the movable device underground in the mine according to the embodiments of the present disclosure obtains the first point cloud information underground in the mine; uses the lidar carried on the movable device to detect underground in the mine at the first sampling frequency to obtain radar signals; predicts the pose of the movable device at the target moment based on the radar signals to obtain the first pose information of the movable device in the body coordinate system at the target moment; determines the second point cloud information corresponding to the movable device at the target moment based on the radar signals; downsamples the first point cloud information and the second point cloud information, and performs point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment; converts the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the movable device in the point cloud coordinate system. Thus, by downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information, the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment can be accurately determined. Furthermore, by converting the second pose information at the second sampling frequency according to the first pose information at the first sampling frequency, the target pose information at the first sampling frequency in the point cloud coordinate system can be accurately obtained. Therefore, the precise positioning of the movable device underground in the mine can be realized according to the target pose information at the first sampling frequency in the point cloud coordinate system. When the first sampling frequency is greater than the second sampling frequency, the target pose information at the first sampling frequency can also meet the autonomous navigation requirements of the movable device underground in the mine.

[0155] It should be noted that the foregoing explanation of the embodiments of the positioning method for the movable device underground in the mine also applies to the positioning device for the movable device underground in the mine of this embodiment, and will not be elaborated here.

[0156] To implement the above embodiments, the present disclosure also proposes an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method described in the above embodiments.

[0157] To implement the above embodiments, the present disclosure also proposes a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method described in the above embodiments is implemented.

[0158] To implement the above embodiments, the present disclosure also proposes a computer program product, including a computer program, and when the computer program is executed by a processor, the method described in the above embodiments is implemented.

[0159] Figure 10 Block diagram of an electronic device according to an embodiment of the present disclosure. Figure 10 The electronic device shown is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0160] As Figure 10 shown, the electronic device 1000 includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a memory 1006 into a random access memory (RAM) 1003. In the RAM 1003, various programs and data required for the operation of the electronic device 1000 are also stored. The processor 1001, the ROM 1002, and the RAM 1003 are connected to each other via a bus 1004. An input / output (I / O) interface 1005 is also connected to the bus 1004.

[0161] The following components are connected to the I / O interface 1005: a memory 1006 including a hard disk, etc.; and a communication part 1007 including a network interface card such as a LAN (Local Area Network) card, a modem, etc., and the communication part 1007 performs communication processing via a network such as the Internet; a drive 1008 is also connected to the I / O interface 1005 as needed.

[0162] Specifically, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program carried on a computer-readable medium, and the computer program includes program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network via the communication part 1007. When the computer program is executed by the processor 1001, the above functions defined in the method of the present disclosure are executed.

[0163] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory 1006 including instructions, and the above instructions can be executed by the processor 1001 of the electronic device 1000 to complete the above method. Optionally, the storage medium can be a non-transitory computer-readable storage medium. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc.

[0164] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc., mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0165] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0166] Any process or method description shown in a flowchart or described in other ways herein can be understood as representing a module, segment, or portion of code including one or more executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present disclosure pertain.

[0167] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable list of executable instructions for implementing logical functions, which can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other appropriate processing as necessary, and then stored in a computer memory.

[0168] It should be understood that various parts of the present disclosure can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0169] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0170] In addition, in various embodiments of the present disclosure, each functional unit may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0171] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present disclosure have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. A positioning method for movable equipment underground in a mine, characterized in that, Including: Obtaining the first point cloud information underground in the mine; Using the lidar mounted on the movable device to detect the underground in the mine at the first sampling frequency to obtain radar signals; Predicting the pose of the movable device at the target moment based on the radar signals to obtain the first pose information of the movable device in the body coordinate system at the target moment; Determining the second point cloud information corresponding to the movable device at the target moment based on the radar signals; Downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment; Converting the sampling frequency of the second pose information according to the first pose information to obtain the target pose information at the first sampling frequency of the movable device in the point cloud coordinate system.

2. The method according to claim 1, characterized in that, The step of downsampling the first point cloud information and the second point cloud information, and performing point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment includes: Determining the point cloud sub-information corresponding to the movable device at the target moment from the first point cloud information; Downsampling the second point cloud information and the point cloud sub-information, and performing point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub-information to obtain the second pose information.

3. The method according to claim 2, wherein The step of downsampling the first point cloud information and the point cloud sub-information, and performing point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub-information to obtain the second pose information at the second sampling frequency of the movable device in the point cloud coordinate system at the target moment includes: Using a grid filter with a first grid size to downsample the second point cloud information and the point cloud sub-information respectively to obtain a third point cloud information and a first point cloud sub-information; Using a grid filter with a second grid size to downsample the second point cloud information and the point cloud sub-information respectively to obtain a fourth point cloud information and a second point cloud sub-information, where the first grid size is greater than the second grid size; Performing point cloud matching on the third point cloud information and the first point cloud sub-information to obtain the reference pose information of the movable device in the point cloud coordinate system at the target moment; Based on the reference pose information, performing point cloud matching on the fourth point cloud information and the second point cloud sub-information to obtain the second pose information.

4. The method according to claim 3, wherein The step of determining the point cloud sub-information corresponding to the movable device at the target moment from the first point cloud information includes: Determining the position information of the movable device at the target moment according to the second point cloud information; Determining the cutting range of the first point cloud information according to the detection range of the lidar; Cut the first point cloud information according to the cutting range and the position information to obtain the point cloud sub-information.

5. The method according to claim 1, characterized in that, The determining the second point cloud information corresponding to the movable device at the target moment based on the radar signal includes: Determine the fifth point cloud information of the movable device in the body coordinate system at the target moment based on the radar signal; Determine the first mapping relationship between the body coordinate system and the point cloud coordinate system at the target moment according to the set pose data of the movable device in the point cloud coordinate system at the target moment; Determine the sixth point cloud information corresponding to the fifth point cloud information in the point cloud coordinate system according to the first mapping relationship; Use the sixth point cloud information as the second point cloud information corresponding to the movable device at the target moment.

6. The method according to claim 1, characterized in that The converting the sampling frequency of the second pose information according to the first pose information to obtain the target pose information of the first sampling frequency of the movable device in the point cloud coordinate system includes: Determine the second mapping relationship between the body coordinate system and the point cloud coordinate system at the initial moment according to the second pose information and the first pose information; wherein, the initial moment is used to indicate that the movable device switches from a stationary state to a start operation state; Use the product of the second mapping relationship and the first pose information as the target pose information of the first sampling frequency of the movable device in the point cloud coordinate system.

7. The method according to any one of claims 1-6, characterized in that, The obtaining the three-dimensional point cloud information in the mine includes: Obtain multiple third point cloud sub-informations at multiple spatial positions in the mine; Use Simultaneous Localization and Mapping (SLAM) to construct point cloud information from the multiple third point cloud sub-informations to obtain the first point cloud information.

8. A positioning device for movable equipment underground in a mine, characterized in that, Includes: An acquisition module, configured to acquire the first point cloud information in the mine; A detection module, configured to detect the mine with a first sampling frequency using a lidar mounted on the movable device to obtain a radar signal; A prediction module, configured to predict the pose of the movable device at the target moment based on the radar signal to obtain the first pose information of the movable device in the body coordinate system at the target moment; A first determination module, configured to determine the second point cloud information corresponding to the movable device at the target moment based on the radar signal; A second determination module, configured to downsample the first point cloud information and the second point cloud information, and perform point cloud matching on the downsampled first point cloud information and the downsampled second point cloud information to obtain the second pose information of the second sampling frequency of the movable device in the point cloud coordinate system at the target moment; A conversion module, configured to convert the sampling frequency of the second pose information according to the first pose information to obtain the target pose information of the first sampling frequency of the movable device in the point cloud coordinate system.

9. The device according to claim 8, characterized in that The second determination module is configured to: Determine the point cloud sub-information corresponding to the movable device at the target moment from the first point cloud information; Downsample the second point cloud information and the point cloud sub-information, and perform point cloud matching on the downsampled second point cloud information and the downsampled point cloud sub-information to obtain the second pose information.

10. An electronic device, characterized in that, Comprising: At least one processor; And A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-7.

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