Mobile device positioning method, apparatus and computer-readable storage medium

Abstract

This application provides a mobile device positioning method, apparatus, and computer-readable storage medium, relating to the field of motion positioning algorithm technology. The method includes: acquiring a mapping map library; wherein the mapping map library is generated by matching a first map and a second map; determining the sensing position of the mobile device under test in the second map of the mapping map library based on target sensing data of the mobile device under test; and determining the target position of the mobile device under test in the first map of the mapping map library based on the sensing position, thereby locating the mobile device under test; wherein the first map is constructed based on image data collected in the target area, and the second map is constructed based on historical sensing data collected by the sensing device as it moves in the target area. By matching different maps corresponding to image data and sensing data to obtain the corresponding mapping map library, the actual position of the mobile device can be determined according to the actual situation of the mobile device, improving the effectiveness and accuracy of positioning.

Description

Technical Field

[0001] This application relates to the field of motion positioning algorithm technology, and more specifically, to a mobile device positioning method, apparatus, and computer-readable storage medium. Background Technology

[0002] During the transportation of molten iron, specific work sites, such as the tapping point under the blast furnace, the tapping point for adding scrap steel, and the location for lifting and placing small ladles in the steelmaking workshop, need to be precisely positioned. Inaccurate positioning may lead to leaks of molten iron. Since the temperature of molten iron can reach as high as 1400℃, leaks of this high-temperature molten liquid may cause dangerous accidents such as damage to production and equipment, resulting in significant economic losses and even threatening the lives of workers.

[0003] In existing technologies, GPS, wheeled odometers, laser rangefinders, RFID, and image recognition are commonly used for locating workstations during molten iron transportation. However, in areas with severe obstructions, such as overpasses or under furnaces, GPS information can be lost or drift significantly, and wheeled odometers also have large cumulative errors. Furthermore, when locating specific workstations under furnaces that extend through the furnace, laser rangefinders cannot function because reflectors cannot be installed. In situations with molten iron or steel spraying everywhere, RFID cards are prone to degradation at high temperatures, leading to a high rate of missed reads. Image-based positioning methods are easily affected by smoke and light intensity. These factors result in low positioning accuracy during molten iron transportation, failing to effectively guarantee safety and efficiency during production. Summary of the Invention

[0004] In view of this, the purpose of this application is to provide a mobile device positioning method, apparatus and computer-readable storage medium to improve the problem of low positioning accuracy of mobile devices in the process of transporting molten iron in the prior art.

[0005] To address the aforementioned problems, in a first aspect, embodiments of this application provide a mobile device positioning method, the method comprising:

[0006] Obtain a mapping map library; wherein the mapping map library is generated by matching a first map and a second map;

[0007] Based on the target sensor data of the mobile device under test, determine the sensor position of the mobile device under test in the second map in the mapping map library;

[0008] Based on the sensor location, the target location of the mobile device under test in the first map is determined in the mapping map library to locate the mobile device under test;

[0009] The first map is constructed based on image data collected in the target area, and the second map is constructed based on historical sensor data collected by the sensor device as it moves in the target area.

[0010] In the above implementation process, by matching image data with different maps corresponding to sensor data to obtain a corresponding mapping map library, the sensing position of the mobile device in the second map corresponding to the sensor data can be determined according to the actual situation of the mobile device. Then, based on the mapping map library and the sensing position, the actual target position of the mobile device under test in the first map can be determined, thus achieving precise positioning of the mobile device. Positioning is unaffected by factors such as high temperature, smoke, dust, light intensity, GPS signal obstruction, or other factors requiring specific installation space (such as laser rangefinder reflector installation). This improves the effectiveness, accuracy, and stability of positioning the mobile device at any location in the work area, effectively ensuring the accuracy of the mobile device at various specific work points during molten iron transportation. It is suitable for various complex working environments, thereby effectively improving production safety and work efficiency.

[0011] Optionally, the first map includes multiple first work routes in the target area, and the second map includes multiple second work routes in the target area;

[0012] The acquisition of the mapping map library includes:

[0013] Mark the start and end positions of each of the first and second work routes;

[0014] Multiple sets of associated routes are determined based on the starting position and the ending position; wherein each set of associated routes includes the first working route and the corresponding second working route;

[0015] The first coordinates in the first working route and the second coordinates in the second working route are matched to obtain the mapping relationship between the first coordinates and the second coordinates;

[0016] The mapping map library is constructed based on the multiple mapping relationships.

[0017] In the above implementation process, since both types of maps contain multiple work routes within the work area, when matching the two types of maps, the associated routes corresponding to the actual routes in the actual work area can be determined based on the actual situation and correspondence of the work routes in each of the two maps. This allows for the matching of coordinates within the two work routes in the associated routes, obtaining the mapping relationship between the two coordinate systems. Multiple mapping relationships are then used to construct a mapping map library for bidirectional conversion between the two maps. This enables one-to-one mapping and effective association of locations between the two different maps, allowing for accurate and effective positioning by combining the map database and the actual situation of the mobile device.

[0018] Optionally, matching each first coordinate in the first working route and each second coordinate in the second working route to obtain the mapping relationship between the first coordinate and the second coordinate includes:

[0019] The first working route and the second working route in the associated route are divided proportionally to determine multiple first coordinates and multiple second coordinates;

[0020] Interpolation processing is performed on multiple first coordinates and multiple second coordinates respectively to obtain equidistant calibration data;

[0021] Based on the equidistant calibration data, the mapping relationship between each first coordinate and the corresponding second coordinate is determined.

[0022] In the above implementation process, when mapping the two types of coordinates in the two maps to a one-to-one correspondence, the working route can first be divided proportionally to determine the two corresponding coordinates. Then, interpolation is performed on the two coordinates separately to achieve equidistant calibration. Based on the obtained equidistant calibration, the two coordinates are mapped one-to-one, resulting in multiple corresponding mapping relationships, thus realizing bidirectional conversion between coordinates at various locations on the two maps. This ability to perform corresponding mapping processing based on the correspondence between the two maps effectively improves the accuracy and precision of the mapping relationships.

[0023] Optionally, determining the sensing location of the mobile device under test in the second map of the mapping map library based on the target sensing data of the mobile device under test includes:

[0024] Acquire the target sensing data collected by the target sensing device in the mobile device under test when it is positioned in the target area;

[0025] Based on the target sensing data, the corresponding sensing location in the second map is determined in the mapping map library.

[0026] In the above implementation process, when locating the mobile device under test, the accuracy of the positioning information in the first map may be affected by factors such as high temperature, smoke, dust, light intensity, GPS signal obstruction, or other factors that require specific installation space (such as the installation of a laser rangefinder reflector). Therefore, the accuracy can be improved by first determining the corresponding sensor position in the second map based on the target sensor data collected by the target sensor device installed in the mobile device under test during positioning in the target area, and then using the mapping map library. The sensor position is unaffected by adverse factors and can quickly and accurately reflect the actual situation of the mobile device under test. Thus, the true target position of the mobile device under test can be obtained through the mapping conversion between the two maps.

[0027] Optionally, determining the target location of the mobile device under test in the first map based on the sensing location in the mapped map library includes:

[0028] Based on the sensor location, the target mapping relationship between the first map and the second map is obtained by querying the mapping map library.

[0029] Based on the target mapping relationship, the target location in the first map corresponding to the sensing location is determined.

[0030] In the above implementation process, a corresponding query can be performed in the mapping map library based on the sensor location to determine the target mapping relationship between the first map and the second map corresponding to the sensor location. This target mapping relationship determines the mapping of position coordinates between the two maps, identifying the target location in the first map corresponding to the sensor location. This target location is then used as the actual position coordinates obtained when locating the mobile device under test. Positioning through the mapping relationship between the two maps enables accurate and effective location in various adverse scenarios, based on the actual situation of the mobile device under test, thereby improving the effectiveness and accuracy of the target location.

[0031] Optionally, the first map is generated by constructing it in the following manner:

[0032] Acquire the image data captured by photographing the target area;

[0033] Feature points are calibrated based on the image data to obtain calibration data;

[0034] The calibration data is processed based on a preset processing technique to obtain a first map with multiple first working routes;

[0035] The preset processing technology includes real-time dynamic technology.

[0036] In the above implementation process, before positioning, feature point calibration and preprocessing can be performed based on the actual image data collected in the target area to construct a corresponding visual point cloud map according to the actual situation of the target area, which effectively improves the real-time performance and accuracy of the first visual map constructed based on the image data.

[0037] Optionally, the second map is generated by constructing it in the following manner:

[0038] The historical sensing data collected by the sensing device as it moves within the target area is acquired; wherein the sensing device includes at least one of a lidar device, an inertial measurement unit, and a navigation satellite device.

[0039] The historical sensor data is coupled to obtain a second map with multiple second working routes.

[0040] In the above implementation process, before positioning, the sensors in the test mobile device can be moved in the target area to collect various types of historical sensor data for coupling processing. Based on the actual position of the test mobile device and each object in the working area, a corresponding laser point cloud map can be constructed, which effectively improves the real-time performance and accuracy of the second laser map constructed based on historical sensor data.

[0041] Optionally, the method further includes:

[0042] Acquire the pose data of the mobile device under test at the target location;

[0043] The working state of the mobile device under test is determined based on the pose data.

[0044] In the above implementation process, after locating the actual target position of the mobile device under test in vision, the working status of the mobile device under test during positioning can be determined based on the pose data collected at the target position and the target position. This enables effective monitoring of the working status of the mobile device under test during molten iron transportation, further improving safety and work efficiency during production.

[0045] Secondly, embodiments of this application also provide a mobile device positioning device, the device comprising: an acquisition module, a first positioning module, and a second positioning module;

[0046] The acquisition module is used to acquire a mapping map library; wherein, the mapping map library is generated based on the matching of a first map and a second map;

[0047] The first positioning module is used to determine the sensing position of the mobile device under test in the second map in the mapping map library based on the target sensing data of the mobile device under test;

[0048] The second positioning module is used to determine the target location of the mobile device under test in the first map in the mapping map library based on the sensing location, so as to locate the mobile device under test;

[0049] The first map is constructed based on image data collected in the target area, and the second map is constructed based on historical sensor data collected by the sensor device as it moves in the target area.

[0050] In the above implementation process, the acquisition module matches the image data with the different maps corresponding to the sensor data to obtain the corresponding mapping map library. The first positioning module determines the sensing position of the mobile device in the second map corresponding to the sensor data based on the actual situation of the mobile device. The second positioning module determines the actual target position of the mobile device under test in the first map based on the mapping map library and the sensing position, so as to achieve accurate positioning of the mobile device.

[0051] Thirdly, embodiments of this application also provide an electronic device, which includes a memory and a processor. The memory stores program instructions, and when the processor reads and runs the program instructions, it executes the steps in any of the above-described implementations of the mobile device positioning method.

[0052] Fourthly, embodiments of this application also provide a computer-readable storage medium storing computer program instructions. When the computer program instructions are read and executed by a processor, they perform the steps in any of the above-described implementations of the mobile device positioning method.

[0053] In summary, the embodiments of this application provide a mobile device positioning method, apparatus, and computer-readable storage medium. By matching image data with different maps corresponding to sensor data to obtain a corresponding mapped map library, the actual location of the mobile device can be effectively determined according to its actual situation. Positioning is unaffected by factors such as high temperature, smoke, dust, light intensity, GPS signal obstruction, or other space-restricted installation requirements (such as laser rangefinder reflector installation). This improves the effectiveness, accuracy, and stability of positioning the mobile device at any location in the work area, effectively ensuring the accuracy of the mobile device at various specific work sites during molten iron transportation. It is suitable for various complex working environments, thereby effectively improving production safety and work efficiency. Attached Figure Description

[0054] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0055] Figure 1 A block diagram illustrating an electronic device provided in an embodiment of this application;

[0056] Figure 2 A flowchart illustrating a mobile device positioning method provided in an embodiment of this application;

[0057] Figure 3 A detailed flowchart of step S200 provided for an embodiment of this application;

[0058] Figure 4 A detailed flowchart of step S230 provided for an embodiment of this application;

[0059] Figure 5 A detailed flowchart of step S300 provided for an embodiment of this application;

[0060] Figure 6 A detailed flowchart of step S400 provided for an embodiment of this application;

[0061] Figure 7 A flowchart illustrating another mobile device positioning method provided in an embodiment of this application;

[0062] Figure 8 A flowchart illustrating yet another mobile device positioning method provided in this application embodiment;

[0063] Figure 9 A flowchart illustrating another mobile device positioning method provided in an embodiment of this application;

[0064] Figure 10 This is a schematic diagram of the structure of a mobile device positioning device provided in an embodiment of this application.

[0065] Icons: 100 - Electronic device; 111 - Memory; 112 - Memory controller; 113 - Processor; 114 - Peripheral interface; 115 - Input / output unit; 116 - Display unit; 700 - Mobile device positioning device; 710 - Acquisition module; 720 - First positioning module; 730 - Second positioning module. Detailed Implementation

[0066] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of the embodiments of this application.

[0067] In existing technologies, to reduce economic losses and safety hazards caused by inaccurate positioning of mobile equipment, such as molten iron transport vehicles, when working at specific work sites during molten iron transportation, technologies such as GPS, wheeled odometers, laser rangefinders, RFID, and image recognition are commonly used for positioning. For example, the spatial outline dimensions of the transporting mobile equipment are obtained based on GNSS (Global Navigation Satellite System) or image technology combined with radar ranging systems. A rail-mounted traction vehicle is then activated to move the mobile equipment according to its spatial outline dimensions and error range to precisely adjust its position. RFID technology is also applied to molten iron transportation positioning to improve the accuracy of vehicle positioning at specific work sites. However, due to the complexity of the steel plant environment during molten iron transportation—for example, in heavily obstructed areas such as viaducts or under furnaces—GPS information can be lost or experience significant drift, and the cumulative error of wheeled odometers is also substantial. Furthermore, when locating specific workstations under the furnace in some through-type furnaces, the laser rangefinder cannot function because a reflector cannot be installed. In situations where molten iron or steel is spraying everywhere, RFID cards in radio frequency identification (RFID) technology are prone to gradual degradation at high temperatures, leading to a high rate of missed reads. Image-based identification and positioning methods are easily affected by smoke and light intensity. This results in current positioning methods during molten iron transportation being easily affected by adverse environmental factors, leading to low positioning accuracy, inaccurate positioning of mobile devices, and poor positioning performance at specific workstations, ultimately failing to effectively guarantee safety and efficiency during production.

[0068] To address the aforementioned issues, this application provides a mobile device positioning method applicable to electronic devices, such as servers, personal computers (PCs), tablets, smartphones, and personal digital assistants (PDAs) with logical computing capabilities. This method enables positioning of mobile devices based on their actual conditions, improving the effectiveness and accuracy of positioning.

[0069] Optionally, please refer to Figure 1 , Figure 1This is a block diagram illustrating an electronic device according to an embodiment of this application. The electronic device 100 may include a memory 111, a memory controller 112, a processor 113, a peripheral interface 114, an input / output unit 115, and a display unit 116. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the electronic device 100. For example, the electronic device 100 may also include components that are more... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0070] The aforementioned memory 111, memory controller 112, processor 113, peripheral interface 114, input / output unit 115, and display unit 116 are electrically connected directly or indirectly to each other to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. The aforementioned processor 113 is used to execute executable modules stored in the memory.

[0071] The memory 111 can be, but is not limited to, Random Access Memory (RAM), Read Only Memory (ROM), Programmable Read-Only Memory (PROM), Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), etc. The memory 111 stores programs. After receiving execution instructions, the processor 113 executes the programs. The methods executed by the electronic device 100 as defined in any embodiment of this application can be applied to the processor 113, or implemented by the processor 113.

[0072] The aforementioned processor 113 may be an integrated circuit chip with signal processing capabilities. The processor 113 may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a digital signal processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor.

[0073] The peripheral interface 114 described above couples various input / output devices to the processor 113 and the memory 111. In some embodiments, the peripheral interface 114, the processor 113, and the memory controller 112 can be implemented on a single chip. In other instances, they can be implemented on separate chips.

[0074] The input / output unit 115 described above is used to provide user input data. The input / output unit 115 can be, but is not limited to, a mouse and a keyboard.

[0075] The aforementioned display unit 116 provides an interactive interface (e.g., a user interface) between the electronic device 100 and the user, or displays image data for the user's reference. In this embodiment, the display unit can be a liquid crystal display (LCD) or a touch display. If it is a touch display, it can be a capacitive touchscreen or a resistive touchscreen that supports single-point and multi-point touch operations. Supporting single-point and multi-point touch operations means that the touch display can sense touch operations generated simultaneously from one or more locations on the touch display and pass the sensed touch operations to the processor for calculation and processing. In this embodiment, the display unit 116 can display specific data or images from a first map, a second map, a mapping database, or various data such as the coordinates of the sensed position or target position obtained from positioning, and its position in the map.

[0076] The electronic device in this embodiment can be used to execute various steps in the various mobile device positioning methods provided in the embodiments of this application. The implementation process of the mobile device positioning method is described in detail below through several embodiments.

[0077] Please see Figure 2 , Figure 2This is a flowchart illustrating a mobile device positioning method provided in an embodiment of this application. The method may include steps S200-S400.

[0078] Step S200: Obtain the mapping map library.

[0079] The mapping map library is a collection of mapping relationships between various locations generated by matching the first map and the second map. The first map is constructed based on image data collected in the target area and is a high-precision visual point cloud map. The second map is constructed based on historical sensor data collected by the sensor device moving in the target area and is a laser point cloud map. The target area is a relevant area determined according to the actual working environment, such as the entire working area of ​​a steel plant, or it can be a specific area within it. The target area can be set and modified accordingly based on actual needs and circumstances.

[0080] Step S300: Determine the sensing position of the mobile device under test in the second map of the mapping map library based on the target sensing data of the mobile device under test.

[0081] The device under test (DUT) can be a mobile device that moves within the work area to perform tasks and requires positioning, such as vehicles used in molten iron transportation, such as locomotives and tank cars. The DUT communicates with the electronic device executing the positioning method through various means such as networks and Bluetooth. The DUT may be equipped with corresponding target sensing devices to collect various types of target sensing data during its movement and operation. The electronic device can obtain the current target sensing data of the DUT in real time through the communication connection when positioning is required. Based on the target sensing data, it can query the second map in the mapping map library to determine the location coordinates corresponding to the historical sensing data corresponding to the target sensing data, which is used as the sensing position obtained by the DUT in the second map.

[0082] Step S400: Based on the sensor location, determine the target location of the mobile device under test in the first map in the mapping map library to locate the mobile device under test.

[0083] Since the first map and the second map are related, the corresponding mapping relationship can be determined in the mapping map library based on the sensor location, thereby determining the visual position coordinates of the mobile device under test in the first map. This coordinates are used as the target position for locating the mobile device under test, thus enabling intuitive and accurate acquisition of the geographical location of the mobile device under test from a visual perspective. This allows for accurate judgment of whether the mobile device under test is accurately located when working at a specific work point, effectively reducing adverse situations such as leakage of high-temperature molten liquid caused by inaccurate positioning during operation.

[0084] exist Figure 2 In the illustrated embodiment, positioning is unaffected by factors such as high temperature, smoke, dust, light intensity, GPS signal obstruction, or other factors that require installation space (such as the installation of a laser rangefinder reflector). This improves the effectiveness, accuracy, and stability of positioning the mobile device at any location in the work area, effectively ensuring the accuracy of the mobile device at various specific work sites during molten iron transportation. It is suitable for a variety of complex working environments, thereby effectively improving safety and work efficiency during production.

[0085] Optionally, since multiple work routes can exist within the work area to facilitate the transfer of molten iron and materials, the first map may include multiple first work routes within the target area, and the second map may include multiple second work routes within the target area. Both the first and second work routes correspond to the actual work routes within the work area, but are represented in different structures or forms on different types of maps.

[0086] Please see Figure 3 , Figure 3 This is a detailed flowchart of step S200 provided in an embodiment of the present application. Step S200 may also include steps S210-S240.

[0087] Step S210: Mark the start and end positions of each first work route and each second work route.

[0088] The starting and ending positions of each work route in the first and second maps can be marked to determine the specific direction and scope of each work route.

[0089] Optionally, during calibration, each working route in the visual point cloud and laser point cloud can be established in two separate maps, such as a pose data table of a railway route, to number each working route. The start and end positions of each working route are uniquely determined in both maps.

[0090] Step S220: Determine multiple sets of associated routes based on the start and end positions.

[0091] Among them, based on RTK (Real-time kinematic, a differential method for processing carrier phase observations from two measurement stations in real time, which sends the carrier phase collected by the reference station to the user receiver for differential coordinate calculation) technology, the same starting and ending positions are marked on the two maps for each actual working route in the working area, so as to determine the first working route and the second working route with the same starting and ending positions, and combine them into a set of corresponding associated routes, thereby performing corresponding association processing on each working route in the first map and the second map.

[0092] Step S230: Match each first coordinate in the first working route with each second coordinate in the second working route to obtain the mapping relationship between the first coordinate and the second coordinate.

[0093] Since there is a correspondence between the coordinates of each location in the first map and the coordinates of each location in the second map, that is, the coordinates of the laser point cloud map in its coordinate system are essentially corresponding to the coordinates of the visual point cloud map in its coordinate system, it is possible to obtain two types of coordinates in the two routes of the associated route, namely, multiple first coordinates in the first working route in the first coordinate system of the first map, and multiple second coordinates in the second working route in the second coordinate system of the second map, so as to match the coordinates in the two coordinate systems accordingly to determine the mapping relationship between each first coordinate and the second coordinate.

[0094] Step S240: Construct a mapping map library based on multiple mapping relationships.

[0095] Among them, a mapping map library can be built on the working map of the working area based on multiple mapping relationships. The working map of the working area can include multiple specific working points, and each specific working point can correspond to a corresponding first coordinate and a second coordinate.

[0096] exist Figure 3 In the illustrated embodiment, locations between two different maps can be mapped one-to-one and effectively associated to achieve accurate and effective positioning by combining the map database and the actual situation of the mobile device.

[0097] Optionally, please refer to Figure 4 , Figure 4 This is a detailed flowchart of step S230 provided in an embodiment of the present application. Step S230 may also include steps S231-S233.

[0098] Step S231: Divide the first working route and the second working route in the associated route into equal proportions to determine multiple first coordinates and multiple second coordinates.

[0099] In this process, multiple proportionally divided coordinate positions can be marked on two routes in the associated route, which can then be used as coordinate data for matching and mapping.

[0100] Step S232: Interpolate multiple first coordinates and multiple second coordinates respectively to obtain equidistant calibration data.

[0101] Interpolation can be performed on the first and second coordinates separately to proportionally interpolate the distance between each pair of points. The interpolation algorithm can be as follows: Let the two second coordinates on the second working route in the second map of the associated route be (X(i), Y(i)) and (X(i+1), Y(i+1)), and let n be the total number of interpolation points between these two points. Then, for each j point belonging to [1, n]:

[0102]

[0103] Various interpolation methods can be used to perform equidistant calibration on two different coordinate systems of the laser point cloud map and the high-precision visual point cloud map, respectively, to obtain the corresponding equidistant calibration data.

[0104] Step S233: Based on the equidistant calibration data, determine the mapping relationship between each first coordinate and the corresponding second coordinate.

[0105] In this process, the coordinates of each location between the two maps are mapped one-to-one using equidistant calibration data to obtain the mapping relationship between the coordinates of each location, so as to complete the two-way conversion from point cloud map coordinates to visual map coordinates.

[0106] exist Figure 4 In the illustrated embodiment, corresponding mapping processing can be performed based on the correspondence between the two maps, effectively improving the accuracy and precision of the mapping relationship.

[0107] Optionally, please refer to Figure 5 , Figure 5 This is a detailed flowchart of step S300 provided in an embodiment of the present application. Step S300 may also include steps S310-S320.

[0108] Step S310: Obtain target sensing data collected by the target sensing device in the mobile device under test when it is positioning in the target area.

[0109] Based on information such as the lidar field of view of the mobile device under test and its vehicle type characteristics, corresponding target sensing devices can be installed on the front, rear, left and right sides, and bottom of the mobile device. These target sensing devices can include lidar equipment, IMU (Inertial Measurement Unit, used to measure the three-axis attitude angles, angular rates, and accelerations of an object), GNSS (Global Navigation Satellite System), and other devices. When locating the mobile device under test, the accuracy of the positioning information in the first map may be affected by factors such as high temperature, smoke, dust, light intensity, GPS signal obstruction, or other space-restricted installation requirements (such as the installation of a laser rangefinder reflector). Therefore, when locating the mobile device under test, various types of target sensing data can be collected from multiple target sensing devices, such as laser data collected by lidar equipment, inertial data collected by inertial measurement units, and navigation data collected by navigation satellite equipment.

[0110] Step S320: Based on the target sensing data, determine the corresponding sensing location in the second map in the mapping map library.

[0111] Specifically, based on the target sensing data and RTK technology, a search can be performed in the second map of the mapping map library to find historical sensing data that is the same as or most similar to the target sensing data as the target sensing data, so as to obtain the location coordinates corresponding to the target sensing data, which are then used as the sensing location obtained by positioning in the second map.

[0112] exist Figure 5 In the embodiment shown, the acquired sensing position is not affected by adverse factors and can quickly and accurately reflect the actual situation of the mobile device under test, thereby obtaining the true target position of the mobile device under test based on the mapping transformation between the two maps.

[0113] Optionally, please refer to Figure 6 , Figure 6 This is a detailed flowchart of step S400 provided in an embodiment of the present application. Step S400 may also include steps S410-S420.

[0114] Step S410: Based on the sensor location, query the mapping map library to obtain the target mapping relationship between the first map and the second map.

[0115] Specifically, it can perform a corresponding query in the mapping map library based on the sensing location, thereby determining the target mapping relationship between the first map and the second map corresponding to the sensing location.

[0116] Optionally, during the query, the specific coordinates of the sensing location can be input into the mapping map library for searching. The second coordinate that is the same as or closest to the sensing location is used as the target coordinate, thereby obtaining the mapping relationship corresponding to the target coordinate from multiple mapping relationships as the target mapping relationship.

[0117] Step S420: Based on the target mapping relationship, determine the target location in the first map corresponding to the sensing location.

[0118] Specifically, the mapping relationship between the two maps is determined based on the target mapping relationship, thus identifying the target position in the first map corresponding to the sensing position. This allows for accurate and effective positioning of the mobile device under test even when it actually operates at a specific work site with poor positioning signal.

[0119] Optionally, the first coordinate in the first map corresponding to the target coordinate can be obtained, and the specific location of the first coordinate can be used as the corresponding target location.

[0120] exist Figure 6 In the illustrated embodiment, positioning is achieved by mapping the location coordinates between two maps. This enables accurate and effective positioning in real-world scenarios with various adverse factors, based on the actual situation of the mobile device under test, thereby improving the effectiveness and accuracy of the target location.

[0121] Optionally, please refer to Figure 7 , Figure 7 This is a flowchart illustrating another mobile device positioning method provided in an embodiment of this application. The method may further include steps S510-S530.

[0122] Step S510: Acquire image data collected by shooting the target area.

[0123] Among them, electronic devices can communicate and connect with various types of shooting equipment. Firstly, due to the harsh environment and tight production tasks in steel plants, shooting equipment can include drones, GNSS drones, etc., equipped with high-definition cameras, to fly at appropriate altitudes according to the terrain and collect relevant image data of the work area from the air.

[0124] Step S520: Feature point calibration is performed based on image data to obtain calibration data.

[0125] In order to further improve the effectiveness of image data processing, the image data can be labeled with corresponding feature points to determine the corresponding labeling data.

[0126] Step S530: The calibration data is processed based on a preset processing technique to obtain a first map with multiple first working routes.

[0127] Among them, the preset processing technology can be a real-time dynamic technology, such as RTK technology or VSLAM (Visual Simultaneous Localization and Mapping, which uses cameras to solve localization and mapping problems). Based on RTK technology and VSLAM, combined with the image calibration data, a high-precision visual point cloud map of the entire working area can be constructed as the first map, and each first working route can be generated in the first map.

[0128] exist Figure 7 In the illustrated embodiment, a corresponding visual point cloud map can be constructed according to the actual situation of the target area, which effectively improves the real-time performance and accuracy of the first visual map constructed from image data.

[0129] Optionally, please refer to Figure 8 , Figure 8 This is a flowchart illustrating another mobile device positioning method provided in an embodiment of this application. The method may further include steps S540-S550.

[0130] Step S540: Acquire historical sensing data collected by the sensing device as it moves in the target area.

[0131] The sensing devices include various equipment such as lidar devices, inertial measurement units, and navigation satellite devices. The sensing devices can be installed in mobile devices used for testing, such as test vehicles. The test vehicles can move to any working position in the working area so that the sensing devices can move in the target area to collect historical sensing data at all locations. The historical sensing data can also include various types of data such as laser data collected by lidar devices, inertial data collected by inertial measurement units, and navigation data collected by navigation satellite devices.

[0132] Step S550: Couple the historical sensor data to obtain a second map with multiple second working routes.

[0133] In this process, we can fully leverage the mapping and positioning advantages of various sensing devices, apply the mapping concept of tightly coupled various sensing devices, and perform coupling processing on various historical sensing data based on factor graphs and graph optimization techniques to establish a comprehensive, high-precision laser point cloud map as a second map, and generate various second working routes in the second map.

[0134] exist Figure 8 In the embodiment shown, a corresponding laser point cloud map is constructed based on the actual positions of the test mobile device and various objects in the working area, which effectively improves the real-time performance and accuracy of the second laser map constructed based on historical sensor data.

[0135] Optionally, please refer to Figure 9 , Figure 9 This is a flowchart illustrating another mobile device positioning method provided in an embodiment of this application. The method may further include steps S610-S620.

[0136] Step S610: Obtain the pose data of the mobile device under test at the target location.

[0137] Among them, when the mobile device under test is working in the working area, it has corresponding pose data, such as orientation angle and angular velocity. After locating the actual target position of the mobile device under test in vision, it can also be based on the pose data collected at the target position of the mobile device under test.

[0138] Step S620: Determine the working status of the mobile device under test based on the pose data.

[0139] Since the pose of the mobile device under test corresponds to its working state, the working state of the mobile device under test during positioning can be determined by combining the target position and pose data. For example, when the target position is close to a specific work point and the orientation angle in the pose data indicates that the device is moving towards that specific work point, the corresponding working state of the mobile device under test is that it is moving to that specific work point to work.

[0140] Optionally, when a device under test malfunctions, such as when the device stays in a certain position for too long, a corresponding abnormal prompt message can be generated to effectively monitor the working status of the device.

[0141] exist Figure 9 In the illustrated embodiment, the operation of the mobile device under test during molten iron transportation can be effectively monitored, further improving safety and work efficiency during production.

[0142] Please see Figure 10 , Figure 10 This is a schematic diagram of the structure of a mobile device positioning device provided in an embodiment of the present application. The mobile device positioning device 700 may include: an acquisition module 710, a first positioning module 720, and a second positioning module 730.

[0143] The acquisition module 710 is used to acquire a mapping map library; wherein, the mapping map library is generated based on the matching of the first map and the second map;

[0144] The first positioning module 720 is used to determine the sensing position of the mobile device under test in the second map in the mapping map library based on the target sensing data of the mobile device under test.

[0145] The second positioning module 730 is used to determine the target position of the mobile device under test in the first map based on the sensor position in the mapped map library, so as to locate the mobile device under test.

[0146] The first map is constructed based on image data collected in the target area, and the second map is constructed based on historical sensor data collected by the sensor device as it moves in the target area.

[0147] In an optional implementation, the first map includes multiple first working routes in the target area, and the second map includes multiple second working routes in the target area; the acquisition module 710 may include a calibration submodule, an association submodule, a matching submodule, and a construction submodule;

[0148] The calibration submodule is used to calibrate the start and end positions of each first working path and each second working path;

[0149] The association submodule is used to determine multiple sets of associated routes based on the start and end positions; each set of associated routes includes a first working route and a corresponding second working route;

[0150] The matching submodule is used to match each first coordinate in the first working route with each second coordinate in the second working route in the associated route to obtain the mapping relationship between the first coordinate and the second coordinate;

[0151] The construction submodule is used to build a mapping map library based on multiple mapping relationships.

[0152] In an optional implementation, the matching submodule is specifically used to: divide the first working route and the second working route in the associated route into equal proportions to determine multiple first coordinates and multiple second coordinates; perform interpolation processing on the multiple first coordinates and multiple second coordinates respectively to obtain equidistant calibration data; and determine the mapping relationship between each first coordinate and the corresponding second coordinate based on the equidistant calibration data.

[0153] In an optional implementation, the first positioning submodule 720 is specifically used to: acquire target sensing data collected by the target sensing device in the mobile device under test when positioning in the target area; and determine the corresponding sensing location in the second map in the mapping map library based on the target sensing data.

[0154] In an optional implementation, the second positioning submodule 730 is specifically used to: query the mapping map library based on the sensing location to obtain the target mapping relationship between the first map and the second map; and determine the target location in the first map corresponding to the sensing location based on the target mapping relationship.

[0155] In an optional embodiment, the mobile device positioning device 700 may further include a first construction module for acquiring image data collected by shooting a target area; performing feature point calibration based on the image data to obtain calibration data; and processing the calibration data based on preset processing technology to obtain a first map with multiple first working routes; wherein the preset processing technology includes real-time dynamic technology.

[0156] In an optional embodiment, the mobile device positioning device 700 may further include a second building module for acquiring historical sensing data collected by the sensing device as it moves in the target area; wherein the sensing device includes at least one of a lidar device, an inertial measurement unit, and a navigation satellite device; and the historical sensing data is coupled and processed to obtain a second map with multiple second working routes.

[0157] In an optional embodiment, the mobile device positioning device 700 may further include a working module for acquiring pose data of the mobile device under test at a target location and determining the working state of the mobile device under test based on the pose data.

[0158] Since the principle of the mobile device positioning device 700 in this embodiment is similar to that of the aforementioned mobile device positioning method, the implementation of the mobile device positioning device 700 in this embodiment can refer to the description in the above-mentioned mobile device positioning method, and the repeated parts will not be described again.

[0159] This application also provides a computer-readable storage medium storing computer program instructions. When the computer program instructions are read and executed by a processor, the steps of any of the methods in the mobile device positioning method provided in this embodiment are performed.

[0160] In the several embodiments provided in this application, it should be understood that the disclosed device can also be implemented in other ways. The device embodiments described above are merely illustrative; for example, the block diagrams in the accompanying drawings illustrate the possible architecture, functions, and operations of the device according to various embodiments of this application. In this regard, each block in the block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagram, and combinations of block diagrams, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0161] In addition, the functional modules in the various embodiments of this application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0162] If the aforementioned functions are implemented as software functional modules 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 this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0163] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application. It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0164] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

[0165] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

Claims

1. A mobile device positioning method, characterized by, The method comprises: obtaining a mapping map library; wherein the mapping map library is generated by matching a first map and a second map; determining a sensing position of a to-be-tested mobile device in the second map in the mapping map library according to target sensing data of the to-be-tested mobile device; determining a target position of the to-be-tested mobile device in the first map in the mapping map library based on the sensing position, so as to locate the to-be-tested mobile device; wherein the first map is constructed according to image data collected in a target region, and the second map is constructed according to historical sensing data collected by a sensing device moving in the target region; wherein the first map comprises a plurality of first working routes in the target region, and the second map comprises a plurality of second working routes in the target region; the obtaining of the mapping map library comprises: calibrating a starting position and an ending position of each of the first working routes and each of the second working routes; determining a plurality of groups of associated routes based on the starting positions and the ending positions; wherein each group of associated routes comprises the first working route and the corresponding second working route; matching each first coordinate in the first working route and each second coordinate in the second working route in the associated routes to obtain a mapping relationship between the first coordinate and the second coordinate; and constructing the mapping map library according to a plurality of the mapping relationships.

2. The method of claim 1, wherein, The matching of each first coordinate in the first working route and each second coordinate in the second working route in the associated routes to obtain a mapping relationship between the first coordinate and the second coordinate comprises: proportionally dividing the first working route and the second working route in the associated routes to determine a plurality of the first coordinates and a plurality of the second coordinates; performing interpolation processing on a plurality of the first coordinates and a plurality of the second coordinates respectively to obtain equidistant calibration data; determining the mapping relationship between each first coordinate and the corresponding second coordinate according to the equidistant calibration data.

3. The method of claim 1, wherein, The determination of a sensing position of a to-be-tested mobile device in the second map in the mapping map library according to target sensing data of the to-be-tested mobile device comprises: obtaining the target sensing data collected by a target sensing device in the to-be-tested mobile device when the target sensing device is positioned in the target region; determining the corresponding sensing position in the second map in the mapping map library based on the target sensing data.

4. The method of claim 3, wherein, The determination of a target position of the to-be-tested mobile device in the first map in the mapping map library based on the sensing position comprises: querying the mapping map library based on the sensing position to obtain a target mapping relationship between the first map and the second map; determining the target position in the first map corresponding to the sensing position based on the target mapping relationship.

5. The method of claim 1, wherein, wherein the first map is constructed by the following way: obtaining the image data collected by photographing the target region; performing feature point calibration based on the image data to obtain calibration data; The calibration data is processed based on a preset processing technique to obtain the first map having a plurality of first working routes. The preset processing technique includes a real-time dynamic technique.

6. The method of claim 1, wherein, The second map is generated by the following manner: The historical sensing data collected by the sensing device moving in the target area is obtained, wherein the sensing device includes at least one of a laser radar device, an inertial measurement unit, and a navigation satellite device. The historical sensing data is coupled to obtain the second map having a plurality of second working routes. The method further includes:

7. The method according to any one of claims 1 to 6, characterized in that, Obtaining pose data of the to-be-tested mobile device at the target position; Determining a working state of the to-be-tested mobile device according to the pose data. The apparatus includes an obtaining module, a first positioning module, and a second positioning module.

8. A mobile device positioning apparatus, characterized by The obtaining module is configured to obtain a mapping map library, wherein the mapping map library is generated by matching a first map and a second map; The first positioning module is configured to determine a sensing position of the to-be-tested mobile device in the second map in the mapping map library according to target sensing data of the to-be-tested mobile device; The second positioning module is configured to determine a target position of the to-be-tested mobile device in the first map in the mapping map library based on the sensing position, so as to position the to-be-tested mobile device; The first map is constructed according to image data collected in a target area, and the second map is constructed according to historical sensing data collected by a sensing device moving in the target area; The first map includes a plurality of first working routes in the target area, and the second map includes a plurality of second working routes in the target area; the obtaining module is specifically configured to calibrate a start position and an end position of each of the first working routes and the second working routes, determine a plurality of groups of associated routes based on the start position and the end position, wherein each group of the associated routes includes the first working route and the corresponding second working route, match each first coordinate in the first working route and each second coordinate in the second working route in the associated routes to obtain a mapping relationship between the first coordinate and the second coordinate, and construct the mapping map library according to a plurality of the mapping relationships. The readable storage medium stores computer program instructions, and the computer program instructions are run by a processor to execute the steps in the method of any one of claims 1-7.

9. A computer readable storage medium, characterized in that, ​

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