Positioning method and device of mobile equipment, mobile equipment and storage medium
By determining the key point coordinates and electronic map coordinates of the target mark in large-area scenarios and calculating vector distances, the problem of low positioning efficiency caused by the small number of marks is solved, and efficient and accurate positioning is achieved.
Patent Information
- Application Number
- CN202410178049.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-02-08
- Publication Date
- 2025-08-12
AI Technical Summary
In large-area scenarios, when the number of labels is small, the positioning efficiency of the mobile device in the prior art is low, which affects the positioning performance.
By determining the first coordinate of the key point of the target identification in the first coordinate system, combining the electronic map coordinates under the second coordinate system, the first vector distance is calculated and the current position is quickly positioned.
The positioning process is simplified, positioning efficiency and accuracy are improved, and the accurate positioning of mobile devices in large-area scenarios is ensured.
Smart Images
Figure CN120470069A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of data processing technology, and in particular to a positioning method and apparatus for a mobile device, a mobile device, and a storage medium. Background Art
[0002] In related technologies, determining the location of a mobile device in a current scene requires combining the results of scanning multiple markers. If the current scene is large and the number of preset markers is small, this can easily lead to low positioning efficiency, thereby affecting the mobile device's ability to locate itself. Summary of the Invention
[0003] In view of this, the present disclosure provides a positioning method and apparatus for a movable device, a movable device, and a storage medium to solve the problem of low efficiency in determining the position of the movable device in the current scenario.
[0004] In a first aspect, the present disclosure provides a method for positioning a movable device, the method comprising:
[0005] Determine the target identifier relative to the current position in the current scene;
[0006] Determining a first vector distance between the key point and the target marker based on a first coordinate of the key point in the first coordinate system, where the first coordinate system corresponds to the movable device;
[0007] Obtaining the second coordinates of the key point in the second coordinate system, where the second coordinate system corresponds to the electronic map of the current scene;
[0008] Based on the second coordinate and the first vector distance, it is determined that the current position corresponds to a target position in the current scene.
[0009] In a second aspect, the present disclosure provides a positioning device for a movable device, the device comprising:
[0010] Identification module, used to determine the target identity relative to the current position in the current scene;
[0011] A processing module, configured to determine a first vector distance between the key point and the target marker based on a first coordinate of the key point in a first coordinate system, wherein the first coordinate system corresponds to the movable device;
[0012] An acquisition module, configured to acquire a second coordinate of the key point in a second coordinate system, where the second coordinate system corresponds to an electronic map of the current scene;
[0013] The positioning module is used to determine the target position corresponding to the current position in the current scene based on the second coordinate and the first vector distance.
[0014] In a third aspect, the present disclosure provides a mobile device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to execute the positioning method for the mobile device of the first aspect or any corresponding embodiment thereof.
[0015] In a fourth aspect, the present disclosure provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for positioning a movable device according to the first aspect or any corresponding embodiment thereof.
[0016] The positioning method for a movable device provided by the present disclosure combines the key point of the target identification relative to the current position in the current scene, the relative distance between the key point and the movable device, and the coordinates of the key point in the corresponding coordinate system of the electronic map of the current scene for positioning, which can effectively simplify the positioning process and thus achieve the purpose of improving positioning efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] In order to more clearly illustrate the specific embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.
[0018] Figure 1 is a flowchart of a method for positioning a movable device according to an embodiment of the present disclosure;
[0019] Figure 2 is a flowchart of another positioning method for a mobile device according to an embodiment of the present disclosure;
[0020] Figure 3 is a schematic diagram of positioning according to an embodiment of the present disclosure;
[0021] Figure 4 is a structural block diagram of a positioning device for a mobile device according to an embodiment of the present disclosure;
[0022] Figure 5 Schematic diagram of the hardware structure of the mobile device according to the embodiment of the present disclosure. DETAILED DESCRIPTION
[0023] To make the purpose, technical solutions, and advantages of the embodiments of the present disclosure more clear, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments of the present disclosure, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present disclosure.
[0024] In related technologies, determining the mobile device's position in the current scene requires combining the results of the mobile device's scanning of multiple identifiers. Specifically, determining the mobile device's position in the current scene requires combining the multiple identifiers detected simultaneously by the mobile device in the current location. If the current scene is large and the preset number of identifiers is small, the mobile device may not be able to identify the preset number of identifiers at the same time, affecting positioning efficiency.
[0025] In view of this, an embodiment of the present disclosure provides a positioning method for a movable device. To determine the position of the movable device in the current scene, a target identifier relative to the current position in the current scene is determined based on the current position of the movable device. Based on the first coordinate of the key point of the target identifier in the first coordinate system, the first vector distance between the movable device and the key point is determined. The first coordinate system corresponds to the movable device. Based on the second coordinate of the key point in the second coordinate system and the first vector distance, the current position is quickly located relative to the target position in the current scene, thereby achieving the purpose of improving positioning efficiency. The second coordinate system corresponds to the electronic map of the current scene.
[0026] According to an embodiment of the present disclosure, an embodiment of a positioning method for a movable device is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.
[0027] In this embodiment, a positioning method for a movable device is provided, which can be used for the above-mentioned movable devices, such as robots, drones, smart vehicles, etc. Figure 1 is a flow chart of a positioning method for a mobile device according to an embodiment of the present disclosure, such as Figure 1 As shown, the process includes the following steps:
[0028] Step S101: Determine a target identifier relative to the current position in the current scene.
[0029] Among them, multiple preset identifiers are set in advance in the current scene so that the mobile device can locate and navigate through the preset identifiers. The preset identifiers can be designated markers or QR codes, etc., and can be set according to needs.
[0030] The current scene can be any designated scene. For example, the current scene can be a warehouse area, a factory area, a logistics center, etc. Mobile devices can perform tasks such as moving and transshipping items within the corresponding scene according to the specified routes and paths.
[0031] Since the movable device moves based on itself and according to a preset moving path during the movement process, in order to determine the position of the movable device in the current scene, the preset marker is detected by the movable device in the current posture and determined as the target marker relative to the current position, and then the target marker is used for rapid positioning.
[0032] Step S102: determining a first vector distance between the target identified key point and the key point based on the first coordinate of the key point in the first coordinate system.
[0033] The first coordinate system corresponds to the movable device. That is, the first coordinate system is established with the movable device as a reference. Preferably, to facilitate rapid route planning for the movable device, the movable device can be set as the origin of the first coordinate system. To determine the relative positional relationship between the target identifier and the movable device, a first vector distance between the movable device and the key point is determined based on the first coordinate of the key point of the target identifier in the first coordinate system and the movable device's own coordinates.
[0034] In some optional examples, the key point is the center point of the target identifier, and thus when determining the first vector distance, the efficiency of determining the first vector distance can be improved.
[0035] Step S103: Obtain the second coordinates of the key point in the second coordinate system.
[0036] The second coordinate system corresponds to the electronic map of the current scene. That is, the second coordinate system can be understood as the global coordinate system of the current scene. Since the target identifier is a preset identifier pre-set in the current scene, after determining the target identifier, the second coordinates of the key point in the second coordinate system can be obtained based on the pre-configured information of the target identifier, so that the mobile device can clearly determine the location of the target identifier on the electronic map through the second coordinates.
[0037] Step S104: determining the target position corresponding to the current position in the current scene based on the second coordinate and the first vector distance.
[0038] The first vector distance includes the relative distance between the key point and the movable device, as well as the relative position offset angle. Therefore, once the second coordinates are determined, combined with the first vector distance, the target coordinates of the movable device on the electronic map can be quickly located, and the target position of the movable device in the current scene can be obtained using these target coordinates.
[0039] The positioning method for a movable device provided in this embodiment combines the key points of the target identification relative to the current position in the current scene, the relative distance between the key points and the movable device, and the coordinates of the key points in the corresponding coordinate system of the electronic map of the current scene for positioning, which can effectively simplify the positioning process and thus achieve the purpose of improving positioning efficiency.
[0040] In this embodiment, a positioning method for a movable device is provided, which can be used for the above-mentioned movable devices, such as robots, drones, smart vehicles, etc. Figure 2 is a flow chart of a positioning method for a mobile device according to an embodiment of the present disclosure, such as Figure 2 As shown, the process includes the following steps:
[0041] Step S201: Determine a target identifier relative to the current position in the current scene.
[0042] Specifically, the above step S201 includes:
[0043] Step S2011: Obtain the point cloud data to be processed collected at the current position.
[0044] Among them, in order to identify the environmental information around the current position and detect whether there is a preset mark at the current position, the point cloud data to be processed collected at the current position is obtained, so that the target mark relative to the current position in the current environment can be identified through the processing results of the point cloud data to be processed.
[0045] Step S2012: Based on a preset brightness threshold interval, identify the point data to be processed whose brightness value is within the brightness threshold interval to obtain a plurality of candidate point cloud data.
[0046] The brightness threshold interval depends on the reflective intensity of the target marker. Different objects have different reflective intensities. To improve the detection efficiency of target markers, a brightness threshold interval is determined based on the reflective intensity of the target marker. This brightness threshold interval is then used to extract the point cloud data to be processed whose brightness values fall within this brightness threshold interval. Based on the shape corresponding to the target marker and the positional relationship between the candidate point data, multiple candidate point cloud data are obtained. The candidate point cloud data includes multiple candidate point data. The candidate point cloud data is used to determine whether the corresponding object is a target marker.
[0047] In some optional implementations, the above step S2012 includes:
[0048] Step a1, traverse the brightness value of each point data to be processed, and take the point data to be processed whose brightness value is within the brightness threshold range as the intermediate point data to obtain the intermediate point cloud data;
[0049] Step a2: clustering the intermediate point cloud data to obtain multiple candidate point cloud data.
[0050] Specifically, in order to quickly determine the object corresponding to the point cloud data, the intermediate point cloud data is clustered to obtain multiple clustering results, and then the point cloud data corresponding to each clustering result is used as candidate point cloud data to be determined whether it is a target identification.
[0051] In other optional examples, in order to reduce the occurrence of misidentification, after the clustering results are obtained, the position of each candidate point data in the current clustering result in the point cloud data to be processed is used to identify whether there is non-middle point data between two adjacent candidate point data. If there is non-middle point data, it is determined whether the number of non-middle point data is within a preset number range. If the number of non-middle point data is within the preset number range, the non-middle point data of that number is added to the current clustering result to avoid misdetection due to partial obstruction of the target identification or abnormal brightness detection. To avoid over-extraction, the preset number range can be set to [0,1]. If there is no non-middle point data, the current clustering result is directly used as the candidate point cloud data.
[0052] Step S2013: determining target point cloud data from a plurality of candidate point cloud data based on preset attribute information of the target identifier.
[0053] Among them, in order to facilitate the mobile device to effectively distinguish the target identifier from other objects, each candidate point cloud data is screened based on the preset attribute information of the target identifier, and the candidate point cloud data of the object formed after fitting that meets the preset attribute information is used as the target point cloud data.
[0054] In some optional implementations, the above step S2013 includes:
[0055] Step b1: determining a preset marker corresponding to the current location in the current scene from the electronic map, and obtaining a first reference coordinate of a target key point of the preset marker in the second coordinate system.
[0056] The attribute information of the preset identifier is the same as the preset attribute information. Because the number of point data points in the target point cloud data corresponding to the target identifier is different at different distances and angles, in order to improve the effectiveness of the detection results, the preset identifier corresponding to the current location in the current scene is first determined from the electronic map, and then the first reference coordinates of the target key point of the preset identifier in the second coordinate system are obtained. In an optional example, the preset identifier corresponding to the current location can be determined based on the moving route of the movable device and the prior pose estimated from the previous location.
[0057] Step b2: determining the second reference coordinates of the target key point in the first coordinate system based on the mapping relationship between the second coordinate system and the first coordinate system and the first reference coordinates.
[0058] Among them, in order to restore the relative position relationship between the target key point and the movable device, after determining the first reference coordinate, the first reference coordinate is mapped to the first coordinate system based on the mapping relationship between the second coordinate system and the first coordinate system, and then the second reference coordinate of the target key point corresponding to the first coordinate system is obtained.
[0059] Step b3: Determine the target vector distance from the preset marker using the second reference coordinate.
[0060] Among them, in the case of a clear second reference coordinate, combined with the coordinates of the movable device in the first coordinate system, the Euclidean distance calculation formula is used to predict the target relative distance and target relative position offset angle between the movable device at its current position and the preset marker, and then obtain the target vector distance between the preset marker.
[0061] Step b4: determining target point cloud features based on the target vector distance and attribute information, and determining candidate point cloud data that meets the target point cloud features as target point cloud data.
[0062] Among them, since the target vector distance is a distance including the target relative position offset angle, the target point cloud features satisfied by the target point cloud data corresponding to the target identification of the movable device at the current position can be determined by combining the target vector distance and attribute information.
[0063] The point cloud features of each candidate point cloud data are determined respectively, and then the candidate point cloud data corresponding to the point cloud features that match the target point cloud features are determined as the target point cloud data.
[0064] In some optional embodiments, the target vector distance includes the target relative distance and the target relative offset angle from the preset mark, and the attribute information includes the target size of the preset mark and the corresponding reflection intensity. Step b4 includes:
[0065] Step b41, determining the data quantity range of the target point data in the target point cloud data based on the target size and the target relative distance;
[0066] Step b42: determining the average brightness range of the target point cloud data based on the reflection intensity and the target relative offset angle;
[0067] Step b43, determining the size range of the target point cloud data by the target size;
[0068] Step b44: Determine the target pointing angle corresponding to the target point cloud data through the target relative offset angle to obtain the target point cloud features.
[0069] Specifically, target point cloud features include: target pointing angle, size range, average brightness range, and data quantity range. Because the amount of target point cloud data acquired may vary from viewpoint to viewpoint, to improve marker detection accuracy, the target point cloud data quantity range is determined based on target size, relative distance to the target, and pre-determined point data generation configuration information. When screening candidate point cloud data, candidate point cloud data that does not meet this data quantity range can be eliminated.
[0070] Because the reflective intensity of the target mark is affected not only by the optical response range and the reflective properties of the material itself, but also by the scanning angle of the mobile device, in order to determine whether the brightness of each candidate point cloud data can reach the target brightness corresponding to the target mark, a mapping relationship between point cloud intensity and laser incident angle is established in advance through data fitting. This then determines the average brightness range of the target point cloud data, thereby filtering out candidate point cloud data whose average brightness does not fall within this average brightness range.
[0071] To improve the effectiveness of the screening, the size range of the target point cloud data is determined based on the target size of the target identifier to filter out candidate point cloud data that are not processed within the size range. Preferably, the distance between two adjacent point data to be processed can be determined in advance based on the configuration information generated by the point cloud, and then the target point cloud data size corresponding to the target size can be determined. Since there may be noise interference when collecting the point data to be processed, the error offset is determined, and then the difference between the target point cloud data size and the error offset is used as the minimum value of the size range, and the sum of the target point cloud data size and the error offset is used as the maximum value of the size range, thereby obtaining the size range.
[0072] Because the target marker is a flat surface, the target pointing angle of each target point data should be the same. In other words, the orientation of the target marker should be the same as the scanning angle of the mobile device. Then, the target relative offset angle can be used to quickly determine the target pointing angle corresponding to the target point cloud data.
[0073] In some other optional implementations, the above step b4 further includes:
[0074] Step b45: if there are multiple target point cloud data that meet the target point cloud characteristics, then the confidence level of each target point cloud data is determined based on the historical movement trajectory of the movable device;
[0075] Step b46: Use the target point cloud data with the highest confidence value as the target point cloud data for obtaining the target identification.
[0076] When there are multiple target point cloud data that meet the target point cloud characteristics, it indicates that the mobile device may have identified multiple target identifiers at its current location. To improve positioning accuracy, the preset identifier corresponding to the mobile device at its current location is predicted based on the historical movement trajectory of the mobile device. The position of each target point cloud data is then matched with the position of the preset identifier, and the confidence level of each target point cloud data is estimated. The target point cloud data with the highest confidence level is then used as the target point cloud data for obtaining the target identifier, thereby reducing the occurrence of false detections.
[0077] Step S2014: Obtain a target identifier relative to the current position through the target point cloud data.
[0078] After the target point cloud data is determined, the target point cloud data is fitted by data fitting to obtain a target identifier relative to the current position.
[0079] Step S202: Determine the first vector distance between the target identified key point and the target identified key point based on the first coordinate of the target identified key point in the first coordinate system. Figure 1 Step S102 of the illustrated embodiment will not be described in detail here.
[0080] Step S203: Obtain the second coordinates of the key point in the second coordinate system. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.
[0081] Step S204: Determine the target position corresponding to the current position in the current scene based on the second coordinate and the first vector distance.
[0082] In some optional implementations, the target identification is based on the laser radar on the mobile device, and the above step S204 includes:
[0083] Step c1, obtaining a second vector distance to the laser radar;
[0084] Step c2, determining a third vector distance between the second coordinate and the origin of the second coordinate system;
[0085] Step c3, determining the target coordinates corresponding to the current position in the second coordinate system based on the first vector distance, the second vector distance, and the third vector distance;
[0086] Step c4: Determine the target position corresponding to the current position in the current scene based on the target coordinates.
[0087] Specifically, there is a certain relative distance between the laser radar and the mobile device. Therefore, to improve positioning accuracy, a second vector distance is obtained from the laser radar. This second vector distance can be obtained from a pre-configured configuration file of the mobile device or determined through detection, and is not limited here.
[0088] like Figure 3 In the second coordinate system shown, the rectangle represents the target marker, the key point represents the center of the target marker, the relatively small circle represents the lidar, and the relatively large circle represents the movable device. To determine the target coordinates, the third vector distance between the second coordinate and the origin of the second coordinate system is determined. Then, using the Pythagorean theorem, the target coordinates corresponding to the current position in the second coordinate system are calculated based on the first, second, and third vector distances. Using these target coordinates, the current position is determined to be the target position corresponding to the current scene.
[0089] The positioning method for a movable device provided in this embodiment performs identification detection based on preset attribute information of the target identification, which can effectively improve the positioning accuracy of the target identification. Therefore, when using a single target identification to locate the target position of the movable device in the current scene, the reliability of the positioning result can be guaranteed, thereby achieving not only the purpose of improving positioning efficiency, but also ensuring the accuracy of the positioning result.
[0090] In some optional implementations, to facilitate effective recognition of preset markers placed in the current scene by the mobile device, reflective materials with high reflectivity may be preferred when configuring the preset markers. This allows for effective differentiation between intermediate point data and noise data during subsequent extraction of intermediate point data. The target size of the preset markers is set to a rectangular sticker with a width of 40 cm and a height between 5 cm and 20 cm. This facilitates rapid identification of target point cloud data based on the size of each candidate point cloud data.
[0091] In other optional implementations, to ensure reliable positioning, the preset markers are placed on a plane that is larger than or equal to the target size, with the markers aligned with the LiDAR's optical window to ensure complete target point cloud data is captured. In one example, the plane can include a pillar, a wall, or a location surrounding a housing.
[0092] As one or more specific application embodiments of the embodiments of the present disclosure, taking a robot as an example, the process of locating the position of the robot in the current scene may be as follows:
[0093] When the robot moves in a warehousing scenario, if a single target identifier relative to the current position is detected at the current position, the target identifier is used to quickly determine the target position of the robot in the warehousing scenario using the positioning method of the movable device provided by the present invention, thereby effectively improving the positioning efficiency.
[0094] In this embodiment, a positioning device for a mobile device is also provided. The device is used to implement the above-mentioned embodiments and preferred embodiments. Details that have already been described will not be repeated. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.
[0095] This embodiment provides a positioning device for a movable device, such as Figure 4 As shown, including:
[0096] Identification module 401, used to determine the target identifier relative to the current position in the current scene;
[0097] A processing module 402 is configured to determine a first vector distance between the target identified key point and the target identified key point based on a first coordinate of the target identified key point in a first coordinate system, where the first coordinate system corresponds to the movable device;
[0098] An acquisition module 403 is configured to acquire a second coordinate of the key point in a second coordinate system, where the second coordinate system corresponds to an electronic map of the current scene;
[0099] The positioning module 404 is configured to determine a target position corresponding to the current position in the current scene based on the second coordinate and the first vector distance.
[0100] In some optional implementations, the identification module 401 includes:
[0101] A data acquisition unit, used to acquire the point cloud data to be processed collected at the current position;
[0102] A first screening unit is configured to identify, based on a preset brightness threshold interval, point data to be processed whose brightness values are within the brightness threshold interval, and obtain a plurality of candidate point cloud data, wherein the brightness threshold interval depends on the reflective intensity of the target marker;
[0103] a second screening unit, configured to determine target point cloud data from a plurality of candidate point cloud data based on preset attribute information of the target identifier;
[0104] The identification unit is used to obtain the target identification relative to the current position through the target point cloud data.
[0105] In some optional embodiments, the first screening unit includes:
[0106] The first processing unit is configured to traverse the brightness value of each point data to be processed, and take the point data to be processed whose brightness value is within the brightness threshold range as the intermediate point data to obtain the intermediate point cloud data;
[0107] The second processing unit is used to perform clustering processing on the intermediate point cloud data to obtain multiple candidate point cloud data.
[0108] In some optional embodiments, the second screening unit includes:
[0109] a third processing unit configured to determine, from the electronic map, a preset marker corresponding to the current location in the current scene, and obtain a first reference coordinate of a target key point of the preset marker in the second coordinate system, wherein attribute information of the preset marker and the preset attribute information are identical;
[0110] A fourth processing unit is configured to determine a second reference coordinate of the target key point in the first coordinate system based on a mapping relationship between the second coordinate system and the first coordinate system and the first reference coordinate;
[0111] a fifth processing unit, configured to determine a target vector distance from a preset marker using a second reference coordinate;
[0112] The sixth processing unit is configured to determine target point cloud features based on the target vector distance and attribute information, and determine candidate point cloud data that meets the target point cloud features as target point cloud data.
[0113] In some optional embodiments, the target vector distance includes a target relative distance from a preset marker and a target relative offset angle, the attribute information includes a target size of the preset marker and a corresponding reflection intensity, and the sixth processing unit includes:
[0114] A first determining unit is configured to determine a data quantity range of target point data in the target point cloud data based on a target size and a target relative distance;
[0115] a second determining unit, configured to determine an average brightness range of the target point cloud data based on the reflection intensity and the target relative offset angle;
[0116] A third determining unit is configured to determine a size range of the target point cloud data according to the target size;
[0117] The fourth determination unit is used to determine the target pointing angle corresponding to the target point cloud data through the target relative offset angle, and obtain the target point cloud features. The target point cloud features include: target pointing angle, size range, average brightness range and data quantity range.
[0118] In some optional implementations, the sixth processing unit further includes:
[0119] a screening subunit, configured to determine the confidence level of each target point cloud data based on the historical movement trajectory of the movable device if there are multiple target point cloud data that meet the target point cloud characteristics;
[0120] The fifth determining unit is configured to use the target point cloud data with the highest confidence value as the target point cloud data for obtaining the target identification.
[0121] In some optional embodiments, the target identification is based on the laser radar on the mobile device, and the positioning module 404 includes:
[0122] A distance acquisition unit, configured to acquire a second vector distance from the laser radar;
[0123] a seventh processing unit, configured to determine a third vector distance between the second coordinate and the origin of the second coordinate system;
[0124] an eighth processing unit, configured to determine target coordinates corresponding to the current position in the second coordinate system based on the first vector distance, the second vector distance, and the third vector distance;
[0125] The ninth processing unit is configured to determine, based on the target coordinates, the target position corresponding to the current position in the current scene.
[0126] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.
[0127] The positioning device of the mobile device in this embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.
[0128] The present disclosure also provides a mobile device having the above Figure 4 The positioning device of the movable device is shown.
[0129] See also Figure 5 , Figure 5 is a structural diagram of a mobile device provided by an optional embodiment of the present disclosure, such as Figure 5As shown, the removable device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. The various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the removable device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple removable devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 5 A processor 10 is taken as an example.
[0130] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.
[0131] The memory 20 stores instructions that can be executed by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.
[0132] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and applications required for at least one function; the data storage area may store data created based on the use of the removable device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the removable device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0133] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.
[0134] The mobile device further includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 5 The bus connection is taken as an example.
[0135] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the mobile device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.
[0136] The embodiments of the present disclosure also provide a computer-readable storage medium. The above-mentioned method according to the embodiments of the present disclosure can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.
[0137] It is understandable that before using the technical solutions disclosed in the various embodiments of this disclosure, the type, scope of use, usage scenarios, etc. of the personal information involved in this disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.
[0138] For example, in response to a user's active request, a prompt message is sent to the user to clearly inform the user that the operation requested will require the acquisition and use of the user's personal information. This allows the user to independently choose whether to provide personal information to software or hardware such as a mobile device, application, server, or storage medium that performs the operations of the disclosed technical solution based on the prompt message.
[0139] As an optional but non-limiting implementation, in response to receiving a user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also contain a selection control for the user to select "agree" or "disagree" to provide personal information to the mobile device.
[0140] It is understandable that the above notification and user authorization process are merely illustrative and do not limit the implementation of the present disclosure. Other methods that comply with relevant laws and regulations may also be applied to the implementation of the present disclosure.
[0141] Although the embodiments of the present disclosure have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present disclosure, and such modifications and variations are all within the scope defined by the appended claims.
Claims
1. A method for positioning a movable device, characterized in that: The method comprises: Determine the target identifier relative to the current position in the current scene; determining a first vector distance between the key point and the target marker based on a first coordinate of the key point in a first coordinate system, wherein the first coordinate system corresponds to the movable device; Obtaining second coordinates of the key point in a second coordinate system, where the second coordinate system corresponds to the electronic map of the current scene; Based on the second coordinate and the first vector distance, it is determined that the current position corresponds to a target position in the current scene.
2. The method according to claim 1, characterized in that Determining a target identifier relative to the current position in the current scene includes: Acquire the point cloud data to be processed collected at the current position; Based on a preset brightness threshold interval, identifying the point data to be processed whose brightness value is within the brightness threshold interval, and obtaining a plurality of candidate point cloud data, wherein the brightness threshold interval depends on the reflective intensity of the target mark; Determining target point cloud data from the plurality of candidate point cloud data based on preset attribute information of the target identifier; The target identifier relative to the current position is obtained through the target point cloud data.
3. The method according to claim 2, characterized in that The method of identifying the point data to be processed whose brightness value is within the preset brightness threshold interval based on the preset brightness threshold interval to obtain multiple candidate point cloud data includes: Traversing the brightness value of each point data to be processed, taking the point data to be processed whose brightness value is within the brightness threshold range as the intermediate point data, and obtaining the intermediate point cloud data; Clustering is performed on the intermediate point cloud data to obtain the plurality of candidate point cloud data.
4. The method according to claim 3, characterized in that The determining the target point cloud data from the plurality of candidate point cloud data based on the preset attribute information of the target identifier includes: Determining, from the electronic map, a preset marker corresponding to the current location in the current scene, and obtaining a first reference coordinate of a target key point of the preset marker in the second coordinate system, wherein attribute information of the preset marker is identical to the preset attribute information; Determining a second reference coordinate of the target key point in the first coordinate system based on a mapping relationship between the second coordinate system and the first coordinate system and the first reference coordinate; Determine the target vector distance between the preset marker and the second reference coordinate; Based on the target vector distance and the attribute information, target point cloud features are determined, and candidate point cloud data that meets the target point cloud features are determined as the target point cloud data.
5. The method according to claim 4, characterized in that The target vector distance includes a target relative distance from the preset marker and a target relative offset angle, the attribute information includes a target size of the preset marker and a corresponding reflection intensity, and determining target point cloud features based on the target vector distance and the attribute information includes: Determining a data quantity range of target point data in the target point cloud data based on the target size and the target relative distance; Determining an average brightness range of the target point cloud data based on the reflected light intensity and the target relative offset angle; Determining the size range of the target point cloud data according to the target size; The target pointing angle corresponding to the target point cloud data is determined by the target relative offset angle to obtain the target point cloud features, wherein the target point cloud features include: the target pointing angle, the size range, the average brightness range, and the data quantity range.
6. The method according to claim 4, characterized in that The step of determining the candidate point cloud data that meets the target point cloud characteristics as the target point cloud data includes: If there are multiple target point cloud data that meet the target point cloud characteristics, determine the confidence level of each target point cloud data based on the historical movement trajectory of the movable device; The target point cloud data with the highest confidence value is used as the target point cloud data for obtaining the target identification.
7. The method according to claim 1, characterized in that The target identifier is identified based on a laser radar on the movable device, and determining, based on the second coordinate and the first vector distance, that the current position corresponds to a target position in the current scene includes: Acquire a second vector distance to the laser radar; determining a third vector distance between the second coordinate and an origin of the second coordinate system; Determining target coordinates corresponding to the current position in the second coordinate system based on the first vector distance, the second vector distance, and the third vector distance; According to the target coordinates, it is determined that the current position corresponds to the target position in the current scene.
8. A positioning device for a movable device, characterized in that: The device comprises: Identification module, used to determine the target identity relative to the current position in the current scene; A processing module, configured to determine a first vector distance between the key point of the target identifier and the key point based on a first coordinate of the key point in a first coordinate system, wherein the first coordinate system corresponds to the movable device; an acquisition module, configured to acquire a second coordinate of the key point in a second coordinate system, where the second coordinate system corresponds to an electronic map of the current scene; A positioning module is used to determine that the current position corresponds to a target position in the current scene based on the second coordinate and the first vector distance.
9. A movable device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the positioning method for a mobile device according to any one of claims 1 to 7 by executing the computer instructions.
10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the positioning method for a movable device according to any one of claims 1 to 7.