Positioning method, readable storage medium and smart device

Abstract

A positioning method, a readable storage medium and a smart device. The positioning method comprises: acquiring an initial pose of a smart device (S101); on the basis of the initial pose and a global point cloud map, acquiring a local point cloud set of the smart device within a preset range (S102); and on the basis of the local point cloud set, acquiring a height positioning result of the smart device (S103).

Description

Positioning method, readable storage medium and intelligent device This application claims priority to Chinese patent application CN 202410163579.7, filed on February 5, 2024, entitled “Positioning method, readable storage medium and intelligent device”. The entire contents of the above Chinese patent application are incorporated into this application by reference. Technical Field

[0001] The present application relates to the field of autonomous driving technology, and specifically provides a positioning method, a readable storage medium, and an intelligent device. Background Art

[0002] In environments without GNSS (Global Navigation Satellite System) support, maintaining high positioning stability, especially in underground parking lots, is a challenging yet crucial challenge. Without GNSS resilience, altitude deviations significantly reduce the accuracy of map matching points, which in turn leads to altitude deviations. This positive feedback loop can cause even slight altitude deviations to rapidly deteriorate to the point where positioning fails.

[0003] The industry typically uses multiple 2D maps of multi-story parking garages to avoid height calculations, while using methods such as floor semantic recognition to determine the floor. This method cannot support cross-floor positioning in multi-story parking garages and relies on relatively complete semantic information in the basement scene.

[0004] Accordingly, a new positioning solution is needed in this field to solve the above problems. Summary of the Invention

[0005] In order to overcome the above-mentioned defects, the present application is proposed to provide a solution or at least partially solve the problem of how to achieve accurate height positioning.

[0006] In a first aspect, the present application provides a positioning method, characterized in that the method is applied to a smart device, and the method includes:

[0007] Obtaining an initial position of the smart device;

[0008] Acquire a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map;

[0009] Obtain a height positioning result of the smart device according to the local point cloud set.

[0010] In one technical solution of the above positioning method, obtaining the height positioning result of the smart device based on the local point cloud set includes:

[0011] Screening the point clouds in the local point cloud set to obtain a final candidate point cloud;

[0012] The height positioning result is obtained according to the final candidate point cloud.

[0013] In a technical solution of the above positioning method, before obtaining the height positioning result in the final candidate point cloud, the method further includes:

[0014] Determining whether a first determination condition is satisfied according to a proportion of the final candidate point cloud in the local point cloud set;

[0015] Determining whether a second determination condition is satisfied based on the number of the final candidate point clouds;

[0016] When both the first determination condition and the second determination condition are satisfied, the step of “obtaining the height positioning result according to the final candidate point cloud” is executed.

[0017] In one technical solution of the above positioning method, judging whether the first determination condition is satisfied based on the proportion of the final candidate point cloud in the local point cloud set includes:

[0018] When the ratio is greater than a preset ratio threshold, it is determined that the first determination condition is met;

[0019] When the ratio is less than or equal to the ratio threshold, it is determined that the first determination condition is not satisfied.

[0020] In one technical solution of the above positioning method, judging whether the second determination condition is satisfied based on the number of the final candidate point clouds includes:

[0021] When the number is greater than a preset number threshold, it is determined that the second determination condition is met;

[0022] When the number is less than or equal to the number threshold, it is determined that the second determination condition is not satisfied.

[0023] In one technical solution of the above positioning method, screening the point clouds in the local point cloud set to obtain the final candidate point cloud includes:

[0024] Acquire a point cloud in the local point cloud set that is parallel to the plane where the smart device is located as an initial candidate point cloud;

[0025] According to the initial candidate point cloud, outlier non-ground point clouds are filtered out to obtain the final candidate point cloud.

[0026] In one technical solution of the above positioning method, obtaining a point cloud in the local point cloud set that is parallel to the plane where the smart device is located as an initial candidate point cloud includes:

[0027] Obtaining an angle between a normal vector of a point cloud in the local point cloud set and a normal vector of a plane where the smart device is located;

[0028] When the included angle is within a first preset angle range or a second preset angle range, the point cloud corresponding to the included angle is used as the initial candidate point cloud;

[0029] The first preset angle range is 0°-preset angle threshold to 0°+preset angle threshold; the second preset angle range is 180°-preset angle threshold to 180°+preset angle threshold.

[0030] In one technical solution of the above positioning method, obtaining the height positioning result according to the final candidate point cloud includes:

[0031] The height positioning result is obtained according to the mean and variance of the heights of the final candidate point cloud.

[0032] In one technical solution of the above positioning method, the global point cloud map is a global NDT map;

[0033] The step of obtaining a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map includes:

[0034] A local point cloud set within a preset range of the smart device is obtained according to the initial pose and the global NDT map.

[0035] In a technical solution of the above positioning method, the preset range includes a first preset range and a second preset range; the first preset range is larger than the second preset range;

[0036] The step of obtaining a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map includes:

[0037] Obtaining a floor positioning result of the smart device;

[0038] When the floor positioning result is obtained, obtaining a local point cloud set within a first preset range of the smart device according to the initial posture and the global point cloud map;

[0039] When the floor positioning result is not obtained, a local point cloud set within a second preset range of the smart device is obtained according to the initial posture and the global point cloud map.

[0040] In one technical solution of the above positioning method, the method further includes:

[0041] When the floor positioning result and the height positioning result are obtained, updating the height positioning result of the floor corresponding to the floor positioning result based on the obtained height positioning result;

[0042] When the floor positioning result is obtained but the height positioning result is not obtained, the historical height positioning result corresponding to the floor positioning result is used as the current height positioning result.

[0043] In a second aspect, a computer-readable storage medium is provided, wherein a plurality of program codes are stored in the computer-readable storage medium, wherein the program codes are suitable for being loaded and run by a processor to execute the positioning method described in any one of the technical solutions of the above-mentioned positioning method.

[0044] In a third aspect, a smart device is provided, comprising:

[0045] at least one processor;

[0046] and, a memory communicatively coupled to the at least one processor;

[0047] Wherein, a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the positioning method described in any one of the technical solutions of the above-mentioned positioning method is implemented.

[0048] The above one or more technical solutions of this application have at least one or more of the following beneficial effects:

[0049] In implementing the technical solution of this application, this application obtains the initial posture of the smart device, obtains a local point cloud set within a preset range of the smart device based on the initial posture and the global point cloud map, and obtains the height positioning result of the smart device based on the local point cloud set. Through the above configuration, this application can realize a universal positioning process that does not distinguish between scenes based on the initial posture of the smart device and the global point cloud map. The positioning process only requires the characteristic elements of the initial posture and the global point cloud map, and does not require the provision of additional semantic floor recognition functions. It can effectively improve the stability of height positioning and has better versatility. It can then realize path planning based on the height positioning result of the smart device and the destination location information, thereby realizing functions such as cross-floor parking. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The disclosure of this application will become more easily understood with reference to the accompanying drawings. Those skilled in the art will readily appreciate that these drawings are for illustrative purposes only and are not intended to limit the scope of protection of this application. Among them:

[0051] FIG1 is a schematic flow chart of the main steps of a positioning method according to an embodiment of the present application;

[0052] FIG2 is a schematic flow chart of the main steps of a positioning method according to an implementation of an embodiment of the present application;

[0053] FIG3 is a schematic diagram of a local point cloud set according to an example of an embodiment of the present application;

[0054] FIG4 is a schematic diagram of a main structural block diagram of a positioning system according to an embodiment of the present application;

[0055] FIG5 is a schematic diagram of a connection relationship between a memory and a processor of a smart device according to an embodiment of the present application. DETAILED DESCRIPTION

[0056] Some embodiments of the present application are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present application and are not intended to limit the scope of protection of the present application.

[0057] In the description of this application, "module" and "processor" may include hardware, software, or a combination of both. A module may include hardware circuitry, various suitable sensors, communication ports, and memory. It may also include software components, such as program code, or a combination of software and hardware. A processor may be a central processing unit, a microprocessor, an image processor, a digital signal processor, or any other suitable processor. A processor has data and / or signal processing capabilities. A processor may be implemented in software, hardware, or a combination of both. Non-transitory computer-readable storage media include any suitable medium capable of storing program code, such as magnetic disks, hard disks, optical disks, flash memory, read-only memory, random access memory, etc. The term "A and / or B" refers to all possible combinations of A and B, such as only A, only B, or both A and B. The terms "at least one of A or B" or "at least one of A and B" have similar meanings to "A and / or B" and may include only A, only B, or both A and B. The singular forms "a" and "the" may also include the plural forms.

[0058] Here we first explain some terms involved in this application.

[0059] An automated driving system (ADS) is a system that continuously performs all dynamic driving tasks (DDT) within its operational domain design (ODD). Specifically, the system is only allowed to fully assume the task of autonomous vehicle control under specified appropriate driving scenarios. When the vehicle meets the ODD conditions, the system is activated, replacing the human driver as the vehicle's primary driver. The DDT refers to the continuous lateral (left and right steering) and longitudinal motion control (acceleration, deceleration, and constant speed) of the vehicle, as well as the detection and response to objects and events in the vehicle's driving environment. The ODD refers to the conditions under which the automated driving system can operate safely. These conditions can include geographic location, road type, speed range, weather, time of day, and national and local traffic laws and regulations.

[0060] In an example of an application scenario of the present application, high-level positioning of smart devices in a multi-story parking lot is achieved.

[0061] Referring to FIG1 , FIG1 is a flow chart showing the main steps of a positioning method according to an embodiment of the present application. As shown in FIG1 , the positioning method in the embodiment of the present application is applied to a smart device, and the positioning method mainly includes the following steps S101 to S103.

[0062] Step S101: Acquire the initial posture of the smart device.

[0063] In this embodiment, the initial position and posture of the smart device can be obtained.

[0064] In one embodiment, the smart device may be a driving device, a smart car, a robot, or the like.

[0065] In one implementation, the initial pose can be obtained based on the smart device's IMU (Inertial Measurement Unit) and wheel speedometer. Alternatively, trajectory prediction can be achieved by fusing data collected by multiple on-board sensors. Alternatively, the initial pose can be obtained based on the output of a laser odometry. Alternatively, a combination of the above methods can be used to obtain the initial pose.

[0066] Step S102: Acquire a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map.

[0067] In this embodiment, a local point cloud set within a preset range centered on the smart device can be obtained from the global point cloud map according to the initial posture.

[0068] In one embodiment, a local point cloud set within a preset range of the smart device can be obtained from the global point cloud map based on the initial position and the floor positioning result of the smart device. When the local point cloud set is obtained in combination with the floor positioning result of the smart device, a larger preset range can be determined because the floor positioning result indicates that the smart device is currently stable on a certain floor. The floor positioning result is the floor on which the smart device is located. The floor positioning result of the smart device can be obtained using methods commonly used in the art, and this application does not limit this.

[0069] In one embodiment, when the floor positioning result is not obtained, or the smart device is not stable on a certain floor, it means that the smart device may be in a cross-floor state. At this time, the smart device may be in a cross-floor aisle. Since it is relatively narrow, a smaller preset range can be determined.

[0070] Step S103: Obtaining the height positioning result of the smart device based on the local point cloud set.

[0071] In this embodiment, the height positioning result of the smart device can be obtained based on the local point cloud set.

[0072] In one embodiment, path planning can be performed based on the height positioning result of the smart device and the destination location information (such as the location information of the target parking space), thereby realizing functions such as cross-level parking.

[0073] Based on the above steps S101 to S103, the embodiment of the present application obtains the initial posture of the smart device, obtains a local point cloud set within a preset range of the smart device based on the initial posture and the global point cloud map, and obtains the height positioning result of the smart device based on the local point cloud set. Through the above configuration, the embodiment of the present application can realize a universal positioning process that does not distinguish between scenes based on the initial posture of the smart device and the global point cloud map. The positioning process only requires the characteristic elements of the initial posture and the global point cloud map, and does not require the provision of additional semantic floor recognition functions. It can effectively improve the stability of height positioning and has better versatility. It can then realize path planning based on the height positioning result of the smart device and the destination location information, thereby realizing functions such as cross-floor parking.

[0074] Step S102 and step S103 are further described below.

[0075] In one implementation of the embodiment of the present application, the global point cloud map is a global NDT map, and step S102 may be further configured as follows:

[0076] According to the initial pose and the global NDT (Normal-Distributions Transform) map, a local point cloud set within the preset range of the smart device is obtained.

[0077] In this embodiment, the global NDT map is applied to achieve lightweight point cloud maps, thereby achieving faster calculation speed.

[0078] In one embodiment of the present application, the preset range includes a first preset range and a second preset range; the first preset range is larger than the second preset range. Step S102 may further include the following steps S1021 to S1023:

[0079] Step S1021: Obtain the floor positioning result of the smart device.

[0080] Step S1022: When the floor positioning result is obtained, a local point cloud set within a first preset range of the smart device is obtained based on the initial posture and the global point cloud map.

[0081] Step S1023: When the floor positioning result is not obtained, a local point cloud set within a second preset range of the smart device is obtained according to the initial posture and the global point cloud map.

[0082] In this embodiment, a preset range can be set based on whether the smart device has obtained a floor positioning result. If a floor positioning result is obtained, it indicates that the smart device is stable on a certain floor, and a larger first preset range can be set. If a floor positioning result is not obtained, it indicates that the smart device may be in a cross-floor state. In this case, the smart device may be in a narrow aisle between floors, so a smaller second preset range can be determined. Then, based on the initial position of the smart device and the global point cloud map, a local point cloud set can be obtained.

[0083] In one implementation of the embodiment of the present application, step S103 may further include the following steps S1031 and S1032:

[0084] Step S1031: Filter the point clouds in the local point cloud set to obtain the final candidate point cloud.

[0085] In this embodiment, step S1031 may further include the following steps S10311 and S10312:

[0086] Step S10311: Obtain the point cloud in the local point cloud set that is parallel to the plane where the smart device is located as the initial candidate point cloud.

[0087] In this embodiment, step S10311 may further include the following steps S103111 and S103112:

[0088] Step S103111: Obtain the angle between the normal vector of the point cloud in the local point cloud set and the normal vector of the plane where the smart device is located.

[0089] Step S103112: When the included angle is within the first preset angle range or the second preset angle range, the point cloud corresponding to the included angle is used as the initial candidate point cloud; wherein the first preset angle range is 0°-preset angle threshold to 0°+preset angle threshold; the second preset angle range is 180°-preset angle threshold to 180°+preset angle threshold.

[0090] In this embodiment, the plane on which the smart device resides is generally parallel to the ground, so the initial candidate point cloud obtained is often points parallel to the ground plane. Point clouds in the local point cloud set where the angle between the normal vector of the point cloud and the normal vector of the plane on which the smart device resides is 0 or 180 degrees can be obtained, and a preset angle threshold can be set to obtain the initial candidate point cloud.

[0091] Step S10312: Based on the initial candidate point cloud, outlier non-ground point clouds are filtered out to obtain the final candidate point cloud.

[0092] In this embodiment, outlier non-ground point clouds may be filtered out from the initial candidate point cloud to obtain a final candidate point cloud.

[0093] In one embodiment, a RANSAC (Random Sample Consensus) method may be used to filter out outlier non-ground point clouds based on their heights.

[0094] Please refer to Figure 3, which is a schematic diagram of a local point cloud set according to an example of an embodiment of the present application. In the local point cloud set in Figure 3, the point cloud corresponding to label 1 is a point cloud that is not parallel to the plane where the smart device is located; the point cloud corresponding to label 2 is an outlier non-ground point cloud; and the point cloud corresponding to label 3 is the final candidate point cloud. That is, after obtaining the local point cloud set, the point clouds corresponding to labels 1 and 2 are filtered out, and the remaining point cloud is the final candidate point cloud (i.e., the point cloud corresponding to label 3). It should be noted that due to the large number of point clouds in Figure 3, the point clouds corresponding to labels 1, 2, and 3 are only illustrative and not all are marked.

[0095] In one embodiment, before step S1032, step S103 may further include the following steps S1033 to S1035:

[0096] Step S1033: judging whether the first determination condition is satisfied according to the proportion of the final candidate point cloud in the local point cloud set.

[0097] In this embodiment, it can be determined based on whether the proportion of the final candidate point cloud in the local point cloud set is greater than a preset proportion threshold; if so, it is determined that the first determination condition is met; if not, it is determined that the first determination condition is not met.

[0098] In one embodiment, the ratio threshold may be 0.8.

[0099] Step S1034: Determine whether the second determination condition is met based on the number of the final candidate point clouds.

[0100] In this embodiment, whether the second determination condition is satisfied can be determined based on the comparison result of the number of the final candidate point clouds with a preset number threshold. When the number is greater than the number threshold, the second determination condition is determined to be satisfied; when the number is less than or equal to the number threshold, the second determination condition is determined not to be satisfied.

[0101] In one implementation, the quantity threshold may be 10.

[0102] Step S1035: When both the first determination condition and the second determination condition are satisfied, execute step S1032.

[0103] Step S1032: Obtain the height positioning result based on the final candidate point cloud.

[0104] In this embodiment, the height positioning result can be obtained according to the mean and variance of the height of the final candidate point cloud.

[0105] In one embodiment, the height positioning result of the smart device can be obtained in combination with the floor positioning result of the smart device. Specifically, when the floor positioning result of the smart device is obtained and the height positioning result is obtained through the above step S103, the height positioning result of the corresponding floor of the floor positioning result can be updated based on the height positioning result. If the floor positioning result of the smart device is obtained but the height positioning result is not obtained through the above step S103, the historical height positioning result corresponding to the floor positioning result can be read based on the floor positioning result as the current height positioning result. That is, assuming that the height of the same floor does not change much, the historical priori output of the height positioning result can be used as the current height positioning result.

[0106] In one embodiment, if the height positioning result is not obtained (the first determination condition or the second determination condition is not met) and the floor positioning result is not obtained, it means that the smart device is on an unstable floor, such as in a passage between floors, and a height positioning failure message is output.

[0107] In one embodiment, please refer to Figure 2, which is a schematic flow chart of the main steps of a positioning method according to one embodiment of the present application. As shown in Figure 2, the positioning method can input the initial position of the smart device and the floor positioning result, where the floor positioning result can be obtained using a floor meter. Based on the floor positioning result, the preset range can be selected by determining whether the smart device is stable on a certain floor. The tunnel mode params correspond to the second preset range (i.e., the floor meter is not connected or is not in a stable floor state), and the floor mode params correspond to the first preset range (i.e., the floor meter is in a stable floor state). A local point cloud set is obtained based on the preset range and the global point cloud map. Based on the local point cloud set, an initial candidate point cloud parallel to the plane where the smart device is located is obtained. Based on the initial candidate point cloud, outlier point clouds are filtered out to obtain a final candidate point cloud. Based on the final candidate point cloud, it is determined whether the calculation is successful. If so, the historical height positioning result of the same floor positioning result is updated as a priori reference in the event that a subsequent height positioning result cannot be obtained. If not, it is determined whether the smart device is stable on a certain floor. If so, the historical height positioning result of the corresponding floor is used. If not, a failure message is output.

[0108] It should be pointed out that although the various steps in the above embodiments are described in a specific order, those skilled in the art will understand that in order to achieve the effect of the present application, different steps do not have to be performed in such an order. They can be performed simultaneously (in parallel) or in other orders. These changes are within the scope of protection of the present application.

[0109] Furthermore, the present application also provides a positioning system.

[0110] Refer to Figure 4, which is a main structural block diagram of a positioning system according to an embodiment of the present application. As shown in Figure 4, the positioning system in the embodiment of the present application mainly includes an initial posture acquisition module, a local point cloud collection acquisition module and a height positioning result acquisition module. In this embodiment, the initial posture acquisition module can be configured to obtain the initial posture of the smart device. The local point cloud collection acquisition module can be configured to obtain a local point cloud collection within a preset range of the smart device based on the initial posture and the global point cloud map. The height positioning result acquisition module can be configured to obtain the height positioning result of the smart device based on the local point cloud collection.

[0111] The above-mentioned positioning system is used to execute the positioning method embodiment shown in Figure 1. The technical principles, technical problems solved and technical effects produced by the two are similar. Technical personnel in this technical field can clearly understand that for the convenience and conciseness of description, the specific working process and related instructions of the positioning system can refer to the contents described in the embodiment of the positioning method, and will not be repeated here.

[0112] It will be understood by those skilled in the art that all or part of the processes in the method for implementing the above embodiment of the present application can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium that can carry the computer program code. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media do not include electric carrier signals and telecommunication signals.

[0113] Furthermore, the present application also provides a computer-readable storage medium. In a computer-readable storage medium embodiment according to the present application, the computer-readable storage medium can be configured to store a program for executing the positioning method of the above-mentioned method embodiment, and the program can be loaded and run by the processor to implement the above-mentioned positioning method. For ease of explanation, only the parts related to the embodiment of the present application are shown. For specific technical details not disclosed, please refer to the method part of the embodiment of the present application. The computer-readable storage medium can be a storage device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiment of the present application is a non-transitory computer-readable storage medium.

[0114] Another aspect of the present application also provides an intelligent device, which may include at least one processor; and a memory communicatively connected to the at least one processor; wherein a computer program is stored in the memory, and when the computer program is executed by the at least one processor, the method described in any of the above embodiments is implemented. The intelligent device of the present application may include driving devices, smart cars, robots and other devices. Please refer to Figure 5, which is a schematic diagram of the connection relationship between the memory and the processor of the intelligent device according to an embodiment of the present application. As shown in Figure 5, Figure 5 exemplarily shows that the memory and the processor are communicatively connected via a bus.

[0115] In some embodiments of the present application, the smart device further includes at least one sensor for sensing information. The sensor is communicatively coupled to any of the types of processors described herein. Optionally, the smart device further includes an autonomous driving system for guiding the smart device to drive autonomously or with assistance. The processor communicates with the sensor and / or autonomous driving system to perform the method described in any of the above embodiments.

[0116] Furthermore, it should be understood that since the configuration of each module is merely for the purpose of illustrating the functional units of the apparatus of the present application, the physical devices corresponding to these modules may be the processor itself, or a portion of the software in the processor, a portion of the hardware, or a combination of software and hardware. Therefore, the number of modules in the figure is merely illustrative.

[0117] Those skilled in the art will appreciate that the various modules in the device can be adaptively split or merged. Such splitting or merging of specific modules will not cause the technical solution to deviate from the principles of this application. Therefore, the technical solutions after splitting or merging will fall within the scope of protection of this application.

[0118] The relevant user personal information that may be involved in the various embodiments of this application is strictly in accordance with the requirements of laws and regulations, following the principles of legality, legitimacy and necessity, and based on the reasonable purposes of business scenarios, to process the personal information that users actively provide during the use of products / services or generated due to the use of products / services, as well as the personal information obtained with the user's authorization.

[0119] The user personal information processed in this application will vary depending on the specific product / service scenario and will be based on the specific scenario in which the user uses the product / service. This may involve the user's account information, device information, driving information, vehicle information, or other related information. The applicant will treat the user's personal information and its processing with a high degree of diligence.

[0120] This application attaches great importance to the security of user personal information and has taken reasonable and feasible security protection measures that comply with industry standards to protect user information and prevent personal information from being accessed, disclosed, used, modified, damaged or lost without authorization.

[0121] Thus far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of the present application is obviously not limited to these specific embodiments. Without departing from the principles of the present application, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present application.

Claims

1. A positioning method, characterized in that: The method is applied to a smart device and includes: Obtaining an initial position of the smart device; Acquire a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map; Obtain a height positioning result of the smart device according to the local point cloud set.

2. The positioning method according to claim 1, wherein: The obtaining of a height positioning result of the smart device according to the local point cloud set includes: Screening the point clouds in the local point cloud set to obtain a final candidate point cloud; The height positioning result is obtained according to the final candidate point cloud.

3. The positioning method according to claim 2, characterized in that: Before obtaining the height positioning result according to the final candidate point cloud, the method further includes: Determining whether a first determination condition is satisfied according to a proportion of the final candidate point cloud in the local point cloud set; Determining whether a second determination condition is satisfied based on the number of the final candidate point clouds; When both the first determination condition and the second determination condition are met, the step of "obtaining the height positioning result according to the final candidate point cloud" is performed.

4. The positioning method according to claim 3, characterized in that: The determining whether the first determination condition is satisfied based on the proportion of the final candidate point cloud in the local point cloud set includes: When the ratio is greater than a preset ratio threshold, it is determined that the first determination condition is met; When the ratio is less than or equal to the ratio threshold, it is determined that the first determination condition is not satisfied.

5. The positioning method according to claim 3, characterized in that: The determining, based on the number of the final candidate point clouds, whether the second determination condition is satisfied includes: When the number is greater than a preset number threshold, it is determined that the second determination condition is met; When the number is less than or equal to the number threshold, it is determined that the second determination condition is not satisfied.

6. The positioning method according to claim 2, characterized in that: The step of screening the point clouds in the local point cloud set to obtain the final candidate point cloud includes: Acquire a point cloud in the local point cloud set that is parallel to the plane where the smart device is located as an initial candidate point cloud; According to the initial candidate point cloud, outlier non-ground point clouds are filtered out to obtain the final candidate point cloud.

7. The positioning method according to claim 6, characterized in that: The step of obtaining a point cloud in the local point cloud set that is parallel to the plane where the smart device is located as an initial candidate point cloud includes: Obtaining an angle between a normal vector of a point cloud in the local point cloud set and a normal vector of a plane where the smart device is located; When the included angle is within a first preset angle range or a second preset angle range, the point cloud corresponding to the included angle is used as the initial candidate point cloud; The first preset angle range is 0°-preset angle threshold to 0°+preset angle threshold; the second preset angle range is 180°-preset angle threshold to 180°+preset angle threshold.

8. The positioning method according to any one of claims 2 to 7, characterized in that: The step of obtaining the height positioning result according to the final candidate point cloud includes: The height positioning result is obtained according to the mean and variance of the heights of the final candidate point cloud.

9. The positioning method according to claim 1, characterized in that: The global point cloud map is a global NDT map; The step of obtaining a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map includes: A local point cloud set within a preset range of the smart device is obtained according to the initial pose and the global NDT map.

10. The positioning method according to any one of claims 1 to 9, characterized in that: The preset range includes a first preset range and a second preset range; the first preset range is larger than the second preset range; The step of obtaining a local point cloud set within a preset range of the smart device according to the initial posture and the global point cloud map includes: Obtaining a floor positioning result of the smart device; When the floor positioning result is obtained, obtaining a local point cloud set within a first preset range of the smart device according to the initial posture and the global point cloud map; When the floor positioning result is not obtained, a local point cloud set within a second preset range of the smart device is obtained according to the initial posture and the global point cloud map.

11. The positioning method according to claim 10, characterized in that: The method further comprises: When the floor positioning result and the height positioning result are obtained, updating the height positioning result of the floor corresponding to the floor positioning result based on the obtained height positioning result; When the floor positioning result is obtained but the height positioning result is not obtained, the historical height positioning result corresponding to the floor positioning result is used as the current height positioning result.

12. A computer-readable storage medium storing a plurality of program codes, characterized in that: The program code is suitable for being loaded and run by a processor to execute the positioning method according to any one of claims 1 to 11.

13. A smart device, characterized in that: The smart device includes: at least one processor; and, a memory communicatively coupled to the at least one processor; The memory stores a computer program, and when the computer program is executed by the at least one processor, the positioning method according to any one of claims 1 to 11 is implemented.

Images