CN110940994B - Positioning initialization method and system thereof - Google Patents

Abstract

The present disclosure provides a positioning initialization method for positioning an initial position and an initial heading angle of an object, including: acquiring laser point clouds of the current environment of the object through a laser radar arranged on the object; dividing a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving line of an object based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds; a plurality of initial poses are formulated based on sub map point clouds corresponding to the plurality of blocks; and matching the laser point cloud with the plurality of planned initial poses to initialize the positioning of the object. The present disclosure also provides a positioning initialization system, a computer system, and a computer-readable storage medium.

Description

Positioning initialization method and system

Technical Field

The present disclosure relates to the field of Internet technology, and more specifically, to a positioning initialization method and system thereof, as well as a computer system and a computer-readable storage medium.

Background technique

In recent years, driverless technology, especially outdoor driverless cars, has played an increasingly important role in e-commerce and food delivery. LiDAR is a relatively robust positioning technology commonly used in driverless cars.

In the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related technology: the existing lidar positioning technology must rely on a third party such as GPS satellites and magnetic compasses to complete positioning initialization. In this case, if there is no GPS signal or the GPS signal is blocked by a building, it will cause a large positioning error, and the magnetic compass is susceptible to interference outdoors, which will also cause a large positioning error.

Summary of the invention

In view of this, the present disclosure provides a positioning initialization method and a positioning initialization system capable of implementing the method, as well as a computer system and a computer-readable storage medium.

One aspect of the present disclosure provides a positioning initialization method for locating the initial position and initial heading angle of an object, comprising: acquiring a laser point cloud of the current environment of the object by means of a laser radar arranged on the object; segmenting a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of the object based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds; formulating a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks; and matching the laser point cloud with the plurality of proposed initial poses to perform positioning initialization on the object.

According to an embodiment of the present disclosure, the above-mentioned multiple initial postures are formulated based on the sub-map point clouds corresponding to the above-mentioned multiple blocks, including: determining the center point of each block based on the sub-map point clouds corresponding to the above-mentioned multiple blocks; and setting multiple heading angles for each center point to formulate the above-mentioned multiple initial postures.

According to an embodiment of the present disclosure, the above-mentioned method of segmenting a plurality of blocks corresponding to a plurality of line segments obtained by dividing the predetermined moving route of the above-mentioned object based on a pre-constructed point cloud map includes: acquiring the above-mentioned point cloud map and the above-mentioned predetermined moving route; segmenting the above-mentioned predetermined moving route into a plurality of line segments; determining the center point of each of the above-mentioned plurality of line segments; and segmenting the point cloud of the above-mentioned point cloud map based on each center point to obtain corresponding blocks.

According to an embodiment of the present disclosure, the point cloud of the point cloud map is segmented based on each center point to obtain corresponding blocks, including: for each center point, the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold are segmented into a block.

According to an embodiment of the present disclosure, for each center point, the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold are divided into a block, including: dividing the point cloud of the point cloud map into a line feature point cloud and a surface feature point cloud; for each center point, the points in the line feature point cloud whose distance from the center point is less than the first threshold are divided into a block; and for each center point, the points in the surface feature point cloud whose distance from the center point is less than the first threshold are also divided into the block; the matching of the laser point cloud with the proposed multiple initial poses includes: dividing the laser point cloud into a line feature laser point cloud and a surface feature laser point cloud; and matching the line feature laser point cloud and the surface feature laser point cloud with the proposed multiple initial poses, respectively.

Another aspect of the present disclosure provides a positioning initialization system for locating the initial position and initial heading angle of an object, including: an acquisition module, used to acquire a laser point cloud of the current environment of the object through a laser radar set on the object; a segmentation module, used to segment a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of the object based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds; a formulation module, used to formulate a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks; and a matching module, used to match the laser point cloud with the proposed plurality of initial poses to perform positioning initialization on the object.

According to an embodiment of the present disclosure, the above-mentioned drafting module includes: a first determination unit, used to determine the center point of each block based on the sub-map point cloud corresponding to the above-mentioned multiple blocks; and a setting unit, used to set multiple heading angles for each center point to draft the above-mentioned multiple initial postures.

According to an embodiment of the present disclosure, the above-mentioned segmentation module includes: an acquisition unit, used to acquire the above-mentioned point cloud map and the above-mentioned predetermined moving route; a first segmentation unit, used to segment the above-mentioned predetermined moving route into multiple line segments; a second determination unit, used to determine the center point of each of the above-mentioned multiple line segments; and a second segmentation unit, used to segment the point cloud of the above-mentioned point cloud map based on each center point to obtain corresponding blocks.

According to an embodiment of the present disclosure, the second segmentation unit is further used to: for each center point, segment the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block.

According to an embodiment of the present disclosure, the above-mentioned second segmentation unit includes: a division subunit, used to divide the point cloud of the above-mentioned point cloud map into line feature point cloud and surface feature point cloud; a first segmentation subunit, used to segment the points in the above-mentioned line feature point cloud whose distance from the center point is less than the above-mentioned first threshold into a block for each center point; and a second segmentation subunit, used to segment the points in the above-mentioned surface feature point cloud whose distance from the center point is less than the above-mentioned first threshold into the block for each center point; the above-mentioned matching module includes: a division unit, used to divide the above-mentioned laser point cloud into line feature laser point cloud and surface feature laser point cloud; and a matching unit, used to respectively match the above-mentioned line feature laser point cloud and the above-mentioned surface feature laser point cloud with the above-mentioned multiple proposed initial poses.

Another aspect of the present disclosure provides a computer system, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the method described above.

Another aspect of the present disclosure provides a non-volatile storage medium storing computer executable instructions, which are used to implement the above method when executed.

Another aspect of the present disclosure provides a computer program, wherein the computer program includes computer executable instructions, and the instructions are used to implement the above method when executed.

According to the embodiments of the present disclosure, since a technical means is adopted to prepare multiple initial postures according to the predetermined moving route of the object for positioning initialization, it at least partially overcomes the technical problems that the existing positioning initialization needs to rely on a third party, and the positioning initialization error is large due to the absence of GPS signal or the GPS signal is blocked or the magnetic compass is interfered with, thereby achieving the technical effect of not needing the help of a third party and with a small positioning initialization error.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

FIG1 schematically shows an exemplary system architecture to which the positioning initialization method and system of the present disclosure can be applied;

FIG2 schematically shows a flow chart of a positioning initialization method according to an embodiment of the present disclosure;

FIG3 schematically shows an application scenario of a positioning initialization method according to an embodiment of the present disclosure;

FIG4 schematically shows an application scenario of a positioning initialization method according to another embodiment of the present disclosure;

FIG5 schematically shows a flow chart of preparing an initial posture according to an embodiment of the present disclosure;

FIG6 schematically shows a schematic diagram of segmenting blocks according to an embodiment of the present disclosure;

FIG7 schematically shows a block diagram of a positioning initialization system according to an embodiment of the present disclosure;

FIG8 schematically shows a block diagram of a proposed module according to an embodiment of the present disclosure;

FIG9 schematically shows a block diagram of a segmentation module according to an embodiment of the present disclosure; and

FIG. 10 schematically shows a block diagram of a computer system suitable for implementing a positioning initialization method according to an embodiment of the present disclosure.

Detailed ways

Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "include", "comprising", etc. used herein indicate the existence of the features, steps, operations and/or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

In the case of using expressions such as "at least one of A, B, and C, etc.", it should generally be interpreted according to the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but not be limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc.). In the case of using expressions such as "at least one of A, B, or C, etc.", it should generally be interpreted according to the meaning of the expression generally understood by those skilled in the art (for example, "a system having at least one of A, B, or C" should include but not be limited to systems having A alone, B alone, C alone, A and B, A and C, B and C, and/or A, B, C, etc.). Those skilled in the art should also understand that any transitional conjunctions and/or phrases that substantially represent two or more optional items, whether in the specification, claims, or drawings, should be understood to give the possibility of including one of these items, either of these items, or both items. For example, the phrase "A or B" should be understood to include the possibility of "A" or "B", or "A and B".

The embodiments of the present disclosure provide a positioning initialization method and a positioning initialization system capable of implementing the method. The method includes obtaining a laser point cloud of the current environment of the object through a laser radar set on the object; segmenting a plurality of blocks corresponding to the predetermined movement route of the object based on the point cloud map, wherein different blocks correspond to different sub-map point clouds; formulating a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks; and matching the laser point cloud with the proposed plurality of initial poses to perform positioning initialization on the object.

FIG1 schematically shows an exemplary system architecture to which the positioning initialization method and system of the present disclosure can be applied. It should be noted that FIG1 is only an example of a system architecture to which the present disclosure embodiment can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but does not mean that the present disclosure embodiment cannot be used in other devices, systems, environments or scenarios.

As shown in FIG1 , the system architecture according to this embodiment may include terminal devices 101, 102, 103, a network 104, a server 105, and a mobile device 106 (such as an unmanned vehicle). The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105, between the terminal devices 101, 102, 103 and the mobile device 106, and between the server 105 and the mobile device 106. The network 104 may include various connection types, such as wired and/or wireless communication links, etc.

The user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 101, 102, 103.

The terminal devices 101 , 102 , and 103 may be various electronic devices with display screens, including but not limited to smart phones, tablet computers, laptop computers, desktop computers, and the like.

The server 105 may be a server that provides various services, such as a background management server (only an example) that provides support for users to work with the terminal devices 101, 102, and 103. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

It should be noted that the positioning initialization method provided in the embodiment of the present disclosure can generally be executed by the server 105. Accordingly, the positioning initialization system provided in the embodiment of the present disclosure can generally be set in the server 105. The positioning initialization method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 105 and can communicate with the terminal device 101, 102, 103 and/or the server 105. Accordingly, the positioning initialization system provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 105 and can communicate with the terminal device 101, 102, 103 and/or the server 105. Alternatively, the positioning initialization method provided in the embodiment of the present disclosure can also be executed by the terminal device 101, 102, or 103, or it can also be executed by other terminal devices different from the terminal device 101, 102, or 103. Accordingly, the positioning initialization system provided in the embodiment of the present disclosure can also be set in the terminal device 101, 102, or 103, or it can be set in other terminal devices different from the terminal device 101, 102, or 103.

It should be understood that the number of terminal devices, networks and servers in Figure 1 is only illustrative. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

FIG2 schematically shows a flow chart of a positioning initialization method according to an embodiment of the present disclosure.

As shown in FIG. 2 , the method for locating the initial position and initial heading angle of an object includes operations S201 to S204 .

In operation S201 , a laser point cloud of an environment in which the object is currently located is acquired by using a laser radar disposed on the object.

In the embodiments of the present disclosure, the object may include but is not limited to an unmanned vehicle (also referred to as an unmanned vehicle), and its application fields may include being used as an unmanned delivery vehicle in the fields of e-commerce and food delivery. The present disclosure will be described in detail below using an unmanned vehicle as an example.

In addition, the technology used by LiDAR is time of flight (TOF). Specifically, it calculates the relative distance between the target and itself based on the return time after the laser encounters an obstacle. The laser beam can accurately measure the relative distance between the edge of the object contour in the field of view and the device. These contour information constitute the so-called point cloud and draw a 3D environmental map with an accuracy of centimeters, thereby improving the measurement accuracy. LiDAR also has unique advantages, such as extremely high distance resolution and angular resolution, high speed resolution, wide speed measurement range, ability to obtain multiple images of the target, and strong anti-interference ability. This enables LiDAR to accurately measure the target position (distance and angle), motion state (speed, vibration and posture) and shape, detect, identify, distinguish and track targets.

Taking unmanned vehicles as an example, during the positioning initialization process, the laser radar will first be used to perform a laser scan of the unmanned vehicle's surrounding environment (including trees and buildings, etc.) to obtain the corresponding laser point cloud.

In operation S202, a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of the object are segmented based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds.

In the disclosed embodiment, based on the positioning of the laser radar in a specific scene, a three-dimensional point cloud map of the scene is pre-constructed.

In operation S203 , a plurality of initial poses are prepared based on the sub-map point clouds corresponding to the plurality of blocks.

In the embodiment of the present disclosure, the initial posture may include an initial position and an initial heading angle.

Take the unmanned vehicle as an example, as shown in Figure 3, assuming that the delivery task undertaken by the unmanned vehicle this time is to deliver a certain product from place A to place B, then during implementation, the road section AB can be divided into multiple blocks, and the corresponding points can be selected from the point cloud corresponding to each block, and then the coordinate position of each point can be determined, and this can be used as the proposed initial position. In addition, since there is no turning point in the AB section, for each initial position, the heading angle corresponding to the outbound trip can be set to 0°, and the heading angle corresponding to the return trip can be set to 180°.

In addition, assuming that the delivery task undertaken by the unmanned vehicle this time is to transport a certain product from place A to place B, and there is a turning point C in the AB section, therefore, for each initial position in the AC section, the heading angle corresponding to the outbound trip can be set to 0°, and the heading angle corresponding to the return trip can be set to 180°, and for each initial position in the CB section, the heading angle corresponding to the outbound trip can be set to the angle corresponding to the direction from C to B, and the heading angle corresponding to the return trip can be set to the angle corresponding to the direction from B to C.

In operation S204, the laser point cloud is matched with the proposed multiple initial poses to initialize the positioning of the object.

Specifically, taking the unmanned vehicle as an example, when the laser point cloud is matched with each proposed initial pose by ICP (i.e., iterative closest point matching), within a fixed number of iterations n, if the final ICP incremental update is less than the predetermined threshold, the ICP iteration is considered to be completed, and the pose at this time is accumulated as the initial pose of the unmanned vehicle; on the contrary, if the final ICP incremental update is greater than the predetermined threshold, the initialization is considered to have failed, and an attempt is made to match the next initial position and initial heading angle until they meet the threshold. If none of them can be met, it means that the initialization has failed.

It should be noted that after the positioning initialization is completed, the subsequent positioning process can be made faster based on the initialization result.

In addition, the positioning initialization solution based on the point cloud map provided by the present invention mainly includes a hardware layer, a data layer, and an algorithm layer. The hardware layer mainly includes a lidar module and a main processor module; the data layer mainly includes point cloud data, point cloud maps (including line feature maps and surface feature maps), and the algorithm layer mainly completes the positioning initialization of the unmanned vehicle based on the point cloud map through global positioning initialization.

Compared with the prior art that uses laser radar positioning, it must rely on the initial posture provided by a third party such as GPS satellites and magnetic compasses to complete positioning initialization, resulting in large errors. According to the embodiments of the present disclosure, because a technical means is adopted to prepare multiple initial postures according to the predetermined moving route of the object for positioning initialization, it at least partially overcomes the technical problems of the prior art that positioning initialization requires the help of a third party, and the positioning initialization error is large due to the lack of GPS signal or the GPS signal is blocked or the magnetic compass is interfered with, thereby achieving the technical effect of not requiring the help of a third party and with a small positioning initialization error.

The method shown in FIG. 2 will be further described below with reference to FIG. 4 to FIG. 6 in combination with specific embodiments.

In addition to the application scenario shown in FIG3, the scheduled moving routes of unmanned vehicles are generally not so regular. For example, FIG4 schematically shows an application scenario of a positioning initialization method according to another embodiment of the present disclosure. As shown in FIG4, the AB section is winding. At this time, if one or several initial heading angles are set for each initial position according to the rules described in the above embodiment, it is very likely to cause inaccurate positioning initialization or even cause positioning initialization failure.

In order to overcome the above-mentioned defects, FIG5 schematically shows a flow chart of preparing an initial posture according to an embodiment of the present disclosure.

As an optional embodiment, as shown in FIG5 , operation S203 of formulating a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks includes operations S501 and S502, wherein:

In operation S501 , based on sub-map point clouds corresponding to a plurality of blocks, a center point of each block is determined.

Determining the center point of each block includes but is not limited to taking the geometric center of each block as the center point of the corresponding block.

In operation S502, a plurality of heading angles are set for each center point to prepare a plurality of initial postures.

For example, all blocks are traversed, and the center P[i] of each block is set as the initial position of the lidar. 0°, 30°, 60°, 90°, 120°, 150°, 180°, 210°, 240°, 270°, 300°, and 330° (i.e., every 30°) are used as a set of initial heading angles for each initial position. The initial position and these initial heading angles are used for ICP matching, and the increment of each ICP iteration is then calculated.

Through the embodiments of the present disclosure, a plurality of initial heading angles are set for each center point, that is, each initial position, so that the initial posture of the object can be located more accurately.

As an optional embodiment, segmenting a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of an object based on a pre-constructed point cloud map includes: acquiring a point cloud map and a predetermined moving route; segmenting the predetermined moving route into a plurality of line segments; determining a center point of each of the plurality of line segments; and segmenting the point cloud of the point cloud map based on each center point to obtain corresponding blocks.

For example, FIG6 schematically shows a schematic diagram of segmenting blocks according to an embodiment of the present disclosure. As shown in FIG6 , assuming that the route L in the point cloud map is the scheduled moving route of the unmanned vehicle this time, when segmenting the blocks, the route L can be divided into m segments according to the length k, and the length of each segment ΔL is the average length = total length / total number of segments, that is, ΔL = k / m, m is a positive integer, and in addition, the center point of each line segment is its geometric center, as shown in FIGO ₁ , O ₂ , O ₃ , O ₄ , O ₅ , ... As shown in FIG6 , m = 8, a segment is formed between two small black dots, and a large black dot on each segment represents the center of the segment.

In addition, in the embodiment of the present disclosure, the center point of each line segment may be used as the center point of the corresponding block.

Further, as an optional embodiment, segmenting the point cloud of the point cloud map based on each center point to obtain corresponding blocks includes: for each center point, segmenting the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block.

On the basis of the above embodiment, after determining the center point of each line segment in the route, the position coordinates P[i] of the center point of each line segment are obtained in the point cloud map, and then based on the position coordinates, the points in the point cloud map whose distance to each center point is less than a first threshold (such as 1) are segmented into a block centered on the center point. For example, for the center point O ₁ , all points in the point cloud map whose distance to the center point O ₁ is less than the first threshold can be segmented into a block centered on O ₁ .

Through the embodiments of the present disclosure, corresponding blocks are segmented based on the center point of each line segment in the line, so that the position of the object can be located more accurately.

Further, as an optional embodiment, for each center point, dividing the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block includes: dividing the point cloud of the point cloud map into a line feature point cloud and a surface feature point cloud; for each center point, dividing the points in the line feature point cloud whose distance from the center point is less than the first threshold into a block; and for each center point, dividing the points in the surface feature point cloud whose distance from the center point is less than the first threshold into the block; accordingly, matching the laser point cloud with multiple proposed initial poses includes: dividing the laser point cloud into a line feature laser point cloud and a surface feature laser point cloud; and matching the line feature laser point cloud and the surface feature laser point cloud with the proposed multiple initial poses respectively.

It should be noted that map point clouds can be classified based on features. Considering that buildings are generally surface structures, while trees and the like are line structures, map point clouds can be divided into line feature point clouds (corresponding to line point cloud maps) and surface feature point clouds (corresponding to surface point cloud maps) based on these geometric structure features. Accordingly, when dividing blocks, line feature point clouds and surface feature point clouds can be divided separately.

In addition, similar to the fact that map point clouds can be divided into point clouds with different features, laser point clouds acquired by LiDAR can also be divided into line feature laser point clouds and surface feature laser point clouds. Specifically, laser point clouds can be divided into line feature laser point clouds and surface feature laser point clouds according to the curvature threshold, where the actual curvature is less than the curvature threshold for surface feature laser point clouds, and the actual curvature is greater than the curvature threshold for line feature laser point clouds. Laser point clouds are data used to represent the surrounding environment of objects such as unmanned vehicles, including each frame of data scanned by LiDAR. The curvature here refers to the rotation rate of the tangent direction angle of a point on the curve to the arc length, which is defined by differentiation, indicating the degree to which the curve deviates from a straight line. The laser point cloud is composed of many points represented by three-dimensional coordinates. If the curvature calculated based on the coordinates of some points is very small (such as close to 0), they are considered to be surface feature points, and the rest are line feature points.

After the point cloud map and laser point cloud are divided as above, ICP matching can be feature-based matching, that is, it becomes point-to-line ICP matching and point-to-surface ICP matching.

Through the embodiments of the present disclosure, the map point cloud is segmented based on features, and the laser point cloud is divided based on corresponding features, so as to facilitate the identification of trees and buildings around the object, thereby facilitating the initialization of positioning the object.

FIG. 7 schematically shows a block diagram of a positioning initialization system according to an embodiment of the present disclosure.

As shown in FIG. 7 , the positioning initialization system 700 includes an acquisition module 701 , a segmentation module 702 , a formulation module 703 and a matching module 704 .

An acquisition module 701 is used to acquire a laser point cloud of the current environment of the object through a laser radar arranged on the object;

A segmentation module 702 is used to segment a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of an object based on a pre-built point cloud map, wherein different blocks correspond to different sub-map point clouds;

A drafting module 703 is used to draft a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks; and

The matching module 704 is used to match the laser point cloud with multiple proposed initial poses to initialize the positioning of the object.

Compared with the prior art that uses laser radar positioning, it must rely on the initial posture provided by a third party such as GPS satellites and magnetic compasses to complete positioning initialization, resulting in large errors. According to the embodiments of the present disclosure, because a technical means is adopted to prepare multiple initial postures according to the predetermined moving route of the object for positioning initialization, it at least partially overcomes the technical problems of the prior art that positioning initialization requires the help of a third party, and the positioning initialization error is large due to the lack of GPS signal or the GPS signal is blocked or the magnetic compass is interfered with, thereby achieving the technical effect of not requiring the help of a third party and with a small positioning initialization error.

As an optional embodiment, as shown in Figure 8, the planning module 703 includes: a first determination unit 801, used to determine the center point of each block based on the sub-map point cloud corresponding to the multiple blocks; and a setting unit 802, used to set multiple heading angles for each center point to plan the multiple initial poses.

Through the embodiments of the present disclosure, a plurality of initial heading angles are set for each center point, that is, each initial position, so that the initial posture of the object can be located more accurately.

As an optional embodiment, as shown in Figure 9, the segmentation module 702 includes: an acquisition unit 901, used to acquire the point cloud map and the predetermined moving route; a first segmentation unit 902, used to segment the predetermined moving route into multiple line segments; a second determination unit 903, used to determine the center point of each of the multiple line segments; and a second segmentation unit 904, used to segment the point cloud of the point cloud map based on each center point to obtain corresponding blocks.

Further, as an optional embodiment, the second segmentation unit is also used to: for each center point, segment the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block.

Through the embodiments of the present disclosure, corresponding blocks are segmented based on the center point of each line segment in the line, so that the position of the object can be located more accurately.

Further, as an optional embodiment, the second segmentation unit includes: a division subunit, used to divide the point cloud of the point cloud map into a line feature point cloud and a surface feature point cloud; a first segmentation subunit, used to segment the points in the line feature point cloud whose distance from the center point is less than the first threshold into a block for each center point; and a second segmentation subunit, used to segment the points in the surface feature point cloud whose distance from the center point is less than the first threshold into the block for each center point; the matching module includes: a division unit, used to divide the laser point cloud into a line feature laser point cloud and a surface feature laser point cloud; and a matching unit, used to respectively match the line feature laser point cloud and the surface feature laser point cloud with the proposed multiple initial poses.

Through the embodiments of the present disclosure, the map point cloud is segmented based on features, and the laser point cloud is divided based on corresponding features, so as to facilitate the identification of trees and buildings around the object, thereby facilitating the initialization of positioning the object.

According to the embodiments of the present invention, any one or more of the modules, units, and sub-units, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, units, and sub-units can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, units, and sub-units can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, units, and sub-units can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

For example, any multiple of the acquisition module 701, the segmentation module 702, the drafting module 703 and the matching module 704 can be combined in one module/unit/sub-unit for implementation, or any one of the modules/units/sub-units can be split into multiple modules/units/sub-units. Alternatively, at least part of the functions of one or more of these modules/units/sub-units can be combined with at least part of the functions of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the acquisition module 701, the segmentation module 702, the drafting module 703 and the matching module 704 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or by any one of the three implementation methods of software, hardware and firmware or by a suitable combination of any of them. Alternatively, at least one of the acquisition module 701, the segmentation module 702, the formulation module 703 and the matching module 704 may be at least partially implemented as a computer program module, and when the computer program module is executed, the corresponding function may be executed.

It should be noted that the system part in the embodiments of the present disclosure corresponds to the method part in the embodiments of the present disclosure. For the description of the system part, please refer to the method part, which will not be repeated here.

Another aspect of the present disclosure provides a computer system, including: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors perform the method described above.

Another aspect of the present disclosure provides a non-volatile storage medium storing computer executable instructions, which are used to implement the above method when executed.

Fig. 10 schematically shows a block diagram of a computer system suitable for implementing a positioning initialization method according to an embodiment of the present disclosure. The computer system shown in Fig. 10 is only an example and should not bring any limitation to the functions and scope of use of the embodiment of the present disclosure.

As shown in FIG10 , the computer system 1000 according to an embodiment of the present disclosure includes a processor 1001, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage part 1008 into a random access memory (RAM) 1003. The processor 1001 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and/or a related chipset and/or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 1001 may also include an onboard memory for caching purposes. The processor 1001 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

In RAM 1003, various programs and data required for the operation of system 1000 are stored. Processor 1001, ROM 1002 and RAM 1003 are connected to each other through bus 1004. Processor 1001 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 1002 and/or RAM 1003. It should be noted that the program can also be stored in one or more memories other than ROM 1002 and RAM 1003. Processor 1001 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

According to an embodiment of the present disclosure, the system 1000 may further include an input/output (I/O) interface 1005, which is also connected to the bus 1004. The system 1000 may further include one or more of the following components connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, etc.; an output section 1007 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a LAN card, a modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. A drive 1010 is also connected to the I/O interface 1005 as needed. A removable medium 1011, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1010 as needed, so that a computer program read therefrom is installed into the storage section 1008 as needed.

According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 1009, and/or installed from the removable medium 1011. When the computer program is executed by the processor 1001, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

The present disclosure also provides a computer-readable storage medium, which may be included in the device/apparatus/system described in the above embodiments; or may exist independently without being assembled into the device/apparatus/system. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

According to an embodiment of the present disclosure, a computer-readable storage medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical cable, radio frequency signal, etc., or any suitable combination of the above.

For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 1002 and/or the RAM 1003 described above and/or one or more memories other than the ROM 1002 and the RAM 1003 .

The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

It will be appreciated by those skilled in the art that the features described in the various embodiments and/or claims of the present disclosure may be combined and/or combined in various ways, even if such combinations and/or combinations are not explicitly described in the present disclosure. In particular, the features described in the various embodiments and/or claims of the present disclosure may be combined and/or combined in various ways without departing from the spirit and teachings of the present disclosure. All of these combinations and/or combinations fall within the scope of the present disclosure.

The embodiments of the present disclosure are described above. However, these embodiments are only for the purpose of illustration and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims (8)

1. A positioning initialization method for positioning an initial position and an initial heading angle of an object, comprising: Acquire a laser point cloud of the current environment of the object by using a laser radar arranged on the object; Segmenting a plurality of blocks corresponding to a plurality of line segments obtained by dividing a predetermined moving route of the object based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds, and the point cloud of the point cloud map is divided into a line feature point cloud and a surface feature point cloud; Formulate a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks, wherein the plurality of initial poses are determined based on a plurality of heading angles; Dividing the laser point cloud into a line feature laser point cloud and a surface feature laser point cloud; and Respectively matching the line feature laser point cloud and the surface feature laser point cloud with the proposed multiple initial poses to initialize the positioning of the object; The method of segmenting a plurality of blocks corresponding to a plurality of line segments obtained by dividing the predetermined moving route of the object based on the pre-built point cloud map includes: For the center point of each line segment, points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold are segmented into a block to obtain a plurality of blocks corresponding to the plurality of line segments. 2. The method according to claim 1, wherein the step of formulating a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks comprises: Determining a center point of each block based on the sub-map point clouds corresponding to the plurality of blocks; and A plurality of heading angles are set for each center point to formulate the plurality of initial postures. 3. The method according to claim 1, wherein for each center point, dividing the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block comprises: Dividing the point cloud of the point cloud map into line feature point cloud and surface feature point cloud; For each center point, divide the points in the line feature point cloud whose distance from the center point is less than the first threshold into a block; and For each center point, points in the surface feature point cloud whose distance from the center point is less than the first threshold are also segmented into the block. 4. A positioning initialization system for locating an initial position and an initial heading angle of an object, comprising: An acquisition module, used for acquiring a laser point cloud of the current environment of the object through a laser radar arranged on the object; A segmentation module, for segmenting a plurality of blocks corresponding to a plurality of line segments obtained by segmenting a predetermined moving route of the object based on a pre-constructed point cloud map, wherein different blocks correspond to different sub-map point clouds, and the point cloud of the point cloud map is divided into a line feature point cloud and a surface feature point cloud; A drafting module, configured to draft a plurality of initial poses based on the sub-map point clouds corresponding to the plurality of blocks, wherein the plurality of initial poses are determined based on a plurality of heading angles; a division unit, used for dividing the laser point cloud into a line feature laser point cloud and a surface feature laser point cloud; and A matching unit, used for matching the line feature laser point cloud and the surface feature laser point cloud with the proposed multiple initial poses respectively; The segmentation module includes: for each center point of the line segment, segmenting the points in the point cloud of the point cloud map whose distance from the center point is less than a first threshold into a block, to obtain multiple blocks corresponding to the multiple line segments. 5. The system according to claim 4, wherein the proposed module comprises: A first determining unit, configured to determine a center point of each block based on sub-map point clouds corresponding to the plurality of blocks; and The setting unit is used to set multiple heading angles for each center point to formulate the multiple initial postures. 6. The system according to claim 4, wherein the segmentation module comprises: A division subunit, used for dividing the point cloud of the point cloud map into a line feature point cloud and a surface feature point cloud; A first segmentation subunit is used to segment, for each center point, points in the line feature point cloud whose distance from the center point is less than the first threshold into a block; and The second segmentation subunit is used to segment, for each center point, points in the surface feature point cloud whose distance from the center point is less than the first threshold into the block. 7. A computer system comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 3. 8. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 3.