A laser radar external parameter calibration method, system, electronic device and computer readable storage medium

Abstract

A laser radar external parameter calibration method, system, electronic device and computer readable storage medium, comprising: synchronizing the time of a first laser radar and a second laser radar, obtaining a first point cloud sequence of the first laser radar and a second point cloud sequence of the second laser radar; using a plane extraction algorithm, extracting a first ground point cloud from the initial time point cloud of the first point cloud sequence, and extracting a second ground point cloud from the initial time point cloud of the second point cloud sequence; determining the normal vector angle of the first ground point cloud and the second ground point cloud; taking the coordinate system of the initial time point cloud of the first point cloud sequence as a reference coordinate system, determining a first point cloud map according to the first point cloud sequence; selecting a first preset time point cloud and a second preset time point cloud corresponding to a preset time from the first point cloud sequence and the second point cloud sequence respectively; determining a calibration result according to the normal vector angle of the first ground point cloud and the second ground point cloud, the first preset time point cloud, the second preset time point cloud and the first point cloud map.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of laser radar external parameter calibration, in particular to a laser radar external parameter calibration method and system, an electronic device and a computer readable storage medium. BACKGROUND

[0002] Laser radars are widely used on high-level automatic driving vehicles, and usually include multiple laser radars on the same vehicle to improve data coverage, but multiple laser radars need to be calibrated at the same time. In the prior art, laser radar external parameter calibration needs to apply a point cloud registration algorithm, which requires that the point cloud data of two laser radars have enough overlapping areas, but in actual applications, this requirement cannot be met due to the relative position of the laser radars. Therefore, the common method to solve the above problem is to rely on a calibration board, or to construct a point cloud map for multiple laser radars, but the setting process of the calibration board needs human intervention, so online calibration cannot be realized. On the other hand, it is difficult to calibrate successfully when there are not enough overlapping areas of point clouds, and the construction of a point cloud map for multiple laser radars requires high computing power of the processor. SUMMARY

[0003] To solve at least one aspect of the above problem, the present application provides a laser radar external parameter calibration method, comprising: synchronizing the time of a first laser radar and a second laser radar, obtaining a first point cloud sequence of the first laser radar and a second point cloud sequence of the second laser radar; using a plane extraction algorithm to extract first ground point clouds from initial time point clouds of the first point cloud sequence and second ground point clouds from initial time point clouds of the second point cloud sequence; determining the normal vector angle of the first ground point clouds and the second ground point clouds; taking the coordinate system of the initial time point clouds of the first point cloud sequence as a reference coordinate system, determining a first point cloud map according to the first point cloud sequence; selecting first preset time point clouds and second preset time point clouds corresponding to a preset time from the first point cloud sequence and the second point cloud sequence respectively; determining a calibration result according to the normal vector angle of the first ground point clouds and the second ground point clouds, the first preset time point clouds, the second preset time point clouds and the first point cloud map.

[0004] Preferably, the step of determining a first point cloud map according to the first point cloud sequence further comprises: performing point cloud registration on adjacent point clouds in the first point cloud sequence to calculate the transformation relationship of adjacent point clouds; calculating and storing the transformation relationship of the coordinate system of each point cloud relative to the reference coordinate system according to the coordinate transformation relationship of the adjacent point clouds, and transforming the first point cloud sequence to the reference coordinate system to obtain a first point cloud map.

[0005] Preferably, the step of determining the calibration result according to the normal vector angle of the first ground point cloud and the second ground point cloud, the first preset time point cloud, the second preset time point cloud and the first point cloud map further comprises: taking the normal vector angle of the first ground point cloud and the second ground point cloud as a rotation initial value, taking zero as a displacement initial value, and taking the rotation initial value and the displacement initial value as a whole as T', obtaining a coordinate conversion relationship T between the first preset time point cloud and the reference coordinate system 1-M , using a point cloud registration algorithm, the point cloud registration initial value being T 1-M T', calculating a coordinate conversion relationship T 2-M between the second preset time point cloud and the first point cloud map, and determining the calibration result as T 1-M -1 T 2-M .

[0006] Preferably, the step of extracting the first ground point cloud from the initial time point cloud of the first point cloud sequence further comprises: filtering the initial time point cloud of the first point cloud sequence according to the distance and angle between the first laser radar installation position and the horizontal plane to obtain point cloud data containing the ground excluding buildings; and using a plane extraction algorithm to extract the first ground point cloud from the obtained point cloud data.

[0007] In another aspect, a laser radar external parameter calibration system is provided, comprising: an acquisition unit, the acquisition unit comprising at least two laser radars, the at least two laser radars being fixedly arranged and synchronously acquiring point cloud data; a memory, the memory storing computer program instructions; and a processor, the processor running the computer program instructions based on the point cloud data to implement the laser radar external parameter calibration method as described above.

[0008] In another aspect, an electronic device is provided, comprising a memory and a processor, the memory storing computer program instructions, the computer program instructions implementing the laser radar external parameter calibration method as described above when executed by a computer.

[0009] In another aspect, a computer readable storage medium is provided, storing computer program instructions, the program instructions implementing the laser radar external parameter calibration method as described above when executed by a computer.

[0010] The laser radar external parameter calibration method of the embodiment has the following beneficial effects:

[0011] (1) The first ground point cloud and the second ground point cloud are extracted from the initial time point clouds of the first point cloud sequence and the second point cloud sequence respectively to calculate the calibration initial value, without relying on a calibration board, the process does not require manual participation, and online calibration can be realized remotely.

[0012] (2) By adopting the method of point cloud registration between the preset time point cloud of the second point cloud sequence and the first point cloud map, the problem of insufficient point cloud overlapping area can be solved, and excessive computing power requirement will not be caused. BRIEF DESCRIPTION OF DRAWINGS

[0013] For a better understanding of the above and other objects, features, advantages and functions of the present application, reference should be made to the embodiments illustrated in the drawings. The same reference numerals in the drawings refer to the same components. It should be understood by those skilled in the art that the drawings are intended to illustrate the preferred embodiments of the present application schematically, and have no limiting effect on the scope of the present application, and the components in the drawings are not drawn to scale.

[0014] Figure 1 A flowchart of a laser radar external parameter calibration method according to an embodiment of the present application is shown;

[0015] Figure 2 A flowchart of determining a first point cloud map according to a first point cloud sequence of a laser radar external parameter calibration method according to an embodiment of the present application is shown;

[0016] Figure 3 A flowchart of determining a calibration result according to a normal vector angle of a first ground point cloud and a second ground point cloud, a first preset time point cloud, a second preset time point cloud and a first point cloud map of a laser radar external parameter calibration method according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0017] Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, which include various details of the embodiments of the present disclosure to assist in understanding, and should be considered as merely exemplary. Therefore, those skilled in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present disclosure. Also, for the sake of clarity and conciseness, the description below omits the description of well-known functions and structures.

[0018] The term "comprising" and variations thereof as used in this document mean "including but not limited to". Unless otherwise specified, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "one example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. can refer to different or same objects. Other explicit and implicit definitions can also be included below.

[0019] To at least partially solve one or more of the above problems and other potential problems, one embodiment of the present disclosure proposes a laser radar external parameter calibration method, comprising:

[0020] Step S1, synchronize the time of the first lidar and the second lidar, obtain the first point cloud sequence of the first lidar and the second point cloud sequence of the second lidar.

[0021] Specifically, the time of the first lidar and the second lidar is set to be synchronized, and the relative positions of the first lidar and the second lidar are fixedly arranged on a movable device, for example, a test vehicle or the like. By moving the movable device, the first lidar and the second lidar are simultaneously moved and the point clouds are synchronously obtained. In some embodiments, by setting a preset route and a preset time of the movable device, the first lidar obtains a first point cloud sequence of the environment field passing through the preset route within the preset time, and the second lidar obtains a second point cloud sequence of the environment field passing through the preset route within the preset time, and the point clouds in the first point cloud sequence and the second point cloud sequence correspond to each other in time. Those skilled in the art can understand that in other embodiments, a third lidar, a fourth lidar, or the like, which is fixedly arranged on the movable device relative to the position of the first lidar and is synchronized in time with the first lidar, can also be included. When the movable device moves along the preset route within the preset time, a third point cloud sequence, a fourth point cloud sequence, or the like, of the environment field in which it is located is obtained, respectively, and the third point cloud sequence, the fourth point cloud sequence, and the first point cloud sequence correspond to each other in time, respectively.

[0022] Step S2, using a plane extraction algorithm, extracting a first ground point cloud from the initial time point cloud of the first point cloud sequence, and extracting a second ground point cloud from the initial time point cloud of the second point cloud sequence.

[0023] Specifically, as shown in Figure 2 the step of extracting a first ground point cloud from the initial time point cloud of the first point cloud sequence using a plane extraction algorithm further includes: step S21, filtering the initial time point cloud of the first point cloud sequence according to the distance and angle between the installation position of the first lidar and the horizontal plane to obtain point cloud data containing the ground excluding buildings; and step S22, using a plane extraction algorithm to extract the plane from the obtained point cloud data to determine the first ground point cloud. Similarly, the initial time point cloud of the second point cloud sequence is filtered according to the distance and angle between the installation position of the second lidar and the horizontal plane to obtain point cloud data containing the ground excluding buildings, and a plane extraction algorithm is used to extract the plane from the obtained point cloud data to determine the second ground point cloud.

[0024] Taking the first point cloud sequence and the second point cloud sequence as examples, the initial point clouds of the first and second point cloud sequences are selected to determine the initial values ​​for the point cloud registration algorithm. In another embodiment, the first ground point cloud can be extracted from any preset point cloud in the first point cloud sequence, and the second ground point cloud can be extracted from the point cloud in the second point cloud sequence corresponding to the preset point cloud. Here, the ground point cloud refers to the set of points in the point cloud formed by the LiDAR hitting the ground.

[0025] Step S3: Determine the angle between the normal vectors of the first ground point cloud and the second ground point cloud.

[0026] The ground surface in the coordinate system of the point cloud at the initial moment of the first point cloud sequence is fitted with the extracted first ground point cloud. The normal vector corresponding to the fitted plane is determined, and the angle between the normal vectors of the first and second ground point clouds is determined by the normal vectors of the first and second ground point clouds. Furthermore, the coarse calibration of the rotation extrinsic parameters is determined.

[0027] Step S4: Using the coordinate system of the point cloud at the initial moment of the first point cloud sequence as the reference coordinate system, determine the first point cloud map based on the first point cloud sequence.

[0028] like Figure 3 As shown, the steps for determining the first point cloud map based on the first point cloud sequence include: step S41, performing point cloud registration on adjacent point clouds in the first point cloud sequence and calculating the transformation relationship between adjacent point clouds; step S42, calculating and storing the transformation relationship between the coordinate system of each point cloud and the reference coordinate system based on the coordinate transformation relationship between adjacent point clouds, and transforming the first point cloud sequence to the reference coordinate system to obtain the first point cloud map.

[0029] Specifically, in this embodiment, the coordinate system of the point cloud at the initial moment of the first point cloud sequence is selected as the reference coordinate system. This coordinate system is the coordinate system of the first lidar at the initial moment, that is, a three-dimensional rectangular coordinate system with the laser emission center of the first lidar at the initial moment as the origin, the X-axis forward, the Y-axis to the left, and the Z-axis upward.

[0030] By traversing the first point cloud sequence, a point cloud registration algorithm is applied to calculate the transformation relationship between adjacent point clouds in the first point cloud sequence. Based on the transformation relationship between multiple point clouds in the first point cloud sequence, all point clouds in the first point cloud sequence are transformed to a reference coordinate system. The transformed first point cloud sequences are then merged to obtain a first point cloud map based on the reference coordinate system of the first lidar.

[0031] As can be understood by those skilled in the art, in another embodiment, any coordinate system in which a point cloud at any moment of the first point cloud series is located can also be selected as the reference coordinate system, and the first point cloud series is converted to the reference coordinate system through the conversion relationship of adjacent point clouds, and further, the first point cloud map is obtained by merging the first point cloud series in the converted coordinate system in the reference coordinate system.

[0032] Step S5: selecting a first preset moment point cloud and a second preset moment point cloud corresponding to a preset moment from the first point cloud sequence and the second point cloud sequence respectively.

[0033] Specifically, after obtaining the first point cloud map with the coordinate system of the initial moment point cloud of the first point cloud sequence as the reference coordinate system, a preset moment is selected, and the point clouds corresponding to the preset moment are selected from the first point cloud sequence and the second point cloud sequence respectively, and the extrinsic calibration result is determined through the first preset moment point cloud, the second preset moment point cloud and the first point cloud map.

[0034] Step S6: determining the calibration result according to the normal vector angle of the first ground point cloud and the second ground point cloud, the first preset moment point cloud, the second preset moment point cloud and the first point cloud map.

[0035] Specifically, the above step further comprises: taking the normal vector angle of the first ground point cloud and the second ground point cloud as the rotation initial value, and taking zero as the displacement initial value, and the rotation and translation initial value is collectively referred to as T', and obtaining the coordinate conversion relationship T between the first preset moment point cloud and the reference coordinate system. 1-M In the process of determining the first point cloud map in step S4, the coordinate conversion relationship of each point cloud in the first point cloud sequence and the initial moment point cloud is calculated, and here, only the coordinate conversion relationship T between the first preset moment point cloud and the initial moment point cloud needs to be found from the calculation results of the step. 1-M That is, the coordinate conversion relationship between the second preset moment point cloud and the first point cloud map is calculated by using a point cloud registration algorithm, and the point cloud registration initial value is T 1-M T', and the coordinate conversion relationship T between the second preset moment point cloud and the first point cloud map is obtained. 2-M Specifically, the point cloud registration algorithm uses ICP (Iterative Closest Point) or NDT (Normal Distribution Transform), and the calibration result is T 1-M -1 T 2-M .

[0036] Determining the calibration result through the first preset moment point cloud, the second preset moment point cloud and the first point cloud map can effectively reduce the calculation amount, reduce the requirement for the processing power of the processor, improve the calculation speed and save the calculation cost.

[0037] The other aspect provides a laser radar external parameter calibration system, comprising: an acquisition unit, the acquisition unit comprising at least two laser radars, the at least two laser radars being fixedly arranged and synchronously acquiring point cloud data; a memory, the memory storing computer program instructions; and a processor, the processor running the computer program instructions based on the point cloud data to implement the laser radar external parameter calibration method as described above.

[0038] Specifically, in the embodiment, the acquisition unit comprises a first laser radar and a second laser radar, the first laser radar and the second laser radar are respectively fixedly arranged on a movable device, so that the relative positions of the first laser radar and the second laser radar are fixed during the movement of the movable device along a preset route within a preset time. It should be noted that the first laser radar and the second laser radar are time-synchronized, so that the time instants of the point clouds in the first point cloud sequence acquired by the first laser radar and the second point cloud sequence acquired by the second laser radar one-to-one correspond. The processor can be a central processing unit or a specific integrated circuit, wherein the processor is in communication connection with the first laser radar and the second laser radar respectively to receive the first point cloud sequence and the second point cloud sequence. The memory adopts a RAM memory, and the memory is electrically connected with the processor to enable it to run the stored computer program instructions to implement the steps in any method embodiment as described above. As can be understood by those skilled in the art, in another embodiment, the acquisition unit can further comprise a third laser radar, a fourth laser radar, etc., and each laser radar is time-synchronized with the first laser radar and is fixedly arranged on the movable device, so that the relative positions of each laser radar and the first laser radar are unchanged during the movement of the movable device, and the third sequence point cloud, the fourth sequence point cloud, etc. time-synchronized with the first point cloud sequence are acquired simultaneously.

[0039] In the embodiment, the processor is configured to execute the following steps by running the computer program instructions of the memory:

[0040] Step S1, synchronizing the time of the first laser radar and the second laser radar, and acquiring a first point cloud sequence of the first laser radar and a second point cloud sequence of the second laser radar.

[0041] Step S2, using a plane extraction algorithm to extract a first ground point cloud from the initial time point cloud of the first point cloud sequence and a second ground point cloud from the initial time point cloud of the second point cloud sequence.

[0042] Step S3, determining the included angle of the normal vectors of the first ground point cloud and the second ground point cloud.

[0043] Step S4, taking the coordinate system of the initial time point cloud of the first point cloud sequence as a reference coordinate system, and determining a first point cloud map according to the first point cloud sequence.

[0044] In step S5, a first preset time point cloud and a second preset time point cloud corresponding to a preset time are selected from the first point cloud sequence and the second point cloud sequence respectively.

[0045] In step S6, a calibration result is determined according to the normal vector included angle of the first ground point cloud and the second ground point cloud, the first preset time point cloud, the second preset time point cloud and the first point cloud map.

[0046] In another aspect, an electronic device is provided, which includes a memory and a processor, the memory stores computer program instructions, the computer program instructions, when executed by the computer, implement any of the laser radar external parameter calibration methods described above.

[0047] The electronic device can be a smart terminal such as a mobile phone, or a computer or a mobile Internet device, wherein the memory can be used to store computer program instructions, such as program instructions / modules corresponding to the laser radar external parameter calibration method in the embodiments of the present application, and the processor executes the computer program instructions stored in the memory to perform various functional applications and data processing, i.e. to implement the laser radar external parameter calibration method described above. The memory can include a high-speed random access memory, and can also include one or more magnetic storage devices, flash memories, or other non-volatile solid state memories. In some examples, the memory can further include a memory remotely arranged with respect to the processor, which can be connected to the terminal through a network. Examples of the above-mentioned network include but are not limited to a local area network, the Internet, a mobile communication network, and combinations thereof. As an example, the above-mentioned memory can include but is not limited to the above-mentioned computer program instructions.

[0048] In another aspect, a computer readable storage medium is provided, which stores computer program instructions, the program instructions, when executed by a computer, implement any of the laser radar external parameter calibration methods described above.

[0049] In the present embodiment, all or part of the steps in the various methods of the above-described embodiments can be completed by running computer program instructions by the hardware related to the terminal device, and the above-mentioned computer program instructions can be stored in a computer readable storage medium, which can include a magnetic disk or optical disk, a flash disk, a read-only memory, a random access memory, etc.

[0050] The above has described various embodiments of the present disclosure, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those skilled in the art without departing from the scope and spirit of the described embodiments. The choice of terms used herein is intended to best explain the principles, practical applications, or technical improvements in the market of the embodiments, or to enable other ordinary skilled persons in the art to understand the present text.

Claims

1. A method for calibrating the extrinsic parameters of a lidar, characterized in that, include: Synchronize the time of the first lidar and the second lidar, and acquire the first point cloud sequence of the first lidar and the second point cloud sequence of the second lidar; A planar extraction algorithm is used to extract a first ground point cloud from the initial point cloud of the first point cloud sequence and a second ground point cloud from the initial point cloud of the second point cloud sequence. Determine the angle between the normal vectors of the first ground point cloud and the second ground point cloud; Using the coordinate system of the point cloud at the initial moment of the first point cloud sequence as the reference coordinate system, the method for determining a first point cloud map based on the first point cloud sequence includes: performing point cloud registration on adjacent point clouds in the first point cloud sequence and calculating the transformation relationship between adjacent point clouds; calculating and storing the transformation relationship of the coordinate system of each point cloud relative to the reference coordinate system based on the coordinate transformation relationship between adjacent point clouds, and transforming the first point cloud sequence to the reference coordinate system to obtain the first point cloud map. Select a first preset time point cloud and a second preset time point cloud corresponding to a preset time from the first point cloud sequence and the second point cloud sequence, respectively; The calibration result is determined based on the angle between the normal vectors of the first and second ground point clouds, the point cloud at the first preset time, the point cloud at the second preset time, and the first point cloud map. This includes: using the angle between the normal vectors of the first and second ground point clouds as the initial value for rotation, and zero as the initial value for displacement, with the initial values ​​of rotation and translation collectively denoted as T', and obtaining the coordinate transformation relationship T between the point cloud at the first preset time and the reference coordinate system. 1-M A point cloud registration algorithm is used, with an initial point cloud registration value of T. 1-M T', calculate the coordinate transformation relationship T between the second preset time point cloud and the first point cloud map. 2-M The calibration result is determined to be T. 1-M -1 T 2-M .

2. The method according to claim 1, characterized in that, The step of extracting the first ground point cloud from the initial point cloud of the first point cloud sequence using a planar extraction algorithm further includes: Based on the distance and angle between the installation location of the first lidar and the horizontal plane, the point cloud at the initial moment of the first point cloud sequence is filtered to obtain point cloud data including the ground, excluding buildings. The obtained point cloud data is extracted using a planar extraction algorithm to determine the first ground point cloud.

3. A lidar extrinsic parameter calibration system, characterized in that, include: The acquisition unit includes at least two lidars, which are relatively fixed and synchronously acquire point cloud data. A memory, wherein the memory stores computer program instructions; A processor that executes computer program instructions based on the point cloud data to implement the lidar extrinsic parameter calibration method as described in any one of claims 1-2.

4. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores computer program instructions that, when executed by a computer, implement the lidar extrinsic parameter calibration method as described in any one of claims 1-2.

5. A computer-readable storage medium, characterized in that, The device stores computer program instructions that, when executed by a computer, implement the lidar extrinsic parameter calibration method as described in any one of claims 1-2.

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