Laser radar point cloud data correction method and device, equipment and storage medium

Abstract

The invention discloses a laser radar point cloud data correction method, device and equipment and a storage medium, relates to the technical field of laser radars, and discloses the laser radar point cloud data correction method, device and equipment and the storage medium, and the method comprises the steps: obtaining first point cloud data; correction parameters are obtained, the first point cloud data are corrected based on the correction parameters, the corrected first point cloud data serve as second point cloud data, and the correction parameters comprise the rotation angle of the scanning line, the movement track of the laser point and the time synchronization error of the laser radar and the sensor. According to the method and the device, the point cloud data are corrected by acquiring different correction parameters, and the point cloud data correction processes corresponding to the correction parameters are different. After the point cloud data is corrected, the point cloud distortion caused by the problems of movement, scanning and the like of a mechanical radar can be overcome, so that the technical effect of improving the precision of the point cloud data is realized.

Description

Technical Field

[0001] The present application relates to the field of laser radar technology, and in particular to a laser radar point cloud data correction method, device, equipment and storage medium. Background Art

[0002] When mechanical laser radar collects and processes point cloud data, due to the rotating scanning mechanism of the laser radar, the time difference of different scan lines in the same frame of point cloud data leads to the misalignment of spatial position, which will cause scan line distortion; because the laser radar collects data during motion, the spatial position of the collection point does not match the actual position, which will cause motion distortion; the data deviation caused by the asynchrony of the timestamp between the laser radar and other sensors (such as GPS, IMU) will cause time synchronization distortion. These problems will affect the accuracy of point cloud data.

[0003] Therefore, how to improve the accuracy of lidar point cloud data is a problem that needs to be solved urgently.

[0004] The above contents are only used to assist in understanding the technical solution of the present application and do not constitute an admission that the above contents are prior art. Summary of the invention

[0005] The main purpose of this application is to provide a laser radar point cloud data correction method, device, equipment and storage medium, aiming to solve the technical problem of how to improve the accuracy of laser radar point cloud data.

[0006] To achieve the above purpose, the present application proposes a laser radar point cloud data method, the method comprising:

[0007] Acquire the first point cloud data;

[0008] Acquire correction parameters, correct the first point cloud data based on the correction parameters, and use the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0009] In one embodiment, obtaining the first point cloud data includes:

[0010] Acquire original point cloud data, and use the original point cloud data as first point cloud data;

[0011] or,

[0012] The corrected point cloud data is acquired, and the corrected point cloud data is used as the first point cloud data.

[0013] In one embodiment, the obtaining of correction parameters and correcting the first point cloud data based on the correction parameters include:

[0014] Acquire a rotation angle of the scan line, and correct the first point cloud data based on the rotation angle;

[0015] or,

[0016] Acquire a motion trajectory of the laser point, and correct the first point cloud data based on the motion trajectory;

[0017] or,

[0018] A time synchronization error between the laser radar and the sensor is obtained, and the first point cloud data is corrected based on the time synchronization error.

[0019] In one embodiment, the step of acquiring a rotation angle of the scan line and correcting the first point cloud data based on the rotation angle includes:

[0020] Acquire scanning parameters and the sequence number of scanning lines, wherein the scanning parameters include a scanning period and the number of scanning lines, and the scanning lines and the first point cloud data are in a one-to-one correspondence;

[0021] Based on the scanning parameter and the sequence number, a time offset of the scanning line is obtained;

[0022] Get the rotation angular velocity and the initial angle of the scan line;

[0023] Based on the initial angle, the rotation angular velocity and the time offset, obtaining a rotation angle of the scan line;

[0024] The first point cloud data is corrected based on the rotation angle.

[0025] In one embodiment, the step of acquiring the motion trajectory of the laser point and correcting the first point cloud data based on the motion trajectory includes:

[0026] Obtain position changes and posture changes;

[0027] If the position change and the posture change conform to the Gaussian process, then the motion trajectory of the laser point is predicted using Gaussian process regression;

[0028] The first point cloud data is corrected based on the motion trajectory.

[0029] In one embodiment, the acquiring of position change and posture change includes:

[0030] Establish a rigid body motion model, and based on the rigid body motion model, obtain the initial rotation matrix and translation vector;

[0031] Get angular velocity and acceleration;

[0032] Obtaining a position change based on the acceleration, wherein the position change refers to a position change of the laser radar sensor relative to a reference coordinate system within a scanning cycle;

[0033] Obtaining a posture change based on the angular velocity and the initial rotation matrix, wherein the posture change refers to a rotation angle change of the laser radar sensor relative to a fixed reference coordinate system;

[0034] In one embodiment, the obtaining of a time synchronization error between the laser radar and the sensor, and correcting the first point cloud data based on the time synchronization error, further includes:

[0035] Get the timestamp of the lidar;

[0036] Get the timestamp of the sensor;

[0037] If it is detected that the timestamp of the laser radar is not synchronized with the timestamp of the sensor, a time synchronization error is calculated;

[0038] The first point cloud data is corrected based on the time synchronization error.

[0039] In addition, to achieve the above purpose, the present application also proposes a laser radar point cloud data correction device, the laser radar point cloud data correction device comprising:

[0040] An acquisition module, used for acquiring first point cloud data;

[0041] The dedistortion module obtains correction parameters, corrects the first point cloud data based on the correction parameters, and uses the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0042] In addition, to achieve the above-mentioned purpose, the present application also proposes a laser radar point cloud data correction device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, and the computer program is configured to implement the steps of the laser radar point cloud data correction method as described above.

[0043] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the lidar point cloud data correction method described above are implemented.

[0044] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, it implements the steps of the lidar point cloud data correction method as described above.

[0045] One or more technical solutions proposed in this application have at least the following technical effects:

[0046] By obtaining different correction parameters, the point cloud data is corrected, wherein each correction parameter corresponds to a different point cloud data correction process. After the point cloud data is corrected, the point cloud distortion caused by the movement, scanning and other problems of the mechanical radar can be overcome, thereby achieving the technical effect of improving the accuracy of the point cloud data. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1 A flowchart diagram of the first embodiment of the laser radar point cloud data correction method of the present application;

[0050] Figure 2 This is a schematic diagram of the module structure of the laser radar point cloud data device according to an embodiment of the present application;

[0051] Figure 3 This is a schematic diagram of the device structure of the hardware operating environment involved in the laser radar point cloud data method in the embodiment of the present application.

[0052] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0053] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0054] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0055] The main solution of the embodiment of the present application is: obtaining first point cloud data; obtaining correction parameters, correcting the first point cloud data based on the correction parameters, and using the corrected first point cloud data as second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0056] In this embodiment, for ease of description, the following description is made using the identification laser radar as the execution entity.

[0057] This application provides a solution to correct point cloud data by obtaining different correction parameters. The correction process of point cloud data corresponding to each correction parameter is different. The following are three cases of point cloud data correction:

[0058] During the rotation scanning process of the LiDAR, different scanning lines in the same frame of data will be spatially misaligned due to the different rotation speeds and scanning frequencies of the LiDAR. The point cloud data can be corrected by obtaining the rotation angle of the scanning line.

[0059] The laser radar collects data during motion, which causes the spatial position of the collected point to be inconsistent with the actual position, resulting in motion distortion. The point cloud dedistortion algorithm based on Gaussian Process Regression (GPR) is combined with the Inertial Measurement Unit (IMU) for tight coupling processing;

[0060] Time synchronization error occurs when the timestamps between the lidar and other sensors (such as GPS, IMU) are not synchronized. According to the time synchronization error, the point cloud data can be time compensated to correct the deviation between different timestamps.

[0061] After the point cloud data has undergone the above correction process, it can overcome the point cloud distortion caused by mechanical laser radar due to movement, scanning and other problems, thereby achieving the technical effect of improving the accuracy of point cloud data.

[0062] It should be noted that the execution subject of this embodiment may be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a laser radar, etc. The following takes a laser radar as an example to illustrate this embodiment and the following embodiments.

[0063] Based on this, the present application embodiment provides a method for correcting laser radar point cloud data, referring to Figure 1 , Figure 1 This is a flow chart of the first embodiment of the laser radar point cloud data correction method of the present application.

[0064] In this embodiment, the laser radar point cloud data correction method of the present application includes steps S10 to S20:

[0065] Step S10, obtaining first point cloud data;

[0066] It should be noted that the first point cloud data refers to the original point cloud data that has not been corrected, or the corrected point cloud data. The rotation of the radar will inevitably cause distortion, and these distortions will be superimposed together, so a point cloud data needs to be processed in multiple ways to reduce different degrees of distortion. Among them, the point cloud data contains three-dimensional coordinates and reflection intensity. The three-dimensional coordinates refer to the basic attributes of each point, including X, Y, and Z coordinates, indicating the position of the point in three-dimensional space. The reflection intensity is related to the laser radar scanning and indicates the intensity of the laser reflected back after the laser hits the object.

[0067] It is understandable that, since the point cloud data needs to be corrected, performing step S10 can avoid the problem of untimely updating of the point cloud data, thereby ensuring that the new first point cloud data can be obtained in a timely and accurate manner when the laser radar performs the correction operation.

[0068] In this embodiment, by acquiring the first point cloud data, it is ensured that the new first point cloud data can be acquired timely and accurately when the laser radar performs the correction operation, thereby avoiding repeated correction.

[0069] Step S20, obtaining correction parameters, correcting the first point cloud data based on the correction parameters, and using the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0070] It should be noted that the correction parameters are used to correct the first point cloud data, including the rotation angle of the scan line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0071] It is understandable that there are many reasons for the distortion of point cloud data, so step S20 can be performed to correct the point cloud data according to corresponding parameters, thereby improving the accuracy of the point cloud data.

[0072] In a first feasible implementation manner, step S10 may include steps A11 to A15:

[0073] Step A11, obtaining scanning parameters and the sequence number of the scanning line;

[0074] It should be noted that the scanning parameters include the scanning cycle and the number of scanning lines. The scanning cycle is the time required for the laser radar to complete a complete scan, and the number of scanning lines refers to the number of independent laser beams that the laser radar can generate when performing a complete scan. Each scanning line represents a data point obtained after the laser radar transmits and receives a laser pulse, and the sequence number of the scanning line refers to the order of the scanning lines generated in a scanning cycle.

[0075] Step A12, obtaining a time offset of a scan line based on the scan parameter and the sequence number;

[0076] It should be noted that the time offset of a scan line refers to the time offset of the scan line relative to the initial scan time.

[0077] For example, assume that the time for the laser radar to rotate one circle is T scan , the scanning frequency is f scan , the number of scan lines is N, then the time t of the nth scan line is n for:

[0078]

[0079] This formula represents the time point t of the nth scan line. n , where t0 is the initial time of the scan, T scan It is the time it takes for the LiDAR to rotate once.

[0080] Step A13, obtaining the rotation angular velocity and the initial angle of the scan line;

[0081] It should be noted that the rotational angular velocity refers to the angle that the laser radar can rotate per unit time when scanning, and the initial angle of the scan line refers to the starting angle of the laser emission of the first scan line when the laser radar starts a complete scan. This angle is defined relative to a reference direction (such as geographic north) or a fixed direction of the laser radar itself.

[0082] Step A14, obtaining the rotation angle of the scan line based on the initial angle, the rotation angular velocity and the time offset.

[0083] For example, if the rotation angular velocity of the laser radar is ω, then at time t n At this moment, the angle θn of the nth scan line is:

[0084] θ n =θ0+ω·(t n -t0)

[0085] This formula indicates that the nth scan line at time t n The rotation angle θ at the moment n , where θ0 is the initial angle.

[0086] Step A15: correcting the first point cloud data based on the rotation angle.

[0087] For example, in the spatial coordinate system, the point cloud data (x, y, z) of the nth scan line can be corrected by the following formula:

[0088] x′=xn cos(θ n )-y n sin(θ n )

[0089] y′=x n sin(θ n )+y n con(θ n )

[0090] z′=z n

[0091] This formula is used to convert the point cloud data (x′, y′, z′) after the scan line distortion correction into the actual space coordinate system. n ,y n , z n ) is the uncorrected point cloud data, θ n is the rotation angle of the nth scan line.

[0092] In this embodiment, by obtaining the rotation angle of the scan line, the scan line distortion generated by the laser radar during the rotation scanning process can be corrected to obtain more accurate point cloud data.

[0093] In a second feasible implementation manner, step S10 may include steps B11 to B15:

[0094] Step B11, establishing a rigid body motion model, and obtaining an initial rotation matrix and a translation vector based on the rigid body motion model;

[0095] It should be noted that the rigid body motion model includes the rotation matrix and translation vector. In three-dimensional space, the rotation matrix and translation vector of the lidar jointly define the position and orientation of the lidar coordinate system relative to the global coordinate system or another coordinate system. These are the basic components of coordinate transformation, which are used to accurately map the point cloud data measured by the lidar to the global coordinate system. The rigid body motion matrix is ​​described as:

[0096]

[0097] Among them, R(t) represents the rotation matrix, t(t) represents the translation vector, and T(t) represents the rigid body transformation matrix at time t.

[0098] Step B12, obtaining angular velocity and acceleration;

[0099] It should be noted that angular velocity refers to the angle that the laser radar can rotate per unit time when scanning, and acceleration refers to the speed that increases per second during the movement of the laser radar.

[0100] Step B13, obtaining a position change based on the acceleration, and obtaining a posture change based on the angular velocity and the initial rotation matrix;

[0101] It should be noted that position change refers to the position change of the lidar sensor relative to a fixed reference coordinate system within a scanning cycle, and attitude change refers to the change in the rotation angle of the lidar sensor relative to a fixed reference coordinate system.

[0102] For example, the rotation matrix R(t) and position p(t) at each moment can be obtained through the angular velocity ω(t) and acceleration a(t) measured by the IMU. The integral of the angular velocity gives the attitude change:

[0103] R(t+Δt)=R(t)exp(ω(t)Δt)

[0104] Where exp represents the matrix exponential.

[0105] Integration of the acceleration yields velocity and position:

[0106] v(t+Δt)=v(t)+a(t)Δt

[0107]

[0108] Step B14: If the position change and the posture change conform to the Gaussian process, use Gaussian process regression to predict the motion trajectory of the laser point.

[0109] It should be noted that the motion trajectory of the laser point refers to the position distribution of the laser point at consecutive time points.

[0110] For example, assuming that the position change of the laser radar conforms to the Gaussian process, the Gaussian process regression is used to predict it:

[0111]

[0112] Among them, m(x) is the mean function, k(x, x') is the covariance function, and the specific regression equation is:

[0113] f * =K(X * ,X)K(X,X) -1 f

[0114] ∈ * =K(X * , X * )-K(X * , X * )K(X,X) -1 K(X,X * )

[0115] Where K(X, X) represents the covariance matrix between training data, and K(X*, X) represents the covariance matrix between test data and training data.

[0116] Step B15: correcting the first point cloud data based on the motion trajectory.

[0117] Exemplarily, for each laser point, motion compensation is performed:

[0118] p′ i =R(t i ) i +t(t i )

[0119] Among them, p′ i is the original laser point, p′ i is the laser point after compensation.

[0120] In this embodiment, the point cloud data distortion caused by the movement of the laser radar is corrected by predicting the movement trajectory of the laser point.

[0121] In a third feasible implementation manner, step S10 may include steps C11 to C13:

[0122] Step C11, obtaining the timestamp of the laser radar and the timestamp of the sensor;

[0123] It should be noted that the timestamp of the lidar refers to the time information recorded when the lidar emits and receives laser pulses, and the timestamp of the sensor refers to the time information related to data acquisition recorded by any sensor (such as camera, IMU, GPS, etc.), which is often used to synchronize sensor data to ensure the timing of the data.

[0124] Step C12, if it is detected that the timestamp is not synchronized with the timestamp of the sensor, calculating a time synchronization error;

[0125] Time synchronization error occurs when the timestamps between the LiDAR and other sensors (such as GPS, IMU) are not synchronized.

[0126] For example, assuming that the timestamp of the lidar is t_Lidar and the timestamp of other sensors is t_Sensor, the time synchronization error can be expressed as:

[0127] Δt=t sensor -t Lidar

[0128] Step C13, correcting the first point cloud data based on the time synchronization error;

[0129] According to the time synchronization error Δt, the point cloud data can be time compensated to correct the deviation between different timestamps.

[0130] In this embodiment, by calculating the timestamps of the laser radar and the sensor, the distortion of the point cloud data caused by the asynchrony of the timestamps is corrected, thereby improving the accuracy of the point cloud data.

[0131] It can be understood that the three implementation methods of step S10 provided above have different angles for correcting the point cloud data. The first implementation method corrects the point cloud data from the perspective of different rotation speeds and scanning frequencies of different scanning lines in the same frame of data due to the different rotation speeds and scanning frequencies of the laser radar; the second implementation method corrects the point cloud data from the perspective that the laser radar collects data during movement, resulting in the spatial position of the collection point not matching the actual position; the third implementation method corrects the point cloud data from the perspective of the time synchronization error between the laser radar and other sensors.

[0132] The above are only three feasible implementations of step S20 provided in this embodiment, and this embodiment does not specifically limit the specific implementation of step S20.

[0133] This embodiment provides a method for correcting laser radar point cloud data, which corrects point cloud data by obtaining different correction parameters, wherein each correction parameter corresponds to a different point cloud data correction process. After the point cloud data is corrected, the point cloud distortion caused by the movement, scanning and other problems of the mechanical radar can be overcome, thereby achieving the technical effect of improving the accuracy of the point cloud data.

[0134] It should be noted that the above examples are only used to understand the present application and do not constitute a limitation on the laser radar point cloud data correction method of the present application. More forms of simple transformations based on this technical concept are all within the scope of protection of the present application.

[0135] This application also provides a laser radar point cloud data correction device, please refer to Figure 2 , the laser radar point cloud data correction device comprises:

[0136] The acquisition module 10 is used to acquire first point cloud data.

[0137] The dedistortion module 20 is used to obtain correction parameters, correct the first point cloud data based on the correction parameters, and use the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0138] The laser radar point cloud data correction device provided by the present application adopts the laser radar point cloud data correction method in the above embodiment, which can solve the technical problem of laser radar point cloud data correction. Compared with the prior art, the beneficial effects of the laser radar point cloud data correction device provided by the present application are the same as the beneficial effects of the laser radar point cloud data correction method provided by the above embodiment, and the other technical features in the laser radar point cloud data correction device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0139] In one embodiment, the acquisition module 10 is further used to acquire original point cloud data and use the original point cloud data as the first point cloud data; or to acquire corrected point cloud data and use the corrected point cloud data as the first point cloud data.

[0140] In one embodiment, the de-distortion module 20 is also used to obtain the rotation angle of the scan line, and correct the first point cloud data based on the rotation angle; or, to obtain the motion trajectory of the laser point, and correct the first point cloud data based on the motion trajectory; or, to obtain the time synchronization error between the laser radar and the sensor, and correct the first point cloud data based on the time synchronization error.

[0141] In one embodiment, the de-distortion module 20 is further used to obtain scanning parameters and the serial number of the scanning line, wherein the scanning parameters include a scanning period and the number of scanning lines, and the scanning line and the first point cloud data are in a one-to-one correspondence; based on the scanning parameters and the serial number, a time offset of the scanning line is obtained; the rotation angular velocity and the initial angle of the scanning line are obtained; based on the initial angle, the rotation angular velocity and the time offset, a rotation angle of the scanning line is obtained; and the first point cloud data is corrected based on the rotation angle.

[0142] In one embodiment, the dedistortion module 20 is further used to obtain position changes and posture changes; if the position changes and the posture changes conform to the Gaussian process, Gaussian process regression is used to predict the motion trajectory of the laser point; and the first point cloud data is corrected based on the motion trajectory.

[0143] In one embodiment, the de-distortion module 20 is also used to establish a rigid body motion model, and obtain an initial rotation matrix and a translation vector based on the rigid body motion model; obtain angular velocity and acceleration; obtain position change based on the acceleration, wherein the position change refers to the position change of the laser radar sensor relative to a certain reference coordinate system within a scanning cycle; obtain posture change based on the angular velocity and the initial rotation matrix, wherein the posture change refers to the change in rotation angle of the laser radar sensor relative to a fixed reference coordinate system.

[0144] In one embodiment, the dedistortion module 20 is also used to obtain the timestamp of the laser radar; obtain the timestamp of the sensor; if it is detected that the timestamp of the laser radar is not synchronized with the timestamp of the sensor, calculate the time synchronization error; and correct the first point cloud data based on the time synchronization error.

[0145] The present application provides a laser radar point cloud data correction device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the laser radar point cloud data correction method in the above-mentioned embodiment one.

[0146] Reference below Figure 3 , which shows a schematic diagram of the structure of a laser radar point cloud data correction device suitable for implementing the embodiment of the present application. The laser radar point cloud data correction device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The laser radar point cloud data correction device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0147] like Figure 3As shown, the laser radar point cloud data correction device may include a processing device 1001 (such as a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM: Read Only Memory) 1002 or the program loaded from the storage device 1003 to the random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the laser radar point cloud data correction device are also stored. The processing device 1001, ROM1002 and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, a touch screen, a touchpad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; output devices 1008 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 1003 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 1009. The communication device 1009 can allow the laser radar point cloud data correction device to communicate with other devices wirelessly or by wire to exchange data. Although the figure shows a laser radar point cloud data correction device with various systems, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems may be implemented or have alternatively.

[0148] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0149] The laser radar point cloud data correction device provided by the present application adopts the laser radar point cloud data correction method in the above embodiment, which can solve the technical problem of laser radar point cloud data correction. Compared with the prior art, the beneficial effects of the laser radar point cloud data correction device provided by the present application are the same as the beneficial effects of the laser radar point cloud data correction method provided by the above embodiment, and the other technical features in the laser radar point cloud data correction device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0150] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0151] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0152] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the laser radar point cloud data correction method in the above-mentioned embodiment.

[0153] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, 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 this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0154] The above-mentioned computer-readable storage medium may be included in the laser radar point cloud data correction device; or it may exist independently without being assembled into the laser radar point cloud data correction device.

[0155] The above-mentioned computer-readable storage medium carries one or more programs. When the above-mentioned one or more programs are executed by the laser radar point cloud data correction device, the laser radar point cloud data correction device: obtains first point cloud data; obtains correction parameters, corrects the first point cloud data based on the correction parameters, and uses the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

[0156] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0157] 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 application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the 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 square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square 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 square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / 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.

[0158] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0159] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned laser radar point cloud data correction method, and can solve the technical problem of laser radar point cloud data correction. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the laser radar point cloud data correction method provided in the above-mentioned embodiment, and will not be repeated here.

[0160] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the above-mentioned laser radar point cloud data correction method.

[0161] The computer program product provided in this application can solve the technical problem of laser radar point cloud data correction. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as the beneficial effects of the laser radar point cloud data correction method provided in the above embodiment, which will not be repeated here.

[0162] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A laser radar point cloud data correction method, characterized in that: The method includes: Acquire the first point cloud data; Acquire correction parameters, correct the first point cloud data based on the correction parameters, and use the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

2. The method according to claim 1, characterized in that The obtaining of the first point cloud data comprises: Acquire original point cloud data, and use the original point cloud data as first point cloud data; or, The corrected point cloud data is acquired, and the corrected point cloud data is used as the first point cloud data.

3. The method according to claim 1, characterized in that The obtaining of correction parameters and correcting the first point cloud data based on the correction parameters include: Acquire a rotation angle of the scan line, and correct the first point cloud data based on the rotation angle; or, Acquire a motion trajectory of the laser point, and correct the first point cloud data based on the motion trajectory; or, A time synchronization error between the laser radar and the sensor is obtained, and the first point cloud data is corrected based on the time synchronization error.

4. The method according to claim 3, characterized in that The step of obtaining a rotation angle of the scan line and correcting the first point cloud data based on the rotation angle includes: Acquire scanning parameters and the sequence number of scanning lines, wherein the scanning parameters include a scanning period and the number of scanning lines, and the scanning lines and the first point cloud data are in a one-to-one correspondence; Based on the scanning parameter and the sequence number, a time offset of the scanning line is obtained; Get the rotation angular velocity and the initial angle of the scan line; Based on the initial angle, the rotation angular velocity and the time offset, obtaining a rotation angle of the scan line; The first point cloud data is corrected based on the rotation angle.

5. The method according to claim 3, characterized in that The step of obtaining the motion trajectory of the laser point and correcting the first point cloud data based on the motion trajectory includes: Obtain position changes and posture changes; If the position change and the posture change conform to the Gaussian process, then the motion trajectory of the laser point is predicted using Gaussian process regression; The first point cloud data is corrected based on the motion trajectory.

6. The method according to claim 5, characterized in that The acquisition of position change and posture change includes Establish a rigid body motion model, and based on the rigid body motion model, obtain the initial rotation matrix and translation vector; Get angular velocity and acceleration; Obtaining a position change based on the acceleration, wherein the position change refers to a position change of the laser radar sensor relative to a reference coordinate system within a scanning cycle; A posture change is obtained based on the angular velocity and the initial rotation matrix, wherein the posture change refers to a rotation angle change of the laser radar sensor relative to a fixed reference coordinate system.

7. The method according to claim 3, characterized in that The step of obtaining a time synchronization error between the laser radar and the sensor, and correcting the first point cloud data based on the time synchronization error, further includes: Get the timestamp of the lidar; Get the timestamp of the sensor; If it is detected that the timestamp of the laser radar is not synchronized with the timestamp of the sensor, a time synchronization error is calculated; The first point cloud data is corrected based on the time synchronization error.

8. A laser radar point cloud data correction method and device, characterized in that: The device comprises: An acquisition module, used for acquiring first point cloud data; The dedistortion module obtains correction parameters, corrects the first point cloud data based on the correction parameters, and uses the corrected first point cloud data as the second point cloud data, wherein the correction parameters include: the rotation angle of the scanning line, the motion trajectory of the laser point, and the time synchronization error between the laser radar and the sensor.

9. A laser radar point cloud data correction method and device, characterized in that: The device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the laser radar point cloud data correction method as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the laser radar point cloud data correction method as described in any one of claims 1 to 7 are implemented.

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