Lidar device and correction method

Abstract

An embodiment discloses a LiDAR device, including: an output unit for illuminating light; a receiving unit for receiving light from a calibration board and generating image information; and a control unit for controlling the output unit and the receiving unit. The control unit identifies multiple points contained in the image information, assigns numbers to the multiple points sequentially, and stores the image information if the numbers assigned to the multiple points match the order of the points on the actual calibration board.

Description

Technical Field

[0001] The embodiments relate to LiDAR correction methods and apparatus. Background Technology

[0002] LiDAR (Light Detection and Ranging) devices use laser pulses emitted from the LiDAR device and then reflected and returned from a target object to measure the distance to the target object or to form the shape of the target object. LiDAR devices are used in various technical fields that require three-dimensional images. For example, LiDAR devices can be applied in various technical fields such as meteorology, aviation, aerospace, and automotive. In recent years, the proportion of LiDAR devices in the field of autonomous driving has increased rapidly.

[0003] Typically, the output unit of a LiDAR device generates an output light signal incident on an object, the receiving unit receives an input light signal reflected from the object, and the information generation unit uses the input light signal received by the receiving unit to generate information about the object.

[0004] Meanwhile, during the process of a LiDAR device receiving input light signals, image distortion caused by lenses may occur. Therefore, a method to correct this image distortion is needed. In related technologies, a checkerboard pattern has been used for correction; however, when using a checkerboard pattern, visible light is required, which presents the problem of demanding very high sensor resolution. Furthermore, in the case of vehicle LiDAR, there is the issue that visible light may not be usable because the driver's field of vision should not be obstructed. Summary of the Invention

[0005] Technical issues

[0006] The embodiments provide a LiDAR device and a LiDAR correction method capable of correcting lens distortion.

[0007] The embodiments also provide a LiDAR device and a LiDAR calibration method, wherein the calibration plate recognition rate is improved during the calibration of the LiDAR device.

[0008] The embodiments also provide a LiDAR device and a LiDAR calibration method, wherein the calibration accuracy of the LiDAR device is improved.

[0009] The problems to be solved in the embodiments are not limited to those described above, but also include the objectives and effects that can be determined from the following technical solutions and embodiments.

[0010] Technical solution

[0011] According to an embodiment, a LiDAR device includes: an output unit configured to illuminate light; a receiving unit configured to receive light from a calibration board and generate image information; and a control unit configured to control the output unit and the receiving unit, wherein the control unit can identify multiple points contained in the image information, sequentially assign numbers to the multiple identified points, and store the corresponding image information when the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board.

[0012] The control unit can upsample image information and identify multiple points contained in the upsampled image information.

[0013] When multiple points contained in an image are not identified, the control unit can rearrange the positions of these points using principal component analysis (PCA).

[0014] The control unit can assign numbers to the rearranged points in sequence.

[0015] The receiving unit can receive light at multiple locations that are different from each other, and generate separate image information for the light received at each of the multiple locations that are different from each other.

[0016] When the image information received at multiple locations that are different from each other is stored in a predetermined quantity or more, the control unit can calculate parameters to correct the distortion of the image information.

[0017] The control unit can perform a Fast Fourier Transform (FFT) on the X and Y axes of the image information to obtain the first data, and then zero-padded the first data.

[0018] The control unit can perform an inverse fast Fourier transform (FFT) on the first data that has been zero-padding to obtain the second data, and obtain the upsampled image information by taking only the real part of the second data and then rounding it to the first decimal place.

[0019] The first data can be spatial frequency component data, and the second data can be complex floating-point data.

[0020] The angles formed by the receiving unit and the calibration plate at multiple different positions can be different from each other, and when there are 20 or more stored image information, the control unit can calculate parameters and correct the distortion of the image information.

[0021] Multiple points can be set at regular intervals according to multiple rows and columns on the calibration board, and the control unit can rearrange the positions of multiple points in the image information when points in different rows overlap each other in the row direction.

[0022] According to an embodiment, a LiDAR calibration method may include: generating image information for a calibration board by a receiving unit by photographing a calibration board including multiple points; upsampling the image information of the calibration board by a control unit; identifying multiple points by the control unit; assigning a number to each of the multiple points by the control unit; and rearranging the numbers assigned to the multiple points in sequence by the control unit.

[0023] LiDAR calibration methods may include a control unit determining whether the numbers assigned to multiple points are consistent with the order of points on the actual calibration board.

[0024] LiDAR correction methods may include storing image information by a control unit, and calculating parameters by the control unit when there are 20 or more stored image information entries.

[0025] The sequential rearrangement of numbers assigned to multiple points by the control unit may include the rearrangement of the positions of multiple points in the image information by the control unit via PCA.

[0026] Beneficial effects

[0027] According to embodiments, a LiDAR device and a LiDAR correction method capable of correcting lens distortion can be provided.

[0028] Alternatively, a LiDAR device and a LiDAR calibration method may be provided, wherein the calibration plate recognition rate is improved during the calibration of the LiDAR device.

[0029] In addition, a LiDAR device and a LiDAR calibration method can be provided, wherein the calibration accuracy of the LiDAR device is improved.

[0030] The various beneficial advantages and effects of the present invention are not limited to the foregoing and should be readily understood through the description of the detailed embodiments of the present invention. Attached Figure Description

[0031] Figure 1 This is a configuration diagram of a LiDAR device according to an embodiment.

[0032] Figure 2 This is a schematic diagram of a calibration plate in a LiDAR calibration method according to an embodiment.

[0033] Figure 3 This is a schematic diagram showing the appearance of the LiDAR device and calibration plate according to an embodiment.

[0034] Figure 4 This is a flowchart of a LiDAR correction method according to an embodiment.

[0035] Figure 5 This is a flowchart of a LiDAR correction method according to another embodiment.

[0036] Figure 6 This is a flowchart of a LiDAR correction method according to another embodiment.

[0037] Figure 7 This is a set of views illustrating the calibration plate recognition rate according to the LiDAR correction method according to an embodiment.

[0038] Figure 8 and Figures 9a to 9e This is a view used to describe the image rearrangement method in the LiDAR correction method according to an embodiment.

[0039] Figure 10 This is a flowchart of a LiDAR correction method according to an embodiment. Detailed Implementation

[0040] In the following, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0041] However, the technical concept of the present invention is not limited to the embodiments to be described, but can be implemented in various different forms, and within the scope of the technical concept of the present invention, one or more components in the embodiments can be used by selective combination and substitution.

[0042] Furthermore, unless specifically defined and described, the terms (including technical and scientific terms) used in the embodiments of the present invention may be interpreted as having the meaning commonly understood by one of ordinary skill in the art to which the present invention pertains, and common terms such as those defined in dictionaries may be interpreted in light of the contextual meaning of the relevant art.

[0043] The terminology used in the embodiments of this invention is for descriptive purposes only and is not intended to limit the invention.

[0044] In this specification, unless the context clearly indicates otherwise, the singular form may include the plural form, and when described as “at least one (or more) of A, B and / or C”, this may include one or more of all possible combinations of A, B and C.

[0045] Furthermore, when describing components of embodiments of the present invention, terms such as first, second, A, B, (a), (b) may be used.

[0046] These terms are used only to distinguish components from other components, and the nature, order, or sequence of components are not limited by these terms.

[0047] Additionally, when a component is described as "linked," "coupled," or "connected" to another component, the component is not only directly linked, coupled, or connected to the other component, but also "linked," "coupled," or "connected" to the other component when another component is arranged between the component and the other component.

[0048] Furthermore, when a component is described as being formed or positioned “above” or “below” another component, the term “above” or “below” includes not only when the two components are in direct contact with each other, but also when one or more other components are formed or arranged between the two components. Additionally, when a component is described as being “above” or “below”, this description can include meanings based on the upward and downward directions of a component.

[0049] Figure 1 This is a configuration diagram of a LiDAR device according to an embodiment.

[0050] Reference Figure 1 According to an embodiment of the present invention, the LiDAR device 100 may include an output unit 110, a receiving unit 120, an information generation unit 130, and a control unit 140.

[0051] Output unit 110 can generate and output an output optical signal in the form of a pulsed wave or a continuous wave. The continuous wave can be in the form of a sine wave or a square wave. By generating the output optical signal in the form of a pulsed wave or a continuous wave, LiDAR device 100 can detect the time difference or phase difference between the output optical signal output from output unit 110 and the input optical signal reflected from the target area and then input to receiving unit 120. Output unit 110 includes a light source and a lens group.

[0052] A lens group can collect light emitted from a light source and output the collected light to the outside. The lens group can be positioned above the light source, separated from it. In this document, "above the light source" can refer to the side of the light source from which it emits light. The lens group can include at least one lens, and when the lens group includes multiple lenses, each lens can be aligned based on a central axis to form an optical system. In this document, the central axis can be the same axis as the optical axis of the optical system. The lens group can also include a scattering member that receives light emitted from the light source, then refracts or diffracts the received light and outputs it.

[0053] The receiving unit 120 can receive light signals reflected from the target area. In this case, the received light signal may be a light signal emitted by the output unit 110 reflected from the target area. The receiving unit 120 includes: an image sensor, a filter disposed on the image sensor, and a lens group disposed on the filter. The receiving unit 120 may include a single-photon avalanche diode (SPAD) sensor.

[0054] The light signal reflected from the target area can pass through the lens group of the receiving unit 120. The optical axis of the lens group of the receiving unit 120 can be aligned with the optical axis of the image sensor. A filter can be disposed between the lens group of the receiving unit 120 and the image sensor. The filter can be disposed in the optical path between the target area and the image sensor. The filter can filter light with a predetermined wavelength range. The filter can transmit light of a specific wavelength. For example, the filter can transmit infrared light and block light outside the infrared band. The image sensor can receive the light signal and output the received light signal as an electrical signal. The image sensor can detect light with a wavelength corresponding to the wavelength of the light output from the output unit 110. For example, the image sensor can detect infrared light. The image sensor can be configured as a structure in which multiple pixels are arranged in a grid.

[0055] The information generation unit 130 uses the input optical signal input to the receiving unit 120 to generate information about the target region. The information about the target region may include three-dimensional information about the target region. For example, the information about the target region may include depth information about the target region.

[0056] The control unit 140 controls the driving of the output unit 110, the receiving unit 120, and the information generation unit 130. The information generation unit 130 and the control unit 140 can be implemented in the form of a printed circuit board (PCB). Alternatively, the information generation unit 130 and the control unit 140 can be implemented in other forms. Alternatively, the control unit 140 can be included in a terminal or vehicle in which the LiDAR device 100 according to an embodiment of the present invention is disposed. For example, the control unit 140 can be implemented as an application processor (AP) of a smartphone equipped with the LiDAR device 100 according to an embodiment of the present invention, or it can be implemented as an electronic control unit (ECU) of a vehicle equipped with the LiDAR device 100 according to an embodiment of the present invention.

[0057] Figure 2 This is a schematic diagram of the calibration plate in the LiDAR calibration method according to the embodiment. Figure 3 This is a schematic diagram showing the appearance of the LiDAR device and calibration plate according to an embodiment.

[0058] refer to Figure 2 and Figure 3 According to the embodiment, the LiDAR calibration method can use a calibration plate 10. The calibration plate 10 may include an LED calibration plate. The calibration plate 10 may include a plurality of points D. The plurality of points D may include LED dots. The plurality of points D may emit light. For example, the plurality of points D may emit infrared light. The LiDAR device 100 can receive the light emitted by the plurality of points D of the calibration plate 10. Specifically, the receiving unit of the LiDAR device 100 can receive the light emitted by the plurality of points D. The plurality of points D may be arranged on the calibration plate 10, spaced apart from each other at regular intervals. For example, M points D0 to D100. M-1 It can be set at regular intervals in the horizontal direction. Furthermore, N points D0 to D... N-1 The calibration plate 10 can be set at regular intervals in the vertical direction. In this case, a total of M×N points can be arranged on the calibration plate 10 at regular intervals. Each of the multiple points D can emit light. The LiDAR device 100 can be arranged at a predetermined interval from the calibration plate 10. Furthermore, the position and angle of the LiDAR device 100 can be changed for LiDAR correction (100' and 100"). As the position and angle of the LiDAR device 100 change, the LiDAR device 100 can photograph the calibration plate 10 from different positions and angles. Therefore, the LiDAR device 100 can generate different image information from different positions and angles.

[0059] Figure 4 This is a flowchart of a LiDAR correction method according to an embodiment.

[0060] refer to Figure 4 First, a calibration board (S100) comprising three or more LED points can be prepared. The calibration board may include three or more points. (Refer to the above.) Figure 2 and Figure 3 The three or more points can form multiple rows and columns and can be set to be spaced apart from each other at regular intervals.

[0061] Next, the position and angle of the LiDAR device can be changed (S101). The position and angle of the imaging calibration plate can be adjusted by changing the position and angle of the LiDAR device.

[0062] After the position and angle of the LiDAR device change, the LiDAR device can photograph the calibration board and generate image information (S102). The receiving unit of the LiDAR device can receive light from the calibration board. The receiving unit can receive light and generate image information of the calibration board.

[0063] The control unit of the LiDAR device can identify multiple points contained in the image information (S103). The control unit can identify multiple points contained in the image of the calibration board captured in the image information. The control unit can identify the points using a speckle detection algorithm. Afterwards, the control unit can determine whether the multiple points have been accurately identified (S104). After determining whether the multiple points have been accurately identified, if it is determined that the multiple points have not been accurately identified, the control unit can again change the position and angle of the LiDAR device and regenerate the image information.

[0064] After determining whether multiple points have been accurately identified, if the multiple points are accurately identified, the control unit can assign numbers to the multiple points (S105). Subsequently, the control unit can determine whether the numbers have been assigned to the multiple points in sequence (S106). If it is determined that the numbers have not been assigned to the multiple points in sequence, the control unit can again change the position and angle of the LiDAR device and regenerate image information.

[0065] When it is determined that the numbers are assigned to multiple points in sequence, the control unit can compare the assigned numbers to the multiple points with the order of the points on the actual calibration board (S107). Afterwards, the control unit can determine whether the assigned numbers to the multiple points are consistent with the order of the points on the actual calibration board (S108). When it is determined that the assigned numbers to the multiple points are inconsistent with the order of the points on the actual calibration board, the control unit can again change the position and angle of the LiDAR device and regenerate the image information.

[0066] When it is determined that the numbers assigned to multiple points match the order of the points on the actual calibration board, the control unit can store the corresponding image information (S109). Subsequently, the control unit can determine whether there are 20 or more stored image information entries captured at different positions and angles of the LiDAR device (S110). If it is determined that there are not 20 or more image information entries, the control unit can change the position and angle of the LiDAR device again and regenerate the image information.

[0067] When it is determined that there are 20 or more image information entries, the control unit can calculate parameters (S111). The control unit can calculate parameters based on the image information and perform LiDAR device calibration. The LiDAR device according to the embodiment can improve the point recognition rate by using a calibration plate that emits infrared light to sense infrared light, and LiDAR calibration can be performed even when using a low-resolution sensor. Furthermore, the method for calibrating the LiDAR in the LiDAR device according to the embodiment can be used in vehicle-mounted dToF LiDAR that uses light in the infrared region band instead of the visible light region.

[0068] Figure 5 and Figure 6This is a flowchart of a LiDAR correction method according to another embodiment.

[0069] Reference Figure 5 First, a calibration board (S200) comprising three or more LED points can be prepared. The calibration board may include three or more points. (Refer to the above.) Figure 2 and Figure 3 The three or more points can form multiple rows and columns and can be set to be spaced apart from each other at regular intervals.

[0070] Next, the position and angle of the LiDAR device can be changed (S201). The position and angle of the imaging calibration plate can be adjusted by changing the position and angle of the LiDAR device.

[0071] After the position and angle of the LiDAR device change, the LiDAR device can photograph the calibration board and generate image information (S202). The receiving unit of the LiDAR device can receive light from the calibration board. The receiving unit can receive light and generate image information of the calibration board.

[0072] The control unit can upsample the generated image information (S203). Upsampling the generated image information improves the point recognition rate of the control unit. The upsampled image information can have increased resolution.

[0073] Figure 6A detailed flowchart of the method (S203) by which the control unit upsamples image information is shown. First, the control unit performs a Fast Fourier Transform (FFT) (S203a). The control unit performs an FFT on the X and Y axes of the image information to obtain first data. The first data may be spatial frequency component data. Next, the control unit zero-padding the first data (S203b). The control unit zero-padding the first data adds zeros to components with higher spatial frequencies. Next, the control unit performs an Inverse Fast Fourier Transform (FFT) (S203c). The control unit performs an Inverse Fast Fourier Transform (FFT) on the zero-padding first data to obtain second data. Specifically, the control unit applies a 2D Inverse Fast Fourier Transform (FFT) again to the zero-padding first data to obtain the second data. The second data may be complex floating-point data. Next, the control unit obtains the upsampled image information (S203d). Specifically, the control unit obtains the upsampled image information by taking only the real part of the second data and rounding it to the nearest decimal place. The upsampled image information generated according to the image information upsampling method of the embodiment can be 256-bit integer data. When the control unit upsamples the image information according to the embodiment, high-resolution image information can be obtained, thereby improving the recognition rate of the image information, and the image information can be accurately corrected even when using a low-performance sensor.

[0074] The control unit of the LiDAR device can identify multiple points contained in the upsampled image information (S204). The control unit can identify multiple points contained in the image of the calibration board captured in the upsampled image information. The control unit can identify points using a speckle detection algorithm. Subsequently, the control unit can determine whether the multiple points have been accurately identified (S105).

[0075] After determining whether multiple points have been accurately identified, if multiple points are determined not to have been accurately identified, the control unit can rearrange the positions of the multiple points (S206). When multiple points contained in the image information are not identified, the control unit can rearrange the positions of the multiple points in the image information through Principal Component Analysis (PCA). The control unit can obtain the principal axes through PCA and redefine the principal axes as the basis vectors of the multiple points. After rearranging the principal components of the multiple points, the control unit can rearrange the numbering of the multiple points. Subsequently, the control unit can return the principal components of the multiple points to their current state. After determining whether multiple points have been accurately identified, if multiple points are determined to have been accurately identified, the control unit can assign numbers to the multiple points (S207). By rearranging the positions of multiple points through PCA, the LiDAR device can improve the recognition rate of the calibration board during the calibration process of the LiDAR device, thus improving the calibration accuracy of the LiDAR device. When the LiDAR device photographs the calibration board from different angles, the rearrangement of the positions of multiple points in the image information through PCA can be used. Even when the LiDAR device photographs the calibration board at a rotated angle, multiple points of the image information can be arranged horizontally, as is the case when the LiDAR device photographs the calibration board at a horizontally set angle.

[0076] After determining whether multiple points have been accurately identified, if the multiple points are accurately identified, or if the positions of the multiple points have been rearranged, the control unit can assign numbers to the multiple points (S207). The control unit can assign numbers to the multiple points and then compare the numbers assigned to the multiple points with the order of the points on the actual calibration board (S208). Afterwards, the control unit can determine whether the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board (S209). If it is determined that the numbers assigned to the multiple points are inconsistent with the order of the points on the actual calibration board, the control unit can again change the position and angle of the LiDAR device and regenerate image information.

[0077] When it is determined that the numbers assigned to multiple points match the order of the points on the actual calibration board, the control unit can store the corresponding image information (S210). Subsequently, the control unit can determine whether 20 or more stored image information entries were captured at different positions and angles of the LiDAR device (S211). If it is determined that there are fewer than 20 image information entries, the control unit can change the position and angle of the LiDAR device again and regenerate the image information.

[0078] When it is determined that there are 20 or more image information entries, the control unit can calculate parameters (S212). The control unit can calculate parameters based on the image information and perform LiDAR device calibration. The LiDAR device according to the embodiment can improve the point recognition rate by using a calibration plate that emits infrared light to sense infrared light, and LiDAR calibration can be performed even when using a low-resolution sensor. Furthermore, the method for calibrating the LiDAR in the LiDAR device according to the embodiment can be used in vehicle-mounted dToF LiDAR that uses light in the infrared region band instead of the visible light region.

[0079] Figure 7 This is a set of views illustrating the calibration plate recognition rate according to the LiDAR correction method according to an embodiment.

[0080] Figure 7 Image a shows the image information before the control unit upsamples the calibration board image information. (Refer to...) Figure 7 a. The image information before upsampling may have low resolution. Figure 7 b shows the point recognition rate of the image information before upsampling. (Reference) Figure 7 b. The image information before upsampling may have a low recognition rate for points. Figure 7 c shows the image information after the control unit upsamples the image information of the calibration board. (Refer to...) Figure 7 c. Upsampled image information can have high resolution. Figure 7 d shows the point recognition rate of the image information after upsampling. (Refer to...) Figure 7 d, Compared to before upsampling, the image information after upsampling can have an improved point recognition rate.

[0081] Figure 8 Figure 9 is a view used to describe the image rearrangement method in the LiDAR correction method according to an embodiment.

[0082] Figure 8 a shows the state before the control unit rearranged the positions of multiple points. This is when the LiDAR device photographs the calibration board at non-horizontal positions and angles, such as... Figure 8 As shown in Figure a, multiple points on the calibration board can be photographed at a predetermined angle instead of horizontally. In this case, during the numbering process of multiple points, multiple points may be photographed at an angle, potentially leading to their identification in an incorrect point order. In the captured image information of the calibration board, the calibration board can be divided into any number of regions. The boundaries of these regions can be formed along the row direction in which the multiple points are arranged. In this case, when multiple points are arranged at an angle instead of in a parallel direction, multiple points arranged in the same row may be located in different regions. For example, in... Figure 8 In 'a', some of the multiple points located in the second row may also be located in the first row region, and may be identified during the alignment of multiple points in the first row region, thus causing alignment errors (e.g., in...). Figure 8 In a, the points aligned to 8, 10, 11, 14, 16, 18, and 20 will be misidentified points.

[0083] As described above, when points in different rows of the image information overlap each other in the row direction, the control unit can rearrange the positions of the multiple points in the image information.

[0084] Figure 8 b shows the state after the control unit rearranges the positions of multiple points. In this case, multiple points can be rearranged so that they are not tilted, and these points can be identified in sequence and accurately.

[0085] Figure 9a This shows the state before the control unit rearranged the positions of multiple points. This is when the LiDAR device photographs the calibration board at non-horizontal positions and angles, such as... Figure 9a As shown, multiple points on the calibration plate can be photographed at a predetermined angle instead of horizontally. Figure 9b The process of the control unit obtaining the principal axis through principal component analysis and redefining the principal axis as the basis vector of multiple points is illustrated. To align the arrangement of the multiple points with the horizontal direction, the direction of the multiple tilted points can be tracked. Figure 9c The diagram shows the state of the control unit rearranging the principal components of multiple points. By rearranging the principal components of multiple points, the arrangement direction of the multiple points can be rearranged to a horizontal direction. Figure 9d The diagram illustrates the state of the control unit rearranging multiple points. When the principal components of multiple points are rearranged, the points can be arranged along multiple rows and columns, and in this case, all points can be assigned numbers by numbering them in the row direction starting from the first column of the first row. Figure 9e The diagram illustrates the state where the principal components return to their existing state after multiple points have been rearranged. When image rearrangement is performed during the calibration of a LiDAR device according to the embodiment, even when the position and angle of the LiDAR device are adjusted when photographing the calibration board, it is possible to prevent image information from being tilted and points from being unrecognized. Therefore, the recognition rate of the calibration board can be improved, thereby increasing the accuracy of the calibration.

[0086] Figure 10 This is a flowchart of the LiDAR correction method S1000 according to an embodiment.

[0087] Reference Figure 10The LiDAR calibration method S1000 according to the embodiment may include: generating image information of the calibration board (S1100); upsampling the image information (S1200); identifying multiple points (S1300); rearranging the positions of the multiple points (S1400); assigning numbers to the multiple points (S1500); determining whether the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board (S1600); storing the image information (S1700); and calculating parameters (S1800). Rearranging the numbers assigned to the multiple points in sequence (S1500) may include the operation of rearranging the positions of the multiple points in the image information by the control unit through principal component analysis (PCA).

[0088] The receiving unit can generate image information of the calibration board. The control unit can upsample the image information generated by the receiving unit. The control unit can identify multiple points from the upsampled image information. When multiple identified points are not accurately identified, the control unit can rearrange the positions of the multiple points. The control unit can assign numbers to the rearranged multiple points. The control unit can determine whether the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board. Subsequently, when the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board, the control unit can store the corresponding image information. When there are 20 or more stored image information entries, the control unit can calculate parameters and perform LiDAR device calibration. The LiDAR calibration method according to the embodiment can be used in LiDAR devices with lenses and can correct distortions caused by lenses.

[0089] Although described above with reference to embodiments, these embodiments are merely examples and do not limit the invention. Those skilled in the art will understand that various modifications and applications, not shown above, can be made without departing from the essential characteristics of the embodiments. For example, each component element specifically shown in the embodiments can be modified for implementation. It should be understood that differences associated with such modifications and applications fall within the scope of the embodiments as defined by the appended claims.

Claims

1. A LiDAR device, comprising: The output unit is configured to emit light; The receiving unit is configured to receive light from the calibration board and generate image information; as well as The control unit is configured to control the output unit and the receiving unit. The control unit identifies multiple points contained in the image information, assigns numbers to the identified multiple points in sequence, and stores the corresponding image information when the numbers assigned to the multiple points are consistent with the order of the points on the actual calibration board.

2. The LiDAR device according to claim 1, wherein, The control unit upsamples the image information and identifies multiple points contained in the upsampled image information.

3. The LiDAR device according to claim 2, wherein, When multiple points contained in the image information are not identified, the control unit rearranges the positions of the multiple points in the image information through principal component analysis (PCA).

4. The LiDAR device according to claim 3, wherein, The control unit assigns numbers to the rearranged points in sequence.

5. The LiDAR device according to claim 4, wherein, The receiving unit receives the light at multiple locations that are different from each other, and generates separate image information for the light received at each of the multiple locations that are different from each other.

6. The LiDAR device according to claim 5, wherein, When a predetermined amount of image information received at multiple locations that are different from each other is stored, the control unit calculates parameters to correct the distortion of the image information.

7. The LiDAR device according to claim 2, wherein, The control unit performs a Fast Fourier Transform (FFT) on the X and Y axes of the image information to obtain first data, and zero-padding is applied to the first data.

8. The LiDAR device according to claim 7, wherein, The control unit performs an inverse fast Fourier transform (FFT) on the first data that has been zero-padded to obtain the second data, and obtains the upsampled image information by taking only the real part of the second data and then rounding it to the first decimal place.

9. The LiDAR device according to claim 8, wherein, The first data is spatial frequency component data, and The second data is complex floating-point data.

10. The LiDAR device according to claim 6, wherein, The angles formed by the receiving unit and the calibration plate at the multiple different positions are different from each other, and When the stored image information consists of 20 or more entries, the control unit calculates the parameters and corrects the distortion of the image information.

Images