Receiving and transmitting optical path active alignment method, electronic equipment and readable storage medium

Abstract

The invention discloses a receiving and transmitting optical path active alignment method, electronic equipment and a readable storage medium, and the method comprises the steps: obtaining N frames of first point clouds, and enabling the N frames of first point clouds to be in one-to-one correspondence with N first candidate positions, which are arranged at intervals in a first direction, of a transmitting plate; selecting a first area, M second areas and M third areas which are sequentially arranged along the first direction in the first point cloud; obtaining a first evaluation function value curve of the first region, a second evaluation function curve of the second region and a third evaluation function value curve of the third region according to the reflectivity information of the N frames of first point clouds; and according to the first evaluation function value curve, the M second evaluation function curves and the M third evaluation function value curves, obtaining a target positioning position of the transmitting plate. Through the mode, the receiving and transmitting alignment degree can be judged according to the reflectivity information design evaluation function, the optimal position is determined through the result of partition calculation, and accurate adjustment and height alignment of a receiving and transmitting light path can be achieved.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of lidar, and in particular to an active alignment method for a light emitting and receiving optical path, an electronic device, and a readable storage medium. Background Art

[0002] AA (Active Alignment) is a technique used in optical systems, especially during the assembly of lidar (LiDAR) and sensors, to ensure the accurate alignment of optical components. This technique typically adjusts the position and angle of optical elements through precise mechanical adjustments and real-time feedback to achieve optimal beam alignment or precise configuration of the optical system. In a LiDAR system, the AA technique is commonly used for the alignment of laser transmitters and receivers to ensure the accurate emission and reception of laser beams, thereby improving measurement accuracy and system performance. Summary of the Invention

[0003] The embodiments of the present application provide an active alignment method for a light emitting and receiving optical path, an electronic device, and a readable storage medium, which can design an evaluation function based on reflectivity information to judge the alignment degree of light emission and reception, and determine the optimal position based on the results of partition calculation, contributing to the precise adjustment and high alignment of the light emitting and receiving optical path, and improving the performance and reliability of the entire system.

[0004] In a first aspect, the embodiments of the present application provide an active alignment method for a light emitting and receiving optical path applied to a lidar. The lidar includes a transmitting board. The method includes: acquiring N frames of first point clouds collected by the lidar, where N is a positive integer, and the N frames of first point clouds correspond one-to-one to N first candidate positions of the transmitting board. The N first candidate positions are arranged at intervals along a first direction, and the first direction is perpendicular to the horizontal plane where the optical axis of the lidar is located or perpendicular to the vertical plane where the optical axis is located; selecting a first region, M second regions, and M third regions from the first point clouds, where the second regions, the first region, and the third regions are arranged in sequence along the first direction, and M is a positive integer; obtaining a first evaluation function value curve of the first region, M second evaluation function curves of the M second regions, and M third evaluation function value curves of the M third regions according to the reflectivity information of the N frames of first point clouds, where the evaluation function value curve represents the correspondence between the evaluation function value and the first candidate position; and obtaining the target positioning position of the transmitting board according to the first evaluation function value curve, the M second evaluation function curves, and the M third evaluation function value curves.

[0005] The above method realizes the design of an evaluation function based on reflectivity information to judge the transceiver alignment degree, which is applicable to lidars of all DTOF (Direct Time of Flight) systems. It can complete the active alignment of the light emitting and receiving optical paths of the lidar relatively quickly and simply, and realize the automatic optical adjustment of the lidar. Secondly, determining the optimal position through the results of zonal calculation helps to achieve precise adjustment and height alignment of the light emitting and receiving optical paths, and improve the performance and reliability of the entire system.

[0006] In one or more embodiments, obtaining the target positioning position of the emission board according to the first evaluation function value curve, M second evaluation function curves, and M third evaluation function value curves includes: obtaining the first peak point of the first evaluation function value curve, the second peak points of the M second evaluation function curves, and the third peak points of the M third evaluation function value curves; determining the target positioning position according to the first peak point, the M second peak points, and the M third peak points.

[0007] The position with the best point cloud quality in the first region can be obtained according to the position corresponding to the first peak point, and the position when the overall point cloud quality is the best can be obtained according to the M second peak points and the M third peak points. In this way, the target positioning position determined by combining the first peak point, the M second peak points, and the M third peak points can take into account the point cloud quality of the center and the whole, which is conducive to realizing the precise adjustment and height alignment of the light emitting and receiving optical paths, and improving the performance and reliability of the entire system.

[0008] In one or more embodiments, obtaining the target positioning position according to the first peak point, the M second peak points, and the M third peak points includes: determining the first positioning position among N first candidate positions according to the first peak point; determining M second positioning positions among N first candidate positions according to the M second peak points; determining M third positioning positions among N first candidate positions according to the M third peak points; calculating the average value of the coordinates of the M second positioning positions and the coordinates of the M third positioning positions to determine the fourth positioning position; obtaining the target positioning position according to the first positioning position and the fourth positioning position.

[0009] The first positioning position is the position with the best point cloud quality in the first region, and the fourth positioning position is the position when the overall point cloud quality is the best. Combining the analysis of the first positioning position and the fourth positioning position not only considers local details but also takes into account the overall structure, and a target positioning position that takes into account the point cloud quality of the center point and the overall point cloud quality can be obtained, effectively improving the accuracy and robustness of the target positioning position, which is conducive to realizing the precise adjustment and height alignment of the light emitting and receiving optical paths, and improving the performance and reliability of the entire system.

[0010] In one or more embodiments, obtaining a target positioning position according to a first positioning position and a fourth positioning position includes: obtaining a minimum value between an absolute value of a difference between coordinates of the first positioning position and coordinates of the fourth positioning position and a first preset threshold; obtaining the target positioning position based on a sum value or a difference value between the coordinates of the first positioning position and the minimum value. The absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position is used to represent a deviation between the first positioning position and the fourth positioning position. When the deviation is less than or equal to the first preset threshold, the target positioning position obtained by using the sum value or the difference value between the coordinates of the first positioning position and the deviation can simultaneously have better center point cloud quality and overall point cloud quality.

[0011] In one or more embodiments, after obtaining the target positioning position of the emission plate, the method further includes: when the emission plate is located at the target positioning position, obtaining a second point cloud collected by a lidar; selecting a region of interest in the second point cloud, where the region of interest includes at least one point cloud block, and the point cloud block includes J rows * K columns of point cloud points, and both J and K are positive integers; obtaining a maximum value and a minimum value of reflectivity of each row of point cloud points or each column of point cloud points in each point cloud block; obtaining a point cloud contrast of the region of interest according to the maximum value and the minimum value corresponding to each point cloud block; determining a distribution state of the reflectivity of the second point cloud according to the point cloud contrast of the region of interest.

[0012] Checking the distribution state of the reflectivity of the second point cloud in a manner different from the foregoing optical path calibration process can effectively confirm whether the foregoing optical path calibration process is successful. If the distribution state of the reflectivity meets the expectation, it indicates that the light receiving and emitting optical paths are correctly aligned, which is beneficial to ensuring the accuracy and reliability of the alignment of the light receiving and emitting optical paths.

[0013] In one or more embodiments, obtaining the point cloud contrast of the region of interest according to the maximum value and the minimum value corresponding to each point cloud block includes: in each point cloud block, determining J first differences, where the first difference is a difference between a maximum value and a minimum value of reflectivity of a single row of point cloud points; determining the point cloud contrast of each point cloud block according to an average value of the J first differences; obtaining the point cloud contrast of the region of interest according to an average value of the point cloud contrasts of each point cloud block.

[0014] According to the average value of the J first differences, the maximum fluctuation range of the values within each point cloud block can be determined. According to the average value of the point cloud contrasts of each point cloud block, the maximum fluctuation range of the values within the region of interest can be determined. If the above fluctuation ranges are small, it means that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, indicating that the distribution state of the reflectivity meets the expectation, and it can be determined that the light receiving and emitting optical paths are correctly aligned.

[0015] In one or more embodiments, the point cloud contrast of the region of interest is obtained according to the maximum value and the minimum value corresponding to each point cloud block, including: for each point cloud block, determining K first ratios, where the first ratio is the ratio of the second difference to the first sum value, the second difference is the difference between the maximum value and the minimum value of the reflectivity of a column of point cloud points, and the first sum value is the sum of the maximum value and the minimum value of the reflectivity of a column of point cloud points; determining the point cloud contrast of each point cloud block according to the average value of the K first ratios; and obtaining the point cloud contrast of the region of interest according to the average value of the point cloud contrasts of the respective point cloud blocks.

[0016] According to the average value of the K first ratios, the maximum fluctuation range of the values within each point cloud block can be determined. According to the average value of the point cloud contrasts of the respective point cloud blocks, the maximum fluctuation range of the values within the region of interest can be determined. If the above fluctuation range is small, it means that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, indicating that the distribution state of the reflectivity meets the expectation, and it can be determined that the optical transceiver path has been correctly aligned.

[0017] In one or more embodiments, the distribution state includes a normal state and an abnormal state. Determining the distribution state of the reflectivity of the second point cloud according to the point cloud contrast of the region of interest includes: when the point cloud contrast of the region of interest is less than or equal to a second preset threshold, determining that the distribution state of the reflectivity of the second point cloud is the normal state; when the point cloud contrast of the region of interest is greater than the second preset threshold, determining that the distribution state of the reflectivity of the second point cloud is the abnormal state.

[0018] The point cloud contrast being less than or equal to the second preset threshold indicates that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, indicating that the distribution state of the reflectivity meets the expectation, and it can be determined that the optical transceiver path has been correctly aligned.

[0019] In a second aspect, an embodiment of the present application provides an electronic device, including: at least one processor and a memory; the memory is coupled to the processor, and the memory is used to store instructions or programs. When the instructions or programs are executed by the at least one processor, the at least one processor is caused to execute the optical transceiver path active alignment method as described above.

[0020] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, and the computer-readable storage medium stores a computer program. When the computer program is executed, the optical transceiver path active alignment method as described above is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] One or more embodiments are illustrated by way of example in the pictures in the corresponding drawings. These exemplary illustrations do not limit the embodiments, and elements with the same reference numerals in the drawings are represented as similar elements.

[0022] Figure 1 is a flowchart of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 2 is a schematic diagram of the first point cloud and each evaluation function curve provided by an embodiment of the present application; Figure 3 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 4 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 5 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 6 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 7 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 8 is a schematic diagram of the second point cloud and the region of interest provided by an embodiment of the present application; Figure 9 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 10 is a schematic diagram of an implementation manner of the active alignment method for the optical transceiver path provided by an embodiment of the present application; Figure 11 is a schematic diagram of the structure of the electronic device provided by an embodiment of the present application.

[0023] Reference numerals: PC1, the first point cloud; ROI1, the first region; ROI2, the second region; ROI3, the third region; ROI4, the region of interest; PC2, the second point cloud; BL1, the first point cloud block; BL2, the second point cloud block; BLT, the T-th point cloud block; 1100, the electronic device; 1101, the processor; 1102, the memory. Detailed implementation manners

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and detailedly described below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0025] It should be noted that when an element is described as "connected" to another element, it can be directly connected to the other element, or there can be one or more intermediate elements therebetween. In addition, the technical features involved in the various embodiments of the present application described below can be combined with each other as long as there is no conflict between them.

[0026] The automatic active alignment of lidar generally includes three steps: transmitting active alignment, receiving active alignment, and transmitting-receiving active alignment. The purpose of transmitting-receiving active alignment is to align the transmitting-receiving mapping relationship to achieve a one-to-one correspondence between the transmitting area and the receiving area. For example, by designing an evaluation function to quantitatively evaluate the size of the point cloud gap, the alignment degree of transmitting and receiving can be evaluated more quickly and simply, thereby realizing the automatic optical adjustment of lidar.

[0027] The existing optical adjustment methods for lidar include signal optical adjustment, image optical adjustment, etc. Signal optical adjustment uses the level of the signal amplitude at a single pixel as the criterion for the alignment degree. Since only one signal is collected at a time, this method is not applicable to flash lidar. Image optical adjustment uses an external light source to illuminate the receiving area, observes and adjusts the relative relationship between the transmitting spot and the receiving image in the rangefinder to complete the optical adjustment of transmitting and receiving. This optical adjustment method requires identifying the feature points of the receiving image and has high requirements for the clarity of the receiving image, and also has limitations.

[0028] Based on this, the embodiments of the present application provide a method for actively aligning the transmitting-receiving optical path. This method can design an evaluation function based on the reflectivity information of the point cloud to judge the alignment degree of transmitting and receiving, and determine the optimal position of the transmitting board through the result of partition calculation, thereby realizing the precise adjustment and height alignment of the transmitting-receiving optical path.

[0029] Please refer to Figure 1 , Figure 1 which is a flowchart of the method for actively aligning the transmitting-receiving optical path provided by the embodiments of the present application. Among them, the method for actively aligning the transmitting-receiving optical path is applied to lidar, and the lidar can be a solid-state lidar, a semi-solid-state lidar, etc., and the present application does not make a unique limitation on this. The lidar can be applied to any device that needs to perform laser detection, such as a mobile robot, a ship, or a vehicle. The lidar includes a transmitting board for emitting detection laser and a receiving board for receiving echo signals. Specifically, the transmitting board can emit pulsed detection laser, and the detection laser is projected onto the target object, and the signal formed by the reflection of the target object is the echo signal; the receiving board receives the echo signal and obtains relevant information of the target object based on the echo signal, such as the distance from the target object.

[0030] As Figure 1 shown, the method for actively aligning the transmitting-receiving optical path includes the following method steps S110 to step S140: Step S110: Obtain N frames of first point clouds collected by a lidar, where N is a positive integer, and the N frames of first point clouds correspond one-to-one to N first candidate positions of a transmitting board. The N first candidate positions are arranged at intervals along a first direction, and the first direction is perpendicular to the horizontal plane where the optical axis of the lidar is located or perpendicular to the vertical plane where the optical axis is located.

[0031] Among them, the first point cloud is obtained by the lidar emitting detection light and receiving the reflected light signal. For example, a flash lidar uses a vertical cavity surface emitting laser array as the emission source and uses a two-dimensional detector array (such as an avalanche photodiode array or a single photon avalanche diode array) to receive the reflected light signal. Different from the point-by-point detection method of a mechanical rotating lidar, the flash lidar obtains the point cloud of the entire field of view at one time. Specifically, the translation of the transmitting board traverses along the first direction. When the transmitting board is at the N first candidate positions, N frames of first point clouds collected by the lidar are obtained.

[0032] The optical axis of the lidar is the central axis for the lidar to emit and receive laser light. With the optical axis as a reference, the horizontal plane is the horizontal direction plane where the optical axis is located, and the vertical plane is the vertical direction plane where the optical axis is located. In some embodiments, if the horizontal plane is defined by the optical axis and the horizontal direction, then its normal direction (that is, the first direction) is the vertical direction (such as the direction of gravity). In some embodiments, if the vertical plane is defined by the optical axis and the direction of gravity, then its normal direction (that is, the first direction) is the horizontal lateral direction (this direction is perpendicular to both the optical axis and the direction of gravity). In some embodiments, the first direction is the row direction of the laser array on the transmitting board or the column direction of the laser array on the transmitting board. In some embodiments, the first direction is the horizontal direction or the vertical direction.

[0033] Step S120: Select a first region, M second regions, and M third regions in the first point cloud, where the second region, the first region, and the third region are arranged in sequence along the first direction, and M is a positive integer.

[0034] Specifically, the first region, the second region, and the third region are regions selected according to requirements, and the sizes of each region are not specifically limited. In some embodiments, the first point cloud has a center line. Along the first direction, the first point cloud is symmetric with respect to the center line, and the center line passes through the first region. Then the first region is a region including the central position of the first point cloud and its nearby positions. Then, according to the fact that the second region, the first region, and the third region are arranged in sequence along the first direction, the second region and the third region are respectively located on both sides of the first region, that is, the second region and the third region are located on both sides of the central position of the first point cloud and are not penetrated by the center line. Figure 2 Exemplarily shows the way of selecting the first region, the second region, and the third region when M is 1, such as Figure 2As shown in the left part of [description], in the first point cloud PC1, the second region ROI2, the first region ROI1, and the third region ROI3 arranged in sequence along the first direction (in this embodiment, the direction perpendicular to the horizontal plane where the optical axis of the lidar is located) are selected.

[0035] Step S130: According to the reflectivity information of N frames of the first point cloud, obtain the first evaluation function value curve of the first region, the second evaluation function curves of M second regions, and the third evaluation function value curves of M third regions, where the evaluation function value curve represents the corresponding relationship between the evaluation function value and the first candidate position.

[0036] The point cloud evaluation function is used to evaluate the state of the point cloud, such as evaluating the detection rate of the point cloud or the alignment degree between the transmitting device and the receiving device, and output the corresponding evaluation function value. In some embodiments, the relationship between the point cloud quality and the evaluation function value is positively correlated, that is, the larger the evaluation function value, the better the point cloud quality; conversely, the lower the evaluation function value, the worse the point cloud quality.

[0037] Specifically, first, for each frame of the first point cloud, according to the reflectivity information of each point cloud point of the first point cloud, the gray value of each point cloud point is obtained. Among them, the reflectivity information, also known as the reflection intensity (Intensity), refers to the proportion of the energy reflected back by the surface when the laser beam emitted by the lidar hits the object surface. The gray value refers to the brightness level of each pixel point in the image. In digital image processing, the gray value is usually represented by an integer from 0 to 255. 0 represents black, 255 represents white, and the intermediate values represent different levels of gray. The point cloud data itself usually consists of a series of spatial coordinates (x, y, z) and other additional information (such as intensity, color, reflectivity, timestamp, etc.). For the point cloud data collected by a lidar or an optical sensor, the gray value is usually used to represent the intensity of the reflected signal received by the sensor. In most LiDAR systems, the gray value of the point cloud corresponds to the reflectivity of each point. In some embodiments, the relationship between the reflectivity and the gray value is positively correlated, that is, when the reflectivity increases, the gray value will also increase accordingly; conversely, when the reflectivity decreases, the gray value will also decrease accordingly. Specifically, when the reflectivity is 100%, the gray value is 255; when the reflectivity is 0, the gray value is 0.

[0038] After that, for each frame of the first point cloud, based on the point cloud evaluation function and the gray values of the point cloud points included in each region (including the first region, the second region, and the third region), the evaluation function values of each region are calculated. Thus, according to N frames of the first point cloud (corresponding to N first candidate positions), N evaluation function values corresponding to each region can be obtained. In this way, the point cloud evaluation function curves corresponding to each region can be obtained.

[0039] TakeFigure 2 For example, among them, in Figure 2 the right part of, the abscissa represents the first candidate position, and the ordinate represents the evaluation function value. As Figure 2 shown, the evaluation function value curve corresponding to the first region ROI1 is the first evaluation function value curve GP1, the evaluation function value curve corresponding to the second region is the second evaluation function curve GP2, and the evaluation function value curve corresponding to the third region is the third evaluation function value curve GP3.

[0040] Step S140: Obtain the target positioning position of the emitting plate according to the first evaluation function value curve, M second evaluation function curves, and M third evaluation function value curves.

[0041] According to the first evaluation function value curve, the specific situation of the point cloud quality in the middle part (i.e., the center) can be obtained. According to the M second evaluation function curves and the M third evaluation function value curves, the specific situation of the overall point cloud quality can be obtained. Therefore, by combining the first evaluation function value curve, the M second evaluation function curves, and the M third evaluation function value curves, it is helpful to achieve a balance between the center and the overall point cloud quality, so that the obtained target positioning position can achieve the height alignment of the light emitting and receiving paths.

[0042] In some embodiments, as Figure 3 shown, the specific implementation process of step S140 includes the following steps S310 to S320: Step S310: Obtain the first peak point of the first evaluation function value curve, the second peak points of the M second evaluation function curves, and the third peak points of the M third evaluation function value curves.

[0043] Step S320: Determine the target positioning position according to the first peak point, the M second peak points, and the M third peak points.

[0044] According to the position corresponding to the first peak point, the position with the best point cloud quality in the first region can be obtained. According to the M second peak points and the M third peak points, the position when the overall point cloud quality is the best can be obtained. In this way, the target positioning position determined by combining the first peak point, the M second peak points, and the M third peak points can balance the point cloud quality of the center and the whole, which is beneficial to achieving precise adjustment and height alignment of the light emitting and receiving paths, and improving the performance and reliability of the entire system.

[0045] In some embodiments, as Figure 4 shown, the specific implementation process of step S320 includes the following steps S410 to S450: Step S410: Determine the first positioning position among the N first candidate positions according to the first peak point.

[0046] Step S420: Determine M second positioning positions from the N first candidate positions according to the M second peak points.

[0047] Step S430: Determine M third positioning positions from the N first candidate positions according to the M third peak points.

[0048] Step S440: Calculate the average value of the coordinates of the M second positioning positions and the coordinates of the M third positioning positions to determine the fourth positioning position.

[0049] Step S450: Obtain the target positioning position according to the first positioning position and the fourth positioning position.

[0050] Take Figure 2 as an example. At this time, M = 1. The first candidate position corresponding to the peak point (i.e., the first peak point) of the first evaluation function value curve GP1 is the first positioning position P1. The first candidate position corresponding to the peak point (i.e., the second peak point) of the second evaluation function value curve GP2 is the second positioning position P2. The first candidate position corresponding to the peak point (i.e., the third peak point) of the third evaluation function value curve GP3 is the third positioning position P3. The fourth positioning position P4 is obtained according to the average value of the coordinates of the second positioning position P2 and the coordinates of the third positioning position P3. Finally, the target positioning position is obtained according to the first positioning position P1 and the fourth positioning position P4.

[0051] In this embodiment, the first positioning position P1 is the position with the best point cloud quality in the first region ROI1, and the fourth positioning position P4 is the position when the overall point cloud quality is the best. Combining the first positioning position P1 and the fourth positioning position P4 for analysis not only considers local details but also takes into account the overall structure, and a target positioning position that takes into account both the center point cloud quality and the overall point cloud quality can be obtained, effectively improving the accuracy and robustness of the target positioning position, which is beneficial to realizing the precise adjustment and height alignment of the light receiving and emitting optical paths, and improving the performance and reliability of the entire system.

[0052] In some embodiments, as Figure 5 shown, the specific implementation process of step S450 includes the following steps S510 to S520: Step S510: Obtain the minimum value between the absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position and the first preset threshold.

[0053] Step S520: Obtain the target positioning position based on the sum or difference of the coordinates of the first positioning position and the minimum value.

[0054] Specifically, denote the coordinates of the first positioning position P1 as CP1, and the coordinates of the fourth positioning position P4 as CP4. Then the target positioning position is: CP1 + min(|CP1 - CP4|, A) or CP1 - min(|CP1 - CP4|, A), where A is the first preset threshold, which is a threshold set in advance and can be set based on the actual application scenario. The embodiments of the present application do not make specific limitations on this. In some embodiments, A is set to any value between 5 μm and 10 μm.

[0055] In this embodiment, on the one hand, adding a smaller value to the coordinates CP1 of the first positioning position P1 as a reference to obtain the target positioning position can make the target positioning position close to the first positioning position P1, which is beneficial to ensuring better center point cloud quality. On the other hand, the absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position is used to represent the deviation between the first positioning position and the fourth positioning position. When this deviation is less than or equal to the first preset threshold, the sum or difference of the coordinates of the first positioning position and the deviation is used to obtain the target positioning position, which can be close to the fourth positioning position P4 on the basis of ensuring that the deviation between the target positioning position and the first positioning position P1 is small, and is beneficial to improving the overall point cloud quality as much as possible on the basis of obtaining better center point cloud quality.

[0056] In some embodiments, if the absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position is greater than the first preset threshold, an alarm signal is output while determining the target positioning position. This is because the absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position being greater than the first preset threshold may be caused by abnormalities or defects in the device (such as unqualified performance, damaged appearance, unqualified parameters, etc.). In this case, an alarm is given to eliminate or repair the abnormal device, rather than assembling the lidar with this device, which not only improves work efficiency but also guarantees the quality of the final product.

[0057] Through the above embodiments, the process of active alignment of the transceiver optical path can be realized. On the one hand, it realizes the design of the evaluation function according to the reflectivity information to judge the alignment degree of the transceiver, which is applicable to all lidars of DTOF (Direct Time of Flight) systems, and can complete the active alignment of the transceiver optical path of the lidar relatively quickly and simply, realizing the automatic optical adjustment of the lidar. On the other hand, determining the best position through the results of the zonal calculation helps to achieve precise adjustment and height alignment of the transceiver optical path, improving the performance and reliability of the entire system.

[0058] After that, the embodiments of the present application also provide a process for verifying the result of the active alignment of the transceiver optical path to further improve the reliability of the system. The specific implementation process will be described later.

[0059] In some embodiments, such as Figure 6 shown, after performing step S140 to obtain the target positioning position, the optical transceiver alignment method further includes the following steps S610 to S650: Step S610: When the transmitting board is located at the target positioning position, obtain the second point cloud collected by the lidar.

[0060] Specifically, fix the transmitting board at the target positioning position. Then, the lidar emits detection light and receives the reflected light signal, and obtains the second point cloud according to the reflected light signal.

[0061] Step S620: Select a region of interest in the second point cloud, where the region of interest includes at least one point cloud block, and the point cloud block includes J rows * K columns of point cloud points, and both J and K are positive integers.

[0062] Among them, the region of interest (ROI, Region of Interest) refers to a region with special significance or that needs to be focused on. It can be a rectangle, a polygon, or a region of any shape. In this embodiment, the region of interest is taken as an example of a rectangle.

[0063] Step S630: Obtain the maximum value and the minimum value of the reflectivity of each row of point cloud points or each column of point cloud points in each point cloud block.

[0064] Step S640: Obtain the point cloud contrast of the region of interest according to the maximum value and the minimum value corresponding to each point cloud block.

[0065] Step S650: Determine the distribution state of the reflectivity of the second point cloud according to the point cloud contrast of the region of interest.

[0066] Specifically, according to the maximum value and the minimum value of the reflectivity of each row of point cloud points (or each column of point cloud points) in each point cloud block, the point cloud contrast of each point cloud block can be obtained; then, combined with the point cloud contrasts of all point cloud blocks in the region of interest, the point cloud contrast of the region of interest can be obtained; finally, according to the point cloud contrast of the region of interest, the distribution state of the reflectivity of the second point cloud can be determined. Among them, the point cloud contrast represents the degree of attribute difference between point clouds in different regions. A high point cloud contrast means there is an obvious difference between adjacent regions; a low point cloud contrast means a gentle change. The distribution state of the reflectivity includes a normal state and an abnormal state. Among them, the abnormal state can refer to poor point cloud, specifically manifested as poor alignment effect, low reflectivity, low detection rate, low abnormal rate, etc.

[0067] This embodiment checks the distribution state of the reflectivity of the second point cloud in a manner different from the foregoing optical path calibration process, which can effectively confirm whether the foregoing optical path calibration process is successful. If the distribution state of the reflectivity meets the expectations, it indicates that the light receiving and emitting optical paths are correctly aligned, which is conducive to ensuring the accuracy and reliability of the alignment of the light receiving and emitting optical paths.

[0068] In some embodiments, as Figure 7 described, the specific implementation process of step S640 includes the following steps S710 to S730: Step S710: In each point cloud block, determine J first differences, where the first difference is the difference between the maximum value and the minimum value of the reflectivity of the single-line point cloud points.

[0069] Step S720: Determine the point cloud contrast of each point cloud block according to the average value of the J first differences.

[0070] Step S730: Obtain the point cloud contrast of the region of interest according to the average value of the point cloud contrasts of each point cloud block.

[0071] Taking Figure 8 as an example, select the region of interest ROI4 in the second point cloud PC2. The region of interest includes T point cloud blocks, and the T point cloud blocks include the first point cloud block BL1, the second point cloud block BL2,..., the T-th point cloud block BLT, where T is a positive integer. Each point cloud block includes 4 rows * 8 columns of point cloud points, that is, J = 4 and K = 8.

[0072] In each point cloud block, the difference between the maximum value and the minimum value of the reflectivity of the point cloud points in each row determines a first difference, and 4 first differences can be determined for 4 rows. Calculate the average value of the 4 first differences as the point cloud contrast of the corresponding point cloud block. Since there are T point cloud blocks, the point cloud contrasts corresponding to the T point cloud blocks can be obtained. Calculate the average value of the T point cloud contrasts as the point cloud contrast of the region of interest. It can be understood that this embodiment is described by taking obtaining the point cloud contrast of the region of interest through the point cloud points in each row as an example. In other embodiments, the point cloud contrast of the region of interest can also be obtained through the point cloud points in each column, and the specific implementation process is similar to the above embodiment, which is within the scope easily understood by those skilled in the art and will not be elaborated here.

[0073] In this embodiment, according to the average value of the J first differences, the maximum fluctuation range of the values within each point cloud block can be determined. According to the average value of the point cloud contrasts of each point cloud block, the maximum fluctuation range of the values within the region of interest can be determined. If the above fluctuation range is small, it means that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, indicating that the distribution state of the reflectivity meets the expectations, and it can be determined that the light receiving and emitting optical paths are correctly aligned.

[0074] Please refer to Figure 9 , Figure 9 which exemplarily shows another way to determine the point cloud contrast of the region of interest provided by the embodiments of the present application. As Figure 9 shown, the specific implementation process of step S640 includes the following steps S910 to S930: Step S910: For each point cloud block, determine K first ratios, where the first ratio is the ratio of the second difference to the first sum, the second difference is the difference between the maximum value and the minimum value of the reflectivity of a column of point cloud points, and the first sum is the sum of the maximum value and the minimum value of the reflectivity of a column of point cloud points.

[0075] Step S920: Determine the point cloud contrast of each point cloud block according to the average value of the K first ratios.

[0076] Step S930: Obtain the point cloud contrast of the region of interest according to the average value of the point cloud contrasts of each point cloud block.

[0077] Taking Figure 8 as an example, in each point cloud block, a second difference is determined by the difference between the maximum value and the minimum value of the reflectivity of a column of point cloud points, a first sum is determined by the sum of the maximum value and the minimum value of the reflectivity of a column of point cloud points, and the ratio of the second difference to the first sum determines the corresponding first ratio for each column. 8 columns can determine 8 first ratios. Calculate the average value of the 8 first ratios as the point cloud contrast of the corresponding point cloud block. Since there are T point cloud blocks, the point cloud contrasts corresponding to the T point cloud blocks can be obtained. Calculate the average value of the T point cloud contrasts as the point cloud contrast of the region of interest. It can be understood that this embodiment is described by taking the point cloud contrast of the region of interest obtained through the point cloud points of each column as an example. In other embodiments, the point cloud contrast of the region of interest can also be obtained through the point cloud points of each row. The specific implementation process is similar to the above embodiment and is within the scope easily understood by those skilled in the art, so it will not be elaborated here.

[0078] In this embodiment, according to the average value of the K first ratios, the maximum fluctuation range of the values within each point cloud block can be determined. According to the average value of the point cloud contrasts of each point cloud block, the maximum fluctuation range of the values within the region of interest can be determined. If the above fluctuation range is small, it means that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, indicating that the distribution state of the reflectivity meets the expectations, and it can be determined that the light emitting and receiving optical paths are correctly aligned.

[0079] In some embodiments, as Figure 10 shown, the specific implementation process of step S450 includes the following steps S1010 to S1020: Step S1010: When the point cloud contrast in the region of interest is less than or equal to the second preset threshold, determine that the distribution state of the reflectivity of the second point cloud is in a normal state.

[0080] Step S1020: When the point cloud contrast in the region of interest is greater than the second preset threshold, determine that the distribution state of the reflectivity of the second point cloud is in an abnormal state.

[0081] Among them, the second preset threshold is a threshold set in advance, which can be set based on the actual application scenario, and the embodiments of the present application do not make specific limitations on this. In some embodiments, the second preset threshold is set to a smaller value. For example, the second preset threshold is set to any value in 0.15±0.05. Only when the point cloud contrast in the region of interest is a smaller value can it be determined that the distribution state of the reflectivity of the second point cloud is in a normal state, which is beneficial to making the result of the aforementioned alignment of the light emitting and receiving optical paths have high reliability. It can be understood that when it is determined that the distribution state of the reflectivity of the second point cloud is in a normal state, it means that the changes in different regions within each point cloud block and different regions within the region of interest are gentle, and the distribution state of the reflectivity meets the expectations. The target positioning position obtained by the Figure 1 shown method can align the heights of the light emitting and receiving optical paths.

[0082] In some embodiments, when it is determined that the distribution state of the reflectivity of the second point cloud is in an abnormal state, an alarm or interception can be performed.

[0083] Please refer to Figure 11 , Figure 11 which is a schematic structural diagram of the electronic device provided by the embodiments of the present application. As Figure 11 shown, the electronic device 1100 includes at least one processor 1101 and a memory 1102. Among them, the memory 1102 can be built into the electronic device 1100, can also be external to the electronic device 1100, and the memory 1102 can also be a remotely set memory, which is connected to the electronic device 1100 through a network.

[0084] The memory 1102, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The memory 1102 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the terminal, etc. In addition, the memory 1102 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 1102 optionally includes a memory remotely provided with respect to the processor 1101, and these remote memories can be connected to the terminal through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0085] By running or executing the software programs and / or modules stored in the memory 1102, and by invoking the data stored in the memory 1102, the processor 1101 executes various functions of the terminal and processes data, thereby performing overall monitoring of the terminal. For example, the active alignment method of the optical transceiver path described in any embodiment of the present application is implemented.

[0086] The processor 1101 can be one or more. Figure 11 Taking one processor 1101 as an example. The processor 1101 and the memory 1102 can be connected through a bus or other means. The processor 1101 may include a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a controller, a field programmable gate array (FPGA) device, etc. The processor 1101 can also be implemented as a combination of computing devices. For example, a combination of a DSP and a microprocessor, multiple microprocessors, one or more microprocessors combined with a DSP core, or any other such configuration.

[0087] An embodiment of the present application also provides a non-volatile computer-readable storage medium storing computer-executable instructions, and the computer-executable instructions are executed by one or more processors. For example, the method steps of any one of the above-described embodiments are executed.

[0088] An embodiment of the present application also provides a computer program product, including a computing program stored on a non-volatile computer-readable storage medium. The computer program includes program instructions, and when the program instructions are executed by a computer, the computer is caused to execute the optical transceiver path alignment method in any of the above method embodiments. For example, the method steps of any one of the above-described embodiments are executed.

[0089] The above are only embodiments of the present application, and do not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present application, or directly or indirectly applied in other related technical fields, shall be equally included in the patent protection scope of the present application.

[0090] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limiting them; under the concept of the present application, the technical features in the above embodiments or different embodiments can also be combined, and the steps can be implemented in any order. Those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the various embodiments of the present application.

Claims

1. An active alignment method for optical transceiver paths, characterized in that Applied to a lidar, the lidar includes a transmitting board, and the method includes: Obtaining N frames of first point clouds collected by the lidar, where N is a positive integer, and the N frames of first point clouds correspond one-to-one to N first candidate positions of the transmitting board. The N first candidate positions are arranged at intervals in a first direction, and the first direction is perpendicular to the horizontal plane where the optical axis of the lidar is located or perpendicular to the vertical plane where the optical axis is located; Selecting a first region, M second regions, and M third regions from the first point clouds, where the second region, the first region, and the third region are arranged in sequence along the first direction, and M is a positive integer; According to the reflectivity information of the N frames of first point clouds, obtaining a first evaluation function value curve of the first region, M second evaluation function curves of the M second regions, and M third evaluation function value curves of the M third regions, where the evaluation function value curve represents the correspondence between the evaluation function value and the first candidate position; According to the first evaluation function value curve, the M second evaluation function curves, and the M third evaluation function value curves, obtaining the target positioning position of the transmitting board.

2. The method according to claim 1, wherein The obtaining the target positioning position of the transmitting board according to the first evaluation function value curve, the M second evaluation function curves, and the M third evaluation function value curves includes: Obtaining a first peak point of the first evaluation function value curve, second peak points of the M second evaluation function curves, and third peak points of the M third evaluation function value curves; Determining the target positioning position according to the first peak point, the M second peak points, and the M third peak points.

3. The method according to claim 2, wherein The obtaining the target positioning position according to the first peak point, the M second peak points, and the M third peak points includes: Determining a first positioning position among the N first candidate positions according to the first peak point; Determining M second positioning positions among the N first candidate positions according to the M second peak points; Determining M third positioning positions among the N first candidate positions according to the M third peak points; Calculating the average value of the coordinates of the M second positioning positions and the coordinates of the M third positioning positions to determine a fourth positioning position; Obtaining the target positioning position according to the first positioning position and the fourth positioning position.

4. The method according to claim 3, wherein The obtaining the target positioning position according to the first positioning position and the fourth positioning position includes: Obtaining the minimum value between the absolute value of the difference between the coordinates of the first positioning position and the coordinates of the fourth positioning position and a first preset threshold; Obtaining the target positioning position based on the sum or difference between the coordinates of the first positioning position and the minimum value.

5. The method according to claim 1, wherein After obtaining the target positioning position of the transmitting board, the method further includes: When the transmitting board is located at the target positioning position, obtaining a second point cloud collected by the lidar; Select a region of interest in the second point cloud, where the region of interest includes at least one point cloud block, and the point cloud block includes J rows * K columns of point cloud points, and both J and K are positive integers; Obtain the maximum and minimum reflectivities of each row or each column of point cloud points in each point cloud block; Obtain the point cloud contrast of the region of interest according to the maximum and minimum values corresponding to each point cloud block; Determine the distribution state of the reflectivity of the second point cloud according to the point cloud contrast of the region of interest.

6. The method according to claim 5, characterized in that, The obtaining the point cloud contrast of the region of interest according to the maximum and minimum values corresponding to each point cloud block includes: In each point cloud block, determine J first differences, where the first difference is the difference between the maximum and minimum reflectivities of a single row of point cloud points; Determine the point cloud contrast of each point cloud block according to the average value of the J first differences; Obtain the point cloud contrast of the region of interest according to the average value of the point cloud contrasts of each point cloud block.

7. The method according to claim 5, characterized in that, The obtaining the point cloud contrast of the region of interest according to the maximum and minimum values corresponding to each point cloud block includes: For each point cloud block, determine K first ratios, where the first ratio is the ratio of a second difference to a first sum value, the second difference is the difference between the maximum and minimum reflectivities of a column of point cloud points, and the first sum value is the sum of the maximum and minimum reflectivities of a column of point cloud points; Determine the point cloud contrast of each point cloud block according to the average value of the K first ratios; Obtain the point cloud contrast of the region of interest according to the average value of the point cloud contrasts of each point cloud block.

8. The method according to claim 5, characterized in that, The distribution state includes a normal state and an abnormal state. The determining the distribution state of the reflectivity of the second point cloud according to the point cloud contrast of the region of interest includes: When the point cloud contrast of the region of interest is less than or equal to a second preset threshold, determine that the distribution state of the reflectivity of the second point cloud is the normal state; When the point cloud contrast of the region of interest is greater than the second preset threshold, determine that the distribution state of the reflectivity of the second point cloud is the abnormal state.

9. An electronic device, characterized in that, Includes: At least one processor and a memory; The memory is coupled to the processor, and the memory is used to store instructions or programs. When the instructions or programs are executed by the at least one processor, the at least one processor executes the optical transceiver active alignment method according to any one of claims 1-8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed, the optical transceiver active alignment method according to any one of claims 1-8 is implemented.

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