Method, device, storage medium and multichannel lidar for determining disturbance points

Abstract

This application discloses a method, apparatus, storage medium, and multi-channel lidar for determining interference points, relating to the field of radar ranging. The method includes: acquiring a target point cloud corresponding to a high-reflectivity object within a target channel; acquiring, based on the target point cloud, point clouds at the same pixel positions as the target point cloud within each channel other than the target channel; determining whether each point cloud to be determined is a suspected interference point based on its distance value and reflectivity, and the distance values ​​and reflectivities of other point clouds in the neighborhood of each point cloud; if so, determining whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points determined by the point cloud to be determined. Using this application embodiment can solve the problem of signal crosstalk in the field of multi-channel lidar technology and improve ranging accuracy.

Description

Technical Field

[0001] This application relates to the field of lidar, and more particularly to a method, apparatus, storage medium, and multi-channel lidar for determining interference points. Background Technology

[0002] Multi-channel LiDAR can scan multiple channels simultaneously, thus expanding the field of view while maintaining the frame rate, and is currently widely used in LiDAR products. Although the emission angles of each channel are different, the laser signal inevitably undergoes reflection during optical path transmission and returns to the multi-channel of the LiDAR. Therefore, each channel may receive echo signals emitted by a channel other than its own and reflected by the target object. Summary of the Invention

[0003] This application provides a method, apparatus, storage medium, and multi-channel lidar for determining interference points, which can solve the problem of signal crosstalk in the field of multi-channel lidar technology and improve ranging accuracy. The technical solution is as follows:

[0004] In a first aspect, embodiments of this application provide a method for determining interference points, the method comprising:

[0005] Acquire the target point cloud corresponding to the high reflectivity object within the target channel; wherein the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold;

[0006] Based on the target point cloud, obtain the point cloud to be determined in each channel other than the target channel, which has the same pixel position as the target point cloud;

[0007] Based on the distance value and reflectivity of each point cloud to be determined, and the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined, determine whether each point cloud to be determined is a suspected interference point;

[0008] If so, determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points corresponding to the point cloud to be determined.

[0009] Secondly, embodiments of this application provide an apparatus for determining interference points, the apparatus comprising:

[0010] The first acquisition module is used to acquire the target point cloud corresponding to the high reflectivity object in the target channel; wherein, the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold.

[0011] The second acquisition module is used to acquire, based on the target point cloud, the point cloud to be determined at the same pixel position as the target point cloud in each channel except the target channel;

[0012] The suspected interference determination module is used to determine whether each point cloud to be determined is a suspected interference point based on the distance value and reflectivity of each point cloud to be determined, as well as the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined.

[0013] An interference determination module is used to determine whether the point cloud to be determined is an interference point, based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined, or based on the range of interference points corresponding to the point cloud to be determined.

[0014] Thirdly, embodiments of this application provide a computer storage medium storing a plurality of instructions adapted for loading by a processor and executing the above-described method steps.

[0015] Fourthly, embodiments of this application provide a multi-channel lidar, which may include: a processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed by the above-described method steps.

[0016] The beneficial effects of the technical solutions provided in some embodiments of this application include at least the following:

[0017] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a point cloud diagram containing interference points provided in an embodiment of this application;

[0020] Figure 2 This is a flowchart illustrating a method for determining interference points provided in an embodiment of this application;

[0021] Figure 3 This is a flowchart illustrating another method for determining interference points provided in an embodiment of this application;

[0022] Figure 4 This is a flowchart illustrating a method for determining whether a suspected interference point is an interference point, as provided in an embodiment of this application.

[0023] Figure 5 This is a dot matrix diagram provided in an embodiment of the present application for determining whether a suspected interference point is an interference point;

[0024] Figure 6 This is a flowchart illustrating a method for determining interference points provided in an embodiment of this application;

[0025] Figure 7 A point cloud raster diagram including a target point cloud and a point cloud to be determined is provided for embodiments of this application;

[0026] Figure 8 This is a schematic diagram of the structure of a device for determining interference points provided in an embodiment of this application;

[0027] Figure 9 This is a schematic diagram of the structure of a multi-channel lidar provided in an embodiment of this application. Detailed Implementation

[0028] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] In the description of this application, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this application, it should be noted that, unless otherwise expressly specified and limited, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances. Furthermore, in the description of this application, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0030] The present application will now be described in detail with reference to specific embodiments.

[0031] like Figure 1 The diagram shown is a point cloud illustration containing interference points provided in an embodiment of this application. The point cloud illustration is obtained by reconstructing point cloud data acquired by a multi-channel lidar. A multi-channel lidar can simultaneously scan multiple channels, thus expanding the field of view while maintaining the frame rate. Although the emission angles of each channel are different, the laser signal inevitably undergoes reflection during optical path transmission and returns to the multi-channel lidar. Therefore, each channel may receive echo signals emitted by a channel other than its own and reflected by the target object; that is, interference points will appear in each channel, such as... Figure 1 Interference point 101 is shown.

[0032] In related technologies, transmission coding is typically used to address channel crosstalk. This involves convolutional coding of the laser emission signal and subsequent processing upon receiving the laser echo to determine if the echo signal originated from the channel that received it. However, in near-field detection, transmission coding cannot completely resolve channel crosstalk due to the dead time of the receiver module's detector. Especially when high-reflectivity objects are present at close range, the echo signal from the receiving channel corresponding to the high-reflectivity object can create false point clouds with lower reflectivity in other channels—interference points—thus affecting the accuracy of ranging.

[0033] In one embodiment, such as Figure 2As shown, a method for determining interference points is proposed. This method can be implemented using a computer program and can run on a device for determining interference points based on the von Neumann architecture. This computer program can be integrated into applications or run as a standalone utility application.

[0034] Specifically, the method for determining interference points includes:

[0035] S101. Obtain the target point cloud corresponding to the high reflectivity object in the target channel.

[0036] A multi-channel lidar includes multiple channels for receiving laser echoes, and among these channels is a target channel. For example, it may include 10 channels numbered 01 to 10, with channel 01 being the target channel. In this embodiment, all point clouds within all channels are traversed, and the channel containing the target point cloud corresponding to a high-reflectivity object is designated as the target channel. This application also includes other methods for determining the target channel.

[0037] A high-reflectivity object can be understood as an object whose distance from a multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and whose reflectivity is greater than or equal to the first reflectivity threshold. For example, the first distance threshold is 3 meters, the second distance threshold is 8 meters, and the first reflectivity threshold is 65%. If a mirror exists within the scanning range of the target channel, and the distance between the mirror and the lidar is 5 meters, and its reflectivity is 98%, then the mirror is a high-reflectivity object.

[0038] Multi-channel lidar uses the echo signal, which includes spatial coordinates, timestamps, and echo intensity, as a single data point. This data point further includes information such as the distance and angle of the corresponding obstacle relative to the multi-channel lidar. The set of points with higher energy is called the point cloud, and the set of points including the aforementioned information is the point cloud data.

[0039] The receiver and data analysis module corresponding to the target channel determine whether the point cloud received through the target channel corresponds to a high-reflectivity object based on the point cloud data. A classification algorithm is then used to further obtain all target point clouds corresponding to a specific high-reflectivity object within the target channel. For example, this involves obtaining all 1894 target point clouds corresponding to a mirror within channel 01, which is the target channel.

[0040] S102. Based on the target point cloud, obtain the point cloud to be determined at the same pixel position as the target point cloud in each channel except the target channel.

[0041] Obtain the two-dimensional coordinates (x, y) of the target point cloud t within the target channel. Iterate through at least one other channel besides the target channel, obtaining the undetermined point clouds at the same pixel position as the target point cloud in each of the at least one other channel. The number of undetermined point clouds is greater than 0. For example, the target point cloud t has two-dimensional coordinates (x, y) in channel 01 within the target channel. The first undetermined point cloud n2, with the same pixel position as the target point cloud t, is also obtained in channel 02 (x, y). Zero-value point cloud data is obtained at the same pixel position as the target point cloud in channels 03, 04, and 05. The second undetermined point cloud n6, with the same pixel position as the target point cloud t, is obtained in channel 06 (x, y). The third undetermined point cloud n7, with the same pixel position as the target point cloud t, is obtained in channel 07 (x, y). The fourth undetermined point cloud n8, with the same pixel position as the target point cloud t, is obtained in channel 08 (x, y), and so on. It is understandable that each channel in a multi-channel LiDAR acquires the same number of point clouds. For example, each channel acquires M×N point clouds, and when each channel generates a point cloud matrix based on the acquired point clouds, the origin, X-axis direction, and Y-axis direction of the same pixel position are used.

[0042] S103. Based on the distance value and reflectivity of each point cloud to be determined, and the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined, determine whether each point cloud to be determined is a suspected interference point.

[0043] When a highly reflective object exists within the scanning range corresponding to the target channel, its echo signal will not only be received by the target channel to form a target point cloud, but also, due to multiple reflections within the radar, will likely be received by other channels. In the point cloud images of these other channels, artifact points, or interference points, will form at the same pixel positions as the target point cloud. The difference between the distance value corresponding to this interference point and the distance threshold corresponding to the target point cloud is less than a preset distance threshold T1, but the reflectivity corresponding to this interference point will be less than the reflectivity corresponding to the target point cloud, and the difference between the reflectivity corresponding to the target point cloud and the reflectivity corresponding to the interference point is greater than or equal to a preset reflectivity threshold P1.

[0044] However, in other channels, the point cloud to be determined at the same pixel position as the target point cloud may be caused by the echo signal of a real obstacle received by the corresponding channel. If the point cloud to be determined does not meet the above conditions for interference points, then the point cloud to be determined is not an artifact point formed by the target point cloud in other channels.

[0045] For example, the preset distance threshold T1 is 10mm, and the preset reflectivity threshold P1 is 10%. The target point cloud t(x, y) and the corresponding undetermined point clouds in other channels are acquired: n2(x, y), n6(x, y), n7(x, y), and n8(x, y), etc. Based on the distance value and reflectivity of each undetermined point cloud, it is determined whether the undetermined point cloud is a suspected interference point. If the distance value of n2(x,y) to the target point cloud t(x,y) is less than the preset distance threshold T1, and the reflectivity of n2(x,y) is less than the reflectivity of the target point cloud t(x,y), and the absolute value of the difference between the reflectivity of n2(x,y) and the reflectivity of the target point cloud t(x,y) is greater than the preset reflectivity threshold P1, then n2(x,y) can be preliminarily determined to be a suspected interference point. Similarly, n6(x,y) is preliminarily determined to be a suspected interference point. If the absolute value of the difference between the distance value of n7(x,y) and the distance value of the target point cloud t(x,y) is greater than the preset distance threshold T1, then n7(x,y) is determined to be a non-suspected interference point. If the reflectivity of n8(x,y) is greater than the reflectivity of the target point cloud t(x,y), then n8(x,y) is determined to be a non-suspected interference point.

[0046] Once a point cloud to be determined is initially identified as a suspected interference point, the reflectivity and distance values ​​of other point clouds in the neighborhood of the point cloud to be determined, which is initially identified as a suspected interference point, are used to further determine whether the determined point cloud is indeed a suspected interference point.

[0047] When a highly reflective object exists within the scanning range corresponding to the target channel, the echo signal from the highly reflective object will not only be received by the target channel to form a target point cloud, but also, due to channel crosstalk of the echo signal, an artifact point will be formed at the same pixel position as the target point cloud in the corresponding point cloud map in other channels. This artifact point corresponds to a specific point cloud range. Further, within the point cloud range corresponding to the artifact point, there exists a point cloud X1 whose absolute difference between its distance value and the distance value of the target point cloud is less than a preset distance threshold T2, and the number of point clouds X1 should be greater than or equal to a statistical threshold M1. Additionally, within the interference point area, there exists a point cloud X2 with a reflectivity less than a preset reflectivity threshold P2, and the number of point clouds X2 should be greater than or equal to a statistical threshold M2. When the reflectivity and distance values ​​of other point clouds in the neighborhood of the point cloud to be determined, initially judged as a suspected interference point, satisfy the conditions corresponding to the point cloud range of the artifact point, the point cloud to be determined is determined to be a suspected interference point. It is understandable that the preset reflectivity threshold P2 is obtained from the reflectivity of the target point cloud and the aforementioned preset reflectivity threshold P1. Specifically, the preset reflectivity threshold P2 is obtained by subtracting the aforementioned preset reflectivity threshold P1 from the reflectivity of the target point cloud.

[0048] Specifically, point clouds n2(x, y) and n6(x, y) are initially identified as suspected interference points in the second and sixth channels, respectively. Point clouds X3 are identified whose absolute difference between the distance value to the neighborhood of point cloud n2(x, y) and the distance value to n2(x, y) is less than a preset distance threshold T3, and point clouds X4 have reflectance less than a preset reflectance threshold P2. The neighborhood is defined as a range centered on the point cloud to be determined, with a length of L1 pixels and a width of L2 pixels. In some embodiments, L1 and L2 are the same value, and / or the preset distance threshold T3 and the preset distance threshold T2 are the same value. The number of point clouds X3 is determined to be greater than... The first statistical threshold is set as follows: if the number of point cloud X3 is greater than the statistical threshold M2, or the ratio of the number of point cloud X3 to the number of all point clouds in the neighborhood of n2(x,y) is greater than the statistical threshold M3, and the ratio of the number of point cloud X4 to the number of all point clouds in the neighborhood of n2(x,y) is greater than the statistical threshold M4, then n2(x,y) is determined to be a suspected interference point. Based on the same process, the absolute value of the difference between the distance value in the neighborhood of n6(x,y) and the distance value in the point cloud n6(x,y) to be determined is less than the preset distance threshold T3, the reflectivity of point cloud X6 is less than the preset reflectivity threshold P2, and the number of point clouds X5 is less than the statistical threshold M1, then n6(x,y) is not a suspected interference point.

[0049] S104. If yes, determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined, or based on the range of interference points determined by the point cloud to be determined.

[0050] Specifically, the method for determining whether a point cloud to be determined is an interfering point is as follows, based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in their neighborhood:

[0051] When a point cloud to be determined is identified as a suspected interference point, the distance differences between the point cloud to be determined and all point clouds in its neighborhood are obtained. Further, the variance of these distance differences is calculated, and point clouds X3 whose absolute values ​​of the distance differences between their neighbors and the point cloud to be determined are identified are found to be less than a preset distance threshold T3. If the variance of the distance difference is less than the variance threshold and the number of point clouds X3 is greater than or equal to the statistical threshold M5, then the identified point cloud originates from the echo signal received by the channel from a real obstacle, rather than an artifact point formed by a highly reflective object in that channel. In other words, if the variance of the distance differences between the point cloud to be determined and other point clouds in its neighborhood is greater than or equal to the variance threshold, or if the number of point clouds X3 is less than the statistical threshold M5, then the point cloud to be determined is identified as an interference point.

[0052] For example, to determine if a point cloud n2(x, y) in the second channel is a suspected interference point, obtain the absolute values ​​of the distance differences between each point cloud and n2(x, y) in the neighborhood of n2(x, y): t1, t2, t3, ..., t z The variance of the distance value is calculated based on the absolute value of the difference between the above distance values. At this time, the variance of the distance value is greater than the variance threshold. The point cloud X3 whose absolute value of the difference between the distance value in the neighborhood and the distance value of the point cloud n2(x,y) to be determined is less than the preset distance threshold T3 is obtained. Even if the number of point clouds X3 is greater than the statistical threshold M5, the point cloud to be determined is still determined as an interference point.

[0053] In another embodiment, this application determines whether the point cloud to be determined is an interference point based on the range of interference points identified in the point cloud to be determined. Specifically, the method for determining whether the point cloud to be determined is an interference point based on the range of interference points identified in the point cloud to be determined is as follows:

[0054] When a point cloud to be determined is identified as a suspected interference point, based on the distance value of the point cloud to be determined, other point clouds originating from the same obstacle as the point cloud to be determined are identified within the channel corresponding to the point cloud to be determined. The point cloud range is then determined based on these other point clouds and defined as the interference point range of the point cloud to be determined. If a high-reflectivity object exists within the scanning range of the target channel, a target point cloud corresponding to the high-reflectivity object will exist in the point cloud image of the target channel. This target point cloud will form an artifact point in other channels, thus forming a point cloud range corresponding to the artifact point. When the point cloud to be determined is an interference point formed by the target point cloud, the point cloud range corresponding to an artifact point will include the interference point range of the point cloud to be determined.

[0055] For example, obtain point cloud X7 in the second channel that belongs to the same obstacle as the point cloud n2(x,y) to be determined, and determine the range of interference points of n2(x,y) based on point cloud X7; obtain the range of point cloud corresponding to the high reflectivity object in the first channel, and map the range of high reflectivity point cloud at the same pixel position in the second channel based on the range of point cloud corresponding to the high reflectivity object; when the range of interference points of n2(x,y) is included in the above high reflectivity point cloud range, determine the point cloud n2(x,y) to be determined as an interference point.

[0056] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification.

[0057] like Figure 3 As shown, a method for determining interference points is proposed. This method can be implemented using a computer program and can run on a device for determining interference points based on the von Neumann architecture. This computer program can be integrated into applications or run as a standalone utility application.

[0058] Specifically, the method for determining interference points includes:

[0059] S201. Obtain the target point cloud corresponding to the high reflectivity object in the target channel.

[0060] High reflectivity objects can be understood as objects whose distance from a multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and whose reflectivity is greater than or equal to the first reflectivity threshold.

[0061] Step S201 is the same as step S101 above, and will not be repeated here.

[0062] S202. Based on the target point cloud, obtain the point cloud to be determined at the same pixel position as the target point cloud in each channel except the target channel.

[0063] Step S202 is the same as step S102 above, and will not be repeated here.

[0064] S203. Based on the distance value and reflectivity of each point cloud to be determined, and the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined, determine whether each point cloud to be determined is a suspected interference point.

[0065] Step S203 is the same as step S103 above, and will not be repeated here.

[0066] S204A. If the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined is greater than or equal to the variance threshold, or if the ratio of the number of the first point cloud in the neighborhood of the point cloud to the number of all point clouds in the neighborhood of the point cloud to be determined is less than the number statistics threshold.

[0067] Among them, the first point cloud is the point cloud whose absolute value of the difference between the distance value in the neighborhood of the point cloud to be determined and the distance value of the point cloud to be determined is less than the third distance threshold.

[0068] When a point cloud to be determined is identified as a suspected interference point, the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood is used to determine whether the point cloud to be determined is an interference point.

[0069] Specifically, when a point cloud to be determined is identified as a suspected interference point, the distance differences between the point cloud to be determined and all point clouds in its neighborhood are obtained. Further, the variance of the distance values ​​is obtained based on these differences. Additionally, the absolute value of the difference between the distance values ​​in the neighborhood and the point cloud to be determined is identified as the first point cloud whose distance difference is less than a third distance threshold. If the variance of the distance values ​​is less than the variance threshold and the number of the first point clouds is greater than or equal to the number statistics threshold, then the identified point cloud originates from the echo signal received by the channel from a real obstacle, rather than an artifact point formed by a highly reflective object in that channel. In other words, if the variance of the distance values ​​between the point cloud to be determined and other point clouds in its neighborhood is greater than or equal to the variance threshold, or if the ratio of the number of the first point clouds to the number of all point clouds in the neighborhood of the point cloud to be determined is less than the number statistics threshold, then the point cloud to be determined is identified as an interference point.

[0070] In one embodiment, the method further includes: acquiring zero-value point cloud data within the neighborhood of the point cloud to be determined, wherein the zero-value point cloud data includes the number of zero-value point clouds in the point cloud to be determined. The point cloud to be determined is determined as an interference point when the variance of the distance values ​​between other point clouds in the neighborhood of the point cloud to be determined is greater than or equal to a variance threshold, or when the ratio of the number of the first point cloud to the total number of point clouds in the neighborhood of the point cloud to be determined is less than a statistical threshold minus the number of zero-value point clouds.

[0071] In this embodiment of the application, when calculating the ratio between the number of points in the first point cloud and the number of all points in the neighborhood of the point cloud to be determined and the number statistics threshold, the number of empty data in the neighborhood is introduced to avoid too much empty data in the neighborhood affecting the calculation of the ratio between the number of points in the first point cloud and the number of all points in the neighborhood of the point cloud to be determined, thereby affecting the judgment of whether the point cloud to be determined is an interference point.

[0072] S204B, The range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range.

[0073] When a point cloud to be determined is identified as a suspected interference point, based on the distance value of the point cloud to be determined, other point clouds originating from the same obstacle as the point cloud to be determined are identified within the channel corresponding to the point cloud to be determined. The point cloud range is then determined based on these other point clouds and defined as the interference point range of the point cloud to be determined. If a high-reflectivity object exists within the scanning range of the target channel, a target point cloud corresponding to the high-reflectivity object will exist in the point cloud image of the target channel. This target point cloud will form an artifact point in other channels, thus forming a point cloud range corresponding to the artifact point. When the point cloud to be determined is an interference point formed by the target point cloud, the point cloud range corresponding to an artifact point will include the interference point range of the point cloud to be determined.

[0074] S205. Identify the point cloud to be determined as an interference point.

[0075] When either step S204A or step S204B is met, the point cloud to be determined is identified as an interference point.

[0076] like Figure 4 The diagram shown is a flowchart illustrating a method for determining whether a suspected interference point is an interference point, according to an embodiment of this application. This method is a possible implementation of determining whether a suspected interference point is an interference point based on the principle of S204B.

[0077] Specifically, the method includes the following steps:

[0078] S2041B. Determine a second point cloud within the target channel whose absolute value of the difference between the distance value and the distance value of the target point cloud is less than a fourth distance threshold, and whose absolute value of the difference between the reflectance and the reflectance of the target point cloud is less than a second reflectance threshold.

[0079] like Figure 5 The diagram shown is a dot matrix diagram for determining whether a suspected interference point is an interference point according to an embodiment of this application. The dot matrix diagram includes: target channel, channel 01, channel 02, channel 03, etc. (not shown in the figure). The target channel corresponds to the target point cloud collected through a high reflectivity object. In channel 01, there is a point cloud d1 to be determined at the same pixel position of the target point cloud in channel 01. The point cloud d1 to be determined is confirmed as a suspected interference point after passing S203. In channel 02, there is a point cloud d2 to be determined at the same pixel position of the target point cloud in channel 02. The point cloud d2 to be determined is confirmed as a suspected interference point after passing S203.

[0080] Among all point clouds acquired by the target channel, the second point cloud is identified as one whose absolute value of the difference between its distance value and the target point cloud's distance value is less than a fourth distance threshold, and whose absolute value of the difference between its reflectance and the target point cloud's reflectance is less than a second reflectance threshold. In other words, the second point cloud corresponds to the point cloud of the high-reflectance object acquired by the target channel.

[0081] S2042B: Determine the point cloud range corresponding to the high reflectivity object in the target channel based on the second point cloud.

[0082] like Figure 5 As shown, the point cloud range corresponding to the high reflectivity object is determined based on the second point cloud included in all point clouds collected by the target channel.

[0083] S2043B: Based on each point cloud within the point cloud range corresponding to the high reflectivity object, determine the point cloud at the same pixel position as the point cloud in each channel except the target channel, and obtain the point cloud range mapped in each channel except the target channel.

[0084] like Figure 5 As shown, the point cloud range corresponding to the high reflectivity object in the target channel is obtained, and the high reflectivity range corresponding to the point cloud range of the high reflectivity object is mapped in the point cloud matrix composed of point cloud data collected by channel 01, and the high reflectivity range corresponding to the point cloud range of the high reflectivity object is mapped in the point cloud matrix composed of point cloud data collected by channel 02.

[0085] S2044B: Determine the third point cloud within the channel corresponding to the point cloud to be determined, where the absolute value of the difference between the distance value and the distance value of the point cloud to be determined is less than the fourth distance threshold.

[0086] The third point cloud in the channel corresponding to the point cloud to be determined is determined based on the distance value. In other words, the point cloud data collected from the channel corresponding to the point cloud to be determined based on the distance value is the point cloud that may come from the same obstacle as the point cloud to be determined, i.e., the third point cloud.

[0087] like Figure 5 As shown, in the point cloud data collected by acquisition channel 01, the absolute value of the difference between the distance value and the distance value of the point cloud d1 to be determined is less than the fourth distance threshold for the third point cloud y1; in the point cloud data collected by acquisition channel 02, the absolute value of the difference between the distance value and the distance value of the point cloud d2 to be determined is less than the fourth distance threshold for the third point cloud y2.

[0088] S2045B: Determine the range of interference points corresponding to the point cloud to be determined based on the third point cloud.

[0089] like Figure 5 As shown, the range of interference points corresponding to the point cloud d1 to be determined is determined based on the third point cloud y1 corresponding to channel 01; the range of interference points corresponding to the point cloud d2 to be determined is determined based on the third point cloud y2 corresponding to channel 02.

[0090] S2046B. Based on the range of interference points and the range of high reflectivity corresponding to the point cloud to be determined, determine whether the point cloud to be determined is an interference point.

[0091] Determine whether the range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range. If yes, determine whether the point cloud to be determined is an interference point; if no, determine whether the point cloud to be determined is a non-interference point.

[0092] like Figure 5 As shown, the range of interference points corresponding to the point cloud d1 to be determined in channel 01 is contained within the high reflectivity range, thus the point cloud d1 to be determined is identified as an interference point. The range of interference points corresponding to the point cloud d2 to be determined in channel 02 is not completely contained within the high reflectivity range. Therefore, the point cloud d2 to be determined may be generated by the echo signal of the real obstacle collected by channel 02, rather than an artifact interference point generated by the target point cloud in channel 02.

[0093] The method for judging interference points provided in the embodiments of this application has high reliability, low computational load, and high computational efficiency, and can effectively judge the artifact interference points corresponding to the target point cloud in other channels.

[0094] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification.

[0095] like Figure 6 As shown, a method for determining interference points is proposed. This method can be implemented using a computer program and can run on a device for determining interference points based on the von Neumann architecture. This computer program can be integrated into applications or run as a standalone utility application.

[0096] S301. Based on the distance value and emissivity of the target point cloud, determine whether the target point cloud initially corresponds to a high reflectivity object.

[0097] A high-reflectivity object can be understood as an object whose distance from the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and whose reflectivity is greater than or equal to the first reflectivity threshold. In this embodiment, the point cloud corresponding to each channel acquired by the multi-channel lidar is used to determine whether the point cloud corresponds to a high-reflectivity object based on the distance value and reflectivity of each point cloud.

[0098] In one embodiment, the specific method for determining whether a target point cloud initially corresponds to a high reflectivity object based on the distance value and reflectivity of the target point cloud is as follows: obtain the distance value and reflectivity of the target point cloud; if the distance value of the target point cloud is less than a first distance threshold and greater than or equal to a second distance threshold, and the reflectivity of the target point cloud is greater than or equal to a first reflectivity threshold, then it is determined that the target point cloud initially corresponds to a high reflectivity object.

[0099] S302. If yes, determine whether the target point cloud corresponds to a high-reflectivity object based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the target point cloud.

[0100] If the target point cloud initially corresponds to a high-reflectivity object, then based on the distance values ​​and reflectivity of other point clouds within the target point cloud's neighborhood, it is further determined whether the target point cloud corresponds to a high-reflectivity object. The neighborhood of the target point cloud can be understood as a range centered on the target point cloud, with a length of L3 pixels and a width of L4 pixels. In some embodiments, L3 and L4 are the same value, and / or have the same length and width as the neighborhood of the point cloud to be determined.

[0101] In one embodiment, the method for determining whether a target point cloud corresponds to a high-reflectivity object based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the target point cloud is as follows:

[0102] Within the neighborhood of the target point cloud, identify the fourth point cloud whose absolute difference between its distance value and the distance value of the target point cloud is less than the fifth distance threshold, and the fifth point cloud whose reflectance is greater than or equal to the third reflectance threshold; wherein the number of the fourth point cloud and the number of the fifth point cloud are both greater than or equal to 0.

[0103] If the ratio of the number of the fourth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first distance statistical threshold, and the ratio of the number of the fifth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first reflectivity statistical threshold, then the target point cloud is determined to correspond to a high reflectivity object.

[0104] like Figure 7 As shown, this application provides a point cloud matrix diagram including a target point cloud and a point cloud to be determined. The point cloud matrix diagram includes: a target point cloud t obtained by the target channel, a point cloud d1 to be determined obtained by channel 01, a point cloud d2 to be determined obtained by channel 02, a point cloud d3 to be determined obtained by channel 03 (not shown in the figure), etc.

[0105] For example, obtain the distance value and reflectance of all point clouds in the neighborhood of the target point cloud t, obtain the fourth point cloud z1 whose absolute value of the difference between its distance value and the distance value of the target point cloud t is less than the fifth distance threshold, and the fifth point cloud z2 whose reflectance is greater than or equal to the third reflectance threshold; if the ratio of the number of fourth point clouds z1 to the number of all point clouds in the neighborhood of the target point cloud is greater than or equal to the first distance statistical threshold, and the ratio of the number of fifth point clouds z2 to the number of all point clouds in the neighborhood of the target point cloud is greater than or equal to the first reflectance statistical threshold, then determine that the target point cloud t corresponds to a high reflectance object.

[0106] The embodiments of this application determine whether a target point cloud corresponds to a high-reflectivity object by using the distance value and reflectivity of the target point cloud. The method for determining the target point cloud is highly reliable, has a small computational load, and is highly efficient. It can effectively determine the target point cloud corresponding to a high-reflectivity object in other channels, thereby obtaining the undetermined point cloud corresponding to other channels besides the target channel.

[0107] In one embodiment, the method further includes: acquiring zero-value point cloud data within the neighborhood of the target point cloud, wherein the zero-value point cloud data includes the number of zero-value point clouds in the target point cloud. When the ratio of the number of the fourth point cloud to the total number of point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to a first distance statistical threshold minus the number of zero-value point clouds, and when the ratio of the number of the fifth point cloud to the total number of point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to a first reflectivity statistical threshold minus the number of zero-value point clouds, the target point cloud is determined to correspond to a high-reflectivity object.

[0108] In another embodiment, the method further includes: determining whether multiple target point clouds correspond to the same high-reflectivity object based on the distance values ​​corresponding to the multiple target point clouds respectively, and classifying the target point cloud corresponding to each high-reflectivity object.

[0109] S303. If yes, based on the target point cloud, obtain the point cloud to be determined at the same pixel position as the target point cloud in each channel outside the target channel.

[0110] Step S303 is the same as step S102 above, and will not be repeated here.

[0111] S304. Based on whether the reflectivity of the point cloud to be determined is less than the fourth reflectivity threshold, and whether the absolute value of the difference between the distance value of the point cloud to be determined and the distance value of the target point cloud is less than the third distance threshold.

[0112] The determination of whether a point cloud to be determined corresponds to a target point cloud is based on whether the reflectivity of the point cloud to be determined is less than a fourth reflectivity threshold, and whether the absolute value of the difference between the distance value of the point cloud to be determined and the distance value of the target point cloud is less than a third distance threshold. In other words, it is determined whether the point cloud to be determined at the same pixel position as the target point cloud in other channels is caused by the echo signal of a real obstacle received in the corresponding channel. If the point cloud to be determined does not meet the above conditions, then the point cloud to be determined is not an artifact point formed by the target point cloud in other channels.

[0113] For example, such as Figure 7 As shown, it is determined whether the reflectivity of the point cloud d1 to be determined is less than the fourth reflectivity threshold, and whether the absolute value of the difference between the distance value of the point cloud d1 to be determined and the distance value of the target point cloud t is less than the third distance threshold.

[0114] S305. If all are yes, determine whether the point cloud to be determined is a suspected interference point based on the distance value and reflectivity of other point clouds in the neighborhood of the point cloud to be determined.

[0115] If all are yes, then it is initially determined that the point cloud to be determined corresponds to the target point cloud. Further, based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the point cloud to be determined, it is determined whether the point cloud to be determined is a suspected interference point.

[0116] In one embodiment, the method for determining whether a point cloud to be determined is a suspected interference point is as follows:

[0117] Within the neighborhood of the point cloud to be determined, there is a first point cloud whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and a sixth point cloud whose reflectance is less than a fourth reflectance threshold; wherein the number of the first point cloud and the number of the sixth point cloud are both greater than or equal to 0.

[0118] If the number of points in the first point cloud is greater than or equal to the second distance statistical threshold, and the ratio of the number of points in the sixth point cloud to the number of all points in the neighborhood corresponding to the point cloud to be determined is greater than or equal to the second reflectivity statistical threshold, the point cloud to be determined is determined as a suspected interference point.

[0119] For example, such as Figure 5As shown, within the neighborhood of the point cloud d1 to be determined, the first point cloud z3, whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and the sixth point cloud z5, whose reflectivity is less than a fourth reflectivity threshold, are obtained. It is determined that the number of the first point cloud z3 is greater than a second distance statistical threshold, and the ratio of the number of the sixth point cloud z4 to the total number of point clouds in the neighborhood corresponding to the point cloud d1 to be determined is greater than a second reflectivity statistical threshold, thus determining the point cloud d1 to be determined as a suspected interference point. Within the neighborhood of the point cloud d2 to be determined, the first point cloud z5, whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and the sixth point cloud z6, whose reflectivity is less than a fourth reflectivity threshold, are obtained. It is determined that the number of the first point cloud z5 is less than a second distance statistical threshold, and the ratio of the number of the sixth point cloud z6 to the total number of point clouds in the neighborhood corresponding to the point cloud d2 to be determined is greater than a second reflectivity statistical threshold, thus determining the point cloud d2 to be determined as a non-suspected interference point.

[0120] In one embodiment, the method further includes: acquiring zero-value point cloud data within the neighborhood of the point cloud to be determined, wherein the zero-value point cloud data includes the number of zero-value point clouds in the target point cloud. If the number of the first point cloud is greater than or equal to a second distance statistical threshold minus the number of zero-value point clouds, and the ratio of the number of the sixth point cloud to the total number of point clouds in the neighborhood corresponding to the point cloud to be determined is greater than or equal to a second reflectivity statistical threshold minus the number of zero-value point clouds, the point cloud to be determined is determined as a suspected interference point.

[0121] S306. If yes, determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between other point clouds in the neighborhood of the point cloud to be determined and the point cloud to be determined, or based on the range of interference points determined by the point cloud to be determined.

[0122] Step S306 is the same as step S104 above, and will not be repeated here.

[0123] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification.

[0124] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0125] Please see Figure 8 This illustration shows a schematic diagram of a device for determining interference points according to an exemplary embodiment of this application. The device for determining interference points can be implemented as all or part of the device through software, hardware, or a combination of both. The device includes a first acquisition module 801, a second acquisition module 802, a suspected interference determination module 803, and an interference determination module 804.

[0126] The first acquisition module 801 is used to acquire the target point cloud corresponding to the high reflectivity object in the target channel; wherein, the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold.

[0127] The second acquisition module 802 is used to acquire, based on the target point cloud, the point cloud to be determined at the same pixel position as the target point cloud in each channel except the target channel;

[0128] The suspected interference determination module 803 is used to determine whether each of the points to be determined is a suspected interference point based on the distance value and reflectivity of each point cloud to be determined, as well as the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined.

[0129] The interference determination module 804 is used to determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined, or based on the range of interference points corresponding to the point cloud to be determined.

[0130] In one possible embodiment, the interference determination module 804 includes:

[0131] The first determining unit is configured to determine if the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined is greater than or equal to a variance threshold, or if the ratio of the number of the first point cloud in the neighborhood of the point cloud to be determined to the number of all point clouds in the neighborhood of the point cloud to be determined is less than a number statistics threshold, wherein the first point cloud is a point cloud whose absolute value of the difference between the distance value in the neighborhood of the point cloud to be determined and the distance value of the point cloud to be determined is less than a third distance threshold.

[0132] It may include: a second determining unit, configured to determine the point cloud to be determined as an interference point if the range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range; wherein, the high reflectivity range is the point cloud range mapped in each channel except the target channel for the point cloud range corresponding to the high reflectivity object.

[0133] In one possible embodiment, the interference determination module 804 further includes:

[0134] An acquisition range unit is used to acquire the point cloud range corresponding to the high reflectivity object within the target channel;

[0135] The mapping acquisition unit is used to determine, based on each point cloud in the point cloud range, the point cloud at the same pixel position as each point cloud in the point cloud range in each channel other than the target channel, so as to obtain the point cloud range mapped by the point cloud range in each channel other than the target channel.

[0136] In one possible embodiment, the range acquisition unit includes:

[0137] A subunit is defined to determine a second point cloud within the target channel whose absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fourth distance threshold, and whose absolute value of the difference between its reflectance and the reflectance of the target point cloud is less than a second reflectance threshold; wherein the number of the second point clouds is greater than 1.

[0138] The range sub-unit is used to determine the range of the point cloud corresponding to the high reflectivity object within the target channel based on the second point cloud.

[0139] In one possible embodiment, the interference determination module 804 includes:

[0140] The third determining unit is used to determine a third point cloud in the channel corresponding to the point cloud to be determined, wherein the absolute value of the difference between the distance value and the distance value of the point cloud to be determined is less than a fourth distance threshold; wherein the number of the third point clouds is greater than or equal to 0.

[0141] The range determination unit is used to determine the range of interference points corresponding to the point cloud to be determined based on the third point cloud.

[0142] In one possible embodiment, the first acquisition module 801 includes:

[0143] The preliminary correspondence unit is used to determine whether the target point cloud initially corresponds to a high-reflectivity object based on the distance value and reflectivity of the target point cloud;

[0144] The high reflectivity determination unit is used to determine, if true, a high reflectivity object corresponding to the target point cloud based on the distance value and reflectivity of other point clouds in the neighborhood of the target point cloud.

[0145] In one possible embodiment, the preliminary matching unit is used to determine that the target point cloud initially corresponds to a high reflectivity object if the distance value of the target point cloud is less than the first distance threshold and greater than or equal to the second distance threshold, and the reflectivity of the target point cloud is greater than or equal to the first reflectivity threshold.

[0146] In one possible embodiment, the high-intensity detection unit includes:

[0147] The fourth determining subunit is used to determine, within the neighborhood of the target point cloud, a fourth point cloud whose absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fifth distance threshold, and a fifth point cloud whose reflectance is greater than or equal to a third reflectance threshold; wherein, the number of the fourth point cloud and the number of the fifth point cloud are respectively greater than or equal to 0.

[0148] The high reflectivity determination subunit is used to determine that the target point cloud corresponds to a high reflectivity object if the ratio of the number of the fourth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to a first distance statistical threshold, and the ratio of the number of the fifth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to a first reflectivity statistical threshold.

[0149] In one possible embodiment, the suspected determination module 803 includes:

[0150] The target matching unit is used to determine whether the point cloud to be determined corresponds to the target point cloud based on whether the reflectivity of the point cloud to be determined is less than a fourth reflectivity threshold and whether the absolute value of the difference between the distance value of the point cloud to be determined and the distance value of the target point cloud is less than a third distance threshold.

[0151] The suspected determination unit is used to determine whether the point cloud to be determined is a suspected interference point based on the distance value and reflectivity of other point clouds in the neighborhood of the point cloud to be determined, if all are yes.

[0152] In one possible embodiment, the suspected determination unit includes:

[0153] The fifth determining subunit is used to determine a first point cloud in the neighborhood of the point cloud to be determined, whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and a sixth point cloud whose reflectance is less than a fourth reflectance threshold; wherein the number of the first point cloud and the number of the sixth point cloud are respectively greater than or equal to 0.

[0154] The suspected determination subunit is used to determine the point cloud to be determined as a suspected interference point if the number of the first point cloud is greater than or equal to the second distance statistics threshold, and the ratio of the number of the sixth point cloud to the number of all point clouds in the neighborhood corresponding to the point cloud to be determined is greater than or equal to the second reflectivity statistics threshold.

[0155] In one possible embodiment, the device for determining interference points further includes:

[0156] The zero-value module is used to determine the number of zero-value point clouds in the neighborhood of the target point cloud; wherein the distance value and reflectivity of the zero-value point clouds are both 0.

[0157] The judgment module is used to determine whether the target point cloud corresponds to a high-reflectivity object based on the distance value and reflectivity of the target point cloud acquired by the target channel, and the distance values ​​and reflectivities of other point clouds in the neighborhood of the target point cloud, respectively. This includes:

[0158] The corresponding module is used to determine whether the target point cloud corresponds to a high reflectivity object based on the distance value and reflectivity of the target point cloud collected by the target channel, the distance value and reflectivity of other point clouds in the neighborhood of the target point cloud, and the number of zero-value point clouds in the neighborhood of the target point cloud.

[0159] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification.

[0160] It should be noted that the apparatus for determining interference points provided in the above embodiments is only illustrated by the division of the above functional modules when executing the method for determining interference points. In practical applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the apparatus for determining interference points and the method for determining interference points provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0161] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0162] This application also provides a computer storage medium that can store multiple instructions, which are adapted to be loaded and executed by a processor as described above. Figures 1-7 The method for determining interference points in the illustrated embodiment can be found in the following documentation for a detailed execution process: Figures 1-7 The specific details of the illustrated embodiments will not be elaborated here.

[0163] This application also provides a computer program product storing at least one instruction, which is loaded and executed by the processor as described above. Figures 1-7 The method for determining interference points in the illustrated embodiment can be found in the following documentation for a detailed execution process: Figures 1-7 The specific details of the illustrated embodiments will not be elaborated here.

[0164] Please see Figure 9 The present application provides a schematic diagram of the structure of a multi-channel lidar, as shown in the embodiment. Figure 9 As shown, the multi-channel lidar 900 may include: at least one processor 901, at least one network interface 904, a user interface 903, a memory 905, and at least one communication bus 902.

[0165] The communication bus 902 is used to enable communication between these components.

[0166] The user interface 903 may include standard wired and wireless interfaces.

[0167] The network interface 904 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0168] The processor 901 may include one or more processing cores. The processor 901 connects to various parts of the server 900 using various interfaces and lines, and performs various functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 905, and by calling data stored in the memory 905. Optionally, the processor 901 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 901 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also be implemented as a separate chip without being integrated into the processor 901.

[0169] The memory 905 may include random access memory (RAM) or read-only memory. Optionally, the memory 905 may include a non-transitory computer-readable storage medium. The memory 905 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 905 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 905 may also be at least one storage device located remotely from the aforementioned processor 901. Figure 9 As shown, the memory 905, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for determining interference points.

[0170] exist Figure 9In the multi-channel lidar 900 shown, the user interface 903 is mainly used to provide an input interface for the user and acquire user input data; while the processor 901 can be used to call the application program for determining interference points stored in the memory 905, and specifically perform the following operations:

[0171] Acquire the target point cloud corresponding to the high reflectivity object within the target channel; wherein the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold;

[0172] Based on the target point cloud, obtain the point cloud to be determined in each channel other than the target channel, which has the same pixel position as the target point cloud;

[0173] Based on the distance value and reflectivity of each point cloud to be determined, and the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined, determine whether each point cloud to be determined is a suspected interference point;

[0174] If so, determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points corresponding to the point cloud to be determined.

[0175] In one possible embodiment, processor 901 executes the "if yes" statement, determining whether the point cloud to be determined is an interference point based on the variance of distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points corresponding to the point cloud to be determined. Specifically, the following is executed:

[0176] If the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined is greater than or equal to a variance threshold, or if the ratio of the number of the first point cloud in the neighborhood of the point cloud to be determined to the total number of point clouds in the neighborhood of the point cloud to be determined is less than a number statistics threshold, then the first point cloud is the point cloud whose absolute value of the difference between the distance value in the neighborhood of the point cloud to be determined and the distance value of the point cloud to be determined is less than a third distance threshold.

[0177] or

[0178] If the range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range, the point cloud to be determined is determined to be an interference point; wherein, the high reflectivity range is the point cloud range mapped in each channel except the target channel for the point cloud range corresponding to the high reflectivity object.

[0179] In one possible embodiment, before processor 901 executes the step of determining the point cloud to be determined as an interference point based on the fact that the range of interference points corresponding to the point cloud to be determined is contained within a high reflectivity range, it specifically performs the following:

[0180] Obtain the point cloud range corresponding to the high reflectivity object within the target channel;

[0181] Based on each point cloud in the point cloud range, determine the point cloud at the same pixel position as each point cloud in the point cloud range in each channel other than the target channel, and obtain the point cloud range mapped by the point cloud range in each channel other than the target channel.

[0182] In one possible embodiment, processor 901 performs the step of obtaining the point cloud range corresponding to the high reflectivity object within the target channel, specifically by:

[0183] Within the target channel, a second point cloud is identified where the absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fourth distance threshold, and the absolute value of the difference between its reflectance and the reflectance of the target point cloud is less than a second reflectance threshold; wherein the number of the second point clouds is greater than 1.

[0184] The point cloud range corresponding to the high reflectivity object within the target channel is determined based on the second point cloud.

[0185] In one possible embodiment, the processor 901 executes the step of determining whether the point cloud to be determined is an interference point based on the range of interference points corresponding to the point cloud to be determined, specifically by:

[0186] Within the channel corresponding to the point cloud to be determined, a third point cloud is identified whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a fourth distance threshold; wherein, the number of the third point clouds is greater than or equal to 0.

[0187] The range of interference points corresponding to the point cloud to be determined is determined based on the third point cloud.

[0188] In one possible embodiment, processor 901 performs the step of acquiring the target point cloud corresponding to the high reflectivity object within the target channel, specifically by:

[0189] Based on the distance value and reflectivity of the target point cloud, determine whether the target point cloud initially corresponds to a high-reflectivity object;

[0190] If so, the high-reflectivity object corresponding to the target point cloud is determined based on the distance value and reflectivity of other point clouds in the neighborhood of the target point cloud.

[0191] In one possible embodiment, the processor 901 executes the step of determining whether the target point cloud initially corresponds to a high-reflectivity object based on the distance value and reflectivity of the target point cloud, specifically by:

[0192] If the distance value of the target point cloud is less than the first distance threshold and greater than or equal to the second distance threshold, and the reflectivity of the target point cloud is greater than or equal to the first reflectivity threshold, then the target point cloud is preliminarily determined to correspond to a high reflectivity object.

[0193] In one possible embodiment, processor 901 executes the "if yes" statement, determining a high-reflectivity object corresponding to the target point cloud based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the target point cloud, specifically by:

[0194] Within the neighborhood of the target point cloud, a fourth point cloud is identified whose absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fifth distance threshold, and a fifth point cloud has a reflectance greater than or equal to a third reflectance threshold; wherein the number of the fourth point cloud and the number of the fifth point cloud are both greater than or equal to 0.

[0195] If the ratio of the number of the fourth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first distance statistics threshold, and the ratio of the number of the fifth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first reflectivity statistics threshold, then the target point cloud is determined to correspond to a high reflectivity object.

[0196] In one possible embodiment, the processor 901 executes the step of determining whether each point cloud to be determined is a suspected interference point based on the distance value and reflectivity of each point cloud to be determined, and the distance values ​​and reflectivity of other point clouds in the neighborhood of each point cloud to be determined. Specifically, the following steps are performed:

[0197] Based on whether the reflectivity of the point cloud to be determined is less than a fourth reflectivity threshold, and whether the absolute value of the difference between the distance value of the point cloud to be determined and the distance value of the target point cloud is less than a third distance threshold, it is determined whether the point cloud to be determined corresponds to the target point cloud.

[0198] If all are yes, then based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the point cloud to be determined, determine whether the point cloud to be determined is a suspected interference point.

[0199] In one possible embodiment, processor 901 executes the step of "if all are yes", determining whether the point cloud to be determined is a suspected interference point based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the point cloud to be determined, specifically:

[0200] Within the neighborhood of the point cloud to be determined, there is a first point cloud whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and a sixth point cloud whose reflectance is less than a fourth reflectance threshold; wherein the number of the first point cloud and the number of the sixth point cloud are both greater than or equal to 0.

[0201] If the number of the first point cloud is greater than or equal to the second distance statistics threshold, and the ratio of the number of the sixth point cloud to the number of all point clouds in the neighborhood corresponding to the point cloud to be determined is greater than or equal to the second reflectivity statistics threshold, the point cloud to be determined is determined to be a suspected interference point.

[0202] In one possible embodiment, before the processor 901 executes the distance value and reflectance of the target point cloud acquired based on the target channel, and the distance value and reflectance of other point clouds in the neighborhood of the target point cloud, respectively, to determine whether the target point cloud corresponds to a high-reflectance object, it further specifically executes:

[0203] Determine the number of zero-value point clouds in the neighborhood of the target point cloud; wherein the distance value and reflectance of the zero-value point clouds are both 0;

[0204] The step of determining whether the target point cloud corresponds to a high-reflectivity object based on the distance and reflectivity of the target point cloud collected by the target channel, and the distance and reflectivity of other point clouds in the neighborhood of the target point cloud, includes:

[0205] Based on the distance value and reflectivity of the target point cloud collected by the target channel, the distance value and reflectivity of other point clouds in the neighborhood of the target point cloud, and the number of zero-value point clouds in the neighborhood of the target point cloud, it is determined whether the target point cloud corresponds to a high reflectivity object.

[0206] This application solves the problem in related technologies of the inability to effectively identify crosstalk artifact point clouds between channels of multi-channel lidar. It obtains the target point cloud corresponding to a high-reflectivity object within a preset distance range in the target channel, and further obtains other undetermined point clouds at the same pixel positions as the target point cloud in other channels. Furthermore, it determines whether the undetermined point cloud is an artifact interference point caused by crosstalk by using the variance of the distance values ​​between the undetermined point cloud and other point clouds in their neighborhood, as well as the range of interference points in the undetermined point cloud. This application can effectively identify interference points within a channel, thereby eliminating interference points and preventing the lidar from misjudging the presence of false target objects due to the existence of interference points. Furthermore, the judgment method of this application can avoid misjudging point clouds generated by real target objects as interference points, affecting ranging accuracy and driving safety, and effectively improving the accuracy of radar identification.

[0207] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory, or random access memory, etc.

[0208] The above-disclosed embodiments are merely preferred embodiments of this application and should not be construed as limiting the scope of this application. Therefore, any equivalent variations made in accordance with the claims of this application shall still fall within the scope of this application.

Claims

1. A method for determining interference points, applied to a multi-channel lidar, wherein the multi-channel lidar includes multiple channels, characterized in that, The method includes: Acquire the target point cloud corresponding to the high reflectivity object within the target channel; wherein the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold; Based on the target point cloud, obtain the point cloud to be determined in each channel other than the target channel, which has the same pixel position as the target point cloud; Based on the distance value and reflectivity of each point cloud to be determined, and the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined, determine whether each point cloud to be determined is a suspected interference point; If so, determine whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points corresponding to the point cloud to be determined.

2. The method according to claim 1, characterized in that, If yes, determining whether the point cloud to be determined is an interference point based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood, or based on the range of interference points corresponding to the point cloud to be determined, includes: If the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined is greater than or equal to a variance threshold, or if the ratio of the number of the first point cloud in the neighborhood of the point cloud to be determined to the total number of point clouds in the neighborhood of the point cloud to be determined is less than a number statistics threshold, then the first point cloud is the point cloud whose absolute value of the difference between the distance value in the neighborhood of the point cloud to be determined and the distance value of the point cloud to be determined is less than a third distance threshold. or If the range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range, the point cloud to be determined is determined to be an interference point; wherein, the high reflectivity range is the point cloud range mapped in each channel except the target channel of the point cloud range corresponding to the high reflectivity object.

3. The method according to claim 2, characterized in that, Before determining the point cloud to be determined as an interference point based on the fact that the range of interference points corresponding to the point cloud to be determined is included within the high reflectivity range, the following steps are included: Obtain the point cloud range corresponding to the high reflectivity object within the target channel; Based on each point cloud in the point cloud range, determine the point cloud at the same pixel position as each point cloud in the point cloud range in each channel other than the target channel, and obtain the point cloud range mapped by the point cloud range in each channel other than the target channel.

4. The method according to claim 3, characterized in that, The step of obtaining the point cloud range corresponding to the high reflectivity object within the target channel includes: Within the target channel, a second point cloud is identified where the absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fourth distance threshold, and the absolute value of the difference between its reflectance and the reflectance of the target point cloud is less than a second reflectance threshold; wherein the number of the second point clouds is greater than 1. The point cloud range corresponding to the high reflectivity object within the target channel is determined based on the second point cloud.

5. The method according to claim 1, characterized in that, The step of determining whether the point cloud to be determined is an interference point based on the range of interference points corresponding to the point cloud to be determined includes: Within the channel corresponding to the point cloud to be determined, a third point cloud is identified whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a fourth distance threshold; wherein, the number of the third point clouds is greater than or equal to 0. The range of interference points corresponding to the point cloud to be determined is determined based on the third point cloud.

6. The method according to claim 1, characterized in that, The acquisition of the target point cloud corresponding to the high reflectivity object within the target channel includes: Based on the distance value and reflectivity of the target point cloud, determine whether the target point cloud initially corresponds to a high reflectivity object; If so, the target point cloud is identified as a high-reflectivity object based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the target point cloud.

7. The method according to claim 6, characterized in that, The step of determining whether the target point cloud initially corresponds to a high-reflectivity object based on the distance value and reflectivity of the target point cloud includes: If the distance value of the target point cloud is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the target point cloud is greater than or equal to a first reflectivity threshold, then the target point cloud is preliminarily determined to correspond to a high reflectivity object.

8. The method according to claim 6, characterized in that, If so, determining the high-reflectivity object corresponding to the target point cloud based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the target point cloud includes: Within the neighborhood of the target point cloud, a fourth point cloud is identified whose absolute value of the difference between its distance value and the distance value of the target point cloud is less than a fifth distance threshold, and a fifth point cloud has a reflectance greater than or equal to a third reflectance threshold; wherein the number of the fourth point cloud and the number of the fifth point cloud are both greater than or equal to 0. If the ratio of the number of the fourth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first distance statistics threshold, and the ratio of the number of the fifth point cloud to the number of all point clouds in the neighborhood corresponding to the target point cloud is greater than or equal to the first reflectivity statistics threshold, then the target point cloud is determined to correspond to a high reflectivity object.

9. The method according to claim 1, characterized in that, The step of determining whether each point cloud to be determined is a suspected interference point based on the distance value and reflectance of each point cloud to be determined, and the corresponding distance values ​​and reflectances of other point clouds in the neighborhood of each point cloud to be determined, includes: Based on whether the reflectivity of the point cloud to be determined is less than a fourth reflectivity threshold, and whether the absolute value of the difference between the distance value of the point cloud to be determined and the distance value of the target point cloud is less than a third distance threshold, it is determined whether the point cloud to be determined corresponds to the target point cloud. If all are yes, then based on the distance values ​​and reflectivity of other point clouds in the neighborhood of the point cloud to be determined, determine whether the point cloud to be determined is a suspected interference point.

10. The method according to claim 9, characterized in that, If all are yes, then based on the distance values ​​and reflectance of other point clouds in the neighborhood of the point cloud to be determined, determine whether the point cloud to be determined is a suspected interference point, including: Within the neighborhood of the point cloud to be determined, there is a first point cloud whose absolute value of the difference between its distance value and the distance value of the point cloud to be determined is less than a third distance threshold, and a sixth point cloud whose reflectance is less than a fourth reflectance threshold; wherein the number of the first point cloud and the number of the sixth point cloud are both greater than or equal to 0. If the number of the first point cloud is greater than or equal to the second distance statistics threshold, and the ratio of the number of the sixth point cloud to the number of all point clouds in the neighborhood corresponding to the point cloud to be determined is greater than or equal to the second reflectivity statistics threshold, the point cloud to be determined is determined to be a suspected interference point.

11. The method according to claim 6, characterized in that, Before determining whether the target point cloud corresponds to a high-reflectivity object based on the distance and reflectivity of the target point cloud acquired by the target channel, and the corresponding distance and reflectivity of other point clouds in the neighborhood of the target point cloud, the process further includes: Determine the number of zero-value point clouds in the neighborhood of the target point cloud; wherein the distance value and reflectance of the zero-value point clouds are both 0; The step of determining whether the target point cloud corresponds to a high-reflectivity object based on the distance and reflectivity of the target point cloud collected by the target channel, and the distance and reflectivity of other point clouds in the neighborhood of the target point cloud, includes: Based on the distance value and reflectivity of the target point cloud collected by the target channel, the distance value and reflectivity of other point clouds in the neighborhood of the target point cloud, and the number of zero-value point clouds in the neighborhood of the target point cloud, it is determined whether the target point cloud corresponds to a high reflectivity object.

12. A device for determining interference points, characterized in that, The device includes: The first acquisition module is used to acquire the target point cloud corresponding to the high reflectivity object in the target channel; wherein, the distance between the high reflectivity object and the multi-channel lidar is greater than or equal to a first distance threshold and less than a second distance threshold, and the reflectivity of the high reflectivity object is greater than or equal to the first reflectivity threshold. The second acquisition module is used to acquire, based on the target point cloud, the point cloud to be determined at the same pixel position as the target point cloud in each channel except the target channel; The suspected interference determination module is used to determine whether each point cloud to be determined is a suspected interference point based on the distance value and reflectivity of each point cloud to be determined, as well as the distance value and reflectivity of other point clouds in the neighborhood of each point cloud to be determined. An interference determination module is used to determine whether the point cloud to be determined is an interference point, based on the variance of the distance values ​​between the point cloud to be determined and other point clouds in the neighborhood of the point cloud to be determined, or based on the range of interference points corresponding to the point cloud to be determined.

13. A computer storage medium, characterized in that, The computer storage medium stores a plurality of instructions, which are adapted to be loaded by a processor and executed as method steps as claimed in any one of claims 1 to 11.

14. A multi-channel lidar, characterized in that, include: A processor and a memory; wherein the memory stores a computer program adapted to be loaded by the processor and executed the method steps as claimed in any one of claims 1 to 11.

Images