Water accumulation detection method, computer readable storage medium and computer device

Abstract

The embodiments of the present application disclose a method for detecting water accumulation, a computer-readable storage medium, and a computer device, including: judging whether there is a point cloud image of water accumulation according to a point cloud image of a laser radar; obtaining a point cloud about water accumulation, wherein the point cloud of water accumulation includes a reflection point cloud and a virtual refraction point cloud; defining standard reflection point cloud data, standard virtual refraction point cloud data, and standard radar position information; obtaining the incident angle of a laser beam when it reaches the water accumulation interface according to the standard radar position information and the standard reflection point cloud data; obtaining the refraction angle of the laser beam in the water accumulation according to the incident angle; and obtaining the refraction angle of the laser beam in the water accumulation according to the incident angle and the refraction angle. ， The standard virtual refraction point cloud data and the standard reflection point cloud data are used to obtain the standard real refraction point cloud data; according to the mapping relationship between the current coordinate system and the first coordinate system, the point cloud data of the real refraction point cloud in the current coordinate system is obtained, thereby realizing high-precision detection of accumulated water.

Description

Technical Field

[0001] The present application relates to the field of laser radar, and in particular to a method for detecting water accumulation, a computer-readable storage medium, and a computer device. Background Art

[0002] When the vehicle is driving, when passing through a culvert / bridge tunnel, if it has rained before or is raining, there will be water accumulation easily because there are usually depressions in the culvert / bridge tunnel. In addition, there will be depressions in damaged road surfaces or soft-base roads, so it is also easy for water to accumulate (such as Figure 5 However, for image sensors, image information cannot accurately reflect the depth and coverage of the water. If the depth of the water is too deep, the vehicle may be forced to shut down / stop operating when it enters the water, affecting driving safety.

[0003] Compared with the color image of the camera, the laser radar can obtain the location information of the acquisition area, so it can form a point cloud image with location information. In theory, the laser radar can be used to obtain information such as the depth and coverage area of ​​the accumulated water. However, when the laser beam emitted by the laser radar encounters accumulated water, the laser beam will be refracted at the interface of the accumulated water. The laser radar itself is unaware of the occurrence of the refraction phenomenon, and still calculates the location information of the laser beam according to normal rectilinear propagation, resulting in incorrect location information, which affects the laser radar's detection of accumulated water. Summary of the invention

[0004] The embodiments of the present application provide a method for detecting water accumulation, a computer-readable storage medium, and a computer device, which can achieve high-precision detection of water accumulation.

[0005] In a first aspect, an embodiment of the present application provides a method for detecting water accumulation, including:

[0006] In the current coordinate system, based on the point cloud image of the laser radar, determine whether there is a point cloud image of accumulated water;

[0007] Acquire a point cloud about the accumulated water, the point cloud of the accumulated water includes a reflection point cloud and a virtual refraction point cloud, the reflection point cloud is a point cloud reflected by the laser radar when the laser beam reaches the interface of the accumulated water, and the virtual refraction point cloud is a point cloud obtained by the laser radar reflecting the laser beam according to the bottom of the accumulated water;

[0008] Define standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information, wherein the standard reflection point cloud data is point cloud data obtained by converting the reflection point cloud in the current coordinate system according to the first coordinate system; the standard virtual refraction point cloud data is point cloud data obtained by converting the virtual refraction point cloud in the current coordinate system according to the first coordinate system; the standard radar position information is position information of the laser radar in the first coordinate system; the first coordinate system is a coordinate system in which the XY axis plane is parallel to the water interface and the Z axis is perpendicular to the water interface;

[0009] The incident angle of the laser beam when it reaches the water interface is obtained based on the standard radar position information and the standard reflection point cloud data ;

[0010] According to the incident angle , and obtain the refraction angle of the laser beam in the water ;

[0011] According to the angle of incidence , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data;

[0012] According to the mapping relationship between the current coordinate system and the first coordinate system, the point cloud data of the real refraction point cloud in the current coordinate system is obtained.

[0013] Optionally, judging whether there is a point cloud image of accumulated water according to the point cloud image of the laser radar includes:

[0014] According to the point cloud data currently received by the laser radar, a point cloud image is formed;

[0015] According to the point cloud image, it is determined whether there is an area parallel to the water accumulation interface in the point cloud image, which is defined as the target area;

[0016] If there is a target area, it is determined whether the number of point clouds generated by each laser beam in the target area meets the preset conditions. If the preset conditions are met, the target area is determined to be waterlogged.

[0017] Optionally, the preset condition is that the number of point clouds generated by each laser beam is 2N, where N is determined based on a receiving module of the laser radar and is a positive integer.

[0018] Optionally, the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data, including:

[0019] According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the XYZ axis is obtained, which is defined as , and ;

[0020] According to the angle of incidence , refraction angle , , and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ;

[0021] Standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

[0022] Optionally, the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data, and obtain the Z-axis coordinate value of standard real refraction point cloud data, including:

[0023] According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained. , It is obtained by the following formula:

[0024]

[0025] In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 It is the Z-axis coordinate value of the standard reflection point cloud data;

[0026] According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis , It is obtained by the following formula:

[0027]

[0028] The Z-axis coordinate value of the standard reflection point cloud data and , get the Z-axis coordinate value of the standard real refraction point cloud data.

[0029] Optionally, the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data, obtain the X / Y axis coordinate values ​​of standard real refraction point cloud data, including:

[0030] According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the X / Y axis is obtained. , It is obtained by the following formula:

[0031] or

[0032] In the formula, X 虚 is the X-axis coordinate value of the standard virtual refraction point cloud data, X 反 is the X-axis coordinate value of the standard reflection point cloud data; Y 虚 is the Y-axis coordinate value of the standard virtual refraction point cloud data, Y 反 is the Y-axis coordinate value of the standard reflection point cloud data;

[0033] according to , and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the X / Y axis , It is obtained by the following formula:

[0034] or

[0035] X / Y axis coordinate values ​​of standard reflection point cloud data and , get the X / Y axis coordinate values ​​of the standard real refraction point cloud data.

[0036] Optionally, the first coordinate system satisfies the following conditions at the same time:

[0037] Condition 1: The XY axis plane of the first coordinate system is parallel to the water surface;

[0038] Condition 2: The Z axis of the first coordinate system is perpendicular to the water surface;

[0039] Condition 3: The projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis / Y axis;

[0040] According to the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data, including:

[0041] According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained, which is defined as ;

[0042] According to the angle of incidence , refraction angle and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ;

[0043] Standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

[0044] Optionally, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is , It is obtained by the following formula:

[0045]

[0046] In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 It is the Z-axis coordinate value of the standard reflection point cloud data.

[0047] Optionally, the incident angle , refraction angle and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ,include:

[0048] According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis , It is obtained by the following formula:

[0049] ;

[0050] If the projection of the laser beam incident on the water surface on the XY axis plane overlaps with the X axis, the Y axis coordinate value of the standard true refraction point cloud data is 0, and the It is obtained by the following formula:

[0051] ;

[0052] If the projection of the laser beam incident on the water surface on the XY axis plane overlaps with the Y axis, the X axis coordinate value of the standard true refraction point cloud data is 0, and the It is obtained by the following formula:

[0053] .

[0054] Optionally, the incident angle of the laser beam when it reaches the water interface is obtained according to the standard radar position information and the standard reflection point cloud data. ,include:

[0055] Obtain the relative distances on the XYZ axes according to the standard radar position information and the standard reflection point cloud data;

[0056] The incident angle of the laser beam when it reaches the water interface is obtained based on the relative distances on the XYZ axis. .

[0057] Optionally, the incident angle of the laser beam when it reaches the water interface is obtained according to the relative distances on the XYZ axes. ,include:

[0058]

[0059] In the formula, ; ; .

[0060] Optionally, the incident angle , and obtain the refraction angle of the laser beam in the water ,include:

[0061] Refraction Angle It is obtained by the following formula:

[0062]

[0063] In the formula, is the relative refractive index corresponding to the accumulated water.

[0064] In a second aspect, an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed on a computer, the computer executes the water accumulation detection method provided by the embodiment of the present application.

[0065] In a third aspect, an embodiment of the present application further provides a computer device, including a memory and a processor, wherein the processor is used to execute the water accumulation detection method provided in the embodiment of the present application by calling a computer program stored in the memory.

[0066] In the embodiment of the present application, the reflection point cloud and virtual refraction point cloud of the current water accumulation are obtained by the laser radar; standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information are defined; the incident angle of the laser beam when it reaches the water accumulation interface is obtained according to the standard radar position information and the standard reflection point cloud data According to the incident angle , and obtain the refraction angle of the laser beam in the water According to the incident angle , refraction angle ， The standard virtual refraction point cloud data and the standard reflection point cloud data are used to obtain the standard real refraction point cloud data, which can realize high-precision detection of accumulated water. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] The technical solution and beneficial effects of the present application will be made apparent by describing in detail the specific implementation methods of the present application in conjunction with the accompanying drawings.

[0068] Figure 1 This is the background technology schematic diagram of this application.

[0069] Figure 2 This is a schematic diagram of Example 1 of the present application.

[0070] Figure 3 This is a flow chart of Example 1 of the present application.

[0071] Figure 4 This is the schematic diagram of Example 4 of the present application.

[0072] Figure 5 This is an example diagram of the background technology of this application.

[0073] Figure 6 This is a flow chart of Example 2 of the present application. DETAILED DESCRIPTION

[0074] It should be noted that the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or modules is not limited to the listed steps or modules, but some embodiments also include steps or modules that are not listed, or some embodiments also include other steps or modules that are inherent to these processes, methods, products or devices.

[0075] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0076] For ease of understanding, the background technology is now explained in detail.

[0077] Taking TOF LiDAR as an example, the LiDAR transmits a detection signal (laser beam) to the scanning area, and then receives the signal (echo signal) reflected from the target in the scanning area. The position information of the target in the scanning area is obtained by comparing the time of the transmitted detection signal (laser beam) with the time of receiving the reflected signal (echo signal). However, when part of the scanning area is water-logged, the laser beam will be refracted in the water when it enters the water medium (water) from the air. Since the laser beam propagates in a straight line by default, the LiDAR obtains the position information of the laser beam after it propagates in a straight line based on the time difference between the transmitted signal and the received signal. However, due to the phenomenon of light refraction, the position information obtained by the LiDAR is incorrect. Figure 1 For example, the laser beam will be refracted in the water interface, and the actual location of the refracted laser beam is point B. However, according to the echo signal at point B, the location information of point A is obtained according to the principle that the laser beam propagates in a straight line. As a result, the laser radar detects water errors, which seriously affects the laser radar's recognition of water.

[0078] In order to solve the above problems, the embodiments of the present application provide a water accumulation detection method, a computer-readable storage medium and a computer device. The execution subject of the water accumulation detection method can be the laser radar provided in the embodiments of the present application, or a computer device integrated with the laser radar. Among them, the computer device can be a device such as a terminal or a server. It can be understood that the method of this embodiment can be executed on a terminal, or on a server, or jointly by a terminal and a server. The above examples should not be understood as limitations on the present application.

[0079] It should be noted that the description order of the following embodiments is not intended to limit the preferred order of the embodiments.

[0080] Example 1

[0081] See also Figure 3 , Figure 3 : is a flow chart of the water accumulation detection method provided in Example 1 of the present application, comprising the following steps:

[0082] S1: In the current coordinate system, based on the point cloud image of the LiDAR, determine whether there is a point cloud image of accumulated water.

[0083] It should be noted that the vehicle can be a motor vehicle, such as a fuel vehicle, a new energy vehicle, a forklift and other means of transportation, and this application does not limit this. The laser radar is set on the vehicle to sense the environmental information around the vehicle for the driver to make decisions or generate corresponding intelligent decision information.

[0084] In a possible implementation, S1 includes:

[0085] S11: forming a point cloud image according to the point cloud data currently received by the laser radar;

[0086] S12: judging whether there is an area parallel to the water accumulation interface in the point cloud image according to the point cloud image, and defining it as a target area;

[0087] It should be noted that for accumulated water that is refracted, the interface of the accumulated water itself will reflect. Since the emitted point clouds are all located at the interface of the accumulated water, and the interface of the accumulated water is parallel to the horizontal plane. Therefore, this feature can be used to further determine whether there is accumulated water. Analyze the received point cloud data, first determine whether there is an area parallel to the horizontal plane in the point cloud image, and if there is such an area, proceed to the next step of judgment. In addition, the current coordinate system is the coordinate system of the point cloud collected by the lidar. If the point cloud data fusion of multiple lidars is involved, the current coordinate system is the coordinate system used by multiple lidars. This application does not impose any restrictions on the selection of the current coordinate system.

[0088] S13: If there is a target area, determine whether the number of point clouds generated by each laser beam in the target area meets a preset condition. If the preset condition is met, the target area is determined to be water accumulation.

[0089] It should be noted that when the laser beam enters the accumulated water, it will be reflected at the interface of the accumulated water and refracted inside the accumulated water. Therefore, both the reflected echo signal and the refracted echo signal will be received by the laser radar. Therefore, in simple terms, for every laser radar that emits a laser beam, two echo signals will be received. Therefore, this feature can be used to further judge the area in S12.

[0090] In a possible implementation, the preset condition is that the number of point clouds generated by each laser beam is 2N, where N is determined based on a receiving module of the laser radar and is a positive integer.

[0091] It should be noted that the number of point clouds that can be generated by each echo signal is determined based on the receiving module of the laser radar. For example, if the laser radar uses only one photoelectric receiving unit (such as APD) to sense the echo signal, one echo signal will generate one point cloud. Combined with the characteristics of the refracted water, the laser radar will receive two echo signals for each laser beam emitted. At this time, each laser beam will generate 2 point clouds. However, if the laser laser radar uses four photoelectric receiving units to sense the echo signal, one echo signal will generate four point clouds. At this time, each laser beam will generate 8 point clouds. Therefore, the N value is determined by how many receiving units each echo signal in the laser radar is received, and then based on the characteristics of receiving two echo signals for each laser beam emitted, the area in S2 is further judged.

[0092] S2: Obtain point clouds about accumulated water. The point clouds of accumulated water include reflected point clouds and virtual refraction point clouds. The reflected point clouds are point clouds reflected by the laser radar when the light signal reaches the interface of accumulated water. The virtual refraction point clouds are point clouds obtained by the laser radar reflecting the light signal from the bottom of the accumulated water.

[0093] It should be noted that the current point cloud of accumulated water can basically be divided into reflection point cloud and virtual refraction point cloud. The reflection point cloud and virtual refraction point cloud can be divided according to the Z-axis value in the position information in the point cloud data. Since the reflection point clouds are all on the water interface, and the water interface is parallel to the horizontal plane. Therefore, the Z-axis values ​​in the reflection point cloud data are basically consistent. Through the above-mentioned feature, point clouds with consistent Z-axis values ​​(or differences less than a preset threshold) can be divided into reflection point clouds. In addition, since the virtual refraction point cloud must be below the water interface (such as Figure 1~Figure 2 Point A is below the water interface), so the remaining point clouds below the reflection point cloud (such as Figure 1~Figure 2 Point A is below point C) is divided into a virtual refraction point cloud.

[0094] S3: Define standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information. The standard reflection point cloud data is the point cloud data obtained by converting the reflection point cloud in the current coordinate system according to the first coordinate system; the standard virtual refraction point cloud data is the point cloud data obtained by converting the virtual refraction point cloud in the current coordinate system according to the first coordinate system; the standard radar position information is the position information of the laser radar in the first coordinate system; the first coordinate system is a coordinate system in which the XY axis plane is parallel to the water interface and the Z axis is perpendicular to the water interface.

[0095] Specifically, at this time, the position information of the reflection point cloud and the virtual refraction point cloud is obtained. However, the determination of the position information needs to be in a clear coordinate system. In order to facilitate the perception of accumulated water later, it is necessary to set up a coordinate system that is convenient for calculation (ie, the first coordinate system). The position information of the reflection point cloud and the virtual refraction point cloud is converted according to the first coordinate system. The first coordinate system is a three-axis coordinate system, which defines the XY axis plane parallel to the accumulated water interface and the Z axis perpendicular to the accumulated water interface. At this point, the position information of the reflection point cloud in the first coordinate system (standard reflection point cloud data) and the position information of the virtual reflection point cloud in the first coordinate system (ie, standard virtual refraction point cloud data) are obtained, and the depth of the accumulated water can also be directly represented by the Z-axis coordinate value in the first coordinate system.

[0096] S4: Obtain the incident angle of the light signal when it reaches the water interface based on the standard radar position information and the standard reflection point cloud data .

[0097] Specifically, the distance between the two points and the length of the three components (i.e., XYZ axis) in the first coordinate system can be obtained through the standard radar position information and the standard reflection point cloud data. The incident angle of the laser beam when it reaches the water interface can be obtained by combining the length of the three components with the inverse trigonometric function. , the incident angle is the angle between the incident laser beam and the normal of the incident water interface.

[0098] In a possible implementation, S4 includes:

[0099] S41: Obtaining respective relative differences on the XYZ axes according to the standard radar position information and the standard reflection point cloud data;

[0100] S42: The incident angle of the laser beam when it reaches the water interface is obtained based on the relative differences on the XYZ axes. .

[0101] In a possible implementation, S42 includes:

[0102] Angle of incidence Calculate using the following formula:

[0103]

[0104] In the formula, ; ; .because X 相 , Y 相 and Z 相 They all represent distance, so the absolute value is taken.

[0105] It should be noted thatX 相 , Y 相 and Z 相 That is, the length of the different components of the distance between the standard radar position information and the standard reflection point cloud data on the XYZ axis. In this embodiment, the length of the projection of the line connecting the laser radar and the reflection point on the XY plane (i.e. ). Then pass Z 相 And the inverse tangent function, the incident angle of the laser beam when it reaches the water interface is obtained In fact, in addition to using the inverse tangent function, other inverse trigonometric functions may also be used, and this application does not impose any limitation on this.

[0106] S5: According to the angle of incidence , and obtain the refraction angle of the laser beam in the water ; The refraction angle is the angle between the refracted laser beam and the normal of the water interface.

[0107] In one possible implementation, the refraction angle Calculate using the following formula:

[0108]

[0109] In the formula, is the relative refractive index corresponding to the accumulated water.

[0110] It is understandable that for LiDAR, a laser beam is generally fired in the air and then may pass through standing water. The value of is the ratio of the refractive index of the water on the refractive side to the refractive index of the medium layer (such as air) on the incident side.

[0111] In one possible implementation, The value range is [1.2,1.5].

[0112] In one possible implementation, The value is 1.333.

[0113] S6: According to the angle of incidence , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data.

[0114] In a possible implementation, S6 includes:

[0115] S61: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the XYZ axis is obtained, which is defined as , and ;

[0116] S62: According to the angle of incidence , refraction angle , , and ; Get the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis, defined as , and ;

[0117] S63: Standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

[0118] Specifically, the three axes XYZ are used as examples for explanation.

[0119] Taking the Z axis as an example, S6 includes the following steps:

[0120] S61: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained. ;

[0121] Obtained by the following formula:

[0122]

[0123] In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 is the Z-axis coordinate value of the standard reflection point cloud data. It represents distance, so it takes the absolute value.

[0124] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis ;

[0125] Obtained by the following formula:

[0126]

[0127] It should be noted that Figure 2 For example, the incident angle α =∠ACE. Therefore, the distance between the reflection point cloud and the virtual refraction point cloud (i.e. CA) can be obtained by Calculated. Since there is an implicit constraint that CA=CB, (CE) can be passed Calculated.

[0128] S63: Z-axis coordinate value of standard reflection point cloud data and , get the Z-axis coordinate value of the standard real refraction point cloud data.

[0129] Taking the X axis as an example, S6 includes the following steps:

[0130] S61: Obtain the distance value on the X axis between the standard virtual refraction point cloud and the standard reflection point cloud according to the standard virtual refraction point cloud data and the standard reflection point cloud data ;

[0131] Obtained by the following formula:

[0132]

[0133] In the formula, X 虚 is the X-axis coordinate value of the standard virtual refraction point cloud data, X 反 is the X-axis coordinate value of the standard reflection point cloud data. It represents distance, so it takes the absolute value.

[0134] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the X axis ;

[0135] Obtained by the following formula:

[0136]

[0137] It should be noted that Figure 2 For example, for the X axis, Figure 2 is the projection of the laser beam transmission process on the XZ plane (i.e. Figure 2In this case, since the position information of the virtual refraction point cloud is obtained based on the data of the real refraction point cloud, the time when the reflection point reaches the virtual refraction point cloud is the same as the time when the reflection point reaches the real refraction point cloud. Further deduction shows that the projections of the two on the XZ plane are also equal, that is, there is an implicit constraint condition of CA=CB, so (ie BE) can be achieved through In addition, since the current calculation is based on the projection on the XZ plane, the projection on the XZ plane does not necessarily mean that ∠ACE is , ∠BCE is not necessarily Therefore, it is impossible to directly calculate it through trigonometric functions. , can only be calculated based on the implicit constraint condition CA=CB .

[0138] S63: The value and value of the standard reflection point cloud data on the X axis , get the value of the standard true refraction point cloud data on the X-axis.

[0139] Taking the Y axis as an example, S6 includes the following steps:

[0140] S61: Obtain the distance value on the Y axis between the standard virtual refraction point cloud and the standard reflection point cloud according to the standard virtual refraction point cloud data and the standard reflection point cloud data ;

[0141] Obtained by the following formula:

[0142]

[0143] In the formula, Y 虚 is the Y-axis coordinate value of the standard virtual refraction point cloud data, Y 反 is the Y-axis coordinate value of the standard reflection point cloud data. It represents distance, so it takes the absolute value.

[0144] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Y axis ;

[0145] Obtained by the following formula:

[0146]

[0147] It should be noted that Figure 2 For example, for the Y axis, Figure 2 is the projection of the laser beam transmission process on the YZ plane (i.e. Figure 2 In this case, since the position information of the virtual refraction point cloud is obtained based on the data of the real refraction point cloud, the time when the reflection point reaches the virtual refraction point cloud is the same as the time when the reflection point reaches the real refraction point cloud. Therefore, the projections of the two on the YZ plane are also equal, that is, there is an implicit constraint condition of CA=CB, so (ie BE) can be achieved through In addition, since the current calculation is based on the projection on the YZ plane, the projection on the YZ plane does not necessarily mean that ∠ACE is , ∠BCE is not necessarily Therefore, it is impossible to directly calculate it through trigonometric functions. , can only be calculated based on the implicit constraint condition CA=CB .

[0148] S63: The value and value of the standard reflection point cloud data on the Y axis , get the value of the standard true refraction point cloud data on the Y axis.

[0149] S7: Obtaining point cloud data of the real refraction point cloud in the current coordinate system according to the mapping relationship between the current coordinate system and the first coordinate system.

[0150] It should be noted that since the mapping relationship between the current coordinate system and the first coordinate system is clear, both the reflection point cloud and the real refraction point cloud are real existing position points. It is just that different position information is obtained based on different coordinate systems. Therefore, based on the mapping relationship between the current coordinate system and the first coordinate system, the position information of the real refraction point cloud in the first coordinate system can be converted into the position information of the real refraction point cloud in the current coordinate system.

[0151] In a possible implementation manner, the water accumulation detection method further includes the following steps after S7:

[0152] S8: Construct a point cloud image of accumulated water based on the point cloud data of the real refraction point cloud in the current coordinate system.

[0153] It should be noted that since the reflection point cloud will not change due to the presence of water accumulation, after obtaining the point cloud data of the real refraction point cloud in the current coordinate system, combined with the point cloud data of the reflection point cloud in the current coordinate system, a three-dimensional point cloud image of the water accumulation can be obtained, thereby obtaining the scope of the water accumulation, the area covered, the location, the depth and other water accumulation information. The above water accumulation information is used by the driver to make decisions or generate corresponding intelligent decision information.

[0154] In a possible implementation manner, the water accumulation detection method further includes the following steps before S1:

[0155] S0: Determine whether the vehicle's current pitch angle exceeds expectations. If so, execute S1.

[0156] It should be noted that if the vehicle passes through a culvert or a bridge tunnel, there is usually a slowly descending slope between the depression and the vehicle. Therefore, the pitch angle of the vehicle can be measured to determine whether it is traveling on a slowly descending slope. If the vehicle is traveling on a slowly descending slope, there is a greater probability that there is water accumulation ahead (rainwater / sewage gathers into water at the lowest point).

[0157] In this embodiment 1, the reflection point cloud and virtual refraction point cloud of the current water accumulation are obtained by the laser radar; standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information are defined; the incident angle of the laser beam when it reaches the water accumulation interface is obtained according to the standard radar position information and the standard reflection point cloud data According to the incident angle , and obtain the refraction angle of the laser beam in the water According to the incident angle , refraction angle ， The standard virtual refraction point cloud data and the standard reflection point cloud data are used to obtain the standard real refraction point cloud data, which can realize high-precision detection of accumulated water.

[0158] Example 2

[0159] Embodiment 2 optimizes the technical solution provided in Embodiment 1 of the present application from the perspective of specific application. For the definitions of terms in Embodiment 2, unless otherwise specified, refer to Embodiment 1. For the detailed contents, technical effects, technical problems solved, and other related information of each step in Embodiment 2, refer to Embodiment 1 unless otherwise specified. Without violating the design purpose and physical laws, some optional items or preferred items in Embodiment 1 are applicable to Embodiment 2.

[0160] See also Figure 6 , Figure 6 : is a flow chart of the water accumulation detection method provided in Example 2 of the present application, comprising the following steps:

[0161] S1: In the current coordinate system, based on the point cloud image of the LiDAR, determine whether there is a point cloud image of accumulated water.

[0162] S2: Obtain point clouds about accumulated water. The point clouds of accumulated water include reflected point clouds and virtual refraction point clouds. The reflected point clouds are point clouds reflected by the laser radar when the light signal reaches the interface of accumulated water. The virtual refraction point clouds are point clouds obtained by the laser radar reflecting the light signal from the bottom of the accumulated water.

[0163] S3: Define standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information. Standard reflection point cloud data is the point cloud data obtained by transforming the reflection point cloud in the current coordinate system according to the second coordinate system; standard virtual refraction point cloud data is the point cloud data obtained by transforming the virtual refraction point cloud in the current coordinate system according to the second coordinate system; standard radar position information is the position information of the laser radar in the second coordinate system; the second coordinate system needs to meet the following conditions at the same time:

[0164] Condition 1: The XY axis plane is parallel to the water surface;

[0165] Condition 2: The projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis / Y axis;

[0166] Condition 3: The coordinate system with the Z axis perpendicular to the water surface.

[0167] Specifically, the second coordinate system is a three-axis coordinate system, which defines the XY axis plane to be parallel to the water interface, the Z axis to be perpendicular to the water interface, and the projection of the laser beam incident on the water interface on the XY axis plane to overlap with the X axis / Y axis. For example, the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis. At this time, the laser beam incident on the water interface, the laser beam reflected by the water interface, the line between the reflection point cloud and the virtual refraction point cloud, and the line between the reflection point cloud and the real refraction point cloud will all be located in the XZ axis plane. Therefore, the Y axis coordinate in the position information of the laser radar, the reflection point cloud, the virtual refraction point cloud, and the real refraction point cloud is 0. For another example, the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the Y axis. At this time, the laser beam incident on the water interface, the laser beam reflected by the water interface, the line between the reflection point cloud and the virtual refraction point cloud, and the line between the reflection point cloud and the real refraction point cloud will all be located in the YZ axis plane. Therefore, the X-axis coordinates in the position information of the laser radar, reflection point cloud, virtual refraction point cloud, and real refraction point cloud are all 0. The above settings will simplify the subsequent formula calculations. At this time, the position information of the reflection point cloud in the second coordinate system (standard reflection point cloud data) and the position information of the virtual reflection point cloud in the second coordinate system (i.e. standard virtual refraction point cloud data) are obtained.

[0168] S4: Obtain the incident angle of the light signal when it reaches the water interface based on the standard radar position information and the standard reflection point cloud data .

[0169] Specifically, the distance between the two points and the length of the three components (i.e., XYZ axis) in the second coordinate system can be obtained through the standard radar position information and the standard reflection point cloud data. The incident angle of the laser beam when it reaches the water interface can be obtained by combining the length of the three components with the inverse trigonometric function. , the incident angle is the angle between the incident laser beam and the normal of the incident water interface.

[0170] In a possible implementation, S5 includes:

[0171] S41: Obtaining respective relative differences on the XYZ axes according to the standard radar position information and the standard reflection point cloud data;

[0172] S42: The incident angle of the laser beam when it reaches the water interface is obtained based on the relative differences on the XYZ axes. .

[0173] In a possible implementation, S42 includes:

[0174] If the projection of the laser beam incident on the water surface on the XY plane overlaps with the X axis, the incident angle Calculate using the following formula:

[0175]

[0176] If the projection of the laser beam incident on the water surface on the XY axis plane overlaps with the Y axis, the incident angle Calculate using the following formula:

[0177]

[0178] In the formula, ; ; .because X 相 , Y 相 and Z 相 They all represent distance, so the absolute value is taken.

[0179] It should be noted that X 相 , Y 相 and Z 相 That is, the length of the different components of the distance between the standard radar position information and the standard reflection point cloud data on the XYZ axis. In this embodiment, the length of the projection of the line connecting the laser radar and the reflection point on the XY plane (i.e. X 相 / Y相 ). Then pass Z 相 And the inverse tangent function, the incident angle of the laser beam when it reaches the water interface is obtained In fact, in addition to using the inverse tangent function, other inverse trigonometric functions may also be used, and this application does not impose any limitation on this.

[0180] S5: According to the angle of incidence , and obtain the refraction angle of the laser beam in the water ; The refraction angle is the angle between the refracted laser beam and the normal of the water interface.

[0181] In one possible implementation, the refraction angle β Calculate using the following formula:

[0182]

[0183] In the formula, is the relative refractive index corresponding to the accumulated water.

[0184] S6: According to the angle of incidence , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data.

[0185] In a possible implementation, S6 includes:

[0186] S61: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained, which is defined as ;

[0187] S62: According to the angle of incidence , refraction angle and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ;

[0188] S63: Standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

[0189] Specifically, the three axes XYZ are used as examples to illustrate the situation where the projection of the laser beam incident on the water accumulation interface on the XY axis plane overlaps with the X / Y axis.

[0190] Taking the Z axis as an example, S6 includes the following steps:

[0191] S61: Obtain the distance value of the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis according to the standard virtual refraction point cloud data and the standard reflection point cloud data ;

[0192] Obtained by the following formula:

[0193]

[0194] In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 is the Z-axis coordinate value of the standard reflection point cloud data. It represents distance, so it takes the absolute value.

[0195] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis ;

[0196] Obtained by the following formula:

[0197]

[0198] It should be noted that Figure 2 For example, the incident angle α =∠ACE. Therefore, the distance between the reflection point cloud and the virtual refraction point cloud (i.e. CA) can be obtained by Calculated. Since there is an implicit constraint that CA=CB, (CE) can be passed Calculated.

[0199] S63: Z-axis coordinate value of standard reflection point cloud data and , get the Z-axis coordinate value of the standard real refraction point cloud data.

[0200] It should be noted that no matter whether the projection of the laser beam incident on the water accumulation interface on the XY axis plane overlaps with the X axis, or the projection of the laser beam incident on the water accumulation interface on the XY axis plane overlaps with the Y axis, the coordinate value of the Z axis does not change. Therefore, no matter whether the projection of the laser beam incident on the water accumulation interface on the XY axis plane overlaps with the X axis, or the projection of the laser beam incident on the water accumulation interface on the XY axis plane overlaps with the Y axis, the Z axis coordinate value of the above standard real refraction point cloud data does not change.

[0201] Taking the X axis as an example, the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis, and S6 includes the following steps:

[0202] S61: Obtain the distance value on the X axis between the standard virtual refraction point cloud and the standard reflection point cloud according to the standard virtual refraction point cloud data and the standard reflection point cloud data ;

[0203] Obtained by the following formula:

[0204]

[0205] In the formula, X 虚 is the X-axis coordinate value of the standard virtual refraction point cloud data, X 反 It is the X-axis coordinate value of the standard reflection point cloud data.

[0206] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the X axis ;

[0207] Obtained by the following formula:

[0208] or

[0209] It should be noted that Figure 2 For example, for the X axis, Figure 2 is the projection of the laser beam transmission process on the XZ plane (i.e. Figure 2 In this case, since the position information of the virtual refraction point cloud is obtained based on the data of the real refraction point cloud, the time when the reflection point reaches the virtual refraction point cloud is the same as the time when the reflection point reaches the real refraction point cloud. Further deduction shows that the projections of the two on the XZ plane are also equal, that is, there is an implicit constraint condition of CA=CB, so (ie BE) can be achieved through In addition, since the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis in the second coordinate system, ∠ACE must be , ∠BCE must be , which can be directly calculated by trigonometric functions This application discusses how to select trigonometric functions to obtain No constraints.

[0210] S63: The value and value of the standard reflection point cloud data on the X axis , get the value of the standard true refraction point cloud data on the X-axis.

[0211] It should be noted that if the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the Y axis, the X axis coordinate value of any point on the YZ axis plane is 0. Therefore, the value of the standard true refraction point cloud data on the X axis does not need to be calculated and is directly assigned to 0.

[0212] Taking the Y axis as an example, the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the Y axis, and S6 includes the following steps:

[0213] S61: Obtain the distance value on the Y axis between the standard virtual refraction point cloud and the standard reflection point cloud according to the standard virtual refraction point cloud data and the standard reflection point cloud data ;

[0214] Obtained by the following formula:

[0215]

[0216] In the formula, Y 虚 is the Y-axis coordinate value of the standard virtual refraction point cloud data, Y 反 It is the Y-axis coordinate value of the standard reflection point cloud data.

[0217] S62: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Y axis ;

[0218] Obtained by the following formula:

[0219] or

[0220] It should be noted that Figure 2 For example, for the Y axis, Figure 2 is the projection of the laser beam transmission process on the YZ plane (i.e. Figure 2 In this case, since the position information of the virtual refraction point cloud is obtained based on the data of the real refraction point cloud, the time when the reflection point reaches the virtual refraction point cloud is the same as the time when the reflection point reaches the real refraction point cloud. Therefore, the projections of the two on the YZ plane are also equal, that is, there is an implicit constraint condition of CA=CB, so (ie BE) can be achieved through In addition, since the projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis in the second coordinate system, ∠ACE must be , ∠BCE must be , which can be directly calculated by trigonometric functions This application discusses how to select trigonometric functions to obtain No constraints.

[0221] S63: The value and value of the standard reflection point cloud data on the Y axis , get the value of the standard true refraction point cloud data on the Y axis.

[0222] It should be noted that if the projection of the laser beam hitting the water interface on the XY axis plane overlaps with the Y axis, the X axis coordinate value of any point on the YZ axis plane is 0. Therefore, the value of the standard true refraction point cloud data on the X axis does not need to be calculated and is directly assigned to 0.

[0223] S7: According to the mapping relationship between the current coordinate system and the second coordinate system, point cloud data of the real refraction point cloud in the current coordinate system is obtained.

[0224] It should be noted that since the mapping relationship between the current coordinate system and the second coordinate system is clear, both the reflection point cloud and the real refraction point cloud are real existing position points. It is just that different position information is obtained based on different coordinate systems. Therefore, based on the mapping relationship between the current coordinate system and the second coordinate system, the position information of the real refraction point cloud in the second coordinate system can be converted into the position information of the real refraction point cloud in the current coordinate system.

[0225] In a possible implementation manner, the water accumulation detection method further includes the following steps after S7:

[0226] S8: Construct a point cloud image of accumulated water based on the point cloud data of the real refraction point cloud in the current coordinate system.

[0227] It should be noted that since the reflection point cloud will not change due to the presence of water accumulation, after obtaining the point cloud data of the real refraction point cloud in the current coordinate system, combined with the point cloud data of the reflection point cloud in the current coordinate system, a three-dimensional point cloud image of the water accumulation can be obtained, thereby obtaining the scope of the water accumulation, the area covered, the location, the depth and other water accumulation information. The above water accumulation information is used by the driver to make decisions or generate corresponding intelligent decision information.

[0228] In a possible implementation manner, the water accumulation detection method further includes the following steps before S1:

[0229] S0: Determine whether the vehicle's current pitch angle exceeds expectations. If so, execute S1.

[0230] It should be noted that if the vehicle passes through a culvert or a bridge tunnel, there is usually a slowly descending slope between the depression and the vehicle. Therefore, the pitch angle of the vehicle can be measured to determine whether it is traveling on a slowly descending slope. If the vehicle is traveling on a slowly descending slope, there is a greater probability that there is water accumulation ahead (rainwater / sewage gathers into water at the lowest point).

[0231] Compared with Example 1, Example 2 achieves the following beneficial effects by setting the second coordinate system:

[0232] The first aspect simplifies and The calculation formula of

[0233] The second aspect avoids the need to calculate in advance in Example 1 To calculate and The constraint is obtained in the calculation When , and Calculations can even be performed in parallel , and Perform calculations;

[0234] On the third aspect, no matter which axis of the X / Y axis is selected to overlap with the projection of the laser beam incident on the water interface on the XY axis plane, the coordinate value of the other axis is 0 (because the virtual refraction point cloud, the real refraction point cloud, the reflection point cloud and the laser radar are all on the XZ axis plane, and the Y axis of any point on the XZ axis plane is 0). Therefore, it is only necessary to calculate the coordinate value of one of the X / Y axes (based on the selection of the second coordinate system) and the coordinate value of the Z axis of the real refraction point cloud (that is, only the coordinate values ​​of the two axes need to be calculated), without the need to calculate the coordinate values ​​of the three axes of XYZ as in Example 1.

[0235] Example 3

[0236] Embodiment 3 provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed on a computer, the computer executes the water accumulation detection method provided in this embodiment.

[0237] Example 4

[0238] Embodiment 4 also provides a computer device, including a memory and a processor, wherein the processor is used to execute the water accumulation detection method provided in this embodiment by calling a computer program stored in the memory.

[0239] In addition, the computer device may be a terminal or a server, such as Figure 4 As shown, it shows a schematic diagram of the structure of the computer device involved in the embodiment of the present application, specifically:

[0240] The computer device may include components such as a processor 401 with one or more processing cores, a memory 402 with one or more storage media, a power supply 403, and an input unit 404. Those skilled in the art will appreciate that Figure 4 The computer device structure shown in the figure does not constitute a limitation on the computer device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently. Among them:

[0241] The processor 401 is the control center of the computer device. It uses various interfaces and lines to connect various parts of the entire computer device. By running or executing software programs and / or modules stored in the memory 402 and calling data stored in the memory 402, it executes various functions of the computer device and processes data, thereby controlling the computer device as a whole. Optionally, the processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 401.

[0242] The memory 402 can be used to store software programs and modules. The processor 401 executes various functional applications and data processing by running the software programs and modules stored in the memory 402. The memory 402 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 402 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 402 may also include a memory controller to provide the processor 401 with access to the memory 402.

[0243] The computer device also includes a power supply 403 for supplying power to various components. Preferably, the power supply 403 can be logically connected to the processor 401 through a power management system, so as to manage charging, discharging, and power consumption through the power management system. The power supply 403 can also include any components such as one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, and power status indicators.

[0244] The computer device may further include an input unit 404, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0245] Although not shown, the computer device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 401 in the computer device will load the executable files corresponding to the processes of one or more application programs into the memory 402 according to the following instructions, and the processor 401 will run the application programs stored in the memory 402 to implement various functions, and the application programs include at least one of the following:

[0246] A computer program that implements the functions of Example 1;

[0247] A computer program that implements the functions of Example 2;

[0248] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0249] Since the instructions stored in the storage medium can execute any step provided in Example 1 or Example 2, the beneficial effects that can be achieved in Example 1 or Example 2 can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0250] According to one aspect of the present application, a computer program product or a computer program is provided, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the method provided in the above-mentioned invention content and embodiments.

[0251] In the above embodiments, the description of each embodiment has its own emphasis. For the part that is not described in detail in a certain embodiment, please refer to the detailed description of the method above, and will not be repeated here.

[0252] The execution order of each step in the above embodiment is only an example and is not intended to limit the present application. The steps may also be executed in other execution orders and are not specifically limited here.

[0253] The device provided in the embodiments of the present application belongs to the same concept as the method in the above embodiments. Any method provided in the above embodiments can be run on the device. The specific implementation process is detailed in Example 1 or Example 2, which will not be repeated here.

[0254] The above is a detailed introduction to the water accumulation detection method, storage medium and computer equipment provided in the embodiments of the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. Water accumulation detection method, It is characterized in that Laser mines are set up on the vehicle, including: In the current coordinate system, based on the point cloud image of the laser radar, determine whether there is a point cloud image of accumulated water; Acquire a point cloud about the accumulated water, the point cloud of the accumulated water includes a reflection point cloud and a virtual refraction point cloud, the reflection point cloud is a point cloud reflected by the laser radar when the laser beam reaches the interface of the accumulated water, and the virtual refraction point cloud is a point cloud obtained by the laser radar reflecting the laser beam according to the bottom of the accumulated water; Define standard reflection point cloud data, standard virtual refraction point cloud data and standard radar position information, wherein the standard reflection point cloud data is point cloud data obtained by converting the reflection point cloud in the current coordinate system according to the first coordinate system; the standard virtual refraction point cloud data is point cloud data obtained by converting the virtual refraction point cloud in the current coordinate system according to the first coordinate system; the standard radar position information is position information of the laser radar in the first coordinate system; the first coordinate system is a coordinate system in which the XY axis plane is parallel to the water interface and the Z axis is perpendicular to the water interface; The incident angle of the laser beam when it reaches the water interface is obtained based on the standard radar position information and the standard reflection point cloud data ; According to the incident angle , and obtain the refraction angle of the laser beam in the water ; According to the angle of incidence , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data; According to the mapping relationship between the current coordinate system and the first coordinate system, the point cloud data of the real refraction point cloud in the current coordinate system is obtained.

2. The method for detecting water accumulation according to claim 1, It is characterized in that Based on the point cloud image of the laser radar, determine whether there is a point cloud image of water accumulation, including: According to the point cloud data currently received by the laser radar, a point cloud image is formed; According to the point cloud image, it is determined whether there is an area parallel to the water accumulation interface in the point cloud image, which is defined as the target area; If there is a target area, it is determined whether the number of point clouds generated by each laser beam in the target area meets the preset conditions. If the preset conditions are met, the target area is determined to be waterlogged.

3. The method for detecting water accumulation according to claim 2, It is characterized in that The preset condition is that the number of point clouds generated by each laser beam is 2N, where N is determined based on the receiving module of the laser radar and is a positive integer.

4. The method for detecting water accumulation according to any one of claims 1 to 3, It is characterized in that According to the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data, including: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the XYZ axis is obtained, which is defined as , and ; According to the angle of incidence , refraction angle , , and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ; According to the standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

5. The method for detecting water accumulation according to claim 4, It is characterized in that According to the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data, and obtain the Z-axis coordinate value of standard real refraction point cloud data, including: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained. , It is obtained by the following formula: ； In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 It is the Z-axis coordinate value of the standard reflection point cloud data; According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis , It is obtained by the following formula: ； According to the Z-axis coordinate value of the standard reflection point cloud data and , get the Z-axis coordinate value of the standard real refraction point cloud data.

6. The method for detecting water accumulation according to claim 5, It is characterized in that According to the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data, obtain the X / Y axis coordinate values ​​of standard real refraction point cloud data, including: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the X / Y axis is obtained. , It is obtained by the following formula: or ; In the formula, X 虚 is the X-axis coordinate value of the standard virtual refraction point cloud data, X 反 is the X-axis coordinate value of the standard reflection point cloud data; Y 虚 is the Y-axis coordinate value of the standard virtual refraction point cloud data, Y 反 is the Y-axis coordinate value of the standard reflection point cloud data; according to , and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the X / Y axis , It is obtained by the following formula: or ; According to the X / Y axis coordinate values ​​of the standard reflection point cloud data and , get the X / Y axis coordinate values ​​of the standard real refraction point cloud data.

7. The method for detecting water accumulation according to any one of claims 1 to 3, It is characterized in that The first coordinate system satisfies the following conditions at the same time: Condition 1: The XY axis plane of the first coordinate system is parallel to the water surface; Condition 2: The Z axis of the first coordinate system is perpendicular to the water surface; Condition 3: The projection of the laser beam incident on the water interface on the XY axis plane overlaps with the X axis / Y axis; According to the incident angle , refraction angle ， Standard virtual refraction point cloud data and standard reflection point cloud data are used to obtain standard real refraction point cloud data, including: According to the standard virtual refraction point cloud data and the standard reflection point cloud data, the distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis is obtained, which is defined as ; According to the angle of incidence , refraction angle and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ; According to the standard reflection point cloud data, , and , and obtain the standard true refraction point cloud data.

8. The method for detecting water accumulation according to claim 7, It is characterized in that The distance value between the standard virtual refraction point cloud and the standard reflection point cloud on the Z axis , It is obtained by the following formula: ； In the formula, Z 虚 is the Z-axis coordinate value of the standard virtual refraction point cloud data, Z 反 It is the Z-axis coordinate value of the standard reflection point cloud data.

9. The method for detecting water accumulation according to claim 8, It is characterized in that According to the incident angle , refraction angle and , the change values ​​of the standard true refraction point cloud and the standard reflection point cloud on the XYZ axis are obtained, which is defined as , and ,include: According to the angle of incidence , refraction angle and , get the change value of the standard true refraction point cloud and the standard reflection point cloud on the Z axis , It is obtained by the following formula: ； If the projection of the laser beam incident on the water surface on the XY axis plane overlaps with the X axis, the Y axis coordinate value of the standard true refraction point cloud data is 0, and the It is obtained by the following formula: ； If the projection of the laser beam incident on the water surface on the XY axis plane overlaps with the Y axis, the X axis coordinate value of the standard true refraction point cloud data is 0, and the It is obtained by the following formula: 。 10. The method for detecting water accumulation according to claim 1, 2, 3, 5, 6, 8 or 9, It is characterized in that The incident angle when the laser beam reaches the water interface is obtained according to the standard radar position information and the standard reflection point cloud data ,include: Obtain the relative distances on the XYZ axes according to the standard radar position information and the standard reflection point cloud data; The incident angle of the laser beam when it reaches the water interface is obtained based on the relative distances on the XYZ axis. .

11. The method for detecting water accumulation according to claim 10, It is characterized in that The incident angle of the laser beam when it reaches the water interface is obtained according to the relative distances on the XYZ axes. ,include: ； In the formula, ; ; .

12. The method for detecting water accumulation according to claim 1, 2, 3, 5, 6, 8, 9 or 11, It is characterized in that The incident angle , and obtain the refraction angle of the laser beam in the water ,include: Refraction Angle β It is obtained by the following formula: ； In the formula, is the relative refractive index corresponding to the accumulated water.

13. Computer readable storage medium, It is characterized in that The storage medium stores a computer program, and when the computer program is executed on a computer, the computer executes the water accumulation detection method according to any one of claims 1 to 12.

14. Computer equipment, It is characterized in that The computer device includes a processor and a memory, wherein a computer program is stored in the memory, and the processor is used to execute the water accumulation detection method according to any one of claims 1 to 12 by calling the computer program stored in the memory.

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