WO2023279225A1

WO2023279225A1 - Point cloud processing method and apparatus for laser radar, and storage medium and terminal device

Info

Publication number: WO2023279225A1
Application number: PCT/CN2021/104432
Authority: WO
Inventors: 皮兴俊
Original assignee: 深圳市速腾聚创科技有限公司
Priority date: 2021-07-05
Filing date: 2021-07-05
Publication date: 2023-01-12
Also published as: CN117616307A

Abstract

Disclosed in the present application are a point cloud processing method and apparatus for a laser radar, and a computer-readable storage medium and a terminal device. The point cloud processing method for a laser radar comprises: acquiring point cloud data which is collected by a laser radar, wherein each scanning point in the point cloud data comprises a distance measurement value and a reflectivity measurement value; according to distance measurement values and reflectivity measurement values of a target scanning point and an adjacent point, determining whether the target scanning point is an expansion point; and if the target scanning point is an expansion point, removing the target scanning point from the point cloud data. By means of the present application, the occurrence of the phenomenon of high reflectivity expansion is prevented, thereby ensuring the accuracy of laser radar recognition.

Description

Laser radar point cloud processing method, device, storage medium and terminal equipment

technical field

The present application relates to the technical field of laser sensing, and in particular to a laser radar point cloud processing method, device, computer-readable storage medium and terminal equipment.

Background technique

With the development of science and technology, the cost of lidar R&D and manufacturing is getting lower and lower, and the penetration rate is getting higher and higher. There are more and more lidars mounted on vehicles to assist in automatic driving. There are generally many traffic signs on the road, indicating the intersection direction, road name, speed limit size, warning information, etc. These traffic signs are generally of the high-reflection type, that is, they have a high reflectivity, which is convenient for lidar to identify . However, in practical applications, the phenomenon of high anti-expansion often occurs, that is, a circle of point clouds with low reflectivity will be attached around the high-inversion card, resulting in misjudgment of perception.

technical problem

One of the purposes of the embodiments of the present application is to provide a laser radar point cloud processing method, device, computer-readable storage medium, and terminal equipment, aiming to solve the high anti-expansion phenomenon that occurs when the laser radar recognizes high-reflective cards.

technical solution

The first aspect of the embodiments of the present application provides a point cloud processing method for lidar, which may include:

Obtain the point cloud data collected by the laser radar; each scan point in the point cloud data includes a distance measurement value and a reflectivity measurement value;

Judging whether the target scanning point is an expansion point according to the distance measurement value and the reflectance measurement value between the target scanning point and the adjacent point; the target scanning point is any scanning point in the point cloud data; the adjacent The point is a scanning point whose distance from the target scanning point in the horizontal direction and in the vertical direction is smaller than a preset threshold;

If the target scan point is an expansion point, then remove the target scan point from the point cloud data.

In a specific implementation of the first aspect, the judging whether the target scanning point is an expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and adjacent points may include:

Judging whether the target scanning point is a horizontal expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and the horizontal adjacent point; the horizontal adjacent point is on the same horizontal line as the target scanning point adjacent points;

According to the distance measurement value and the reflectance measurement value of the target scanning point and the vertical adjacent point, it is judged whether the target scanning point is a vertical expansion point; the vertical adjacent point is at the same location as the target scanning point Adjacent points on a vertical line;

If the target scanning point is a horizontal expansion point or a vertical expansion point, then determine that the target scanning point is an expansion point.

In a specific implementation of the first aspect, the judging whether the target scanning point is a horizontal expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and horizontal adjacent points may include:

Calculate the distance difference on the left side and the distance difference on the right side respectively according to the distance measurement value between the target scanning point and the horizontal adjacent point;

Judging whether the left distance difference, the right distance difference, the middle reflectance value and the right reflectance value meet a preset first condition or whether the left distance difference, the right distance difference, the left Whether the reflectance value and the middle reflectance value meet the preset second condition; the left reflectance value is the reflectance value of the leftmost horizontal adjacent point, and the middle reflectance value is set The reflectance measurement value of the target scanning point, the reflectance value on the right side is the reflectance value of the rightmost horizontal adjacent point;

If the first condition or the second condition is met, it is determined that the target scanning point is a horizontal expansion point.

In a specific implementation of the first aspect, the calculating the distance difference on the left side and the distance difference on the right side respectively according to the measured distance values between the target scanning point and the horizontal adjacent point may include:

respectively calculating the first absolute value of the difference between the distance measurement values of the leftmost several horizontal adjacent points and the distance measurement value of the target scanning point;

determining the first absolute value with the largest value as the left distance difference;

Respectively calculating the second absolute value of the difference between the distance measurement values of the rightmost several horizontal adjacent points and the distance measurement value of the target scanning point;

The second absolute value with the largest value is determined as the right distance difference.

In a specific implementation of the first aspect, the first condition may be the intersection of the following conditions:

The left distance difference is greater than or equal to a preset distance upper limit threshold;

The right distance difference is less than or equal to a preset distance lower limit threshold;

The intermediate reflectivity value is less than or equal to a preset reflectivity lower limit threshold;

The right reflectivity value is greater than or equal to a preset reflectivity upper threshold.

In a specific implementation of the first aspect, the second condition may be the intersection of the following conditions:

The right distance difference is greater than or equal to a preset distance upper limit threshold;

The left distance difference is less than or equal to a preset distance lower limit threshold;

The left reflectivity value is greater than or equal to a preset reflectivity upper threshold.

In a specific implementation of the first aspect, the judging whether the target scanning point is a vertical expansion point according to the distance measurement value and the reflectance measurement value between the target scanning point and a vertical adjacent point may include:

calculating the upper side distance difference and the lower side distance difference respectively according to the distance measurement values between the target scanning point and the vertical adjacent point;

judging whether the upper distance difference, the lower distance difference, the middle reflectance value, and the lower reflectance value meet a preset third condition or whether the upper distance difference, the lower distance difference, the upper Whether the reflectance value and the intermediate reflectance value meet the preset fourth condition; the upper side reflectance value is the reflectance value of the uppermost vertically adjacent point, and the intermediate reflectance value is set The reflectance measurement value of the target scanning point, the reflectance value of the lower side is the reflectance value of the vertical adjacent point on the lowermost side;

If the third condition or the fourth condition is met, it is determined that the target scanning point is a vertical expansion point.

In a specific implementation of the first aspect, the calculating the upper side distance difference and the lower side distance difference respectively according to the distance measurement values between the target scanning point and the vertical adjacent point may include:

Calculating the third absolute value of the difference between the distance measurement values of the several vertical adjacent points on the uppermost side and the distance measurement values of the target scanning point respectively;

determining the third absolute value with the largest value as the upper distance difference;

Calculating the fourth absolute value of the difference between the measured distance values of several vertical adjacent points on the lowermost side and the measured distance values of the target scanning point;

The fourth absolute value with the largest value is determined as the lower distance difference.

In a specific implementation of the first aspect, the third condition may be the intersection of the following conditions:

The upper distance difference is greater than or equal to a preset distance upper limit threshold;

The lower distance difference is less than or equal to a preset distance lower limit threshold;

The lower side reflectance value is greater than or equal to a preset upper reflectance threshold.

In a specific implementation of the first aspect, the fourth condition may be the intersection of the following conditions:

The lower distance difference is greater than or equal to a preset distance upper threshold;

The upper distance difference is less than or equal to a preset distance lower limit threshold;

The upper side reflectivity value is greater than or equal to a preset upper reflectivity threshold.

The second aspect of the embodiments of the present application provides a laser radar point cloud processing device, which may include a functional module that implements the steps of any one of the above laser radar point cloud processing methods.

The third aspect of the embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the point cloud processing of any one of the above-mentioned laser radars is realized. method steps.

The fourth aspect of the embodiments of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and operable on the processor, when the processor executes the computer program Steps for realizing any one of the above-mentioned laser radar point cloud processing methods.

A fifth aspect of the embodiments of the present application provides a computer program product, which, when the computer program product is run on a terminal device, causes the terminal device to execute the steps of any one of the above methods for processing a laser radar point cloud.

Beneficial effect

The beneficial effect of the embodiment of the present application is that the embodiment of the present application makes full use of the characteristics of the expansion point in the distance measurement value and the reflectance measurement value. After obtaining the point cloud data collected by the laser radar, according to the target scanning point and relative The distance measurement value and the reflectance measurement value of the adjacent points determine whether the target scanning point is an expansion point, and remove the identified expansion point from the point cloud data, thereby avoiding the occurrence of high anti-expansion phenomenon and ensuring the accuracy of lidar recognition. accuracy.

Description of drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the accompanying drawings that need to be used in the embodiments or exemplary technical descriptions. Obviously, the accompanying drawings in the following descriptions are only for this application. For some embodiments, those skilled in the art can also obtain other drawings based on these drawings without creative efforts.

Figure 1 is a schematic diagram of a laser radar;

Figure 2 is a schematic diagram of a point cloud of a high-reverse card in an ideal state;

Fig. 3 is the schematic diagram of light beam spatial distribution;

Figure 4 is a schematic diagram of high anti-expansion;

Figure 5 is a schematic diagram of the point cloud after high de-expansion;

FIG. 6 is a flow chart of an embodiment of a method for processing a laser radar point cloud in an embodiment of the present application;

Fig. 7 is a logical block diagram of the expansion point identification process;

Figure 8 is a schematic diagram of the point cloud effect before removing the expansion point;

Figure 9 is a schematic diagram of the point cloud effect after removing the expansion point;

FIG. 10 is a structural diagram of an embodiment of a laser radar point cloud processing device in the embodiment of the present application;

FIG. 11 is a schematic block diagram of a terminal device in an embodiment of the present application.

Embodiments of the present invention

In order to make the purpose, features and advantages of the present application more obvious and understandable, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the following The described embodiments are only some of the embodiments of the present application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the scope of protection of this application.

It should be understood that when used in this specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and/or components, but does not exclude one or more other features. , whole, step, operation, element, component and/or the presence or addition of a collection thereof.

In addition, in the description of the present application, the terms "first", "second", "third" and so on are only used to distinguish descriptions, and should not be understood as indicating or implying relative importance.

In the embodiment of the present application, the distance and reflectivity of the target object can be measured based on laser radar. Lidar is an instrument that uses laser sending and receiving to measure distance. Different lasers emit laser beams at different vertical angles in the air. At the same time, the photoelectric sensor receives the echo returned by the target object and converts it into a weak electrical signal. Afterwards, through analog-to-digital conversion, the distance and reflectivity of the target are calculated in the digital domain to form a vertical scanning field of view. When the motor rotates to the next angle, the entire transmitting and receiving unit repeats the same action again. After processing, the target distance at adjacent angles is obtained, and the distance and reflectivity of all target objects at different horizontal angles are collected to form a horizontal scanning field of view. The scanning in the horizontal direction and the vertical direction cooperate with each other to form the three-dimensional distance information of the space target, and then further perceptual processing is performed to determine the shape, size and type of the target object.

Figure 1 shows a schematic diagram of a typical laser radar, in which the control and processing unit is used to control the system to work according to a certain sequence of transmission and reception, and at the same time process the received data to obtain the distance and reflectivity results of the target object. The unit is usually a plurality of semiconductor laser arrays, which emit laser light according to a certain timing under the drive of voltage. When there is a target object in the emission direction, the returned echo passes through the receiving lens to the receiving photoelectric sensor, and is converted into an electrical signal, which is amplified in the receiving unit. It is converted into a digital quantity, and after subsequent digital processing, the distance and reflectance results are formed.

Reflectance is a physical quantity that characterizes the optical reflection ability of an object. After any object in nature is exposed to light, it will absorb and reflect the incident light. Different types of objects have different properties of electromagnetic waves, so their properties of reflecting incident light are also different. That is to say, when the incident light is constant, the intensity of the reflected light is different when it hits different substances. For example, the signs on the road are high-reflective objects, which have a strong ability to reflect incident light. If they emit light with a little weak energy, when they hit the high-reflective signs, they can almost all be reflected back from the original path. In the receiving unit, there is no detected easily.

Generally, the reflectivity of the target object can be calculated according to the ratio of the received echo energy reflected back by the target to the transmitted energy. The reflectivity of the high-reflection card is extremely high, and it is usually an isolated target. When the emission beam is in an ideal state, assuming that the emission is a straight line, the emission beam enters the high-reverse card from the open target during the rotation process, without excessive state, and directly enters the high-reverse card. Figure 2 is a schematic diagram of the point cloud formed by scanning at this time. Since the beam is an ideal straight line, there is no transition when scanning the high-reverse board, so the result of the point cloud represents the actual width of the high-reversal board.

The actual emitted light beam is non-ideal, as shown in Figure 3, there is energy distribution on the vertical plane along the emission direction, the farther away from the center of the vertical plane, the smaller the light energy. When the light beam sweeps the high-reflection card from left to right, the edge of the beam passes through the high-reflection card first, because the reflection ability of the high-reflection card is quite strong, and the small energy at the edge of the beam is reflected back to the radar for reception, and is detected, with low reflection rate form. As shown in Figure 4, as the beam enters more of the high-reflection board, the echo energy gradually increases until all the beams enter the high-reflection board and appear in the form of high reflectivity. The formed point cloud is higher than the actual The width should be wide. The point cloud outside the actual width of the high-definition board presents a form of low reflectivity due to the small beam edge energy, and the point cloud within the actual width of the high-definition board presents a form of high reflectivity due to the large energy of the main beam, which is called High anti-expansion.

As shown in Figure 5, when the phenomenon of high anti-expansion occurs, a point cloud with very low reflectivity is attached around the high anti-expansion, and then transitions to a point cloud with high internal reflectivity. In the actual automatic driving perception calculation, if there is confusion or misjudgment in the perception calculation, it will be regarded as a ring-shaped low-reverse card surrounded by a high-reverse card.

In order to remove the low inverse expansion point cloud around the high inverse point cloud, this application makes full use of the characteristics of the expansion point in the distance measurement value and reflectivity measurement value. After obtaining the point cloud data collected by the lidar, according to the target The distance measurement value and reflectance measurement value between the scanning point and the adjacent point judge whether the target scanning point is an expansion point, and remove the identified expansion point from the point cloud data, thereby avoiding the occurrence of high anti-expansion phenomenon and ensuring Accuracy of lidar recognition.

Figure 6 is a flow chart of an embodiment of a point cloud processing method of a laser radar in the embodiment of the present application, and the specific processing process may include the following steps:

Step S601 , acquiring point cloud data collected by lidar.

Wherein, each scanning point in the point cloud data includes a distance measurement value and a reflectivity measurement value. Taking the scanning point whose horizontal scanning sequence number is m and vertical scanning sequence number is n as an example, its distance measurement value can be recorded as Dis(m,n), and its reflectance measurement value can be recorded as Reflect(m,n).

The typical value of the interval between adjacent horizontal scanning serial numbers is 1/18000 seconds. When the typical frame rate is 10 frames, the horizontal angle difference between adjacent dot frequencies is 0.2 degrees, and the typical angular interval between adjacent vertical scanning serial numbers is 0.1 degrees. .

Step S602 , judging whether the target scanning point is an expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and adjacent points.

Wherein, the target scanning point may be any scanning point in the point cloud data; the adjacent point may be a scanning point whose distance from the target scanning point in the horizontal direction and in the vertical direction is smaller than a preset threshold.

Taking the horizontal direction as an example, whether the target scanning point is a horizontal expansion point can be judged according to the distance measurement value and the reflectance measurement value between the target scanning point and horizontal adjacent points.

Wherein, the horizontal adjacent point is an adjacent point on the same horizontal line as the target scanning point. With the target scanning point as the center and the horizontal adjacent points on both sides, the data of k scanning points can be stored in total. The specific number of k can be set according to the actual situation. Preferably, the typical value of k can be set to 9.

For example, if the scanning point whose horizontal scanning number is m and vertical scanning number is n is taken as the target scanning point, it is necessary to store the data from Dis(m-(k-1)/2,n) to Dis(m+(k-1) /2,n), and k distance measurements from Reflect(m-(k-1)/2,n) to Reflect(m+(k-1)/2,n).

Firstly, the left distance difference and the right distance difference can be calculated respectively according to the distance measurement values between the target scanning point and the horizontal adjacent points.

In a specific implementation of the embodiment of the present application, the absolute value of the difference between the distance measurement value of the leftmost horizontal adjacent point and the distance measurement value of the target scanning point can be determined as the left distance difference, that is :

DisDifL＝abs(Dis(m－(k－1)/2,n)－Dis(m,n))

The absolute value of the difference between the distance measurement value of the rightmost horizontal adjacent point and the distance measurement value of the target scanning point is determined as the right distance difference, namely:

DisDifR=abs(Dis(m+(k-1)/2,n)-Dis(m,n))

Among them, abs is the absolute value function, DisDifL is the distance difference on the left side, and DisDifR is the distance difference on the right side.

It should be noted that in actual application scenarios, there may be a large error in the distance measurement value. If only the leftmost and rightmost horizontal adjacent points are used for calculation, it may affect the final recognition result of the expansion point. Accuracy. Therefore, in another specific implementation of the embodiment of the present application, several horizontal adjacent points on the leftmost side and several horizontal adjacent points on the rightmost side can be considered comprehensively, so as to improve the final identification result of the expansion point the accuracy rate.

Taking the calculation of the distance difference on the left as an example, the first absolute value of the difference between the distance measurement value of the leftmost s horizontal adjacent points and the distance measurement value of the target scanning point can be calculated respectively, and the value The largest first absolute value is determined as the left distance difference. Wherein, s is a positive integer, and its specific value can be set according to the actual situation. Preferably, s can be set to 2, and the left distance difference can be calculated according to the following formula:

DisDifL＝max(abs(Dis(m－(k－1)/2,n)－Dis(m,n)),abs(Dis(m－(k－1)/2+1,n)－Dis(m, n)))

Among them, max is the maximum value function.

Similarly, for the calculation of the distance difference on the right side, the second absolute value of the difference between the distance measurement values of the rightmost s horizontal adjacent points and the distance measurement value of the target scanning point can be calculated respectively, and will be taken as The second absolute value with the largest value is determined as the right distance difference. When s is 2, the right distance difference can be calculated according to the following formula:

DisDifR＝max(abs(Dis(m+(k－1)/2－1,n)－Dis(m,n)),abs(Dis(m+(k－1)/2,n)－Dis(m, n))).

Then, left, middle, and right reflectance values may be determined, respectively.

The left reflectance value is the reflectance value of the leftmost horizontal adjacent point, the middle reflectance value is the reflectance measurement value of the target scanning point, and the right reflectance value is the reflectance of the rightmost horizontal adjacent point value, namely:

ReflectL＝Reflect(m－(k－1)/2,n)

ReflectC = Reflect(m,n)

ReflectR＝Reflect(m+(k－1)/2,n)

Among them, ReflectL is the left reflectance value, ReflectC is the middle reflectance value, and ReflectR is the right reflectance value.

After obtaining the left distance difference, the right distance difference, the left reflectivity value, the middle reflectivity value and the right reflectivity value, it can be judged whether these values satisfy the preset first condition or the second condition. If the first condition or the second condition is satisfied, the target scanning point is determined to be the horizontal expansion point.

Among them, the first condition can be the intersection of the following four conditions, that is, the following four conditions need to be met at the same time:

The distance difference on the left side is greater than or equal to the preset distance upper limit threshold, that is, DisDifL≥ThreDisB, ThreDisB is the distance upper limit threshold, and its specific value can be set according to the actual situation. Preferably, its typical value can be set to 1 meter;

The distance difference on the right side is less than or equal to the preset distance lower limit threshold, that is, DisDifR≤ThreDisS, ThreDisS is the distance lower limit threshold, and its specific value can be set according to the actual situation. Preferably, its typical value can be set to 0.1 meters;

The intermediate reflectance value is less than or equal to the preset reflectivity lower limit threshold, that is, ReflectC≤ThreReflectS, ThreReflectS is the reflectivity lower limit threshold, and its specific value can be set according to the actual situation. Preferably, its typical value can be set to 15;

The reflectance value on the right is greater than or equal to the preset reflectance upper limit threshold, that is, ReflectR≥ThreReflectB, ThreReflectB is the reflectance upper limit threshold, and its specific value can be set according to the actual situation. Preferably, its typical value can be set to 200.

When the first condition is met, it can be considered that the target scanning point is the expansion point on the left side of the high-reversed card.

The second condition can be the intersection of the following four conditions, that is, the following four conditions need to be met at the same time:

The distance difference on the right is greater than or equal to the preset distance upper limit threshold, that is, DisDifR≥ThreDisB;

The left distance difference is less than or equal to the preset distance lower limit threshold, that is, DisDifL≤ThreDisS;

The intermediate reflectance value is less than or equal to the preset reflectance lower limit threshold, that is, ReflectC≤ThreReflectS;

The left reflectance value is greater than or equal to the preset reflectance upper threshold, that is, ReflectL≥ThreReflectB.

When the second condition is met, it can be considered that the target scanning point is the expansion point on the right side of the high-reversed card.

Similar to the horizontal direction, in the vertical direction, whether the target scanning point is a vertical expansion point can be judged according to the distance measurement value and reflectivity measurement value between the target scanning point and the vertical adjacent point.

Wherein, the vertical adjacent point is the adjacent point on the same vertical line as the target scanning point. With the target scanning point as the center and the vertical adjacent points above and below it, the data of k scanning points can be stored in total. For example, if the scanning point whose horizontal scanning number is m and vertical scanning number is n is taken as the target scanning point, it is necessary to store the values from Dis(m,n-(k-1)/2) to Dis(m,n+(k- 1)/2) for k distance measurements, and k reflectance measurements from Reflect(m,n-(k-1)/2) to Reflect(m,n+(k-1)/2).

First, the upper distance difference and the lower distance difference may be calculated respectively according to the distance measurement values between the target scanning point and the vertical adjacent point.

In a specific implementation of the embodiment of the present application, the absolute value of the difference between the distance measurement value of the uppermost vertical adjacent point and the distance measurement value of the target scanning point can be determined as the upper side distance difference, that is :

DisDifU＝abs(Dis(m,n-(k-1)/2)-Dis(m,n))

The absolute value of the difference between the distance measurement value of the vertically adjacent point on the lowermost side and the distance measurement value of the target scanning point is determined as the lower side distance difference, that is:

DisDifD=abs(Dis(m,n+(k-1)/2)-Dis(m,n))

Among them, DisDifL is the distance difference on the upper side, and DisDifR is the distance difference on the lower side.

It should be noted that in actual application scenarios, there may be a large error in the distance measurement value. If only the uppermost and lowermost vertical adjacent points are used for calculation, it may affect the final recognition result of the expansion point. Accuracy. Therefore, in another specific implementation of the embodiment of the present application, several vertical adjacent points on the uppermost side and several vertical adjacent points on the lowermost side can be considered comprehensively, thereby improving the final identification of expansion points The accuracy of the result.

The calculation of the distance difference on the upper side is taken as an example. The third absolute value of the difference between the distance measurement values of the uppermost s vertical adjacent points and the distance measurement value of the target scanning point can be calculated respectively, and the maximum value The third absolute value of is determined as the upper side distance difference. When s is 2, the upper side distance difference can be calculated according to the following formula:

DisDifU＝max(abs(Dis(m,n－(k－1)/2)－Dis(m,n)), abs(Dis(m,n－(k－1)/2+1)－Dis(m, n))).

Similarly, for the calculation of the distance difference on the lower side, the fourth absolute value of the difference between the distance measurement values of the lowermost s vertical adjacent points and the distance measurement value of the target scanning point can be calculated respectively, and The fourth absolute value with the largest value is determined as the lower distance difference. When s is 2, the lower side distance difference can be calculated according to the following formula:

DisDifD＝max(abs(Dis(m,n+(k-1)/2-1)-Dis(m,n)),abs(Dis(m,n+(k-1)/2)-Dis(m, n))).

Then, upper side reflectance values, intermediate reflectance values and lower side reflectance values may be determined respectively.

The upper side reflectance value is the reflectance value of the uppermost vertical adjacent point, the middle reflectance value is the reflectance measurement value of the target scanning point, and the lower side reflectance value is the reflection of the lowermost vertical adjacent point Rate value, that is:

ReflectU＝Reflect(m,n-(k-1)/2)

ReflectC = Reflect(m,n)

ReflectD＝Reflect(m,n+(k－1)/2)

Among them, ReflectU is the reflectance value of the upper side, ReflectC is the reflectance value of the middle side, and ReflectD is the reflectance value of the lower side.

After obtaining the upper distance difference, the lower distance difference, the upper reflectivity value, the middle reflectivity value and the lower reflectivity value, it can be judged whether these values satisfy the preset third condition or the fourth condition. If the third condition or the fourth condition is satisfied, then the target scanning point is determined to be the vertical expansion point.

Among them, the third condition can be the intersection of the following four conditions, that is, the following four conditions need to be met at the same time:

The upper distance difference is greater than or equal to the preset distance upper limit threshold, that is, DisDifU≥ThreDisB;

The lower distance difference is less than or equal to the preset distance lower limit threshold, that is, DisDifD≤ThreDisS;

The lower reflectivity value is greater than or equal to the preset upper reflectivity threshold, that is, ReflectD≥ThreReflectB.

When the third condition is met, it can be considered that the target scanning point is the expansion point on the upper side of the high-reversed card.

The fourth condition can be the intersection of the following four conditions, that is, the following four conditions need to be met at the same time:

The lower distance difference is greater than or equal to the preset distance upper threshold, that is, DisDifD≥ThreDisB;

The upper distance difference is less than or equal to the preset distance lower limit threshold, that is, DisDifU≤ThreDisS;

The upper reflectance value is greater than or equal to the preset reflectance upper threshold, that is, ReflectU≥ThreReflectB.

When the fourth condition is met, it can be considered that the target scanning point is the expansion point on the lower side of the high-reversed card.

Regardless of whether the target scanning point is a horizontal expansion point or a vertical expansion point, it may be determined that the target scanning point is the expansion point.

It should be noted that the above process only takes one scan point as an example to illustrate the identification process of the expansion point. According to this processing method, all the scan points in the point cloud data can be traversed to identify all the expansion points.

Fig. 7 is a logic block diagram of the identification process of the expansion point in the horizontal direction. As shown in the figure, its specific implementation process may include:

1. Write the distance measurement value Dis(m,n) and the reflectivity measurement value Reflect(m,n) of the current scanning point into the cache, the write address is determined by the current horizontal scanning number m, and the read address is determined by the horizontal scanning number m-1 Sure.

2. Read the distance measurement value from the cache, and write it into the shift register corresponding to the distance measurement value. Here, a total of k shift registers are set for the distance measurement value, and the stored distance measurement values are sequentially recorded as: Dis (m－k,n), Dis(m－k+1,n),..., Dis(m－(k+1)/2,n),..., Dis(m－2,n), Dis(m -1,n). Similarly, the reflectance measurement value is read from the cache, and written into the shift register corresponding to the reflectance measurement value, here a total of k shift registers are set for the reflectance measurement value, and the reflectance measurement value stored therein In turn, it is recorded as: Reflect(m－k,n), Reflect(m－k+1,n),..., Reflect(m－(k+1)/2,n),..., Reflect(m－2,n ), Reflect(m－1,n), and set:

ReflectL＝Reflect(m－k,n)

ReflectC＝Reflect(m－(k+1)/2,n)

ReflectR＝Reflect(m－1,n)

3. In the first reflectance discriminator, judge according to the following conditions:

If ReflectC≤ThreReflectS and ReflectR≥ThreReflectB, set the decision result ReflectLDeter=1, otherwise, set the decision result ReflectLDeter=0.

In the second reflectance discriminator, the judgment is made according to the following conditions:

If ReflectC≤ThreReflectS and ReflectL≥ThreReflectB, set the decision result ReflectRDeter=1, otherwise, set the decision result ReflectRDeter=0.

4. Perform the following calculations in the four subtractors:

Sub00＝Dis(m－k,n)－Dis(m－(k+1)/2,n)

Sub01＝Dis(m－k+1,n)－Dis(m－(k+1)/2,n)

Sub02＝Dis(m－2,n)－Dis(m－(k+1)/2,n)

Sub03＝Dis(m－1,n)－Dis(m－(k +1)/2,n)

Among them, Sub00, Sub01, Sub02, and Sub03 are the calculation results of the four subtractors respectively.

5. In the four absolute value calculators, calculate the absolute values of the calculation results of the four subtractors respectively.

Specifically, in the first absolute value calculator, if Sub00≥0, set its output Abs00=Sub00, otherwise, set Abs00=-Sub00;

In the second absolute value calculator, if Sub01≥0, set its output Abs01=Sub01, otherwise, set Abs01=-Sub01;

In the third absolute value calculator, if Sub02≥0, set its output Abs02=Sub02, otherwise, set Abs02=-Sub02;

In the fourth absolute value calculator, if Sub03≥0, then set its output Abs03=Sub03, otherwise, set Abs03=-Sub03.

6. In the two comparators, find the maximum value of the absolute value in pairs.

Specifically, in the first comparator, if Abs00≥Abs01, set its output DisDifL=Abs00, otherwise, set DisDifL=Abs01;

In the second comparator, if Abs02≥Abs03, set its output DisDifR=Abs02, otherwise, set DisDifR=Abs03.

7. In the first distance discriminator, judge according to the following conditions:

If DisDifL≥ThreDisB and DisDifR≤ThreDisS, set the decision result DisLDeter=1, otherwise, set the decision result DisLDeter=0.

In the second distance discriminator, the judgment is made according to the following conditions:

If DisDifR≥ThreDisB and DisDifL≤ThreDisS, set the decision result DisRDeter=1, otherwise, set the decision result DisRDeter=0.

8. The output result of the first distance discriminator and the output result of the first reflectance discriminator are input to the expansion discriminator on the left, and the logical AND operation is performed according to the following formula:

SpreadL＝DisLDeter & ReflectLDeter

The output result of the second distance discriminator and the output result of the second reflectance discriminator are input to the expansion discriminator on the right, and the logical AND operation is performed according to the following formula:

SpreadR＝DisRDeter & ReflectRDeter

The result SpreadL output by the left expansion decision unit and the result SpreadR output by the right expansion decision unit are input into the expansion decision unit, and the logical OR operation is performed according to the following formula:

Spread＝SpreadL∣SpreadR

If Spread is 1, the scanning point corresponding to the shift register in the middle is a horizontal expansion point, and if Spread is 0, the scanning point corresponding to the shift register in the middle is not a horizontal expansion point.

The identification process of the expansion point in the vertical direction is similar to the identification process of the expansion point in the horizontal direction, which can be referred to above, and will not be repeated here.

Step S603, if the target scanning point is an expansion point, remove the target scanning point from the point cloud data.

Figure 8 is a schematic diagram of the point cloud effect before the expansion point is removed. It can be seen that there will be a circle of point clouds with very low reflectivity around the high-reverse card. Figure 9 is a schematic diagram of the point cloud effect after removing the expansion points, from which it can be seen that the expansion points around the high-reversed cards have been eliminated.

To sum up, this application makes full use of the characteristics of the expansion point in the distance measurement value and reflectivity measurement value. After obtaining the point cloud data collected by the laser radar, the distance between the target scanning point and the adjacent point is measured Value and reflectance measurement value to judge whether the target scanning point is an expansion point, and remove the identified expansion point from the point cloud data, thereby avoiding the occurrence of high anti-expansion phenomenon and ensuring the accuracy of lidar recognition.

Corresponding to the point cloud processing method for lidar described in the above embodiments, FIG. 10 shows a structural diagram of an embodiment of a point cloud processing device for lidar provided in the embodiment of the present application.

In this embodiment, a laser radar point cloud processing device may include:

The point cloud data acquisition module 1001 is used to obtain the point cloud data collected by the lidar; each scanning point in the point cloud data includes a distance measurement value and a reflectance measurement value;

An expansion point judging module 1002, configured to determine whether the target scanning point is an expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and adjacent points; the target scanning point is any point in the point cloud data. A scanning point; the adjacent point is a scanning point whose distance from the target scanning point in the horizontal direction and in the vertical direction is smaller than a preset threshold;

The expansion point removal module 1003 is configured to remove the target scanning point from the point cloud data if the target scanning point is an expansion point.

Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the above-described devices and modules can refer to the corresponding process in the foregoing method embodiments, and details are not repeated here.

In the above-mentioned embodiments, the descriptions of each embodiment have their own emphases, and for parts that are not detailed or recorded in a certain embodiment, refer to the relevant descriptions of other embodiments.

FIG. 11 shows a schematic block diagram of a terminal device provided by an embodiment of the present application. For ease of description, only parts related to the embodiment of the present application are shown.

As shown in FIG. 11 , the terminal device 11 of this embodiment includes: a processor 110 , a memory 111 , and a computer program 112 stored in the memory 111 and operable on the processor 110 . When the processor 110 executes the computer program 112, the steps in the above-mentioned embodiments of the point cloud processing method of each laser radar are realized. Alternatively, when the processor 110 executes the computer program 112, functions of the modules/units in the foregoing device embodiments are implemented.

Exemplarily, the computer program 112 can be divided into one or more modules/units, and the one or more modules/units are stored in the memory 111 and executed by the processor 110 to complete this application. The one or more modules/units may be a series of computer program instruction segments capable of accomplishing specific functions, and the instruction segments are used to describe the execution process of the computer program 112 in the terminal device 11 .

Those skilled in the art can understand that FIG. 11 is only an example of the terminal device 11, and does not constitute a limitation on the terminal device 11. It may include more or less components than those shown in the figure, or combine some components, or different components. For example, the terminal device 11 may also include an input and output device, a network access device, a bus, and the like.

The processor 110 may be a central processing unit (Central Processing Unit, CPU), or other general-purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Field-Programmable Gate Array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor, or the like.

The storage 111 may be an internal storage unit of the terminal device 11 , for example, a hard disk or a memory of the terminal device 11 . The memory 111 may also be an external storage device of the terminal device 11, such as a plug-in hard disk equipped on the terminal device 11, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, flash memory card (Flash Card), etc. Further, the memory 111 may also include both an internal storage unit of the terminal device 11 and an external storage device. The memory 111 is used to store the computer program and other programs and data required by the terminal device 11 . The memory 111 can also be used to temporarily store data that has been output or will be output.

Those skilled in the art can clearly understand that for the convenience and brevity of description, only the division of the above-mentioned functional units and modules is used for illustration. In practical applications, the above-mentioned functions can be assigned to different functional units, Completion of modules means that the internal structure of the device is divided into different functional units or modules to complete all or part of the functions described above. Each functional unit and module in the embodiment may be integrated into one processing unit, or each unit may exist separately physically, or two or more units may be integrated into one unit, and the above-mentioned integrated units may adopt hardware It can also be implemented in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the present application. For the specific working process of the units and modules in the above system, reference may be made to the corresponding process in the foregoing method embodiments, and details will not be repeated here.

Those skilled in the art can appreciate that the units and algorithm steps of the examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be regarded as exceeding the scope of the present application.

In the embodiments provided in this application, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the device/terminal device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units Or components may be combined or may be integrated into another system, or some features may be omitted, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist separately physically, or two or more units may be integrated into one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

If the integrated module/unit is realized in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments in the present application can also be completed by instructing related hardware through computer programs. The computer programs can be stored in a computer-readable storage medium, and the computer When the program is executed by the processor, the steps in the above-mentioned various method embodiments can be realized. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form. The computer-readable storage medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory ), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the computer-readable storage medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable Storage media excludes electrical carrier signals and telecommunication signals.

The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: it can still implement the foregoing Modifications to the technical solutions described in the examples, or equivalent replacement of some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the application, and should be included in the Within the protection scope of this application.

Claims

A point cloud processing method of lidar, is characterized in that, comprises:

Obtain the point cloud data collected by the laser radar; each scan point in the point cloud data includes a distance measurement value and a reflectivity measurement value;

Judging whether the target scanning point is an expansion point according to the distance measurement value and the reflectance measurement value between the target scanning point and the adjacent point; the target scanning point is any scanning point in the point cloud data; the adjacent The point is a scanning point whose distance from the target scanning point in the horizontal direction and in the vertical direction is smaller than a preset threshold;

If the target scan point is an expansion point, then remove the target scan point from the point cloud data.
The point cloud processing method of lidar according to claim 1, characterized in that, judging whether the target scanning point is an expansion point according to the distance measurement value and the reflectance measurement value between the target scanning point and the adjacent point, comprises :

Judging whether the target scanning point is a horizontal expansion point according to the distance measurement value and reflectance measurement value between the target scanning point and the horizontal adjacent point; the horizontal adjacent point is on the same horizontal line as the target scanning point adjacent points;

According to the distance measurement value and the reflectance measurement value of the target scanning point and the vertical adjacent point, it is judged whether the target scanning point is a vertical expansion point; the vertical adjacent point is at the same location as the target scanning point Adjacent points on a vertical line;

If the target scanning point is a horizontal expansion point or a vertical expansion point, then determine that the target scanning point is an expansion point.
The point cloud processing method of laser radar according to claim 2, characterized in that, it is judged whether the target scanning point is horizontal according to the distance measurement value and reflectivity measurement value between the target scanning point and the horizontal adjacent point Expansion points, including:

Calculate the distance difference on the left side and the distance difference on the right side respectively according to the distance measurement value between the target scanning point and the horizontal adjacent point;

Judging whether the left distance difference, the right distance difference, the middle reflectance value and the right reflectance value meet a preset first condition or whether the left distance difference, the right distance difference, the left Whether the reflectance value and the middle reflectance value meet the preset second condition; the left reflectance value is the reflectance value of the leftmost horizontal adjacent point, and the middle reflectance value is set The reflectance measurement value of the target scanning point, the reflectance value on the right side is the reflectance value of the rightmost horizontal adjacent point;

If the first condition or the second condition is met, it is determined that the target scanning point is a horizontal expansion point.
The point cloud processing method of lidar according to claim 3, characterized in that, the left distance difference and the right distance difference are respectively calculated according to the distance measurement value of the target scanning point and the horizontal adjacent point, include:

respectively calculating the first absolute value of the difference between the distance measurement values of the leftmost several horizontal adjacent points and the distance measurement value of the target scanning point;

determining the first absolute value with the largest value as the left distance difference;

Respectively calculating the second absolute value of the difference between the distance measurement values of the rightmost several horizontal adjacent points and the distance measurement value of the target scanning point;

The second absolute value with the largest value is determined as the right distance difference.
The point cloud processing method of lidar according to claim 3, is characterized in that, described first condition is the intersection of following conditions:

The left distance difference is greater than or equal to a preset distance upper limit threshold;

The right distance difference is less than or equal to a preset distance lower limit threshold;

The intermediate reflectivity value is less than or equal to a preset reflectivity lower limit threshold;

The right reflectivity value is greater than or equal to a preset reflectivity upper threshold.
The point cloud processing method of lidar according to claim 3, is characterized in that, described second condition is the intersection of following conditions:

The right distance difference is greater than or equal to a preset distance upper limit threshold;

The left distance difference is less than or equal to a preset distance lower limit threshold;

The intermediate reflectivity value is less than or equal to a preset reflectivity lower limit threshold;

The left reflectivity value is greater than or equal to a preset reflectivity upper threshold.
The point cloud processing method of laser radar according to claim 2, characterized in that, it is judged whether the target scanning point is Vertical expansion points, including:

calculating the upper side distance difference and the lower side distance difference respectively according to the distance measurement values between the target scanning point and the vertical adjacent point;

judging whether the upper distance difference, the lower distance difference, the middle reflectance value, and the lower reflectance value meet a preset third condition or whether the upper distance difference, the lower distance difference, the upper Whether the reflectance value and the intermediate reflectance value meet the preset fourth condition; the upper side reflectance value is the reflectance value of the uppermost vertically adjacent point, and the intermediate reflectance value is set The reflectance measurement value of the target scanning point, the reflectance value of the lower side is the reflectance value of the vertical adjacent point on the lowermost side;

If the third condition or the fourth condition is met, it is determined that the target scanning point is a vertical expansion point.
The point cloud processing method of lidar according to claim 7, characterized in that, the upper side distance difference and the lower side distance difference are respectively calculated according to the distance measurement value between the target scanning point and the vertical adjacent point ,include:

Calculating the third absolute value of the difference between the distance measurement values of the several vertical adjacent points on the uppermost side and the distance measurement values of the target scanning point respectively;

determining the third absolute value with the largest value as the upper distance difference;

Calculating the fourth absolute value of the difference between the measured distance values of several vertical adjacent points on the lowermost side and the measured distance values of the target scanning point;

The fourth absolute value with the largest value is determined as the lower distance difference.
The point cloud processing method of lidar according to claim 7, is characterized in that, described third condition is the intersection of following conditions:

The upper distance difference is greater than or equal to a preset distance upper limit threshold;

The lower distance difference is less than or equal to a preset distance lower limit threshold;

The intermediate reflectivity value is less than or equal to a preset reflectivity lower limit threshold;

The lower side reflectance value is greater than or equal to a preset upper reflectance threshold.
The point cloud processing method of lidar according to claim 7, is characterized in that, described fourth condition is the intersection of following conditions:

The lower distance difference is greater than or equal to a preset distance upper threshold;

The upper distance difference is less than or equal to a preset distance lower limit threshold;

The intermediate reflectivity value is less than or equal to a preset reflectivity lower limit threshold;

The upper side reflectivity value is greater than or equal to a preset upper reflectivity threshold.
A point cloud processing device for laser radar, characterized in that it comprises:

The point cloud data acquisition module is used to obtain the point cloud data collected by the laser radar; each scanning point in the point cloud data includes a distance measurement value and a reflectivity measurement value;

An expansion point judging module, used to judge whether the target scanning point is an expansion point according to the distance measurement value and the reflectance measurement value between the target scanning point and the adjacent point; the target scanning point is any one of the point cloud data A scanning point; the adjacent point is a scanning point whose distance from the target scanning point in the horizontal direction and in the vertical direction is smaller than a preset threshold;

An expansion point removal module, configured to remove the target scanning point from the point cloud data if the target scanning point is an expansion point.
A computer-readable storage medium, the computer-readable storage medium stores a computer program, characterized in that, when the computer program is executed by a processor, the laser radar according to any one of claims 1 to 10 is realized. Steps of the point cloud processing method.
A terminal device, comprising a memory, a processor, and a computer program stored in the memory and operable on the processor, characterized in that, when the processor executes the computer program, the computer program according to claims 1 to 1 is implemented. The step of the point cloud processing method of lidar described in any one in 10.