CN110175344B - Laser radar wire harness distribution adjustment optimization method for automatic driving scene - Google Patents
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Abstract
The invention relates to the field of laser radar sensors and automatic driving, in particular to a laser radar wire harness distribution adjusting and optimizing method for an automatic driving scene. According to the method, a laser radar wire harness model is established according to the specified optimized wire harness quantity. And then, setting optimization parameters according to the requirements of the environment perception task, and performing coarse optimization. And finally, performing fine optimization and tuning on the coarse optimization result to obtain optimized laser beam distribution. The obtained optimized laser beam distribution can be tested and verified in virtual environments such as a driving simulator and the like, and the effect of the laser beam distribution on an environment perception task is improved. Compared with the uniform wiring harness distribution of the existing common multi-line laser radar, the method has pertinence to a specific target detection task, so that the optimized sensor has the characteristics of high detection accuracy and wide range in target detection.
Description
Technical Field
The invention relates to the field of laser radar sensors and automatic driving, in particular to a laser radar wire harness distribution adjusting and optimizing method for an automatic driving scene.
Background
In recent years, the unmanned technology is gradually a research hotspot of universities and enterprises at home and abroad, and also attracts public attention due to the frequent bright phase of the unmanned technology in commercial application tests. In the process of realizing automatic driving of the unmanned vehicle, an information perception subsystem of an autonomous driving system is a key basis of automatic driving of the unmanned vehicle and is a premise of ensuring safety and stability of the unmanned vehicle and normal driving without collision.
With the improvement of precision and integration of vehicle gauge sensing sensors in recent years, more and more sensors are deployed and applied to unmanned automobile platforms, wherein laser radar sensors gradually become main sensors on unmanned automatic automobiles due to high-precision distance detection, information richness and high reliability which is insensitive to illumination conversion compared with vehicle-mounted cameras.
Many researches are focused on using point cloud data of a laser radar sensor to realize and complete environment perception tasks in automatic driving related scenes, including tasks of object target detection, classification, tracking and the like. Because the scanning of the laser radar sensor is dispersed along with the distance, the point cloud obtained by scanning at the middle and long distances is sparse, and the effects of other algorithms such as target detection are further influenced, so that how to comprehensively improve the scanning and algorithm perception effects of the laser radar at different distances is still an open important problem.
In the prior art, patent No. CN 102837658B proposes a system and a method for fusing multiple lidar data on an intelligent vehicle, where the method scans based on a method for fusing multiple lidar data, and improves the sensing effect by increasing the number of sensors of the lidar, but the lidar has a high economic cost, and fusing multiple lidar data increases the data amount and complexity of lidar data processing, and increases the processing difficulty.
In the prior art, patent No. CN 109375238A proposes an omnidirectional variable rotation step angle lidar and a scanning method thereof, which uses a variable rotation step angle lidar scanning method to scan, and can increase the number of laser spots projected on a target object in the horizontal direction, but the number of laser spots projected on the target object in the vertical direction is not increased, and vertical distribution information of the target object cannot be further enriched, so that the improvement effect in the sensing task is limited.
Disclosure of Invention
The invention aims to overcome at least one defect in the prior art, and provides a laser radar wire harness distribution adjustment optimization method aiming at an automatic driving scene, which has pertinence to a specific target detection task, so that the optimized sensor has the characteristics of high detection accuracy and wide range in target detection.
In order to solve the technical problems, the invention adopts the technical scheme that: a laser radar beam distribution adjustment optimization method for an automatic driving scene comprises the following steps:
s1, constructing a laser radar sensor wire harness model: defining a scanning horizontal corner variable of laser radar rotation according to a rotating structure of the multi-line laser radar sensor; according to the structure of a multi-transmitter in the vertical direction of the multi-line laser radar, defining the variable of vertical elevation distribution of a transmitting channel;
s2, aiming at the wiring harness distribution targets at different distances, constructing an optimized target evaluation function: firstly, aiming at short distance, in order to obtain a vertical visual field as large as possible, a sub-objective function of beam divergence is established to improve the target detection effect in the short-distance visual field. Aiming at the detection in the middle and long distance, a sub-objective function of the beam focusing is established for the purpose of focusing effect as large as possible so as to improve the target detection effect of the long-distance visual field. Aiming at a specific installation position of the laser radar, establishing a sub-target function for avoiding a blind area so as to avoid the laser beam from falling in the blind area;
s3, adjusting optimization parameters to perform coarse optimization according to the perception task: setting an attention point in an interest area and the weight of each sub-target function according to a target detection task of actual automatic driving scene environment perception, and performing coarse optimization; the coarse optimization firstly generates candidate angle values by setting coarse optimization resolution. For each candidate angle distribution combination, calculating evaluation values corresponding to the angle distribution, and further iteratively selecting the angle combination with the optimal total evaluation as a coarse optimization result;
s4, performing fine optimization and tuning according to the result of the coarse optimization to obtain optimized radar wire harness distribution; fine optimization firstly sets an optimized step length, then takes a result of coarse optimization as initial estimation, and carries out fine adjustment optimization by using the fine optimization step length to obtain a final evaluation optimal result;
and S5, carrying out simulation test and verification on the optimized laser radar. And carrying out simulation test and verification on the optimized laser radar. Because the existing mass production laser radar sensor in the market can not adjust the vertical direction light emission angle, the laser radar for customizing the angle distribution of the wire harness has long period and high cost, the method provides the simulation test and verification of the optimized laser radar in the automatic driving simulation environment. The simulation firstly realizes a laser radar sensor model in an automatic driving simulation environment, customizes the virtual radar according to an optimized wire harness distribution result, then sets a common driving scene, and performs data acquisition and algorithm test on the optimized and contrasted laser radar in the same scene, thereby improving the performance of the optimized laser radar according to the comparison of the algorithm result.
In the invention, starting from the laser radar sensor, the richness of point cloud data information obtained by scanning the laser radar is improved, and the effect of obtaining a specific perception task in an automatic driving scene is improved. According to the invention, the distribution of the vertical laser beams of a single laser radar sensor is adjusted and optimized, so that the problem of high cost in a scanning method of multi-radar fusion is avoided, the utilization rate of the laser beams of the single laser radar is improved, and compared with the scanning method with a variable rotation step angle, the method can effectively improve the number of laser points projected on a target object within a certain distance range, and further has better performance in a subsequent detection algorithm.
Further, in the step S1, according to the structure of the horizontal rotation of the multiline lidar sensor and the structure of the vertical direction multi-transmitter, a scanning horizontal rotation angle variable and a vertical elevation distribution variable of a transmitting channel of the lidar sensor are defined, and the specific process includes:
the laser radar sensor is provided with a motor which rotates in a horizontal plane to obtain a horizontal visual angle of 360 degrees; in the rotation with equal gaps, the laser radar emits laser light to perform scanning once, and the rotation angle sequence of the scanning is defined as:
rotation＝{θi,i＝0,1,…,m}
where m is the total number of horizontal rotation steps, θiFor the ith horizontal rotation angle, the angular resolution of the horizontal acquisition determines:
due to the limitation of the motion structure, the laser radar is provided with different laser emission channels in the vertical direction, and the emission angle distribution is as follows:
wherein n is the number of vertical channels, betajAnd the beam distribution c of the laser radar is formed by combining different angles for the jth vertical laser beam channel angle.
Further, the constructing an optimization objective function in the step S2 specifically includes:
s21, the overall evaluation function is composed of a multi-target function and defined as:
wherein
To total optimization objective evaluation function, Fk(c) As a sub-target evaluation function, gammakAs its weight, c*Optimizing the obtained wire harness distribution result; the total evaluation is obtained by accumulating a plurality of weighted sub-target evaluation functions;
s22, considering the divergence of the line beam distribution in short-distance target detection, defining a sub-target function as follows:
wherein h is the installation height of the laser radar sensor,
evaluating the divergence of the beam distribution c of the ROI in the region of interest and assigning different weight values (μ) in different distances μ, the weight value function of the divergence being defined as:
μfocus_ito set a point of interest, siFor the weight scale coefficient corresponding to the focus point, (mu) at the set mufocus_iThe weight at the point of interest is minimized to control the divergence that maximizes the distribution of the line beam within certain specified areas of interest;
dis (μ, c, h) is an evaluation function for evaluating divergence of a laser beam distribution c, which is defined as:
where the I (μ, c, h) function counts and filters the laser beams that touch the μ vertical plane at a specified distance μ, the Dis (μ, c, h) function then calculates the Range of the beams and from the maximum | maxrange (I (μ, c, h))minC, h)) carrying out normalization to obtain the divergence evaluation of the beam distribution c at the mu position;
s23, defining a second sub-target function as follows according to the focality of the line beam distribution in the target detection of the medium and long distance under consideration:
wherein h is the installation height of the laser radar sensor,
evaluating the focality of the beam distribution c of the ROI in the region of interest, and assigning different weight values rho (mu) in different distances mu, wherein the weight value function of the focality is defined as:
similar to the weight value function for the divergence of the line beam, ρ (μ) is at a set μfocus_iThe weighted value at the focus point is minimum so as to control and maximize the focality of the beam distribution in some specified areas;
con (μ, c, h) is an evaluation function for evaluating the focusability of the laser beam distribution c, which is defined as:
this function counts the number of beams in contact with the vertical plane at a distance μ and depends on the maximum | maxCount (I (μ)maxC, h)) carrying out normalization to obtain the focality evaluation of the beam distribution c at the mu position;
s24, besides considering divergence and focalization of the wiring harness distributed in certain areas, near the installation position, due to the limitation of the platform, the emitted laser beam may fall on a blind area formed by the installation platform, such as a car roof, so that in order to avoid waste caused by the laser beam falling in the blind area, the method adds the consideration of the limitation of the laser beam blind area, and the sub-objective functions are defined as follows:
the objective function
Adding a penalty weight for the laser beam falling within the Blind zone BZ, where h (μ) is a predefined Blind zone height at a distance μ, the weight function Blind (μ, c, h (μ)) being defined as follows:
the function consists of additive penalty values given by the light beams falling in the blind area, and the penalty values are calculated by a polynomial formula approximately limited as follows:
wherein o is the number of beams falling in the blind area, S is the proportionality coefficient of the set weight, and n is the polynomial order of the approximate limit.
Furthermore, the coarse optimization distribution firstly generates a candidate angle value set from a set angle distribution upper bound to a set angle distribution lower bound by setting a coarse optimization resolution and taking the resolution as a step length; in the coarse optimization iteration process, selecting an angle value as a candidate combination according to the number of the specified laser radar lines in a candidate angle value set; for each candidate angle distribution combination, calculating evaluation value corresponding to the angle distribution
Further iteratively selecting a total evaluationOptimum angle combination c*As a coarse optimization result.
Further, the step S4 specifically includes: for the laser beam angle distribution c obtained in the previous step*According to the specified fine optimization resolution, for c*The angle value of (1) is adjusted and substituted
Calculating an evaluation value, adjusting the iteration direction according to the evaluation value, and finally obtaining an optimization result c*。
Compared with the prior art, the beneficial effects are:
1. the laser beam distribution of the laser radar sensor is adjusted and optimized based on the single laser radar sensor, and compared with a multi-laser radar sensor fusion method, the method does not need to fuse point cloud data, and has the advantages of low cost, simple structure, small point cloud data amount and the like;
2. according to the invention, by adjusting and optimizing the laser beam distribution in the vertical direction of the laser radar sensor, the number of laser points projected on a target object can be increased within a certain distance range, the characteristics of the laser radar sensor can be further extracted, and the performance of algorithms such as target detection and the like can be improved;
3. the laser beam distribution of the laser radar sensor is adjusted and optimized through a multi-objective optimization method, the sub-objective functions of beam divergence are established in a short distance to obtain the vertical visual field as large as possible, the sub-objective functions of beam focusing established in a medium distance and a long distance to obtain the focusing effect as good as possible, the sub-objective functions for avoiding the blind area are established in the specific installation position of the laser radar, and the laser beams are prevented from falling into the blind area.
Drawings
Fig. 1 is an overall architecture diagram of the laser radar beam distribution adjustment optimization method for an automatic driving scene according to the present invention.
FIG. 2 is a basic flow diagram of the coarse optimization process of the present invention.
FIG. 3 is a basic flow diagram of the fine optimization process of the present invention.
Detailed Description
The drawings are for illustration purposes only and are not to be construed as limiting the invention; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted. The positional relationships depicted in the drawings are for illustrative purposes only and are not to be construed as limiting the invention.
Example 1:
as shown in fig. 1, a method for adjusting and optimizing the distribution of laser radar beams in an automatic driving scenario includes the following steps:
step 1, constructing a laser radar sensor wire harness model;
the specific process comprises the following steps:
the laser radar sensor is provided with a motor which rotates in a horizontal plane to obtain a horizontal visual angle of 360 degrees; in the rotation with equal gaps, the laser radar emits laser light to perform scanning once, and the rotation angle sequence of the scanning is defined as:
rotation＝{θi,i＝0,1,…,m}
where m is the total number of horizontal rotation steps, θiIs the ith horizontal rotation angle; the angular resolution of the horizontal acquisition determines:
due to the limitation of the motion structure, the laser radar is provided with different laser emission channels in the vertical direction, and the emission angle distribution is as follows:
wherein n is the number of vertical channels, betajAnd the beam distribution c of the laser radar is formed by combining different angles for the jth vertical laser beam channel angle.
Step 2, aiming at the wiring harness distribution targets at different distances, an optimized target evaluation function is constructed;
s21, the overall evaluation function is composed of a multi-target function and defined as:
wherein
To total optimization objective evaluation function, Fk(c) As a sub-target evaluation function, gammakAs its weight, c*Optimizing the obtained wire harness distribution result; the total evaluation is obtained by accumulating a plurality of weighted sub-target evaluation functions;
s22, considering the divergence of the line beam distribution in short-distance target detection, defining a sub-target function as follows:
wherein h is the installation height of the laser radar sensor,
evaluating the divergence of the beam distribution c of the ROI in the region of interest and assigning different weight values (μ) in different distances μ, the weight value function of the divergence being defined as:
μfocus_ito set a point of interest, siFor the weight scale coefficient corresponding to the focus point, (mu) at the set mufocus_iThe weight at the point of interest is minimized to control the divergence that maximizes the distribution of the line beam within certain specified areas of interest;
dis (μ, c, h) is an evaluation function for evaluating divergence of a laser beam distribution c, which is defined as:
where the I (μ, c, h) function counts and filters the laser beams that touch the μ vertical plane at a specified distance μ, the Dis (μ, c, h) function then calculates the Range of these beams and from the maximum | maxRange (I (μ)minC, h)) and carrying out normalization to obtain the divergence evaluation of the beam distribution c at the mu position;
s23, defining a second sub-target function as follows according to the focality of the line beam distribution in the target detection of the medium and long distance under consideration:
wherein h is the installation height of the laser radar sensor,
evaluating the focality of the beam distribution c of the ROI in the region of interest, and assigning different weight values rho (mu) in different distances mu, wherein the weight value function of the focality is defined as:
similar to the weight value function for the divergence of the line beam, ρ (μ) is at a set μfocus_iThe weighted value at the focus point is minimum so as to control and maximize the focality of the beam distribution in some specified areas;
con (μ, c, h) is an evaluation function for evaluating the focusability of the laser beam distribution c, which is defined as:
this function counts the number of beams in contact with the vertical plane at a distance μ and depends on the maximum | maxCount (I (μ)maxC, h)) carrying out normalization to obtain the focality evaluation of the beam distribution c at the mu position;
s24, besides considering divergence and focalization of the wiring harness distributed in certain areas, near the installation position, due to the limitation of the platform, the emitted laser beam may fall on a blind area formed by the installation platform, such as a car roof, so that in order to avoid waste caused by the laser beam falling in the blind area, the method adds the consideration of the limitation of the laser beam blind area, and the sub-objective functions are defined as follows:
the objective function
Adding a penalty weight for the laser beam falling within the Blind zone BZ, where h (μ) is a predefined Blind zone height at a distance μ, the weight function Blind (μ, c, h (μ)) being defined as follows:
the function consists of additive penalty values given by the light beams falling in the blind area, and the penalty values are calculated by a polynomial formula approximately limited as follows:
wherein o is the number of beams falling in the blind area, S is the proportionality coefficient of the set weight, and n is the polynomial order of the approximate limit.
And 3, adjusting optimization parameters to perform coarse optimization according to the perception task: firstly, generating a candidate angle value set from a set angle distribution upper bound to a set angle distribution lower bound by setting a coarse optimization resolution and taking the resolution as a step length; in the coarse optimization iteration process, selecting an angle value as a candidate combination according to the number of the specified laser radar lines in a candidate angle value set; for each candidate angle distribution combination, calculating evaluation value corresponding to the angle distribution
Then, the optimal angle combination c of the total evaluation is selected in an iteration mode*As a coarse optimization result;
as shown in fig. 2, a basic flowchart of the coarse optimization process of the present invention includes the following specific steps:
1. setting a coarse optimization parameter, wherein the upper bound of a candidate angle threshold is 0 degree, the lower bound is 24 degrees, and the coarse optimization resolution is 1 degree;
2. based on the specified number 16 of radar beams, a candidate set of angular distributions is generated, the size of the set being about 7.4x105；
3. Setting optimization evaluation parameters, wherein the radar installation height h is set to be 2.0, and the region of interest is set to be ROI [5, 50%]Weight gamma of sub-target of near focusingdisSet one point of interest to μ in 1.0 (μ)focus_15.0, corresponding coefficient s120.0. Weight gamma of medium-long distance divergent sub-targetconSetting one focus point of interest to μ in ρ (μ) at 5.0focus_15.0, corresponding coefficient s1＝20.0；
4. Iteratively selecting the angle distribution of the wire harness, and calculating an evaluation value;
5. and outputting the highest evaluation value and the corresponding angle distribution of the wire harness as a coarse optimization result.
Step 4, fine optimization and tuning are carried out according to the result of the coarse optimization, and optimized radar wire harness distribution is obtained; fine optimization firstly sets an optimized step length, then takes a result of coarse optimization as initial estimation, and carries out fine adjustment optimization by using the fine optimization step length to obtain a final evaluation optimal result; for the laser beam angle distribution c obtained in the previous step*According to the specified fine optimization resolution, for c*The angle value of (1) is adjusted and substituted
Calculating an evaluation value, adjusting the iteration direction according to the evaluation value, and finally obtaining an optimization result c*；
As shown in fig. 3, a basic flowchart of the fine optimization processing procedure of the present invention is shown, and the specific operation steps are as follows:
1. setting fine optimization parameters, wherein the fine optimization resolution is 0.01 degrees;
2. introducing a coarse optimization result as an initial estimation;
3. adjusting the angle values in the angle distribution by taking the fine optimization resolution as a step length, and calculating an evaluation value;
4. adjusting the optimization direction and readjusting the angle distribution according to the evaluation value change in the step 3, and performing the step 3 until the evaluation value converges to the optimum value;
5. and (4) repeating the step (3) and the step (4) for each angle value in the angle distribution, and finally obtaining the optimal laser radar wire harness angle distribution.
And 5, carrying out simulation test and verification on the optimized laser radar. And carrying out simulation test and verification on the optimized laser radar. Because the existing mass production laser radar sensor in the market can not adjust the vertical direction light emission angle, the laser radar for customizing the angle distribution of the wire harness has long period and high cost, the method provides the simulation test and verification of the optimized laser radar in the automatic driving simulation environment. The simulation firstly realizes a laser radar sensor model in an automatic driving simulation environment, customizes the virtual radar according to an optimized wire harness distribution result, then sets a common driving scene, and performs data acquisition and algorithm test on the optimized and contrasted laser radar in the same scene, thereby improving the performance of the optimized laser radar according to the comparison of the algorithm result.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (4)
1. A laser radar beam distribution adjustment optimization method for an automatic driving scene is characterized by comprising the following steps:
s1, constructing a laser radar sensor wire harness model: defining a scanning horizontal corner variable of laser radar rotation according to a rotating structure of the multi-line laser radar sensor; according to the structure of a multi-transmitter in the vertical direction of the multi-line laser radar, defining the variable of vertical elevation distribution of a transmitting channel;
s2, aiming at the wiring harness distribution targets at different distances, constructing an optimized target evaluation function: aiming at short distance, establishing a sub-target function of beam divergence; aiming at the detection in the middle and long distances, establishing a sub-objective function of the beam focusing; aiming at a specific installation position of the laser radar, establishing a sub-target function for avoiding a blind area;
s3, adjusting optimization parameters to perform coarse optimization according to the perception task: setting an attention point in an interest area and the weight of each sub-target function according to a target detection task of actual automatic driving scene environment perception, and performing coarse optimization;
s4, performing fine optimization and tuning according to the result of the coarse optimization to obtain optimized radar wire harness distribution; fine optimization firstly sets an optimized step length, then takes a result of coarse optimization as initial estimation, and carries out fine adjustment optimization by using the fine optimization step length to obtain a final evaluation optimal result;
s5, carrying out simulation test and verification on the optimized laser radar;
wherein, the constructing of the optimization objective function in the step S2 specifically includes:
s21, the overall evaluation function is composed of a multi-target function and defined as:
wherein
To total optimization objective evaluation function, Fk(c) As a sub-target evaluation function, gammakAs its weight, c*Optimizing the obtained wire harness distribution result; the total evaluation is obtained by accumulating a plurality of weighted sub-target evaluation functions;
s22, considering the divergence of the line beam distribution in short-distance target detection, defining a sub-target function as follows:
wherein h is the installation height of the laser radar sensor,
evaluating the divergence of the beam distribution c of the ROI in the region of interest and assigning different weight values (μ) in different distances μ, the weight value function of the divergence being defined as:
μfocus_ito set a point of interest, siFor the weight scale coefficient corresponding to the focus point, (mu) at the set mufocus_iThe weight at the point of interest is minimized to control the divergence that maximizes the distribution of the line beam within certain specified areas of interest;
dis (μ, c, h) is an evaluation function for evaluating divergence of a laser beam distribution c, which is defined as:
where the I (μ, c, h) function counts and filters the laser beams that touch the μ vertical plane at a specified distance μ, the Dis (μ, c, h) function then calculates the Range of the beams and from the maximum maxRange (I (μ, c, h))minC, h)) carrying out normalization to obtain the divergence evaluation of the beam distribution c at the mu position;
s23, defining a second sub-target function as follows according to the focality of the line beam distribution in the target detection of the medium and long distance under consideration:
wherein h is the installation height of the laser radar sensor,
evaluating the focality of the beam distribution c of the ROI in the region of interest, and assigning different weight values rho (mu) in different distances mu, wherein the weight value function of the focality is defined as:
similar to the weight value function for the divergence of the line beam, ρ (μ) is at a set μfocus_iThe weighted value at the focus point is minimum so as to control and maximize the focality of the beam distribution in some specified areas;
con (μ, c, h) is an evaluation function for evaluating the focusability of the laser beam distribution c, which is defined as:
this function counts the number of beams in contact with the vertical plane at a distance mu and depends on the maximum value maxCount (I (mu) ()maxC, h)), and normalizing to obtain the focality evaluation of the beam distribution c at the mu position;
s24, besides considering divergence and focusing of the wiring harness distributed in certain areas, in the vicinity of the installation position, due to the limitation of the platform, the emitted laser beam may fall on a blind area formed by the installation platform, and in order to avoid waste caused by the laser beam falling in the blind area, the consideration of the limitation of the laser beam blind area is added, and the sub-objective functions are defined as follows:
the objective function
Adding a penalty weight for the laser beam falling within the Blind zone BZ, where h (μ) is a predefined Blind zone height at a distance μ, the weight function Blind (μ, c, h (μ)) being defined as follows:
the function consists of additive penalty values given by the light beams falling in the blind area, and the penalty values are calculated by a polynomial formula approximately limited as follows:
wherein o is the number of beams falling in the blind area, S is the proportionality coefficient of the set weight, and n is the polynomial order of the approximate limit.
2. The method as claimed in claim 1, wherein the step S1 defines a scanning horizontal rotation angle variable of the lidar rotation and a vertical elevation angle distribution variable of the transmission channel according to a horizontal rotation structure and a vertical multi-transmitter structure of the multi-line lidar sensor, and includes:
the laser radar sensor is provided with a motor which rotates in a horizontal plane to obtain a horizontal visual angle of 360 degrees; in the rotation with equal gaps, the laser radar emits laser light to perform scanning once, and the rotation angle sequence of the scanning is defined as:
rotation＝{θi，i＝0，1，...，m}
where m is the total number of horizontal rotation steps, θiIs the ith horizontal rotation angle; from the horizontalThe angular resolution of the acquisition determines:
due to the limitation of the motion structure, the laser radar is provided with different laser emission channels in the vertical direction, and the emission angle distribution is as follows:
wherein n is the number of vertical channels, betajAnd the beam distribution c of the laser radar is formed by combining different angles for the jth vertical laser beam channel angle.
3. The lidar beam distribution adjustment and optimization method for an automatic driving scene according to claim 2, wherein the coarse optimization distribution first generates a candidate angle value set by setting a coarse optimization resolution, taking the resolution as a step length, and from a set upper limit of the angle distribution to a set lower limit of the angle distribution; in the coarse optimization iteration process, selecting an angle value as a candidate combination according to the number of the specified laser radar lines in a candidate angle value set; for each candidate angle distribution combination, calculating evaluation value corresponding to the angle distribution
Then, the optimal angle combination c of the total evaluation is selected in an iteration mode*As a coarse optimization result.
4. The lidar beam distribution adjustment and optimization method for an autonomous driving scenario according to claim 3, wherein the step S4 specifically comprises: for the laser beam angle distribution c obtained in the previous step*According to the specified fine optimization resolution, for c*The angle value of (1) is adjusted and substituted
Calculating an evaluation value, adjusting the iteration direction according to the evaluation value, and finally obtaining an optimization result c*。
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