CN108508430B - Laser radar rotation control method for target detection - Google Patents

Laser radar rotation control method for target detection Download PDF

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CN108508430B
CN108508430B CN201810291619.0A CN201810291619A CN108508430B CN 108508430 B CN108508430 B CN 108508430B CN 201810291619 A CN201810291619 A CN 201810291619A CN 108508430 B CN108508430 B CN 108508430B
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laser radar
target
point cloud
detection
crank
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CN108508430A (en
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尹栋
李�杰
相晓嘉
李梦洁
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National University of Defense Technology
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/481—Constructional features, e.g. arrangements of optical elements
    • G01S7/4817—Constructional features, e.g. arrangements of optical elements relating to scanning
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/483—Details of pulse systems
    • G01S7/486—Receivers
    • G01S7/4868—Controlling received signal intensity or exposure of sensor

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  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Optical Radar Systems And Details Thereof (AREA)

Abstract

The invention discloses a laser radar rotation control method for target detection, which comprises the following steps: s1, installing a laser radar on an operation platform to form a detection system, and respectively acquiring the variation trend of point cloud distribution acquired by the operation platform at different operation speeds along with the variation of scanning speed of the laser radar according to the installation position information and the detection target position information of the laser radar in advance; s2, when the detection system detects a target, acquiring the running speed of the running platform in real time, acquiring the change trend of corresponding point cloud distribution according to the running speed acquired in real time, and determining the currently required laser radar scanning speed according to the acquired change trend of the point cloud distribution; and S3, controlling the laser radar to rotate according to the scanning speed of the laser radar determined in the step S2 to finish target detection. The method has the advantages of simple implementation method, rich point cloud data obtained by scanning, small working blind area, long effective detection distance and the like.

Description

Laser radar rotation control method for target detection
Technical Field
The invention relates to the technical field of target detection in an unmanned system, in particular to a laser radar rotation control method for target detection.
Background
The laser radar is used as a novel active ranging sensor, has high measurement precision and long detection distance, is not influenced by environmental illumination change, can quickly acquire target information complementary with an image, and is particularly suitable for detecting obstacles in an unmanned system. Pedestrian and vehicle detection is always a hotspot concerned in research fields such as intelligent traffic, unmanned automobiles, automobile safety auxiliary driving and the like, and the pedestrian detection based on visual information is easily influenced by illumination, target posture change and shielding, so that the detection precision is reduced; in a real complex traffic environment, the higher the precision of target detection and the longer the effective detection distance, the earlier the system obtains the early warning, and the longer the decision-making and control layer time is left during high-speed movement, so that the laser radar is carried in the unmanned system to realize the detection of the obstacle of the unmanned system.
Aiming at target detection of a laser radar, at present, research is usually conducted on how to utilize point cloud information obtained by the laser radar to realize accurate detection of obstacles, and the problem of quality of the obtained point cloud information is not researched and considered.
In order to make up the disadvantage of weak geometric shape information of a target obtained by a single line laser radar and improve the quality of point cloud data obtained by the laser radar, one method is to use a 2D laser radar or 3D laser scanning to realize uniform scanning, wherein, the 3D laser scanning usually comprises the steps of fixedly connecting a 2D laser radar and an IMU (inertial measurement unit) at one end of a spring, generating vibration by the dead weight of the 2D laser radar and the IMU at the head part of the spring, and then obtaining 3D point cloud by resolving the pose recorded by the IMU in real time, however, the scanning angle and speed are directly set to control the laser radar scanning in both the 2D scanning mode and the 3D scanning mode, the running speed of the carrier platform is not considered, however, the movement speed of the carrier platform can affect the swing scanning of the laser radar, so that the quality of point cloud obtained by controlling the scanning of the laser radar is still not high, and the effective detection distance of the system is affected; the other method is to interpolate the sparse point cloud data in the horizontal direction by using a RBF interpolation algorithm, and then adjust the density of the three-dimensional point cloud after being densified by using a resampling algorithm.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: aiming at the technical problems in the prior art, the invention provides the laser radar rotation control method which is simple in implementation method, rich in point cloud data obtained by scanning, small in working blind area and long in effective detection distance and is used for target detection.
In order to solve the technical problems, the technical scheme provided by the invention is as follows:
a laser radar rotation control method for target detection comprises the following steps:
s1, installing a laser radar on an operation platform to form a detection system, and respectively acquiring the variation trend of point cloud distribution acquired by the operation platform at different operation speeds along with the variation of scanning speed of the laser radar according to the installation position information and the detection target position information of the laser radar in advance;
s2, when the detection system detects a target, acquiring the running speed of the running platform in real time, acquiring the corresponding change trend of the point cloud distribution according to the running speed acquired in real time, and determining the currently required laser radar scanning speed according to the acquired change trend of the point cloud distribution;
and S3, controlling the laser radar to rotate according to the scanning speed of the laser radar determined in the step S2 to finish target detection.
As a further improvement of the present invention, the specific step of acquiring the variation trend of the point cloud distribution at different operating speeds in step S1 includes:
s11, pre-constructing a relation model between the total point cloud covering a detection target and the installation position information, the detection target position information, the running speed of a running platform and the scanning speed of the laser radar;
s12, respectively calculating the running speed of the running platform and the total number of point clouds covering the detection target when the scanning speed of the laser radar is different according to the relation model, the current installation position information of the laser radar and the position information of the detection target;
and S13, determining the change trend of the point cloud distribution according to the distribution state of the total point cloud number of each coverage detection target.
As a further improvement of the present invention, the specific steps of constructing the relationship model in step S11 are as follows:
s111, establishing a geometric relation between a detection target and the laser radar according to the installation position information, the scanning angle information and the detection target position information of the laser radar;
s112, constructing total scanning line number L covering detection targets according to the established geometric relationNMounting height H of laser radar, height T of detection target, and distance S between detection target and operation platformdThe relationship between them is LN＝fi(Sd,H,T,li) Wherein
Figure GDA0002473890380000021
S113, L total scanning lines according to the coverage targetNCalculating the total number P of single-frame point clouds covering the targetnumComprises the following steps:
Figure GDA0002473890380000022
wherein K is a reduction coefficient, NjThe number of points on each scan line covering the target;
s114, covering the total number P of the single-frame point clouds of the detection targetnumThe relationship model is constructed as follows:
Figure GDA0002473890380000031
Figure GDA0002473890380000032
Figure GDA0002473890380000033
wherein the content of the first and second substances,
Figure GDA0002473890380000034
total number of point clouds, V, covering the inspection targetcoThe relative movement speed of the running platform and the detection target,
Figure GDA0002473890380000035
in order to update the period for the data processing,
Figure GDA0002473890380000036
time required for collecting one frame of point cloud for laser radar, NfIs composed of
Figure GDA0002473890380000037
The number of point cloud frames covering the detection target obtained in the time period,
Figure GDA00024738903800000312
the pitch angular velocity scanned by the lidar.
As a further improvement of the present invention, the specific steps of step S12 are: taking the X axis as the point cloud frame number N of the coverage targetfThe Y axis corresponds to the distance S between the detection target and the operation platformdConstructing an XOY two-dimensional plane, and taking the Z-axis correspondence as the relative movement speed V of the operation platform and the detection targetcoThe relative movement speed V of the running platform and the detection targetcoDividing the XOY two-dimensional plane into multiple grids, and calculating the point cloud total number covering the detection target
Figure GDA0002473890380000038
Then, according to the calculated point cloud total number covering the detection target
Figure GDA0002473890380000039
Is marked in the corresponding grid.
As a further improvement of the invention, the specific steps for marking are as follows: if the calculated total point cloud number of the coverage target
Figure GDA00024738903800000310
Not less than the threshold T of the minimum number of data points required for detecting the targetnumIf not, adding a second mark; in step S13, the change trend of the point cloud distribution is determined according to the dense state of the first marker and the second marker.
As a further improvement of the present invention, the specific steps of determining the currently required laser radar scanning speed in step S2 are as follows: determining the slope in each XOY plane as
Figure GDA00024738903800000311
Intercept is the safety braking distance SsafeThe straight line of the laser radar scanning speed selection method is used as a safety braking condition curve, an area which is above the safety braking condition curve and is the first mark in the grid is used as a feasible area, and the corresponding laser radar scanning speed is selected from the feasible area according to the dense state of the first mark and is used as the currently required laser radar scanning speed.
As a further improvement of the present invention, the step S1 further includes a step of configuring a rocker mechanism with a crank without a snap-back characteristic for the lidar, and the step S3 drives the crank in the rocker mechanism to rotate in a single direction specifically according to the scanning speed of the lidar determined in the step S2, so as to control the lidar to rotate at the determined scanning speed.
As a further improvement of the invention, the specific steps of configuring the rocker mechanism with the crank without snap-back characteristic are as follows:
a crank rocker mechanism with a crank AB, a connecting rod BC, a rocker CD and a frame AD is configured;
determining the length relation among the crank AB, the connecting rod BC, the rocker CD and the frame AD and the angular velocity relation between the crank AB and the rocker CD so that the crank-rocker mechanism has a quick-return-free characteristic;
and determining the relation between the swing angle phi of the rocker CD and the position of the detection target so as to enable the crank-rocker mechanism to control the laser radar to rotate, wherein the laser beam covering the detection target is the most.
As a further improvement of the present invention, the length relationship is specifically: the sum of the squares of the lengths of the crank AB and the frame AD is equal to the sum of the squares of the lengths of the connecting rod BC and the rocker CD, i.e. the crank AB and the frame AD are connected by a connecting rod
Figure GDA0002473890380000041
And the length of the crank AB and the rocker CD and the swing angle phi between the crank AB and the rocker CD meet l1＝l3sin(φ/2)；
The angular velocity relationship is specifically:
Figure GDA0002473890380000042
wherein the content of the first and second substances,
Figure GDA0002473890380000043
is the angular velocity of the rocker CD and,
Figure GDA0002473890380000044
is the angular velocity of the crank AB and,
Figure GDA0002473890380000045
respectively are the included angles of the crank AB, the connecting rod BC, the rocker CD and the positive direction of the rack AD, and
Figure GDA0002473890380000046
Figure GDA0002473890380000047
wherein the coefficients A, B and C are respectively:
Figure GDA0002473890380000048
as a further improvement of the present invention, the relationship between the pivot angle Φ of the rocker CD and the detection target position specifically satisfies the following formula:
φ＝θU+θD；
wherein theta isUIs the elevation angle, theta, of the lidarDIs the angle of depression, omega, of a lidarmaxIs the maximum vertical scan angle of the laser beam, and
T>when the hydrogen content is H, the reaction is carried out,
Figure GDA0002473890380000049
when T is less than or equal to H, thetaU＝0，
Figure GDA00024738903800000410
T is the height of the detected target, H is the installation height of the laser radar, SdFor detecting the distance between the target and the running platform.
Compared with the prior art, the invention has the advantages that:
1) according to the invention, the laser radar is carried in the operation platform, the target point cloud information is acquired based on the periodic pitching scanning of the laser radar, the influence of the operation speed of the operation platform on the scanning of the laser radar is considered, and the rotation of the laser radar is controlled based on the operation speed of the operation platform, so that the accurate point cloud data acquisition can be realized by adapting to different operation conditions of the operation platform, more abundant point cloud data can be acquired, the problem of point cloud sparsity is solved, meanwhile, the working blind area is reduced, the effective detection distance of the system is improved, and more accurate target detection can be realized by abundant point cloud data.
2) According to the method, a relation model between the total point cloud covering the detection target and the installation position information of the laser radar, the detection target position information, the running speed of the running platform and the scanning speed of the laser radar is established, the total point cloud covering the detection target can be obtained through accurate calculation by combining the installation state of the laser radar, the detection target position state and the running state of the running platform, and the accurate point cloud distribution state can be obtained.
3) The invention further constructs an XOY plane by taking the number of point cloud frames with the X axis corresponding to the coverage target and the Y axis corresponding to the distance between the detection target and the operation platform, and takes the Z axis corresponding to the relative motion speed of the operation platform and the detection target, the corresponding XOY plane is respectively divided into a plurality of grids when the relative motion speed of the operation platform and the detection target takes a plurality of specified values, the point cloud total number of the corresponding coverage detection target in each grid is calculated and then marked in the corresponding grid, the point cloud change trend along with the change of the laser radar scanning speed is obtained by the marking statistical result of each grid, and the optimal laser radar scanning speed can be quickly and conveniently determined.
4) The invention further controls the laser radar to rotate by adopting the crank and rocker mechanism without the quick return characteristic, the control is simple to realize and the control precision is high, the system updating frequency, the pitching device angular speed and the pitching limit position are determined in the safe distance range, the quality of the remote target point cloud data acquisition can be further improved under the condition of ensuring safe driving, the number of laser points obtained by covering the target surface is the largest and the distribution is the most uniform, and the quick and accurate remote target detection can be realized.
5) The invention further utilizes the motion model and the rod length condition of the crank-rocker mechanism without the snap-back characteristic to obtain the relation between the laser radar pitch angle speed and the direct current motor rotating speed, the laser radar pitch angle speed is controlled by the running speed of the running platform, the rocker mechanism can be realized to realize the accurate control of the laser radar based on the snap-back characteristic, and the acquisition quality of point cloud data can be improved, so that the effective detection distance of the system is further improved.
Drawings
Fig. 1 is a schematic flow chart of an implementation of a laser radar rotation control method for target detection according to the present embodiment.
Fig. 2 is a schematic diagram of a lidar ranging model constructed in the embodiment.
Fig. 3 is a schematic diagram of the point cloud distribution results of pedestrians measured at different distances in the embodiment.
Fig. 4 is a schematic diagram of statistical results of the relationship between the number of the pedestrian point clouds and the distance between adjacent data points along with the distance obtained in the embodiment.
Fig. 5 is a schematic diagram illustrating a geometric relationship between a detection target and a lidar constructed in the present embodiment.
Fig. 6 is a schematic diagram of the principle of determining the relative movement speed and the system update period in the present embodiment.
Fig. 7 is a schematic view of a geometric model of the pitching mechanism constructed in the present embodiment.
Fig. 8 is a schematic diagram of the determination of the pitch limit in the present embodiment.
FIG. 9 is a schematic diagram of a simulated waveform of rotational speed obtained in an embodiment of the present invention.
FIG. 10 is a diagram illustrating a comparison result of the point clouds obtained in the embodiment of the present invention.
Detailed Description
The invention is further described below with reference to the drawings and specific preferred embodiments of the description, without thereby limiting the scope of protection of the invention.
As shown in fig. 1, the laser radar rotation control method for target detection in this embodiment includes the steps of:
s1, installing a laser radar in an operation platform to form a detection system, and respectively acquiring the variation trend of point cloud distribution acquired when the operation platform is at different operation speeds along with the variation of scanning speed of the laser radar according to the installation position information and the detection target position information of the laser radar in advance;
s2, when the detection system detects a target, acquiring the running speed of the running platform in real time, acquiring the change trend of corresponding point cloud distribution according to the running speed acquired in real time, and determining the currently required laser radar scanning speed according to the change trend of the point cloud distribution;
and S3, controlling the laser radar to rotate according to the scanning speed of the laser radar determined in the step S2 to finish target detection.
The embodiment carries the laser radar in the operation platform, collects the target point cloud information based on the periodic pitching scanning of the laser radar, considers the influence of the operation speed of the operation platform on the laser radar scanning, obtains the variation trend of the point cloud distribution along with the change of the laser radar scanning speed when the operation platform is at different operation speeds in advance, determines the required laser radar scanning speed by the real-time operation speed of the operation platform when the target is detected, can control the laser radar to rotate based on the operation speed of the operation platform, enables the operation platform to adapt to different operation working conditions of the operation platform to realize accurate point cloud data collection, can collect more abundant point cloud data compared with the traditional method of directly setting the scanning angle and speed of the laser radar, solves the problem of point cloud sparse, reduces the working blind area, improves the effective detection distance of the system, and can realize more accurate target detection by abundant point cloud data, the method is particularly suitable for detecting the obstacles in various motion states in the unmanned system.
In this embodiment, the specific step of obtaining the variation trend of the point cloud distribution at different operating speeds in step S1 includes:
s11, pre-constructing a relation model between the total point cloud covering a detection target and the installation position information of the laser radar, the position information of the detection target, the running speed of a running platform and the scanning speed of the laser radar;
s12, respectively calculating the total number of point clouds covering the detection target when the running speed of the running platform and the scanning speed of the laser radar are different values according to the relation model, the installation position information of the current laser radar and the position information of the detection target;
and S13, determining the change trend of the point cloud distribution according to the distribution state of the total number of the point clouds covering the detection targets.
According to the embodiment, the relation model between the total point cloud covering the detection target and the installation position information of the laser radar, the detection target position information, the running speed of the running platform and the scanning speed of the laser radar is built, the total point cloud covering the detection target can be obtained by combining the laser radar installation state, the detection target position state and the running state of the running platform, and accurate point cloud distribution state is obtained, so that the control accuracy of the laser radar is further improved.
In this embodiment, a laser radar scanning mathematical model is specifically established first, and a relationship between point cloud distribution on a detection target surface and a detection target shape and a location thereof is established according to the laser radar model to determine an influence of the point cloud distribution on target detection, and the detailed steps are as follows:
① laser radar mathematical modeling and remote target point cloud data characteristic analysis
In this embodiment, specifically using the V L P-16 lidar, the established V L P-16 lidar ranging model is shown in fig. 2, where fig. (a) is a lidar model, O-XYZ is a lidar coordinate system, fig. (b) is a top view, where α is a horizontal scanning angle, fig. (c) is a side view, where ω is a vertical scanning angle, there are 16 laser pulses distributed at equal angles on the YOZ plane and symmetric about the Y axis, the vertical scanning angle ω of each laser beam is a fixed value, and ρ is a distance from a data point to the center of the lidar, and a point (ρ, ω, α) in the polar coordinate system is converted to (X, Y, Z) in the cartesian coordinate system by using equation (1).
Figure GDA0002473890380000071
When the three-dimensional laser radar works, the laser beams are emitted outwards in a fan-shaped mode, the farther the target is away from the laser radar, the larger the distance between the adjacent laser beams is, and the more sparse the target point cloud is. In this embodiment, statistical analysis is specifically performed on 1020 actually measured pedestrian samples, and the statistical results are shown in fig. 3 and 4, where fig. 3 is point cloud distribution of pedestrians measured at different distances, fig. 4 is a variation relationship (laser radar operating frequency is 600rpm) between the obtained pedestrian point cloud distribution and a laser radar distance, where fig. 4(a) is a statistical relationship between the point cloud number of 1020 scanned pedestrians and a distance from the center of the laser radar, and fig. 4(b) is a statistical relationship between a distance between adjacent data points and a distance from the adjacent data points to the laser radar, where HAG represents a horizontal average interval between adjacent laser beams, and SAG represents an average interval between adjacent scanning beams. As can be seen from fig. 3 and 4, the farther the target is from the laser radar, the fewer the number of points covering the target and the more sparsely the target is distributed, and the interval between adjacent data points in the horizontal direction and the adjacent scanning in the vertical directionThe greater the spacing between lines, i.e. the farther the target is from the lidar, the number of scan lines covering the target LNAnd the number of data points PnumThe fewer adjacent laser beams are spaced apart by X in the horizontal and vertical directionsg,YgThe larger the point cloud of the target surface acquired by the laser radar is, the more sparse the point cloud of the target surface is.
② model construction of total number of point clouds covering detection target
In this embodiment, three preconditions are specifically set:
(1) the radar is horizontally arranged, and the targets are in contact with the ground and are vertical to the ground;
(2) the target can be surrounded by a minimal cube with length L, width W and height T, and the length and width of the cube are two interchangeable concepts considering the change of the target pose;
(3) when the laser radar works, the time interval of emission between adjacent laser beams is 2.304us, which is far less than the minimum scanning period of the laser radar and can be ignored, and during actual calculation, 16 laser beams are supposed to be emitted simultaneously.
As shown in FIG. 5, the present embodiment first constructs a geometric relationship between the detection target and the lidar, where |, nαIs a scanning plane of vertical direction, omega1,ω2For two adjacent laser beams and YαThe included angle between the axes is that in a radar coordinate system OXYZ, the coordinate of a point P is (X, Y, Z), and P' is the projection of the point P in an XOY plane, so that the distance between a target and the laser radar is
Figure GDA0002473890380000072
FIG. 5(b) shows IIαSchematic plan development, where ωmaxAt the maximum vertical scan angle, H is the lidar mounting height (lidar height from ground), li(i-1, 2) represents a straight line where PP' is located in fig. 5(b), and l may be defined according to a magnitude relationship between the laser radar installation height H and the target height TiThe following two cases are distinguished:
Figure GDA0002473890380000073
when detecting the eyeWhen the standard height T is more than or equal to the installation height H of the laser radar, namely T is more than or equal to H, the number L of the scanning lines covering the target can be obtainedNComprises the following steps:
Figure GDA0002473890380000081
when the height T of the detected target is less than the installation height H of the laser radar, namely T is less than H, the number of the scanning lines covering the target is LNComprises the following steps:
Figure GDA0002473890380000082
wherein floor (-) and atan (-) are negative infinite integral function and arctangent function, omega, respectively△2 degrees is the included angle of the adjacent laser beams in the vertical direction,
Figure GDA0002473890380000083
from the above, the total number of scanning lines covering the target LNIs formed by the installation height H of the laser radar, the height T of a detected target and the relation l between the twoi(i 1,2) and the distance S between the detection target and the lidardIf it is determined, the following expressions (2) to (4) can be comprehensively written:
LN＝fi(Sd,H,T,li) (5)
wherein li(i-1, 2) corresponds to fiSpecific expression of (·).
Because the included angle between two adjacent laser beams in the horizontal direction of the laser radar is determined by the rotating speed of the internal rotating motor, the rotating speed of the internal rotating motor is set as n, the unit is r/s, the time period from the complete emission of the first group of laser beams to the complete emission of the second group of laser beams is △ t, and then the included angle α between two adjacent laser beams in the horizontal direction is set as α△360n △ t. as shown in fig. 5(a), the minimum horizontal scan angle of the laser beam covering the target in the horizontal direction is αminMaximum horizontal scan angle of αmaxInterval △ between themα＝αmax-αminNumber of points per scanning line covering the detection target
Figure GDA0002473890380000084
The total number of points P covering the detection targetnumComprises the following steps:
Figure GDA0002473890380000085
and K is a reduction coefficient, the value can be the percentage of the area of the target in the minimum rectangular area surrounding the target, the change of the target relative to the attitude of the laser radar is considered, and the specific value can be 1.5-2.0.
According to the geometric model of the laser radar, the horizontal interval X between two adjacent laser beamsgAnd a vertical spacing YgRespectively as follows:
Figure GDA0002473890380000086
wherein Dn,t,Dn,t+△tRespectively, the distance from the nth laser beam to the target at the time t, t + △ t in the horizontal direction, Dn,t,Dn+1,tRespectively, the distances from two laser beams n, n +1 adjacent to each other in the vertical direction to the target at time t.
Suppose that the unmanned vehicle is t ═ t1At a time S ahead of itdisThe rice has a moving target for a period of time thereafter
Figure GDA0002473890380000087
NfRespectively covering the total number of data points of the target and the number of point cloud frames obtained by the data points, covering the total number P of single-frame point clouds of the detected targetnumAs shown in the above equation (6), the total number of points covering the detection target in the time period
Figure GDA0002473890380000091
Comprises the following steps:
Figure GDA0002473890380000092
wherein, Pnum,kPoints representing the collected k frame point cloud, VcoFor the relative movement speed of the operation platform and the detection target,
Figure GDA0002473890380000093
in order to update the period for the data processing,
Figure GDA0002473890380000094
time required for collecting one frame of point cloud for laser radar, NfIs composed of
Figure GDA0002473890380000095
And the number of point cloud frames covering the detection target is obtained in the time period. After the minimum cube surrounding the target, the lidar mounting height H and the frame rate at which it operates are determined, l can be determined from equations (3) to (5)iValue of and fiSpecific expression (c).
According to the working principle of the laser radar, one frame of point cloud data can be obtained when the internal motor of the laser radar rotates for one circle, namely the frame rate acquired by the laser radar is equal to the rotating speed n of the internal rotating motor, and the unit is r/s, the time taken by the laser radar to acquire one frame of point cloud
Figure GDA0002473890380000096
System data processing update cycle
Figure GDA0002473890380000097
In order to ensure that the data points covering the target are distributed as uniformly as possible, a system update period is provided
Figure GDA0002473890380000098
The lidar performing a pitching movement over time, i.e.
Figure GDA0002473890380000099
Figure GDA00024738903800000910
The pitch angular velocity scanned by the lidar.
According to the method, a relation model between the total point cloud covering the detection target and the installation position information of the laser radar, the position information of the detection target, the running speed of the running platform and the scanning speed of the laser radar can be obtained, so that the relation between the point cloud distribution on the surface of the target and the shape and the direction of the target can be obtained. Namely, the specific steps of constructing the relationship model in step S11 are as follows:
s111, establishing a geometric relation between a detection target and the laser radar according to the installation position information, the scanning angle information and the detection target position information of the laser radar;
s112, constructing total scanning line number L covering detection targets according to the established geometric relationNMounting height H of laser radar, height T of detection target, and distance S between detection target and operation platformdThe relationship between them is LN＝fi(Sd,H,T,li) Wherein
Figure GDA00024738903800000911
S113, L total scanning lines according to coverage targetsNCalculating the total number P of single-frame point clouds covering the targetnumSpecifically, as shown in the above formula (6);
s114, covering the total number P of single-frame point clouds of the detection targetnumThe relationship model is constructed as follows:
Figure GDA00024738903800000912
Figure GDA00024738903800000913
Figure GDA00024738903800000914
in this embodiment, the specific steps of step S12 are as follows: number of point cloud frames N with X-axis correspondence as coverage targetfThe Y axis corresponds to the distance S between the detection target and the running platformdConstruction of XOY blocksSurface and relative movement speed V of the operation platform and the detection target corresponding to the Z axiscoThe relative movement speed V of the running platform and the detection targetcoDividing XOY plane corresponding to multiple values into multiple grids, and calculating point cloud total number covering detection target in each grid
Figure GDA0002473890380000101
Then, according to the total point cloud number covering the detection target obtained by calculation
Figure GDA0002473890380000102
Is marked in the corresponding grid. By the above-mentioned mode, the relative movement speed V is correspondedcoThe marking statistical result of each grid in the XOY plane can obtain the point cloud change trend along with the change of the scanning speed of the laser radar, so that the required scanning speed of the laser radar can be quickly and conveniently determined to solve the problem of point cloud sparsity.
In this embodiment, the specific steps for marking are as follows: if the calculated total point cloud number covering the target
Figure GDA0002473890380000103
Not less than the threshold T of the minimum number of data points required for detecting the targetnumIf not, adding a second mark, and marking whether the threshold value T is not less than the minimum data point number by using the first mark and the second marknumTotal number of point clouds of condition
Figure GDA0002473890380000104
Meanwhile, the density of the point cloud distribution can be further determined according to the statistical results of the first mark and the second mark; in step S13, the change trend of the point cloud distribution can be determined according to the states of the first marker and the second marker.
Relative velocity of motion V obtained in an embodiment of the inventioncoAnd the system data processing update period TsThe relationship is shown in FIG. 6, wherein the X, Y and Z axes respectively represent the number of the accumulated point cloud frames NfDetecting the targetDistance S from running platformdisAnd relative movement velocity Vco，VcoThe value of (A) determines the number of layers of the image, and a system parameter of (N) is recorded in each square in the XOY plane of each layerf,Sdis,Vco) Total number of point clouds covering the detected object
Figure GDA0002473890380000105
If it is
Figure GDA0002473890380000106
More than or equal to the threshold value T of the minimum number of data points required for detecting the targetnumThe square uses the first mark and the greater the number of the first marks indicates
Figure GDA0002473890380000107
The greater the value, if
Figure GDA0002473890380000108
A second marker is used.
In this embodiment, the specific steps of determining the currently required laser radar scanning speed in step S2 are as follows: determining the slope in each XOY plane as
Figure GDA00024738903800001011
Intercept is the safety braking distance SsafeThe straight line is used as a safety braking condition curve, an area which is above the safety braking condition curve and is a first mark in the grid is taken as a feasible area, and the corresponding laser radar scanning speed is selected from the feasible area according to the dense state of the first mark to be used as the currently required laser radar scanning speed.
The operation platform of the embodiment is specifically an unmanned vehicle, and in order to ensure that the unmanned vehicle safely runs on a road, the detection distance S of the detection system is specifically configuredfindGreater than the braking safety distance S of the vehiclesafeAssuming that the minimum number of data points required for accurately detecting the target is TnumMeanwhile, the emergency braking condition is considered, so that the condition that the detection distance of the system is more than or equal to the system data updating process is met when the vehicle safely runsThe sum of the driving distance of the automobile and the safety braking distance is as follows:
Figure GDA0002473890380000109
as shown in fig. 6, each layer XOY plane corresponds to only one straight line, i.e. a safety braking condition curve, and the slope of the straight line is
Figure GDA00024738903800001010
Intercept is the safety braking distance SsafeThe area above the safety braking condition curve is the area meeting the safety braking condition, and the safe driving of the vehicle is ensured in the area. The embodiment specifically takes the safe braking condition curve and the minimum data point TnumAs a constraint condition, when a safety braking condition is met, the total number of point clouds covering the detection target
Figure GDA0002473890380000111
Not less than the minimum number of data points TnumAs feasible region, finally determining the optimal V according to the point cloud distribution state in feasible regioncoAnd NfThe required scanning speed of the laser radar can be determined, the quality of the collected point cloud can be ensured while the safe driving is ensured, the defect that the three-dimensional laser radar is weak in obtaining the geometric shape information of the surface of the remote target is overcome, and the accurate detection of the obstacle in the safe distance is realized.
When V is shown in FIG. 6coThe larger the value is, the larger the slope of the straight line is, the number of the first marks meeting the constraint condition is reduced but the number of the first marks is increased, the value of the green grid area at the upper left corner of the straight line in the graph is a feasible area meeting the constraint equation, and the optimal V can be selected in the area according to the actual application requirementcoAnd NfAt this time, the system data processing update cycle
Figure GDA0002473890380000112
In this embodiment, step S1 further includes configuring a rocker mechanism with a crank having a snapback-free characteristic for the lidar, that is, controlling the rotation of the lidar by a pitch mechanism, and step S3 drives the crank in the rocker mechanism to rotate in a single direction according to the scanning speed of the lidar determined in step S2, so as to control the rotation of the lidar according to the scanning speed of the lidar determined in step S2. The laser radar is controlled to rotate by adopting the crank rocker mechanism without the quick return characteristic as the pitching mechanical device, the control is simple to realize, the control precision is high, the quality of remote target point cloud data acquisition can be further improved under the condition of ensuring safe driving, and the rapid and accurate remote target detection can be realized.
In this embodiment, the specific steps of the configuration of the rocker mechanism in step S1 are as follows:
a crank rocker mechanism with a crank AB, a connecting rod BC, a rocker CD and a frame AD is configured;
determining the length relationship among the crank AB, the connecting rod BC, the rocker CD and the rack AD and the angular velocity relationship between the crank AB and the rocker CD so that the crank-rocker mechanism has a quick-return-free characteristic;
and determining the relationship between the swing angle phi of the rocker and the height and the position of the target so as to enable the crank-rocker mechanism to control the laser radar to rotate and cover the laser beam of the target at most.
In order to realize accurate detection of obstacles in a safe distance, the crank-rocker mechanism without snap-back characteristic of the embodiment is shown in fig. 7, wherein a diagram (a) is a crank-rocker mechanism, and a diagram (b) is a coordinate transformation principle; the crank AB, the connecting rod BC, the rocker CD, the frame AD and the length are respectively l1，l2，l3，l4When the crank AB is used as a driving part and the included angle of the polar position is equal to zero, the crank rocker mechanism has no quick return characteristic, the forward stroke and the return stroke of the rocker are equal, namely the reciprocating motion speeds of the rocker are equal. As shown in fig. 7(a), the lidar may rotate around the pin D, | | OD | | | | l |, and0the value of the rocker is equal to the sum of the height between the center of the laser transmitter and the bottom surface of the laser radar and the radius of the pin shaft, and DC 'are two limit positions where the rocker DC is located when the crank AB is located on B' and the connecting rod BC are collinear twice.
In this embodiment, the length relationship is specifically: the length square sum of the crank AB and the frame AD is equal to the connecting rod BC and the swingThe sum of squares of the lengths of the rods CD, i.e.
Figure GDA0002473890380000113
And the lengths of the crank AB and the rocker CD and the swing angle phi between the crank AB and the rocker CD satisfy l1＝l3sin(φ/2)；
The angular velocity relationship is specifically:
Figure GDA0002473890380000121
wherein the content of the first and second substances,
Figure GDA0002473890380000122
is the rocker angular velocity, is the crank angular velocity,
Figure GDA0002473890380000123
the coefficients A, B, C are respectively:
Figure GDA0002473890380000124
Figure GDA0002473890380000125
respectively are the included angles of the crank, the connecting rod and the rocker with the positive direction of the frame.
Through the configuration, the crank rocker mechanism meets the no-snap-back characteristic.
As shown in FIG. 7(b), the lidar is driven by the crank-rocker mechanism to make periodic pitching motions in the YOZ plane, and the data point P measured by the lidar can be represented as P (ρ, ω, α, θ), where P is
Figure GDA0002473890380000126
Assuming that the position of the joystick at time t is 0 is as shown in fig. 7(a), the lidar coordinate system is a world coordinate system, and the data point obtained at any time in the pitching process can be calculated by equation (11) as (X) in the world coordinate systemW,YW,ZW) Coordinates are as follows:
Figure GDA0002473890380000127
wherein S (. cndot.), C (. cndot.), and S (. cndot.), respectively represent sin (. cndot.), and cos (. cndot.).
In order to ensure that the laser beam covering the target is the most, the embodiment is used for the maximum elevation angle theta when the laser radar moves in a pitching modeUAngle of depression thetaDThe relation with the detection target is as follows: 1) when the crank-rocker mechanism is at the pitch limit position, the maximum vertical scanning angle omega is providedmaxRespectively covering the highest point and the lowest point of the target; 2) distance l between laser radar coordinate origin and pin shaft D0And is negligible. The geometric relationship between the limit position of the pitching motion and the detection target is shown in fig. 8, where PP 'is the target, the height | | | PP' | | | | T, and the distance of the detection target from the laser radar | | | O 'P' | | SdH is the installation height of the laser radar, then when T>H, in △ OCP, ∠ POC ═ θU-ωmaxThe tangent value is:
Figure GDA0002473890380000128
wherein, ω ismaxThe maximum vertical scan angle for the laser beam is 15 deg. the same relationship can be found in △ OCP':
Figure GDA0002473890380000129
the swing angle phi of the rocker is as follows:
φ＝θU+θD(14)
when T is less than or equal to H, namely when the installation height of the radar is greater than the target height, the elevation angle theta of the laser radarUWhen the depression angle is calculated by equation (13) at 0, the relationship between the swing angle of the rocker and the height and position of the detection target can be obtained by equations (12) to (14).
Length l of rocker in embodiments of the invention372.87mm, detection target height T2 m, when laser radar mounting height took different values, to long-distance target, laser radar's mounting height influence was little, along with the increase of distance, the pivot angle of rockerThe change is smaller and gradually flattens. In the embodiment, the system updating frequency, the pitching device angular velocity and the pitching limiting position are determined in the safe distance range by the method, so that the number of laser points obtained by covering the target surface is the largest and the laser points are distributed most uniformly. The swing angle of the rocker can be 33 degrees, which can meet the requirement of the unmanned system on the detection of the remote target.
In the embodiment, a direct current motor is specifically adopted to drive the crank to rotate in one direction, and after the length of each rod is determined, the angular speed of the crank can be calculated by using a formula (10)
Figure GDA0002473890380000131
Timing the angular velocity of the rocker
Figure GDA0002473890380000132
In order to ensure that the data points covering the detection target are distributed as uniformly as possible, a system updating period is specified
Figure GDA0002473890380000133
Within the time, the laser radar finishes one pitching motion, namely, the crank is controlled to rotate for one circle, and if the motor rotates at a constant speed, the laser radar controls the crank to rotate for one circle
Figure GDA0002473890380000134
From formula (10):
Figure GDA0002473890380000135
the relation between laser radar pitch angle speed and direct current motor rotational speed is obtained to this embodiment utilization no quick return characteristic crank rocker mechanism's motion model and pole length condition, by operation platform's operating speed control laser radar pitch angle speed, can realize the accurate control that rocker mechanism realized laser radar based on no quick return characteristic, can improve the collection quality that increases point cloud data and then the effective detection distance of lift system.
In order to meet the requirements of stepless smooth speed regulation and excellent dynamic and static performances of the rotating tripod head within a certain range, the embodiment specifically adopts a direct-current double-closed-loop PI speed regulation system, the speed regulation is carried out by regulating the armature voltage, and the rotating speed of the motor is regulated by the direct-current motor double-closed-loop PI speed regulation system, so that the control of the laser radar rotating tripod head is realized. Under the condition of constant excitation, the mathematical model of the direct current motor is as follows:
Figure GDA0002473890380000136
wherein, the back electromotive force E of the motor is Cen, electromagnetic torque Te＝Cmid，TlFor load torque, GD2For converting the moving part of the motor drive system into the moment of inertia, U, on the motor shaftd,idR, L are armature voltage, armature return current, total resistance and inductance, C, respectivelye,CmMotor potential constant and torque constant, respectively.
In order to verify the effectiveness of the control method, the embodiment further performs simulation verification on the rotation control effect of the laser radar by constructing a direct current motor double closed loop speed regulation model and a crank rocker mechanism motion model by using Simulink, wherein a direct current chopper circuit is introduced into the direct current motor double closed loop speed regulation simulation model by a speed regulation system, armature voltage speed regulation is changed by controlling the duty ratio of PWM, and parameters of each module are set according to practical application, and the obtained simulation result is shown in FIG. 9, and can be known from the simulation result that the rotating speed of the motor reaches a steady-state rotating speed in about 0.3s under the condition of constant load, the simulation rotating speed is very close to a given rotating speed, the overshoot is very small, and the practical application can be met; as shown in fig. 10, the lengths of the components of the crank-rocker mechanism employed in the present embodiment are: crank l120.70mm, connecting rod l290.00mm, rocker l372.87mm, frame l4113.94mm, the horizontal installation height H of laser radar is 0.95m, the working speed n of internal rotary motor is 20r/s, the height T of pedestrian is 1.65m, and the crank rotates at angular speed
Figure GDA0002473890380000141
Rotating at a constant speed; through calculation, the laser radar can complete one-time scanning of the human body within 1ms, and the method can be used for scanning the human bodyIn the process, the radar pitch angle theta is less than 1 degree, so that the human body scanning line can be approximately considered to be horizontal, and the distance S between the pedestrian and the laser radar is shown in fig. 10(a)d1.5m, relative speed V of unmanned vehiclecoWhen the point cloud is 0, the human body point cloud is compared with the human body point cloud of the pitching device, and V is shown in fig. 10(b) and (c)co＝30km/s,SdWhen the point cloud of the human body is 10m or 20m, the point cloud of the human body is compared after the pitching device is introduced, and fig. 10(d), (e) and (f) respectively show Vco＝50km/s,SdWhen the human body point cloud is 10m,20m and 30m, human body point cloud comparison after the pitching device is introduced.
As can be seen from fig. 10(a), the pedestrian point clouds become dense and the information amount becomes rich after the pitching mechanical device is introduced, and fig. 10(b) to (f) are point cloud comparisons at two motion speeds by introducing the pitching device, and the rocker angular velocity
Figure GDA0002473890380000142
The value of (2) is positively correlated with the relative motion speed of the unmanned platform, namely the faster the motion speed is, the shorter the system data updating period is, the larger the swing angular speed of the laser radar is, and in one system data updating period
Figure GDA0002473890380000143
The distance between the point cloud scanning lines is shortened along with the shortening of the relative distance between the target and the motion platform, the point cloud quality is obviously improved, and the method is well suitable for the running speed of the platform. By adopting the control method of the embodiment, under different motion states of the unmanned platform, sparse point cloud on the surface of a remote target is effectively improved, and effective detection distance for ensuring safe operation of the unmanned platform is increased.
The foregoing is considered as illustrative of the preferred embodiments of the invention and is not to be construed as limiting the invention in any way. Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Therefore, any simple modification, equivalent change and modification made to the above embodiments according to the technical spirit of the present invention should fall within the protection scope of the technical scheme of the present invention, unless the technical spirit of the present invention departs from the content of the technical scheme of the present invention.

Claims (9)

1. A laser radar rotation control method for target detection is characterized by comprising the following steps:
s1, installing a laser radar on an operation platform to form a detection system, and respectively acquiring the variation trend of point cloud distribution acquired by the operation platform at different operation speeds along with the variation of scanning speed of the laser radar according to the installation position information and the detection target position information of the laser radar in advance;
s2, when the detection system detects a target, acquiring the running speed of the running platform in real time, acquiring the corresponding change trend of the point cloud distribution according to the running speed acquired in real time, and determining the currently required laser radar scanning speed according to the acquired change trend of the point cloud distribution;
s3, controlling the laser radar to rotate according to the scanning speed of the laser radar determined in the step S2 to complete target detection;
the specific step of obtaining the variation trend of the point cloud distribution at different operating speeds in step S1 includes:
s11, pre-constructing a relation model between the total point cloud covering a detection target and the installation position information, the detection target position information, the running speed of a running platform and the scanning speed of the laser radar;
s12, respectively calculating the running speed of the running platform and the total number of point clouds covering the detection target when the scanning speed of the laser radar is different according to the relation model, the current installation position information of the laser radar and the position information of the detection target;
and S13, determining the change trend of the point cloud distribution according to the distribution state of the total point cloud number of each coverage detection target.
2. The lidar rotation control method for object detection according to claim 1, wherein the specific steps of constructing the relationship model in step S11 are as follows:
s111, establishing a geometric relation between a detection target and the laser radar according to the installation position information, the scanning angle information and the detection target position information of the laser radar;
s112, constructing total scanning line number L covering detection targets according to the established geometric relationNMounting height H of laser radar, height T of detection target, and distance S between detection target and operation platformdThe relationship between them is LN＝fi(Sd,H,T,li) Wherein
Figure FDA0002473890370000011
S113, L total scanning lines according to the coverage targetNCalculating the total number P of single-frame point clouds covering the targetnumComprises the following steps:
Figure FDA0002473890370000012
wherein K is a reduction coefficient, NjThe number of points on each scan line covering the target;
s114, covering the total number P of the single-frame point clouds of the detection targetnumThe relationship model is constructed as follows:
Figure FDA0002473890370000021
Figure FDA0002473890370000022
Figure FDA0002473890370000023
wherein the content of the first and second substances,
Figure FDA0002473890370000024
total number of point clouds, V, covering the inspection targetcoThe relative movement speed of the running platform and the detection target,
Figure FDA0002473890370000025
in order to update the period for the data processing,
Figure FDA0002473890370000026
time required for collecting one frame of point cloud for laser radar, NfIs composed of
Figure FDA0002473890370000027
The number of point cloud frames covering the detection target obtained in the time period,
Figure FDA0002473890370000028
the pitch angular velocity scanned by the lidar.
3. The lidar rotation control method for object detection according to claim 2, wherein the specific steps of step S12 are: taking the X axis as the point cloud frame number N of the coverage targetfThe Y axis corresponds to the distance S between the detection target and the operation platformdConstructing an XOY two-dimensional plane, and taking the Z-axis correspondence as the relative movement speed V of the operation platform and the detection targetcoThe relative movement speed V of the running platform and the detection targetcoDividing the XOY two-dimensional plane into multiple grids, and calculating the point cloud total number covering the detection target
Figure FDA0002473890370000029
Then, according to the calculated point cloud total number covering the detection target
Figure FDA00024738903700000210
Is marked in the corresponding grid.
4. The lidar rotation control method for object detection according to claim 3, wherein the marking comprises: if the calculated stationThe total number of point clouds covering the target
Figure FDA00024738903700000211
Not less than the threshold T of the minimum number of data points required for detecting the targetnumIf not, adding a second mark; in step S13, the change trend of the point cloud distribution is determined according to the dense state of the first marker and the second marker.
5. The lidar rotation control method for object detection according to claim 4, wherein the specific steps of determining the currently required lidar scanning speed in step S2 are: determining the slope in each XOY plane as
Figure FDA00024738903700000212
Intercept is the safety braking distance SsafeThe straight line of the laser radar scanning speed selection method is used as a safety braking condition curve, an area which is above the safety braking condition curve and is the first mark in the grid is used as a feasible area, and the corresponding laser radar scanning speed is selected from the feasible area according to the dense state of the first mark and is used as the currently required laser radar scanning speed.
6. The lidar rotation control method for object detection according to any of claims 1 to 5, wherein the step S1 further comprises a step of configuring a rocker mechanism with a crank having a snapback-free characteristic for the lidar, and the step S3 drives the crank in the rocker mechanism to rotate in one direction specifically according to the lidar scanning speed determined in the step S2, so as to control the lidar to rotate at the determined scanning speed.
7. The lidar rotation control method for object detection according to claim 6, wherein the specific step of configuring the rocker mechanism with a crank having no snap-back characteristic is:
a crank rocker mechanism with a crank AB, a connecting rod BC, a rocker CD and a frame AD is configured;
determining the length relation among the crank AB, the connecting rod BC, the rocker CD and the frame AD and the angular velocity relation between the crank AB and the rocker CD so that the crank-rocker mechanism has a quick-return-free characteristic;
and determining the relation between the swing angle phi of the rocker CD and the position of the detection target so as to enable the crank-rocker mechanism to control the laser radar to rotate, wherein the laser beam covering the detection target is the most.
8. The lidar rotation control method for object detection according to claim 7,
the length relationship is specifically as follows: the sum of the squares of the lengths of the crank AB and the frame AD is equal to the sum of the squares of the lengths of the connecting rod BC and the rocker CD, i.e. the crank AB and the frame AD are connected by a connecting rod
Figure FDA0002473890370000031
And the length of the crank AB and the rocker CD and the swing angle phi between the crank AB and the rocker CD meet l1＝l3sin(φ/2)；
The angular velocity relationship is specifically:
Figure FDA0002473890370000032
wherein the content of the first and second substances,
Figure FDA0002473890370000033
is the angular velocity of the rocker CD and,
Figure FDA0002473890370000034
is the angular velocity of the crank AB and,
Figure FDA0002473890370000035
respectively are the included angles of the crank AB, the connecting rod BC, the rocker CD and the positive direction of the rack AD, and
Figure FDA0002473890370000036
Figure FDA0002473890370000037
wherein the coefficients A, B and C are respectively:
Figure FDA0002473890370000038
9. the lidar rotation control method for target detection according to claim 7 or 8, wherein a relationship between a pivot angle Φ of the rocker CD and a detection target position specifically satisfies the following equation:
φ＝θU+θD；
wherein theta isUIs the elevation angle, theta, of the lidarDIs the angle of depression, omega, of a lidarmaxIs the maximum vertical scan angle of the laser beam, and when T>When the hydrogen content is H, the reaction is carried out,
Figure FDA0002473890370000039
when T is less than or equal to H, thetaU＝0，
Figure FDA00024738903700000310
T is the height of the detected target, H is the installation height of the laser radar, SdFor detecting the distance between the target and the running platform.
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