CN113703002B - Road condition analysis method based on laser radar measurement data - Google Patents
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/02—Systems using the reflection of electromagnetic waves other than radio waves
- G01S17/06—Systems determining position data of a target
- G01S17/08—Systems determining position data of a target for measuring distance only
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Abstract
The invention discloses a road condition analysis method based on laser radar measurement data, wherein the laser radar is arranged at the front upper part of a helmet, the detection direction is set to be the front lower part, the helmet is provided with a horn, a charging interface and a switch button, a controller is arranged in the helmet and comprises a processor, a vibrator connected with the processor, the switch button and the horn are connected with the processor, a sensor coordinate system XYZ and a world coordinate system XYZ are established at the central position of the laser radar, a Y axis is overlapped with a Y axis, the X axis points to the front and forms a beta-angle with the X axis, and the Z axis is vertically upwards, and the processor is used for realizing the road condition analysis method and comprises the following steps: the processor reads data f k (i, j) output by the laser radar and converts the data into a point [ X ij k,Yij k,Zij k]‑1 ] in a world coordinate system; searching for an obstacle in a set formed by the points [ X ij k,Yij k,Zij k]‑1 ] and extracting obstacle information; and carrying out obstacle prompt.
Description
Technical Field
The patent relates to a road condition analysis method based on laser radar measurement data, which belongs to the technical field of sensor data processing and artificial intelligence.
Background
The laser radar is based on a laser ranging principle, measures the distance between a sensor and an object, can rotate for a certain angle in the horizontal direction and the vertical direction, realizes 3D detection, has the advantages of high detection speed, high resolution and high ranging precision, and therefore, the laser radar enters the fields of automatic driving of automobiles and autonomous navigation of robots, and becomes an indispensable detection means for obstacle detection and obstacle avoidance. Meanwhile, with the development of society and the improvement of living standard, people with vision disorder are very urgent to walk out of the familiar living space, and can go out for shopping, walk and social interaction normally, but due to the deficiency of vision function, the vision disorder people are very easy to fall down in the advancing process, and serious injury can be caused.
Disclosure of Invention
To above-mentioned problem, this patent is in order to satisfy the wish that vision disorder personnel go out, provides a road conditions analysis method based on laser radar measured data, according to the detected data, analysis road conditions, discernment concave region and protruding barrier to report and remind, provide the safety guarantee for the vision disorder personnel trip.
The technical scheme that this patent adopted to solve its technical problem is:
The road condition analysis method based on laser radar measurement data is characterized in that the laser radar is arranged at the front upper part of a helmet, the detection direction is set to be the front lower part, voice broadcast horns are arranged at the two sides of the helmet, a charging interface and switch keys are arranged on the side face of the helmet, a controller is arranged in the helmet, the controller comprises a processor for centralized control, a vibrator which is connected with the processor and consists of a flat motor, and further comprises a charging circuit which is connected with the charging interface, the output of the charging circuit is connected with a rechargeable battery, the output of the rechargeable battery is connected with a power circuit, the power circuit outputs power required by the controller and other modules, and the laser radar, the switch keys and the horns are connected with the processor; the laser radar is used for detecting the condition of the ground in front, a sensor coordinate system XYZ is established at the central position, an X-axis points to the detection central direction of the laser radar and forms a beta-included angle with the horizontal direction, a Y-axis points to the left, a world coordinate system XYZ is established at the same time, the Y-axis is combined with the Y-axis, the X-axis points to the front, the Z-axis points to the vertical direction, the laser radar outputs data f k(i,j)＝{(dk ij,αi, j.theta) }, wherein k=0, 1,2 is the detected sequence number, alpha i is the detection angle of the laser radar in the vertical direction, i is the data sequence number in the vertical direction, i=0, 1,2 is the line number of the laser radar, j is the data sequence number in the horizontal direction, j=0, 1,2 is the detected angle increment of the laser radar in the horizontal direction, and the processor is used for realizing the road condition analysis method, and the road condition analysis method comprises the following steps:
(1) Every fixed period deltat, the processor reads the laser radar output data f k(i,j)＝{(dk ij,αi, j·θ) }, and converts the data into a detection angle of a point [xij k,yij k,zij k]-1＝[dij k·cosαi·sin(j·θ-θ0),dij k·cosαi·cos(j·θ-θ0),dij k·sinαi], in a sensor coordinate system, wherein θ 0 is j=0; converting the point [ x ij k,yij k,zij k]-1 ] into a point in the world coordinate system by adopting a coordinate conversion method
(2) In the set of points [ X ij k,Yij k,Zij k]-1 ], an obstacle is searched for, and obstacle information is extracted: the specific steps of the distance D, the azimuth delta, the height H and the width W are as follows:
(2a) The search point [ X ij k,Yij k,Zij k]-1's neighbors in the positive direction of the X-axis [ X mn k,Ymn k,Zmn k]-1, i.e., X mn k＞Xij k, while [(Xmn k-Xij k)2+(Ymn k-Yij k)2]1/2 is smallest, where m=0, 1, 2..n-1, n=0, 1,2., calculate ΔXij k＝Xmn k-Xij k,ΔZij k＝Zmn k-Zij k, and gradient g ij k＝ΔZij k/ΔXij k;
(2b) When DeltaX ij k＞TX, storing the point [ X ij k,Yij k,ΔZij k]-1 ] into a data link list L 0, wherein T X is the threshold value of the shock increase of the concave area X; when g ij k is larger than Tg, storing the point [ X ij k,Yij k,Zij k]-1 ] into a data link list L 1,Tg as a convex obstacle gradient threshold;
(2c) After traversing all points, if the data link list L 0 is not empty, calculating the parameters of the concave area: distance d=minx (L 0), azimuth δ=arctan (AvergeY (L 0)/AvergeX(L0)), height h= Averge Δz (L 0), width w=maxy (L 0)-MinY(L0);
If the data linked list L 1 is not empty, calculating a convex obstacle parameter: distance d=minx (L 1), azimuth δ=arctan (AvergeY (L 1)/AvergeX(L1)), height h= MaxZ (L 1)-MinZ(L1), width w=maxy (L 1)-MinY(L1);
Wherein MinX, minY and MinZ are respectively formulas for calculating minimum values of X coordinates, Y coordinates and Z coordinates in the data link list, maxY and MaxZ are formulas for calculating maximum values of Y coordinates and Z coordinates of the midpoint of the data link list, and AvergeX, avergeY and Averge delta Z are formulas for calculating mean values of X coordinates, Y coordinates and delta Z in the data link list.
(3) If an obstacle is found, the processor alerts the user through the vibrator and broadcasts obstacle information through the horn.
The beneficial effects of this patent mainly show in: 1. based on the detection data of the laser radar, the road condition is analyzed, the concave area and the convex obstacle are identified, voice and vibration prompt is carried out, the travel safety 2 of visually impaired people is guaranteed, the calculation method is simple, the calculation speed is high, and the real-time requirement can be met.
Drawings
FIG. 1 is a schematic view of the appearance and coordinate system of the present invention;
FIG. 2 is a schematic diagram of the detection of a recessed area according to the present invention;
fig. 3 is a schematic diagram of the raised obstacle detection of the present invention.
Detailed Description
The invention is further described below with reference to the accompanying drawings:
Referring to fig. 1-3, in order to assist in analyzing and identifying road conditions during autonomous travel of visually impaired people, a road condition analysis method based on laser radar measurement data is provided. The laser radar 2 is arranged on the front upper part of the helmet 1, and the helmet 1 can protect the head of a user in the case of accident on one hand and can also be provided with electronic equipment on the other hand. The two sides of the helmet 1 are provided with voice broadcast horns 5, so that voice broadcast can be carried out, and danger warning can be carried out; the side of the helmet 1 is provided with a charging interface 3 and a switch button 4, and the charging interface 3 can be connected with an external charging power supply.
The helmet 1 is internally provided with a controller, the controller comprises a processor for centralized control, and a vibrator connected with the processor, wherein the vibrator consists of a flat motor and is used for danger prompt. The charging device also comprises a charging circuit connected with the charging interface 3, wherein the output of the charging circuit is connected with a rechargeable battery, the output of the rechargeable battery is connected with a power supply circuit, and the power supply circuit outputs power supplies required by the controller and other modules. The laser radar 2, the switch key4 and the loudspeaker 5 are connected with the processor to realize centralized control. The switch button 4 is used for starting or closing the controller.
The detection direction of the laser radar 2 is set to be the front lower part, and the condition of the front ground is detected. For data calculation, a sensor coordinate system XYZ is established at the center position, an X axis points to the detection center direction of the laser radar 2 and forms a beta angle with the horizontal direction, a Y axis points to the left side, a world coordinate system XYZ is established at the same time, the Y axis is coincident with the Y axis, the X axis points to the right front, and the Z axis points to the vertical direction. The laser radar 2 outputs data f k(i,j)＝{(dk ij,αi, j·θ) }, where k=0, 1,2 is a detection sequence number, α i is a detection angle of the laser radar 2 in a vertical direction, i is a data sequence number in the vertical direction, i=0, 1,2 is N-1, N is a line number of the laser radar 2, j is a data sequence number in a horizontal direction, j=0, 1,2 is a detection angle increment of the laser radar 2 in the horizontal direction. Preferably, the laser radar 4 is a Velodyne VLP16 laser radar, N is 16, α 0 to α 15 are sequentially-15 °,1 °, -13 °,3 °, -11 °,5 °, -9 °,7 °, -7 °,9 °, -5 °,11 °, -3 °,13 °, -1 °,15 °, θ=0.1 °, and since the detection range of VLP16 in the horizontal direction is 360 °, the value range of j is only 120 °, i.e., j=0, 1, 2..1200.
The processor is used for realizing a road condition analysis method, and the road condition analysis method comprises the following steps:
(1) Every fixed period deltat, the processor reads the output data f k(i,j)＝{(dk ij,αi, j·θ) of the laser radar 2, and converts the output data f k(i,j)＝{(dk ij,αi, j·θ into a detection angle of a point [xij k,yij k,zij k]-1＝[dij k·cosαi·sin(j·θ-θ0),dij k·cosαi·cos(j·θ-θ0),dij k·sinαi], in a sensor coordinate system, where θ 0 is j=0; converting the point [ x ij k,yij k,zij k]-1 ] into a point in the world coordinate system by adopting a coordinate conversion method
The laser radar 2 obtains distances between the object reflection point and the laser radar 2 in different angles and directions, and the distances need to be converted into coordinates under a sensor coordinate system, and further converted into coordinates under a world coordinate system, so that convenience is provided for subsequent data processing.
(2) In the set of points [ X ij k,Yij k,Zij k]-1 ], an obstacle is searched for, and obstacle information is extracted: the specific steps of the distance D, the azimuth delta, the height H and the width W are as follows:
(2a) The search point [ X ij k,Yij k,Zij k]-1's neighbors in the positive direction of the X-axis [ X mn k,Ymn k,Zmn k]-1, i.e., X mn k＞Xij k, while [(Xmn k-Xij k)2+(Ymn k-Yij k)2]1/2 is smallest, where m=0, 1, 2..n-1, n=0, 1,2., calculate ΔXij k＝Xmn k-Xij k,ΔZij k＝Zmn k-Zij k, and gradient g ij k＝ΔZij k/ΔXij k;
Since the walking direction of the user is the positive direction toward the X-axis, the current point [ X ij k,Yij k,Zij k]-1 and its neighboring point [ X mn k,Ymn k,Zmn k]-1 ] in the positive direction of the X-axis are selected to calculate the feature parameters when performing the feature calculation.
(2B) When DeltaX ij k＞TX, storing the point [ X ij k,Yij k,ΔZij k]-1 ] into a data link list L 0, wherein T X is the threshold value of the shock increase of the concave area X; when g ij k is larger than Tg, storing the point [ X ij k,Yij k,Zij k]-1 ] into a data link list L 1,Tg as a convex obstacle gradient threshold;
As shown in fig. 2, when a downward concave region, such as a downward step, is encountered, due to the linear propagation characteristic of the laser, laser detection points on both sides of the edge of the concave region have the following characteristics: first, the X coordinate increases significantly; second, the absolute value of the Z coordinate increases. Δz ij k is proportional to Δx ij k, and therefore Δx ij k＞TX is used as a pit area criterion; as shown in fig. 3, when a raised obstacle, such as an upright wall surface, is encountered, the laser light projected by the lidar 2 is projected on a vertical elevation, and thus has the following characteristics: first, the X-coordinate does not increase or increases subtly; second, the Z coordinate varies significantly, as distinguished from the fact that the Z coordinate of a level ground does not vary. The gradient g ij k＝ΔZij k/ΔXij k is thus used to amplify this variation as a criterion for protruding obstacles.
(2C) After traversing all points, if the data link list L 0 is not empty, calculating the parameters of the concave area: distance d=minx (L 0), azimuth δ=arctan (AvergeY (L 0)/AvergeX(L0)), height h= Averge Δz (L 0), width w=maxy (L 0)-MinY(L0);
If the data linked list L 1 is not empty, calculating a convex obstacle parameter: distance d=minx (L 1), azimuth δ=arctan (AvergeY (L 1)/AvergeX(L1)), height h= MaxZ (L 1)-MinZ(L1), width w=maxy (L 1)-MinY(L1);
Wherein MinX, minY and MinZ are respectively formulas for calculating minimum values of X coordinates, Y coordinates and Z coordinates in the data link list, maxY and MaxZ are formulas for calculating maximum values of Y coordinates and Z coordinates of the midpoint of the data link list, and AvergeX, avergeY and Averge delta Z are formulas for calculating mean values of X coordinates, Y coordinates and delta Z in the data link list.
In the height H parameter calculation, there is a difference between the concave area and the convex obstacle: the morphological characteristics of the concave region are mainly concentrated at the edge of the concave region, so that the delta Z ij k of the edge point is taken as the height H parameter of the concave region; the morphological characteristics of the raised barrier are distributed on the vertical elevation, so that the Z coordinate distribution range of the detection point on the vertical elevation is taken as the height H parameter of the raised barrier
(3) If an obstacle is found, the processor alerts the user through the vibrator and broadcasts the obstacle information through the horn 5.
Through vibration and voice prompt and early warning, the travel safety of the user can be effectively ensured.
Claims (1)
1. The road condition analysis method based on laser radar measurement data is characterized in that the laser radar is arranged at the front upper part of a helmet, the detection direction is set to be the front lower part, voice broadcast horns are arranged at the two sides of the helmet, a charging interface and switch keys are arranged on the side face of the helmet, a controller is arranged in the helmet, the controller comprises a processor for centralized control, a vibrator which is connected with the processor and consists of a flat motor, and further comprises a charging circuit which is connected with the charging interface, the output of the charging circuit is connected with a rechargeable battery, the output of the rechargeable battery is connected with a power circuit, the power circuit outputs power required by the controller and other modules, and the laser radar, the switch keys and the horns are connected with the processor; the laser radar is used for detecting the condition of the ground in front, a sensor coordinate system XYZ is established at the central position, an X-axis points to the detection central direction of the laser radar and forms a beta-angle with the horizontal direction, a Y-axis points to the left side, a world coordinate system XYZ is established at the same time, the Y-axis is combined with the Y-axis, the X-axis points to the front, the Z-axis points to the vertical direction, the laser radar outputs data f k(i,j)＝{(dk ij,αi, j.theta) }, wherein k=0, 1,2 is the detection angle of the laser radar in the vertical direction, i is the data sequence number in the vertical direction, i=0, 1,2 is N-1, N is the line number of the laser radar, j is the data sequence number in the horizontal direction, j=0, 1,2 is the detection angle increment of the laser radar in the horizontal direction, and the laser radar is characterized in that: the processor is used for realizing a road condition analysis method, and the road condition analysis method comprises the following steps:
(1) Every fixed period deltat, the processor reads the laser radar output data f k(i,j)＝{(dk ij,αi, j·θ) }, and converts the data into a detection angle of a point [xij k,yij k,zij k]-1＝[dij k·cosαi·sin(j·θ-θ0),dij k·cosαi·cos(j·θ-θ0),dij k·sinαi], in a sensor coordinate system, wherein θ 0 is j=0; converting the point [ x ij k,yij k,zij k]-1 ] into a point in the world coordinate system by adopting a coordinate conversion method
(2) In the set of points [ X ij k,Yij k,Zij k]-1 ], an obstacle is searched for, and obstacle information is extracted: the specific steps of the distance D, the azimuth delta, the height H and the width W are as follows:
(2a) The search point [ X ij k,Yij k,Zij k]-1's neighbors in the positive direction of the X-axis [ X mn k,Ymn k,Zmn k]-1, i.e., X mn k＞Xij k, while [(Xmn k-Xij k)2+(Ymn k-Yij k)2]1/2 is smallest, where m=0, 1, 2..n-1, n=0, 1,2., calculate ΔXij k＝Xmn k-Xij k,ΔZij k＝Zmn k-Zij k, and gradient g ij k＝ΔZij k/ΔXij k;
(2b) When DeltaX ij k＞TX, storing the point [ X ij k,Yij k,ΔZij k]-1 ] into a data link list L 0, wherein T X is the threshold value of the shock increase of the concave area X; when g ij k is larger than Tg, storing the point [ X ij k,Yij k,Zij k]-1 ] into a data link list L 1,Tg as a convex obstacle gradient threshold;
(2c) After traversing all points, if the data link list L 0 is not empty, calculating the parameters of the concave area: distance d=minx (L 0), azimuth δ=arctan (AvergeY (L 0)/AvergeX(L0)), height h= Averge Δz (L 0), width w=maxy (L 0)-MinY(L0);
If the data linked list L 1 is not empty, calculating a convex obstacle parameter: distance d=minx (L 1), azimuth δ=arctan (AvergeY (L 1)/AvergeX(L1)), height h= MaxZ (L 1)-MinZ(L1), width w=maxy (L 1)-MinY(L1);
Wherein MinX, minY and MinZ are respectively formulas for calculating minimum values of X coordinates, Y coordinates and Z coordinates in the data link list, maxY and MaxZ are formulas for calculating maximum values of Y coordinates and Z coordinates of the midpoint of the data link list, and AvergeX, avergeY and Averge delta Z are formulas for calculating mean values of X coordinates, Y coordinates and delta Z in the data link list;
(3) If an obstacle is found, the processor alerts the user through the vibrator and broadcasts obstacle information through the horn.
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| CN106420287A (en) * | 2016-09-30 | 2017-02-22 | 深圳市镭神智能系统有限公司 | Head-mounted type blind guide device |
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