CN117572458B - Dirt shielding detection method for laser radar window and related equipment thereof - Google Patents
Dirt shielding detection method for laser radar window and related equipment thereof Download PDFInfo
- Publication number
- CN117572458B CN117572458B CN202311481871.5A CN202311481871A CN117572458B CN 117572458 B CN117572458 B CN 117572458B CN 202311481871 A CN202311481871 A CN 202311481871A CN 117572458 B CN117572458 B CN 117572458B
- Authority
- CN
- China
- Prior art keywords
- point cloud
- shielding
- column
- columns
- window
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 88
- 238000000034 method Methods 0.000 claims abstract description 46
- 230000003287 optical effect Effects 0.000 claims description 27
- 238000002592 echocardiography Methods 0.000 claims description 25
- 208000006440 Open Bite Diseases 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 abstract description 4
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 238000010586 diagram Methods 0.000 description 9
- 238000004590 computer program Methods 0.000 description 8
- 238000003860 storage Methods 0.000 description 8
- 238000005259 measurement Methods 0.000 description 6
- 238000004891 communication Methods 0.000 description 5
- 238000012545 processing Methods 0.000 description 5
- 230000006870 function Effects 0.000 description 4
- 238000005260 corrosion Methods 0.000 description 3
- 230000007797 corrosion Effects 0.000 description 3
- 238000009826 distribution Methods 0.000 description 3
- 230000007613 environmental effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000005299 abrasion Methods 0.000 description 2
- 238000011109 contamination Methods 0.000 description 2
- 239000000428 dust Substances 0.000 description 2
- 239000000463 material Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000035945 sensitivity Effects 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000010267 cellular communication Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000002925 chemical effect Effects 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 239000011521 glass Substances 0.000 description 1
- 238000004020 luminiscence type Methods 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 239000013618 particulate matter Substances 0.000 description 1
- 230000000704 physical effect Effects 0.000 description 1
- 229920003023 plastic Polymers 0.000 description 1
- 238000011897 real-time detection Methods 0.000 description 1
- 239000004576 sand Substances 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 239000010865 sewage Substances 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Classifications
-
- 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
-
- 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
- G01S7/4802—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
-
- 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
- G01S7/4811—Constructional features, e.g. arrangements of optical elements common to transmitter and receiver
-
- 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
- G01S7/4811—Constructional features, e.g. arrangements of optical elements common to transmitter and receiver
- G01S7/4813—Housing arrangements
-
- 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
- G01S7/497—Means for monitoring or calibrating
-
- 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
- G01S7/497—Means for monitoring or calibrating
- G01S2007/4975—Means for monitoring or calibrating of sensor obstruction by, e.g. dirt- or ice-coating, e.g. by reflection measurement on front-screen
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Electromagnetism (AREA)
- Optical Radar Systems And Details Thereof (AREA)
Abstract
The application relates to a method for detecting dirt shielding of a laser radar window and related equipment thereof. Wherein the method comprises the following steps: performing point cloud column type classification on the point cloud column obtained by performing primary light emission and detection on the secondary echo number and the primary echo intensity mean value obtained by performing primary light emission on a plurality of light emission channels; after a point cloud frame formed by a plurality of continuous point cloud columns is obtained through multiple light emission and detection, counting normal point cloud columns, shielding point cloud columns and out-of-range point cloud columns in the point cloud frame respectively, and classifying the point cloud frame types based on the count values of the normal point cloud columns, the shielding point cloud columns and the out-of-range point cloud columns; and under the condition that a plurality of continuous point cloud frames are all shielding point cloud frames, determining that dirt or shielding exists in the laser radar window. The application at least solves the problem of high hardware cost caused by additionally arranging the light-emitting device in the window dirt detection method in the related technology, and reduces the manufacturing cost.
Description
Technical Field
The application relates to the technical field of laser radar optical systems, in particular to a method for detecting dirt shielding of a laser radar window and relevant equipment thereof.
Background
The laser radar is an unmanned important sensor, and the window dirt detection device is not generally arranged in the existing laser radar to detect the window, so that the laser radar can encounter weather such as rain, snow, sand wind and the like in the running process of the unmanned vehicle, dust, scratches, sewage, mud stains, corrosion and the like can be formed on the optical window, the laser radar cannot normally acquire the environmental information around the unmanned vehicle, and therefore the window dirt information of the laser radar is acquired to be favorable for the laser radar to normally detect.
In the window dirt detection method in the related art, a light emitting device is additionally arranged for detecting window dirt, so that the structure is complex and the hardware cost is increased.
Disclosure of Invention
The method and the related equipment for detecting the dirt shielding of the laser radar window at least solve the problem of high hardware cost caused by additionally arranging the light emitting device in the window dirt detection method in the related technology.
A method for detecting dirt shielding of a laser radar window is applied to a laser radar with a plurality of light emission channels, and comprises the following steps:
classifying the point cloud column types of the point cloud column obtained by primary light emission and detection based on the secondary echo number and the primary echo intensity mean value obtained by primary light emission of a plurality of light emission channels, wherein the point cloud column types comprise a normal point cloud column, a shielding point cloud column and an over-range point cloud column;
After a point cloud frame formed by a plurality of continuous point cloud columns is obtained through multiple light emission and detection, counting normal point cloud columns, shielding point cloud columns and out-of-range point cloud columns in the point cloud frame respectively, and classifying the point cloud frame based on count values of the normal point cloud columns, the shielding point cloud columns and the out-of-range point cloud columns, wherein the point cloud frame types comprise shielding point cloud frames and non-shielding point cloud frames;
and under the condition that a plurality of continuous point cloud frames are all shielding point cloud frames, determining that dirt or shielding exists in the laser radar window.
In some embodiments, determining that the lidar window is dirty or blocked when the detection results in a plurality of continuous point cloud frames that are all blocked point cloud frames includes:
under the condition that a plurality of continuous shielding point cloud columns exist in a plurality of continuous shielding point cloud frames, determining that a laser radar window is shielded;
And determining that the laser radar window is dirty under the condition that a plurality of discontinuous shielding point cloud columns exist in a plurality of continuous shielding point cloud frames.
In some of these embodiments, after determining that the lidar window is dirty or occluded, the method further comprises:
And acquiring a dirty shielding detection result based on the corresponding relation between the shielding point cloud column and the view angle, wherein the dirty shielding detection result comprises a view angle range influenced by dirty or shielding, and/or the area occupied by dirty or shielding on the window, and the view angle comprises a horizontal view angle and a vertical view angle.
In some embodiments, based on the number of secondary echoes and the average value of the intensity of the primary echoes detected by the primary light emission of the plurality of light emission channels, classifying the point cloud column type of the point cloud column obtained by the primary light emission and the detection includes:
Acquiring the number of secondary echoes obtained by detecting primary light emission of a plurality of light emission channels, the average value of the primary echo intensities detected by detection channels without detecting the secondary echoes, and a preset primary echo intensity threshold value and a preset secondary echo number threshold value;
under the condition that the secondary echo number is smaller than a secondary echo number threshold value and the primary echo intensity average value is larger than a primary echo intensity threshold value, determining the point cloud column as a shielding point cloud column;
under the condition that the secondary echo number is smaller than a secondary echo number threshold value and the primary echo intensity average value is not larger than a primary echo intensity threshold value, determining the point cloud column as an over-range point cloud column;
And under the condition that the secondary echo number is not smaller than the secondary echo number threshold value, determining the point cloud column as a normal point cloud column.
In some of these embodiments, the method further comprises:
acquiring a plurality of secondary echo numbers obtained by detecting a plurality of light emission channels by emitting light for a plurality of times at the same field angle;
And under the condition that the maximum value of the plurality of secondary echo numbers is not smaller than the secondary echo number threshold value, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns.
In some of these embodiments, the method further comprises:
Acquiring channels of a plurality of light emission channels which emit light for a plurality of times at the same field angle and are detected to obtain secondary echoes, and marking the channels as normal channels;
And under the condition that the number of the normal channels is not smaller than the threshold value of the secondary echo number, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns.
In some of these embodiments, the primary echo intensity threshold is determined based on a mean value of the primary echo intensities detected in the absence of a dirty, unobstructed lidar window; the second echo number threshold is smaller than the number of light emission channels of the laser radar.
In some embodiments, classifying the point cloud frame based on the count values of the normal point cloud column, the occlusion point cloud column, and the over-range point cloud column includes:
Acquiring a preset normal point Yun Lieshu threshold value, a shielding point cloud column number threshold value and an oversrange point cloud column number threshold value;
Under the condition that the count value of the normal point cloud column in the point cloud frame is larger than the threshold value of the normal point cloud column, determining that the point cloud frame is a non-shielding point cloud frame;
Determining that the point cloud frame is a non-shielding point cloud frame under the condition that the count value of the normal point cloud column in the point cloud frame is not greater than the normal point cloud column threshold and the count value of the overscan point cloud column is greater than the overscan point cloud column threshold;
Determining that the point cloud frame is a non-shielding point cloud frame under the condition that the count value of the normal point cloud column in the point cloud frame is not greater than the normal point cloud column threshold, the count value of the over-range point cloud column is not greater than the over-range point cloud column threshold and the count value of the shielding point cloud column is not greater than the shielding point cloud column threshold;
And determining the point cloud frame as an occlusion point cloud frame under the condition that the count value of the normal point cloud column in the point cloud frame is not greater than the normal point cloud column threshold, the count value of the overscan point cloud column is not greater than the overscan point cloud column threshold and the count value of the occlusion point cloud column is greater than the occlusion point cloud column threshold.
In some embodiments, determining that the lidar window is dirty or blocked when the detection results in a plurality of continuous point cloud frames that are all blocked point cloud frames includes:
If the point cloud frame is an occlusion point cloud frame, the count value of the occlusion point cloud frame is automatically increased, otherwise, the count value of the occlusion point cloud frame is emptied;
And determining that the laser radar window is dirty or blocked under the condition that the count value of the blocked point cloud frame is larger than the preset threshold value of the blocked point cloud frame.
In some of these embodiments, after determining that the lidar window is dirty or occluded, the method further comprises:
Acquiring a plurality of view angle ranges with dirt or shielding obtained by dirt shielding detection of a plurality of laser radar windows based on the corresponding relation between the shielding point cloud column and the view angles;
and taking the intersection of the multiple view angle ranges as a dirty shielding detection result of the laser radar window.
A laser radar optical system comprises a shell with a window, a light detection device with a plurality of light receiving and transmitting channels, and a device for executing the dirt shielding detection method of the laser radar window.
A vehicle comprising the lidar optical system described above.
According to the dirt shielding detection method and the relevant equipment of the laser radar window, provided by the embodiment of the invention, the point cloud column type classification is carried out on the point cloud column obtained by primary light emission and detection through the secondary echo number and the primary echo intensity average value obtained by primary light emission based on a plurality of light emission channels, wherein the point cloud column type comprises a normal point cloud column, a shielding point cloud column and an overscan point cloud column; after a point cloud frame formed by a plurality of continuous point cloud columns is obtained through multiple light emission and detection, counting normal point cloud columns, shielding point cloud columns and out-of-range point cloud columns in the point cloud frame respectively, and classifying the point cloud frame based on count values of the normal point cloud columns, the shielding point cloud columns and the out-of-range point cloud columns, wherein the point cloud frame types comprise shielding point cloud frames and non-shielding point cloud frames; under the condition that a plurality of continuous point cloud frames are all occlusion point cloud frames, the fact that the laser radar window is dirty or occluded is determined, at least the problem that hardware cost is high due to the fact that a light emitting device is additionally arranged in a window dirty detection method in the related art is solved, and manufacturing cost is reduced.
The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below to provide a more thorough understanding of the other features, objects, and advantages of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is evident that the drawings in the following description are only some embodiments of the invention, from which other embodiments can be obtained for a person skilled in the art without inventive effort.
Fig. 1 is a flowchart of a method for detecting a dirt shielding of a lidar window according to the present embodiment.
Fig. 2 is an alternative flowchart of a method for detecting a dirt shielding of a lidar window according to this embodiment.
Fig. 3 is a schematic diagram of a point cloud detected by the lidar of the present embodiment.
FIG. 4 is a diagram showing the relationship between the affected field angle range and the surface dirt or shielding area of the window according to the present embodiment.
Fig. 5 is a schematic structural diagram of the electronic device of the present embodiment.
Detailed Description
Embodiments of the present embodiment will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present embodiments are illustrated in the accompanying drawings, it is to be understood that the present embodiments may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided to provide a more thorough and complete understanding of the present embodiments. It should be understood that the drawings and the embodiments of the present embodiments are presented for purposes of illustration only and are not intended to limit the scope of the embodiments.
A lidar window refers to a transparent window or optical element in the lidar optical system for allowing the laser beam to pass through and interact with the surrounding environment. This window is typically made of an optical material, such as glass or transparent plastic, and has special optical properties to ensure transmission and detection of the laser beam. The window of the lidar is an important component that plays a key role in protecting the optics of the lidar system, transmitting the laser beam, and ensuring accurate measurement of the target. Different application scenarios and environmental conditions may require different types of windows to meet specific needs.
The function of the lidar window includes the following aspects: 1. protecting the laser transmitter and receiver: the window may prevent external elements such as dust, particulates, dirt, etc. from entering the lidar system, thereby protecting the optical elements of the laser transmitter and receiver from damage or contamination. 2. Transparency: the window must be transparent to ensure that the laser beam can pass through it, interact with the target object and return to the receiver for measurement. 3. Optical properties: the optical properties of the window must be matched to the requirements of the laser system to ensure that the laser beam does not distort or scatter as it passes through the window. 4. Abrasion and corrosion resistance: windows are often required to have sufficient abrasion and corrosion resistance to cope with physical and chemical effects under different environmental conditions.
In some related technologies, an additional device is needed to determine whether a window of the laser radar has a dirty condition, so that the laser radar has a complex structure and relatively high cost; other related technologies for determining that a radar window is blocked have complex implementation process and low efficiency.
In order to solve the above problems, the present embodiment provides a method for detecting a fouling shielding of a lidar window. The dirt shielding detection method is applied to a laser radar with a plurality of light emission channels, for example, a 16-line, 32-line, 64-line or more rotating mirror type and vibrating mirror type laser radar is adopted. The rotating mirror type laser radar at least comprises a linear array light emitter, a linear array light detector, a rotating mirror and an operation unit. The rotating mirror can be a single-sided rotating mirror or a multi-sided rotating mirror. In addition, the light emitter and the light detector of the rotary mirror type laser radar of the present embodiment may be coaxially or non-coaxially arranged, and the rotary mirror type laser radar may include one or more groups of light detection units, each group of light detection units including one light emitter and one light detector. For example, in the case of a rotary mirror type laser radar including two sets of light detection units, the two sets of light detection units are respectively disposed on both sides of a rotary mirror to realize correlation so as to perform stitching of a horizontal view angle and/or a vertical view angle. In the lidar employing multiple sets of light detection units, the detection of the dirt shielding of the window may be performed separately or jointly for each set of light detection units, for example, the dirt shielding area of the window may be based on the union or intersection of the dirt shielding detection results of each set of light detection units.
Judging whether shielding exists in the window by taking the array of the lasers as a unit (namely, the data acquired by one-time light emission of the lasers), and specifically judging the condition:
Condition 1: after each time the laser emits a beam, whether a secondary measurement echo can be detected. The laser emits light once for measurement, firstly, a certain amount of echo is generated by a light machine and a window, a primary echo is generated at a receiving end, a certain amount of echo is generated after an object is required to be actually measured, and a secondary echo is generated at the receiving end. When the radar window is shielded, the echo of the shielding object is overlapped with the window and the optical machine, and when the radar cannot detect the secondary echo, the shielding exists in the laser luminescence measurement.
Condition 2: the increase amplitude of the shallow surface echo (i.e., the primary echo of the lidar) is determined. The intensity of the primary echo generated by the optical machine and the window at the receiving end is stable, the intensity is not changed along with the working temperature and the change of the using environment of the radar (the radar system end is provided with temperature bias calibration, laser power calibration and intensity calibration guarantee), when the laser radar window is shielded, the echo (secondary echo) of the shielding object and the primary echo are overlapped to lead to the broadening intensity of the pulse width of the primary echo to be stronger, and whether the light is shielded (shielded by the shielding object) and the dirt (the dirt of the window is caused by the dirt) is judged according to whether the intensity of the primary echo measured by the primary laser light is increased.
Condition 3: duration and distribution. The laser radar comprises a laser, a scanning system (consisting of a motor and a rotating mirror), a laser, a scanning system and a display, wherein one frame of point cloud of the laser radar emits light for many times, the scanning system (consisting of the motor and the rotating mirror) rotates to complete the test within the whole visual field range, the laser emits light for each time, the horizontal angle and the vertical angle of the test of the light can be marked through the state of the scanning system, after one frame of measurement is completed, the number of shielding columns in one frame of point cloud is counted, shielding of the radar is judged when the number of shielding columns is larger than a certain threshold, and then whether a shielding object is polluted by a window or shielded by a real object is continuously judged according to the distribution state of the shielding columns or not by the horizontal vertical angle.
The method for detecting the dirt shielding of the laser radar window can be applied to the operation unit of the rotating mirror type or vibrating mirror type laser radar so as to realize the dirt shielding detection of the window.
In this embodiment, the dirt refers to discontinuous particulate matter or dirt formed on the window of the lidar; shielding means forming a large area, continuous light barrier in front of the window of the lidar.
Fig. 1 is a flowchart of a method for detecting dirt shielding of a lidar window according to the embodiment, and as shown in fig. 1, the flowchart includes the following steps:
Step S101, classifying the point cloud column types of the point cloud column obtained by the primary light emission and detection based on the secondary echo number and the primary echo intensity mean value obtained by the primary light emission of the plurality of light emission channels, wherein the point cloud column types comprise a normal point cloud column, a shielding point cloud column and an overscan point cloud column.
Step S102, after a point cloud frame formed by a plurality of continuous point cloud columns is obtained through multiple light emission and detection, counting normal point cloud columns, shielding point cloud columns and overscan point cloud columns in the point cloud frame respectively, and classifying the point cloud frame based on count values of the normal point cloud columns, the shielding point cloud columns and the overscan point cloud columns, wherein the point cloud frame type comprises shielding point cloud frames and non-shielding point cloud frames.
Step S103, determining that dirt or shielding exists in the laser radar window under the condition that a plurality of continuous point cloud frames are all shielding point cloud frames.
Taking a rotary mirror type laser radar as an example, after a light emitter of the laser radar emits a beam of laser, reflecting out a window through rotary scanning of a rotary mirror and reaching a detection object in a view field range; because the window cannot completely transmit light and part of laser light can be reflected and received by the light detector, the light detection unit receives two echoes in one light emission of the light emitter, wherein the one echo is formed by window reflection, and the second echo is formed by reflection of a detection object. The primary echo and the secondary echo can be judged through the time interval from the light emitter to the light detector detecting the echo energy; in normal detection, the primary echo intensity is much lower than the secondary echo intensity.
When the laser radar works, after one laser beam is emitted, if a detection object exists in the range of the laser radar to block laser, a primary echo and a secondary echo are formed and detected by the optical detection unit. If the detection object does not block the laser in the range of the laser radar or the detection object is out of the range of the laser radar, a primary echo is formed and detected by the optical detection unit, or although the primary echo and the secondary echo are formed, the intensity of the secondary echo is too low to be captured by the optical detection unit and only the primary echo can be detected by the optical detection unit. If dirt or shielding exists on the window of the laser radar, the laser emission is just blocked, the optical detection unit does not receive secondary echoes, and the optical detection unit can receive echoes with intensity far greater than that of the primary echo under normal conditions due to the dirt or shielding and reflecting more energy, and the echoes can be recognized as the primary echo by the optical detection unit.
Therefore, the point cloud detected by the primary light emission of one light emission channel may be a normal point cloud recorded with the time difference information of the primary echo and the secondary echo, or may be a point cloud recorded with the time difference information of only the primary echo, where the point cloud of the latter may be further classified into a shielding point cloud (for convenience of description, the shielding dirty cloud is collectively referred to as a shielding point cloud, hereinafter the same) and an overscan point cloud according to the echo intensity. Therefore, in some embodiments, in each row of point clouds detected by performing primary light emission on each light channel, whether each point cloud records secondary echo time difference information or not and the primary echo intensity recorded in the point clouds can be used for classifying the point clouds, and determining which window positions corresponding to the point clouds are dirty or blocked according to the number of the point clouds classified as blocked point clouds in each row of point clouds. However, since the detection speed of the lidar is very fast, the number of point clouds obtained by scanning each frame of the 16-line lidar with a horizontal view angle of 120 ° and a horizontal view angle resolution of 0.04 ° can be up to 16×2883, and as the number of lines increases, the horizontal resolution increases, and the number of point clouds generated in unit time increases exponentially, if the information of each point cloud is processed in real time, the required operation resources and the consumed operation time cost are quite large, and even the scheduling of the operation resources required for normal detection of the lidar may be affected. Therefore, how to further improve the efficiency of detecting the dirt shielding of the window without adding additional hardware is another technical problem that is not solved in the related art.
Therefore, in the above embodiment, the information of each point cloud is not focused, but the type of each column of point cloud column of each column of point cloud obtained by multi-channel light emission detection is focused, the type of the point cloud frame is determined according to the type of each column of point cloud column in the point cloud frame, and then the judgment of whether the window is dirty or blocked is realized by combining multiple frames of point clouds. Meanwhile, when the type of the point cloud column is classified, the time difference and echo intensity information in each point cloud are not relied on, but secondary echoes are counted, and the point cloud column is classified into more types (normal point cloud column, shielding point cloud column and overscan point cloud column) in a mode of averaging the primary echo intensities corresponding to all or part of the point clouds in the point cloud column, so that the operation efficiency is improved and the operation complexity is reduced. The closer the number of secondary echoes is to the number of light emission channels (i.e. the number of lines of light emitters), the more laser emitted by most channels is normally emitted by the window and reflected by the object in the range, i.e. the more point clouds in the point cloud column are normal point clouds, and when the number of normal point clouds is greater than a certain threshold value, the point cloud column can be considered as a normal point cloud column. When the number of secondary echoes is not greater than a certain threshold, most of the point clouds in the array are possibly overscan point clouds, or most of the point clouds in the array are possibly shielding point clouds, and at this time, the ratio of the overscan point clouds to the shielding point clouds in the array can be judged according to the intensity mean value of the primary echo, for example, the smaller the intensity mean value of the primary echo or the closer to a normal calibration value is, the more the overscan point clouds are, the larger the intensity mean value of the primary echo is, and the more the shielding point clouds are. Therefore, according to the secondary echo number and the primary echo intensity average value obtained by detecting the primary light emission of the plurality of light emission channels, the types of the point cloud columns obtained by detecting the primary light emission can be classified into a normal point cloud column, a shielding point cloud column and an over-range point cloud column.
Fig. 2 is an alternative flowchart of a method for detecting a dirt shielding of a lidar window according to this embodiment. The method of detecting the contamination shielding shown in fig. 1 is further described below with reference to fig. 2. In order to achieve the above object, the method for detecting a dirty shielding in this embodiment includes the steps of:
in step S2101, the number of secondary echoes detected by the light emitting channels performing primary light emission, the average value of the primary echo intensities detected by the detecting channels not detecting the secondary echoes, and a primary echo intensity threshold and a secondary echo number threshold set in advance are obtained.
Step S2102, determining that the point cloud column is a blocked point cloud column when the secondary echo number is smaller than the secondary echo number threshold and the primary echo intensity average is larger than the primary echo intensity threshold.
In step S2103, when the number of secondary echoes is smaller than the threshold value of the number of secondary echoes and the average value of the intensities of the primary echoes is not greater than the threshold value of the intensity of the primary echoes, the point cloud array is determined to be an over-range point cloud array.
In step S2104, when the number of secondary echoes is not smaller than the threshold value of the number of secondary echoes, the point cloud column is determined to be a normal point cloud column.
Step S2201, after performing multiple light emission and detecting to obtain a point cloud frame composed of multiple continuous point cloud columns, respectively counting a normal point cloud column, a blocked point cloud column and an overscan point cloud column in the point cloud frame; and acquiring a preset normal point Yun Lieshu threshold, a shielding point cloud column number threshold and an overscan point cloud column number threshold.
Step S2202, when the count value of the normal point cloud column in the point cloud frame is greater than the threshold value of the normal point cloud column number, determines that the point cloud frame is a non-occlusion point cloud frame.
Step S2203 determines that the point cloud frame is a non-occlusion point cloud frame when the count value of the normal point cloud column in the point cloud frame is not greater than the normal point cloud column number threshold and the count value of the over-range point cloud column is greater than the over-range point cloud column number threshold.
Step S2204 determines that the point cloud frame is a non-occlusion point cloud frame when the count value of the normal point cloud column is not greater than the normal point cloud column number threshold, the count value of the over-range point cloud column is not greater than the over-range point cloud column number threshold, and the count value of the occlusion point cloud column is not greater than the occlusion point cloud column number threshold in the point cloud frame.
Step S2205 determines that the point cloud frame is an occlusion point cloud frame when the count value of the normal point cloud column is not greater than the normal point cloud column number threshold, the count value of the overscan point cloud column is not greater than the overscan point cloud column number threshold, and the count value of the occlusion point cloud column is greater than the occlusion point cloud column number threshold.
In step S2301, when the detection results that the plurality of continuous point cloud frames are all occlusion point cloud frames, it is determined that the lidar window is dirty or occluded.
In step S2302, in the case that the detection results in the non-occlusion point cloud frame exists in the plurality of continuous point cloud frames, it is determined that the laser radar window is not dirty or occluded.
In step S2401, when there are a plurality of continuous occlusion point cloud columns in the plurality of continuous occlusion point cloud frames, it is determined that there is occlusion in the lidar window.
Step S2402, determining that the lidar window is dirty when there are a plurality of discontinuous occlusion point cloud columns in the plurality of continuous occlusion point cloud frames.
In the step S2101, when the primary echo intensity average value is calculated, only the primary echo intensity detected by the detection channel in which the secondary echo is not detected is used, compared with the primary echo intensity average value and all of the primary echo intensity average values in the row of point cloud rows, the influence of the normal point cloud on the primary echo intensity average value is eliminated, so that the influence of the shielding point cloud can be more obviously reflected by the primary echo intensity average value, and the detection accuracy is improved.
In the above embodiment, the primary echo intensity threshold is determined based on the primary echo intensity mean value detected in the case of a non-dirty and non-occluded lidar window; the secondary echo number threshold is smaller than the number of channels of the light emission channel of the laser radar, for example, when the number of channels of the light emission channel is 16, the secondary echo number threshold may be 14 or 15.
In some embodiments, the step S2301 includes: if the point cloud frame is an occlusion point cloud frame, the count value of the occlusion point cloud frame is automatically increased, otherwise, the count value of the occlusion point cloud frame is emptied; and determining that the laser radar window is dirty or blocked under the condition that the count value of the blocked point cloud frame is larger than the preset threshold value of the blocked point cloud frame. For example, when the threshold of the number of the shielding point cloud frames is set to 30, it is determined that the laser radar window is dirty or shielded when the continuous 30 frames of the point cloud frames are all of the type of the shielding point cloud frames. It can be seen that the higher the threshold of the number of the cloud frames of the shielding point is, the more accurate the detection result is, but the smaller the real-time detection is. Therefore, the above-described occlusion point cloud frame number threshold is determined based on detection instantaneity and sensitivity of the dirty occlusion detection.
Fig. 3 is a schematic view of a point cloud detected by the lidar of the present embodiment, fig. 3 is an example of standing behind the lidar in the laser emission direction, the horizontal axis in fig. 3 is a horizontal angle of view, and the vertical axis is a vertical angle of view. The point clouds shown in fig. 3 are obtained by six 16-line light emitters distributed on the left and right of the turning mirror, one frame of point cloud frame obtained by each light emitter is denoted as one Area in the figure, and the point cloud frames obtained by the six 16-line light emitters correspond to Area1, area2, area3, area4, area5, and Area6, respectively. Each line in fig. 3 represents a row of point clouds formed by one channel, a column of point clouds corresponding to a certain horizontal angle of view along the vertical angle of view is called a point cloud column, and each point cloud column contains 16 point clouds in a frame of point clouds formed by 16 line light emitters. The boundary of the whole point cloud of the laser radar shown in fig. 3 is the view field of the laser radar, and each position on the view field actually corresponds to a corresponding position of the laser radar window, for example, a region with a vertical view angle of-15 ° to +15° and a horizontal view angle of 150 ° to 30 ° in the point cloud schematic diagram shown in fig. 3 can be regarded as a window corresponding to a shape similar to that of the region. If a plurality of continuous or discontinuous shielding point cloud frames exist in a certain point cloud frame, according to column identification information of shielding point cloud columns, the field angle range distributed by the point cloud columns can be determined to be the field angle range affected by dirt or shielding, for example, a region which is approximately parallelogram and is near a horizontal field angle of 111-127 degrees and a vertical field angle of +2- +11 degrees in fig. 3 is the field angle range affected by dirt or shielding.
Fig. 4 is a schematic diagram showing the relationship between the affected angle of view range and the area of the dirty or blocked area on the surface of the window in this embodiment, and as shown in fig. 4, the lidar transmits and receives detection laser light and laser echo from the window 10, and the entire area that can be detected is included in the field of view 20. If the detector detects a multi-frame point cloud frame, one or more columns of laser points Yun Lie are determined as the shielding point cloud columns, that is, the distribution area of the shielding point cloud columns can be determined according to the identifications of the laser point cloud columns, that is, the view angle range 30 affected by dirt or shielding in fig. 4. According to the principle of light propagation, the laser forming the boundary of the view angle range 30 passes through the window 10 on the graph boundary shown by the dirty region 40 in fig. 4, the dirty region 40 and the view angle range 30 affected by the dirty or blocked are approximately in a graph, and the area occupied by the dirty or blocked window can be calculated according to the proportional relationship between the actual size of the view field 20 and the actual size of the window.
In some embodiments, after determining that the lidar window has a smudge or a blockage, acquiring a smudge and blockage detection result based on a corresponding relation between a cloud of blockage points and a field angle, wherein the smudge and blockage detection result comprises a field angle range affected by the smudge or the blockage, and/or an area occupied by the smudge or the blockage on the window, and the field angle comprises a horizontal field angle and a vertical field angle. Or based on the corresponding relation between the shielding point cloud column and the view angles, acquiring a plurality of view angle ranges with dirt or shielding obtained by dirt shielding detection of the laser radar window for a plurality of times; and taking the intersection of the multiple view angle ranges as a dirty shielding detection result of the laser radar window.
In some embodiments, the alarm information and the view field schematic diagram may be displayed on the display screen, where the view field schematic diagram is marked with a dirty shielding detection result for the user to intuitively view.
It will be appreciated that the detection object is not always present within the field of view. According to the relevant statistical data, the point cloud capable of detecting the secondary echo in the field of view along with the movement of the detection object or the laser radar in the application scene of the vehicle-mounted laser radar generally only accounts for about 22% of all the point clouds. If the threshold value of the secondary echo number set in the above step is too small, the point cloud column where the occluded point cloud is obviously present is erroneously judged as a normal point cloud column, thereby reducing the detection accuracy. Therefore, the secondary echo threshold is generally set to be close to the number of channels (the number of lines). In this way, in the practical application scene, most of the point cloud columns are not classified into normal point cloud columns, and the problem of detection accuracy reduction or efficiency reduction caused by too many point cloud columns which need to be further classified into a shielding point cloud column and an overscan point cloud column is caused.
Thus, in some of these embodiments, the normal point cloud columns are also identified by way of a combination of multi-frame probing. The principle is that if a certain point cloud in the point cloud column can detect a secondary echo in a short time, the point cloud is not shielded or dirty in the short time, so that the point cloud is considered to be a normal point cloud in the short time.
Accordingly, the dirt shielding detection method further comprises the following steps: acquiring channels of a plurality of light emission channels which emit light for a plurality of times at the same field angle and are detected to obtain secondary echoes, and marking the channels as normal channels; and under the condition that the number of the normal channels is not smaller than the threshold value of the secondary echo number, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns. Or acquiring a plurality of secondary echo numbers obtained by detecting a plurality of light emission channels by carrying out light emission for a plurality of times at the same field angle; and under the condition that the maximum value of the plurality of secondary echo numbers is not smaller than the secondary echo number threshold value, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns.
The embodiment also provides a laser radar optical system, which comprises a shell with a window, a light detection device with a plurality of light receiving and transmitting channels, and a device for executing the dirt shielding detection method of the laser radar window.
With reference to fig. 5, a block diagram of an electronic device that may be used as an embodiment of the present invention to perform the above-described method for detecting a fouling occlusion of a lidar window will now be described, which is an example of a hardware device that may be applied to aspects of the present invention. Electronic devices are intended to represent various forms of digital electronic computer devices, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 5, the electronic device includes a computing unit 501 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device can also be stored. The computing unit 501, ROM 502, and RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the electronic device are connected to the I/O interface 505, including: an input unit 506, an output unit 507, a storage unit 508, and a communication unit 509. The input unit 506 may be any type of device capable of inputting information to an electronic device, and the input unit 506 may receive input numeric or character information and generate key signal inputs related to user settings and/or function controls of the electronic device. The output unit 507 may be any type of device capable of presenting information and may include, but is not limited to, a display, speakers, video/audio output terminals, vibrators, and/or printers. Storage unit 508 may include, but is not limited to, magnetic disks, optical disks. The communication unit 509 allows the electronic device to exchange information/data with other devices over a computer network such as the internet and/or various telecommunications networks and may include, but is not limited to, modems, network cards, infrared communication devices and/or wireless communication transceivers, such as bluetooth devices, wiFi devices, wiMax devices, cellular communication devices and/or the like.
The computing unit 501 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 501 include, but are not limited to, a CPU, a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing units, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 performs the various methods and processes described above. For example, in some embodiments, method embodiments of the present invention may be implemented as a computer program tangibly embodied on a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device via the ROM 502 and/or the communication unit 509. In some embodiments, the computing unit 501 may be configured to perform the above-described methods by any other suitable means (e.g., by means of firmware).
A computer program for implementing the methods of embodiments of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be implemented. The computer program may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of embodiments of the present invention, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable signal medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The present embodiment also provides a non-transitory machine-readable medium storing computer instructions for causing a computer to perform the above-described method.
The embodiment also provides a vehicle, which comprises the laser radar optical system.
Through the embodiment, under the condition that the working state of the radar is not influenced, the radar shielding state, the shielding area, the dirt state and the dirt area can be accurately detected through a radar window state detection algorithm, and the judging result is output in real time; by modifying different system parameters (various thresholds in the method), different models of radar can be quickly adapted, such as: the laser can receive the different numbers of array lines (conventionally, 8 lines, 16 lines, 32 lines and 64 lines), the different materials of window and the different angles of inclination, and the like, and can also realize the control of detection sensitivity.
It should be noted that the term "comprising" and its variants as used in the embodiments of the present invention are open-ended, i.e. "including but not limited to". The term "based on" is based at least in part on. The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments. References to "one or more" modifications in the examples of the invention are intended to be illustrative rather than limiting, and it will be understood by those skilled in the art that "one or more" is intended to be interpreted as "one or more" unless the context clearly indicates otherwise.
The steps described in the method embodiments provided in the embodiments of the present invention may be performed in a different order and/or performed in parallel. Furthermore, the method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "embodiment" in this specification means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the invention. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive. The various embodiments in this specification are described in a related manner, with identical and similar parts being referred to each other. In particular, for apparatus, devices, system embodiments, the description is relatively simple as it is substantially similar to method embodiments, see for relevant part of the description of method embodiments.
The above examples merely represent a few embodiments of the present invention, which are described in more detail and are not to be construed as limiting the scope of the patent claims. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of the invention should be assessed as that of the appended claims.
Claims (12)
1. A method for detecting dirt shielding of a laser radar window is applied to a laser radar with a plurality of light emitting channels, and is characterized by comprising the following steps:
Classifying the point cloud column types of the point cloud column obtained by the primary light emission and detection based on the secondary echo number and the primary echo intensity mean value obtained by the primary light emission of the plurality of light emission channels, wherein the point cloud column types comprise a normal point cloud column, a shielding point cloud column and an overscan point cloud column;
After a point cloud frame formed by a plurality of continuous point cloud columns is obtained through multiple light emission and detection, counting normal point cloud columns, shielding point cloud columns and overscan point cloud columns in the point cloud frame respectively, and classifying the point cloud frame based on count values of the normal point cloud columns, the shielding point cloud columns and the overscan point cloud columns, wherein the point cloud frame types comprise shielding point cloud frames and non-shielding point cloud frames;
And under the condition that a plurality of continuous point cloud frames are all shielding point cloud frames, determining that dirt or shielding exists in the laser radar window.
2. The method of claim 1, wherein determining that the lidar window is dirty or occluded if the detection results in a plurality of consecutive point cloud frames that are all occlusion point cloud frames comprises:
Under the condition that a plurality of continuous shielding point cloud columns exist in a plurality of continuous shielding point cloud frames, determining that shielding exists in the laser radar window;
And determining that the laser radar window is stained under the condition that a plurality of discontinuous shielding point cloud columns exist in a plurality of continuous shielding point cloud frames.
3. The method of claim 2, wherein after determining that the lidar window is dirty or occluded, the method further comprises:
And acquiring a dirty shielding detection result based on the corresponding relation between the shielding point cloud column and the view angle, wherein the dirty shielding detection result comprises a view angle range influenced by dirty or shielding, and/or the area occupied by dirty or shielding on the window, and the view angle comprises a horizontal view angle and a vertical view angle.
4. The method of claim 1, wherein classifying the point cloud column type for the point cloud column detected by the light emission based on the number of secondary echoes and the average value of the primary echo intensities detected by the light emission channels for the light emission comprises:
Acquiring the number of secondary echoes obtained by detecting the primary light emission of the plurality of light emission channels, the average value of the primary echo intensities detected by the detection channels without detecting the secondary echoes, and a preset primary echo intensity threshold value and a preset secondary echo number threshold value;
determining the point cloud column as a shielding point cloud column under the condition that the secondary echo number is smaller than the secondary echo number threshold value and the primary echo intensity average value is larger than the primary echo intensity threshold value;
Determining the point cloud column as an over-range point cloud column under the condition that the secondary echo number is smaller than the secondary echo number threshold value and the primary echo intensity average value is not larger than the primary echo intensity threshold value;
And under the condition that the secondary echo number is not smaller than the secondary echo number threshold value, determining the point cloud column as a normal point cloud column.
5. The method according to claim 4, wherein the method further comprises:
Acquiring a plurality of secondary echo numbers obtained by detecting the plurality of light emission channels by emitting light for a plurality of times at the same field angle;
And under the condition that the maximum value of the plurality of secondary echo numbers is not smaller than the secondary echo number threshold value, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns.
6. The method according to claim 4, wherein the method further comprises:
Acquiring channels of the plurality of light emission channels which emit light for multiple times at the same angle of view and detect to obtain secondary echoes, and marking the channels as normal channels;
and under the condition that the number of the normal channels is not smaller than the threshold value of the secondary echo number, determining that the point cloud columns obtained by detecting the light emission of the plurality of light emission channels under the same view angle are all normal point cloud columns.
7. The method of claim 4, wherein the primary echo intensity threshold is determined based on a primary echo intensity mean detected in the absence of a dirty and unobstructed lidar window; the secondary echo number threshold is smaller than the channel number of the light emission channel of the laser radar.
8. The method of claim 1, wherein classifying the point cloud frames based on count values of normal point cloud columns, occlusion point cloud columns, and overscan point cloud columns comprises:
Acquiring a preset normal point Yun Lieshu threshold value, a shielding point cloud column number threshold value and an oversrange point cloud column number threshold value;
Under the condition that the count value of a normal point cloud column in the point cloud frame is larger than the threshold value of the normal point cloud column, determining that the point cloud frame is a non-shielding point cloud frame;
Determining that the point cloud frame is a non-occlusion point cloud frame when the count value of the normal point cloud column in the point cloud frame is not greater than the normal point Yun Lieshu threshold and the count value of the over-range point cloud column is greater than the over-range point cloud column threshold;
Determining that the point cloud frame is a non-occlusion point cloud frame when the count value of the normal point cloud column in the point cloud frame is not greater than the normal point Yun Lieshu threshold, the count value of the over-range point cloud column is not greater than the over-range point cloud column threshold, and the count value of the occlusion point cloud column is not greater than the occlusion point cloud column threshold;
and determining the point cloud frame as an occlusion point cloud frame under the condition that the count value of the normal point cloud column in the point cloud frame is not greater than the normal point Yun Lieshu threshold, the count value of the over-range point cloud column is not greater than the over-range point cloud column threshold and the count value of the occlusion point cloud column is greater than the occlusion point cloud column threshold.
9. The method of claim 1, wherein determining that the lidar window is dirty or occluded if the detection results in a plurality of consecutive point cloud frames that are all occlusion point cloud frames comprises:
If the point cloud frame is an occlusion point cloud frame, the count value of the occlusion point cloud frame is automatically increased, otherwise, the count value of the occlusion point cloud frame is emptied;
and determining that the laser radar window is polluted or shielded under the condition that the count value of the shielding point cloud frame is larger than the preset shielding point cloud frame number threshold value.
10. The method of claim 1, wherein after determining that the lidar window is dirty or occluded, the method further comprises:
Acquiring a plurality of view angle ranges with dirt or shielding obtained by dirt shielding detection of a plurality of laser radar windows based on the corresponding relation between the shielding point cloud column and the view angles;
and taking the intersection of the multiple view angle ranges as a dirt shielding detection result of the laser radar window.
11. A lidar optical system comprising a housing having a window, a light detection device having a plurality of light-transceiving channels, and means for performing the method of detection of fouling shielding of a lidar window according to any of claims 1 to 10.
12. A vehicle comprising the lidar optical system of claim 11.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311481871.5A CN117572458B (en) | 2023-11-08 | 2023-11-08 | Dirt shielding detection method for laser radar window and related equipment thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311481871.5A CN117572458B (en) | 2023-11-08 | 2023-11-08 | Dirt shielding detection method for laser radar window and related equipment thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117572458A CN117572458A (en) | 2024-02-20 |
| CN117572458B true CN117572458B (en) | 2024-05-31 |
Family
ID=89889052
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311481871.5A Active CN117572458B (en) | 2023-11-08 | 2023-11-08 | Dirt shielding detection method for laser radar window and related equipment thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117572458B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118191785B (en) * | 2024-02-22 | 2024-11-05 | 江苏优探智能科技有限公司 | Laser radar detection method and related equipment thereof |
| CN118707500B (en) * | 2024-06-27 | 2025-06-27 | 探维科技(苏州)有限公司 | Angle calibration device and angle calibration method for laser radar |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111429400A (en) * | 2020-02-21 | 2020-07-17 | 深圳市镭神智能系统有限公司 | Method, device, system and medium for detecting dirt of laser radar window |
| CN114839161A (en) * | 2022-03-31 | 2022-08-02 | 广州小鹏自动驾驶科技有限公司 | Contamination detection method, device, vehicle and storage medium |
| WO2022179207A1 (en) * | 2021-02-26 | 2022-09-01 | 华为技术有限公司 | Window occlusion detection method and apparatus |
| CN115542296A (en) * | 2021-06-29 | 2022-12-30 | 苏州一径科技有限公司 | Laser radar smudge and smudge detection method and electronic device |
| WO2023061481A1 (en) * | 2021-10-15 | 2023-04-20 | 北京一径科技有限公司 | Radar failure determining method and device and storage medium |
| CN116009015A (en) * | 2021-09-23 | 2023-04-25 | 上海禾赛科技有限公司 | Photomask contamination detection method and photomask contamination detection system for laser radar |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN118519120A (en) * | 2021-08-31 | 2024-08-20 | 深圳市速腾聚创科技有限公司 | Laser radar shielding detection method and device, storage medium and laser radar |
-
2023
- 2023-11-08 CN CN202311481871.5A patent/CN117572458B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111429400A (en) * | 2020-02-21 | 2020-07-17 | 深圳市镭神智能系统有限公司 | Method, device, system and medium for detecting dirt of laser radar window |
| WO2022179207A1 (en) * | 2021-02-26 | 2022-09-01 | 华为技术有限公司 | Window occlusion detection method and apparatus |
| CN115542296A (en) * | 2021-06-29 | 2022-12-30 | 苏州一径科技有限公司 | Laser radar smudge and smudge detection method and electronic device |
| CN116009015A (en) * | 2021-09-23 | 2023-04-25 | 上海禾赛科技有限公司 | Photomask contamination detection method and photomask contamination detection system for laser radar |
| WO2023061481A1 (en) * | 2021-10-15 | 2023-04-20 | 北京一径科技有限公司 | Radar failure determining method and device and storage medium |
| CN114839161A (en) * | 2022-03-31 | 2022-08-02 | 广州小鹏自动驾驶科技有限公司 | Contamination detection method, device, vehicle and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| Analysis of Real World Sensor Behavior for Rising Fidelity of Physically Based Lidar Sensor Models;Philipp Rosenberger et al.;2018 IEEE Intelligent Vehicles Symposium;20181231;26-30 * |
| 基于强度数据的地面激光点云自适应非监督分类;谭凯;程效军;;激光与光电子学进展;20160310(03);第1-7页 * |
| 多线激光雷达越野环境障碍检测;刘大学 等;计算机仿真;20090731;第26卷(第7期);第159-163页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117572458A (en) | 2024-02-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117572458B (en) | Dirt shielding detection method for laser radar window and related equipment thereof | |
| US10908268B2 (en) | Method for identification of a noise point used for LiDAR, and LiDAR system | |
| US12140710B2 (en) | Method for identification of a noise point used for LiDAR, and LiDAR system | |
| CN106951847B (en) | Obstacle detection method, apparatus, device and storage medium | |
| CN112698301B (en) | Laser radar target recognition method, device and equipment based on distance intensity correlation | |
| CN106919908B (en) | Obstacle identification method and device, computer equipment and readable medium | |
| JP2020076589A (en) | Object detection device | |
| CN106934347B (en) | Obstacle identification method and device, computer equipment and readable medium | |
| CN108627812A (en) | A kind of laser radar atmospheric visibility measurement method and device | |
| EP4286892A1 (en) | Window occlusion detection method and apparatus | |
| CN111177869A (en) | Method, device and device for determining sensor layout scheme | |
| CN117607839A (en) | Dirt detection method and device, cleaning method and device for laser radar light window | |
| CN112101069A (en) | Method and device for determining driving area information | |
| CN114813652A (en) | Contamination reminding method and device applied to laser radar and storage medium | |
| CN117496165B (en) | Rain and snow noise filtering method and device, electronic equipment and storage medium | |
| US20220292829A1 (en) | Method and device for determining smoke | |
| CN115177186B (en) | Cleaning method, cleaning device, cleaning robot and computer readable storage medium | |
| CN110987872B (en) | Forward scatter sensor | |
| WO2024120491A1 (en) | Method and apparatus for detecting obstruction for lidar, and storage medium | |
| CN119335554A (en) | Laser data processing method, device and laser sensor | |
| WO2024131976A1 (en) | Obstruction detection methods and obstruction detection devices for lidars, and lidars | |
| CN116740581B (en) | Method for determining material identification model, method for returning to base station and electronic equipment | |
| CN116609757A (en) | Detection method, device, equipment and medium for laser radar specular reflection ghost | |
| CN117310659B (en) | Method for judging light window shielding state of laser radar and related products | |
| CN116434181A (en) | Ground point detection method, device, electronic equipment and medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |