CN114646976A - Single-line laser radar road surface detection device based on holder and detection method thereof - Google Patents
Single-line laser radar road surface detection device based on holder and detection method thereof Download PDFInfo
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- CN114646976A CN114646976A CN202210301116.3A CN202210301116A CN114646976A CN 114646976 A CN114646976 A CN 114646976A CN 202210301116 A CN202210301116 A CN 202210301116A CN 114646976 A CN114646976 A CN 114646976A
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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
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01B—MEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
- G01B11/00—Measuring arrangements characterised by the use of optical techniques
- G01B11/30—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces
- G01B11/303—Measuring arrangements characterised by the use of optical techniques for measuring roughness or irregularity of surfaces using photoelectric detection means
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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
- G01S17/86—Combinations of lidar systems with systems other than lidar, radar or sonar, e.g. with direction finders
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10032—Satellite or aerial image; Remote sensing
- G06T2207/10044—Radar image
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Abstract
The invention discloses a single line laser radar road surface detection device based on a holder and a detection method thereof, wherein the device is arranged at the front part of an automatic driving vehicle and comprises a rotating holder device; the rotating holder device comprises a holder base, a servo steering engine and a bearing plate; the cradle head base is a square bearing platform, one side of the cradle head base is connected with a servo steering engine through a rotating shaft, and the other side of the cradle head base is connected with an L-shaped supporting seat through a rotating shaft; the L-shaped supporting rod is fixed on the bearing plate through a screw; and the holder base is connected with a single-line laser radar and a gyroscope module. This cloud platform adopts the structure that square platform supported, and integrated steering wheel, controller equal the cloud platform in, with the rotation of steering wheel drive cloud platform, with the work of STM32 controller control steering wheel, make single line laser radar swing according to the rule curve, then according to obstacles and pit etc. on testing result analysis ground, accomplish multi-thread laser radar's effect with single line laser radar to reduce cost.
Description
Technical Field
The invention relates to a single-line laser radar road surface detection device based on a holder and a detection method thereof, and belongs to the technical field of unmanned vehicle road surface detection devices.
Background
In the field of unmanned and outdoor robots, road surface detection, or passable area detection, is an important issue, which determines whether a vehicle can travel normally and safely in a complex environment or in an unknown area. At present, the road surface detection mostly scans a 3D model of the surrounding environment through a multi-line laser radar, and the change of the environment of the previous frame and the next frame is compared by applying a correlation algorithm, so that the surrounding environment condition is detected. The multiline laser radar is a main means for detecting the road surface at present due to high precision and suitability for most scenes. However, multiline lidar is relatively expensive to manufacture, and the more and more dense the line bundle, the more expensive the cost.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a single-line laser radar road surface detection device based on a holder and a detection method thereof, so that the technical problems are solved.
In order to achieve the purpose, the invention adopts the technical scheme that: a single line laser radar road surface detection device based on a holder comprises a rotating holder device; the rotating holder device comprises a holder base, a servo steering engine and a bearing plate; the cradle head base is a square bearing platform, one side of the cradle head base is connected with a servo steering engine through a rotating shaft, and the other side of the cradle head base is connected with an L-shaped supporting seat through a rotating shaft; the L-shaped supporting rod is fixed on the bearing plate through a screw; the holder base is connected with a laser radar and a gyroscope module;
the servo steering engine takes STM32 as a core and is used for driving the holder base and the laser radar to do pitching motion of-60 degrees to 60 degrees;
the gyroscope module is used for sending the pose data of the laser radar to the STM32 controller for processing, acquiring the pose information of the laser radar in real time and finally uploading the pose information to the upper computer;
the device also comprises a holder control module; the holder control module is used for carrying out instruction control on a motor controller of the servo steering engine; the motor controller records the position by recording the step number;
the obstacle avoidance system of the laser radar comprises a global navigation module and a local obstacle avoidance module; the global navigation module is used for guiding the unmanned vehicle to travel along a planned route; the local obstacle avoidance module is used for avoiding collision between the vehicle and an obstacle.
Furthermore, the servo steering engine adopts PID closed loop control to automatically detect and adjust the attitude parameters, and the attitude parameters are displayed on the upper computer. After the upper computer sends a rotation command and a scanning command, the driving motor drives the laser radar to start rotating and simultaneously scans the surrounding environment.
In the formula ukIs the output control quantity of the controller, ekAnd ek-1The current angle error and the last angle error are respectively. k is a radical ofp、ki、kdThe proportional coefficient, the integral coefficient and the differential coefficient of the control system are respectively corresponded.
Further, the laser radar carries out 360-degree all-directional scanning on the periphery within a fixed radius range; the number of points of one scanning circle of the laser radar is determined by the rotating speed of the radar rotating part and the data acquisition frequency, and when the rotating speed of the laser radar rotating part is fixed, the higher the data acquisition frequency of the laser radar is, the more the number of points of one scanning circle is; when the data acquisition frequency of the laser radar is fixed, the higher the rotating speed of the rotating part of the laser radar is, the fewer the number of points in one scanning circle is.
Further, the global navigation module establishes map information by inputting key points in a map when determining a driving route, wherein the data processing module completes control over the vehicle by using the map information to realize navigation over the unmanned vehicle.
A detection method of a single-line laser radar road surface detection device based on a holder comprises the following steps;
the method comprises the following steps: collecting data through a laser radar carried on a holder base, wherein the data comprises the distance and the angle between an obstacle and a sensor;
step two: the pose information of the laser radar is monitored in real time through a gyroscope module carried at the bottom of the platform;
step three: the servo steering engine controls the rotating shaft to rotate so as to drive the holder base to integrally rotate, the degree of freedom of the laser radar is increased, and information fusion is carried out on the data and the degree of freedom to generate point cloud numbers;
step four: performing a point cloud splicing test by adopting a point cloud matching algorithm to generate a 3D laser point cloud picture;
step five: according to the generated point cloud information, carrying out feature detection on the ground flatness to generate a front ground grid map;
step six: the planned path of the unmanned vehicle is adjusted by detecting the flatness of the front ground grid, and the chassis of the unmanned vehicle is controlled to move so as to avoid the collision of obstacles; and when the distance is smaller than a preset threshold value, calculating according to the local grid map to obtain an obstacle avoidance path.
And further, the fourth specific step is that point cloud segmentation is carried out on a real-time three-dimensional point cloud picture acquired by the three-dimensional laser radar, then feature points are extracted from the point cloud picture for feature matching, and then position and pose map optimization and loop detection are carried out to obtain high-precision three-dimensional positioning data and a three-dimensional point cloud map.
The invention has the beneficial effects that: the invention adopts a structure supported by a square platform, integrates a steering engine and a controller into a tripod head, drives the rotation of the tripod head by the steering engine, controls the work of the steering engine by an STM32 controller, enables a single-line laser radar to swing according to a regular curve, analyzes obstacles, pits and the like on the ground according to a detection result, achieves the effect of a multi-line laser radar by the single-line laser radar, and reduces the cost.
Drawings
FIG. 1 is a schematic diagram of the apparatus of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood, however, that the description herein of specific embodiments is only intended to illustrate the invention and not to limit the scope of the invention.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs, and the terms used herein in the specification of the present invention are for the purpose of describing particular embodiments only and are not intended to limit the present invention.
As shown in figure 1, a single line laser radar road surface detection device based on cloud platform, including rotating cloud platform device and laser radar 1 two parts, it includes cloud platform base 2, steering wheel 3, loading board 4 to rotate cloud platform device. The holder base 2 is a square bearing platform. A servo steering engine 3 is fixed on the side face of the base 2, and the servo steering engine 3 is used for driving the holder base 2 to do pitching motion and do pitching motion of-60 degrees to 60 degrees together with the single-line laser radar 1; and the holder base 2 connected with the laser radar 1 is provided with a hole for compatible connection of the holder and the radar. The support rod 5 is used for connecting the holder base 2 with the rotating shaft 6. The support rod 5 is connected with the rotating shaft 6 in a matching way through a slide rail. The support rod 5 is connected with the bearing plate 4 through a screw hole and a screw nut, so that the rotating shaft 6 can drive the holder base 2 to do pitching motion. The lidar 1 itself is rotatable through 360 °. And the position and pose information of the laser radar is acquired in real time through a gyroscope module 7 carried on the holder base 2.
In this embodiment, servo steering engine 3 uses STM32 to realize pitching motion as the core drive cloud platform base. After the upper computer sends a rotation command and a scanning command, the servo steering engine 3 is driven to drive the laser radar 1 to start rotating and do pitching motion, and meanwhile, the surrounding environment is scanned. The laser radar 1 performs 360 deg. omni-directional scanning around within a fixed radius. And the onboard gyroscope module 7 sends the pose data of the laser radar 1 to the STM32 controller for processing, acquires the pose information of the laser radar 1 in real time and finally uploads the pose information to the upper computer of the vehicle main controller.
The holder control module is used for carrying out instruction control on a motor controller of the servo steering engine 3; the motor controller records the position by recording the step number; in order to facilitate observation and control of the cradle head, the step number is converted into an angle, and a corresponding conversion formula is shown as a formula. The angle range of the tripod head is regulated to be-60 degrees. Angle 0.02/subdivision. And selecting a corresponding serial port, setting the baud rate to be 9600, and clicking to open the serial port to control the rotation of the holder. The parameters of the current angle, the subdivision number, the maximum speed, the starting speed, the stopping speed, the acceleration coefficient, the maximum current, the automatic attenuation factor, the speed compensation factor and the current compensation factor can be changed, and the parameters can be stored by clicking the 'write controller parameters' after the parameters are changed. Clicking on "read controller parameter" may display the controller parameter to the corresponding text box. Clicking on "power down save" may save the remaining parameters except for the current angle (the current angle power down may become 0). The numerical value of the set angle is set, then after the 'rotation' is clicked, the controller can control the holder to rotate to the set angle according to the set parameters such as the speed and the subdivision number, and the text box corresponding to the current angle can display the angle change in real time.
In order to conveniently observe the laser radar data, a program is compiled to realize curve drawing of the laser radar polar coordinate data. The method is to collect data once every 100ms and to perform median filtering on the distance information to prevent the distance information from having a skip value. And then drawing the filtered distance and the corresponding angle value into a polar coordinate curve.
The detection method of the single-line laser radar road surface detection device based on the holder is characterized by comprising the following steps;
the method comprises the following steps: data are collected through a laser radar 1 carried on a holder base 2, and the data comprise the distance and the angle between an obstacle and a sensor;
step two: the pose information of the laser radar 1 is monitored in real time through a gyroscope module carried at the bottom of the platform;
step three: the servo steering engine 3 controls the rotating shaft 6 to rotate so as to drive the holder base 2 to integrally rotate, the degree of freedom of the laser radar 1 is increased, and data and the degree of freedom are subjected to information fusion to generate point cloud numbers;
step four: performing a point cloud splicing test by adopting a point cloud matching algorithm to generate a 3D laser point cloud picture;
step five: according to the generated point cloud information, carrying out feature detection on the ground flatness to generate a front ground grid map;
step six: the planned path of the unmanned vehicle is adjusted by detecting the flatness of the front ground grid, and the chassis of the unmanned vehicle is controlled to move so as to avoid the collision of obstacles; and when the distance is smaller than a preset threshold value, calculating to obtain an obstacle avoidance path through an optimized A-x + BIT algorithm and a DWA fusion algorithm according to the local grid map.
In this embodiment, the road surface detection system designed this time establishes a three-dimensional point cloud chart after the computer acquires the information of the relevant obstacle. Since the unmanned sweeper is moving continuously, the distance data in the ROS is provided by the laser radar in batches within each time stamp, and the frequency of the measured data is high for the accuracy of the measurement result, repeated data can be generated. In order to reduce the repeated parts, the three-dimensional subgraph is built. Firstly, point cloud segmentation is carried out on a real-time three-dimensional point cloud picture acquired by a three-dimensional laser radar, then, characteristic points are extracted from the point cloud picture for characteristic matching, and then, position and pose picture optimization and loop detection are carried out to obtain high-precision three-dimensional positioning data and a three-dimensional point cloud map. In the establishment, the Cartogrer algorithm is applied and can be divided into two parts: local SLAM (front-end detection) and Global SLAM (back-end closed loop). The Cartographer algorithm combines Local SLAM and Global SLAM, both of which require optimization of the position and attitude information of the drone, i.e., the lidar scanning data (x, y, θ) (x and y are translations, θ is rotation angle), known as scans. And acquiring a real-time gravity direction by using an inertia measurement module, acquiring the attitude of the laser radar sensor, calculating a scanned plane according to the attitude of the laser radar sensor, converting distance data acquired by a radar into projection data, and projecting the projection data onto a 2D map. The Local SLAM in the Cartogrier is a process of changing scanning data of one frame into a plurality of raster maps, and in the process of executing the Local SLAM, a system can match each frame of data scanned by a laser radar module with a raster map obtained before to obtain a new raster map, and the map is continuously perfected. The scanning data is continuously matched in a nonlinear optimization mode, and the process is called scanning matching. With continuous matching, errors are gradually accumulated, and the errors need to be eliminated through a back-end closed loop.
The laser radar 1 is a single-line laser radar, and an obstacle avoidance system of the laser radar is divided into two parts, namely a global navigation module and a local obstacle avoidance module. The global planning, whether based on the sampling RRT algorithm or the heuristic search a-algorithm, can search out a global path from the starting point to the end point in a relatively short time, but cannot avoid obstacles in a dynamic environment. The local path planning DWA algorithm can detect obstacles in unknown environments, but has two disadvantages: firstly, only one target point is provided, and the optimal path cannot be obtained in a large-scale environment due to the lack of intermediate guidance; second, known obstacles are not distinguished from unknown obstacles, resulting in low dynamic obstacle avoidance sensitivity. Therefore, RRT and A can be improved and fused, the extracted key turning points are used as intermediate target points of DWA, the defects that a global planning algorithm cannot avoid dynamic obstacles and the local planning algorithm is low in global capability are overcome, and therefore global dynamic path obstacle avoidance is achieved. The traditional BIT algorithm is divided into: and the system comprises a batch sampling point generation module, a connecting module, an edge selection module, a node expansion module and a trimming module. The convergence speed of BIT depends on the size of the oval area, and the size of the oval area depends on the length of the current optimal path, so that the current path is reviewed, and the path cost caused by redundant points is reduced. The evaluation function of the conventional DWA algorithm includes three aspects of bearing evaluation, speed evaluation, and distance evaluation, and the evaluation function indicates that the unmanned vehicle advances at a large speed toward the destination while maintaining the distance from the obstacle. The traditional DWA algorithm is easy to fall into local optimization, and for the problem, global path points are used as relay points of the improved DWA algorithm, and a track point evaluation function is added to guide the DWA algorithm to carry out local planning. The evaluation function of the original dynamic window method can be effectively expanded by designing a path fusion sub-function, and the calculation formula is as follows:
wherein (x)1，y1) Deriving local path end coordinates based on sampling trajectories for dynamic windowing, (x)2，y2) And obtaining global path node coordinates for improving the A-algorithm. Now, the evaluation function of the updated dynamic window method is as follows:
G(v，ω)＝σ[ε·heading(v，ω)+τ·dist(v，ω)+γ·vel(v，ω)+κ·fusion(v，ω)]
where k is a weight.
In short, by designing a path fusion sub-function, an optimal smooth path considering real-time obstacle avoidance can be acquired in the global map.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents or improvements made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (6)
1. A single line laser radar road surface detection device based on a holder is characterized by comprising a rotating holder device; the rotating holder device comprises a holder base (2), a servo steering engine (3) and a bearing plate (4); the cradle head base (2) is a square bearing platform, one side of the cradle head base (2) is connected with a servo steering engine (3) through a rotating shaft (6), and the other side of the cradle head base is connected with an L-shaped supporting seat (5) through the rotating shaft (6); the L-shaped supporting rod (5) is fixed on the bearing plate (4) through a screw; the holder base (2) is connected with a single-line laser radar (1) and a gyroscope module (7);
the servo steering engine (3) takes the STM32 as a core and is used for driving the holder base (2) and the laser radar (1) to do pitching motion of-60 degrees to 60 degrees;
the gyroscope module (7) is used for sending the pose data of the laser radar (1) to the STM32 controller for processing, acquiring the pose information of the laser radar in real time and finally uploading the pose information to the upper computer;
the device also comprises a holder control module; the holder control module is used for carrying out instruction control on a motor controller of the servo steering engine (3); the motor controller records the position by recording the step number;
the obstacle avoidance system of the single-line laser radar (1) comprises a global navigation module and a local obstacle avoidance module; the global navigation module is used for guiding the unmanned vehicle to travel along a planned route; the local obstacle avoidance module is used for avoiding collision between the vehicle and an obstacle.
2. The single-line laser radar road surface detection device based on the holder is characterized in that the servo steering engine (3) automatically detects and adjusts the attitude parameters by adopting PID closed-loop control, and displays the attitude parameters on an upper computer. After the upper computer sends a rotation command and a scanning command, the driving motor drives the laser radar to start rotating and simultaneously scans the surrounding environment;
in the formula ukIs the output control quantity of the controller, ekAnd ek-1The angle error of the current time and the angle error of the last time are respectively;
kp、ki、kdrespectively corresponding to the proportional coefficient of the control system,Integral coefficients and differential coefficients.
3. The single line laser radar road surface detection device based on the tripod head according to claim 1, wherein the single line laser radar (1) carries out 360-degree all-around scanning on the periphery within a fixed radius range; the number of points of the single-line laser radar (1) which scans for one circle is determined by the rotating speed of the rotating part of the radar and the data acquisition frequency, and when the rotating speed of the rotating part of the single-line laser radar (1) is fixed, the higher the data acquisition frequency of the laser radar is, the more the number of points of the single-line laser radar which scans for one circle is; when the data acquisition frequency of the laser radar (1) is fixed, the higher the rotating speed of the rotating part of the laser radar (1), the fewer the number of points in one scanning circle.
4. The single line laser radar road surface detection device based on the pan-tilt-zoom-.
5. A detection method of a single-line laser radar road surface detection device based on a holder is characterized by comprising the following steps;
the method comprises the following steps: data are collected through a laser radar (1) carried on a holder base (2), and the data comprise the distance and the angle between an obstacle and a sensor;
step two: the pose information of the laser radar (1) is monitored in real time through a gyroscope module carried at the bottom of the platform;
step three: the servo steering engine (3) controls the rotating shaft (6) to rotate so as to drive the holder base (2) to integrally rotate, the degree of freedom of the laser radar (1) is increased, and information fusion is carried out on data and the degree of freedom to generate a point cloud number;
step four: performing a point cloud splicing test by adopting a point cloud matching algorithm to generate a 3D laser point cloud picture;
step five: according to the generated point cloud information, carrying out feature detection on the ground flatness to generate a front ground grid map;
step six: the planned path of the unmanned vehicle is adjusted by detecting the flatness of the front ground grid, and the chassis of the unmanned vehicle is controlled to move so as to avoid the collision of obstacles; and when the distance is smaller than a preset threshold value, calculating to obtain an obstacle avoidance path through a fusion algorithm of A, RRT and DWA according to the local grid map.
6. The holder-based single line laser radar road surface detection device according to claim 5, wherein the fourth specific step is to perform point cloud segmentation on a real-time three-dimensional point cloud map acquired by the three-dimensional laser radar, extract feature points from the point cloud map for feature matching, and perform pose map optimization and loop detection to obtain high-precision three-dimensional positioning data and a three-dimensional point cloud map.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116587991A (en) * | 2023-07-17 | 2023-08-15 | 深圳市蓝鲸智联科技有限公司 | Car bottom obstacle scanning early warning system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116587991A (en) * | 2023-07-17 | 2023-08-15 | 深圳市蓝鲸智联科技有限公司 | Car bottom obstacle scanning early warning system |
| CN116587991B (en) * | 2023-07-17 | 2023-11-14 | 深圳市蓝鲸智联科技股份有限公司 | Car bottom obstacle scanning early warning system |
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