CN115222815A - Obstacle distance detection method, obstacle distance detection device, computer device, and storage medium - Google Patents
Obstacle distance detection method, obstacle distance detection device, computer device, and storage medium Download PDFInfo
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Abstract
The application relates to an obstacle distance detection method, an obstacle distance detection device, a computer device, a storage medium and a computer program product. The method comprises the following steps: acquiring original point cloud data and image data corresponding to the original point cloud data; performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data; detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line; projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to an obstacle contact line in the ground point cloud projection area; and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance. The method can improve the accuracy of the obstacle distance detection.
Description
Technical Field
The present application relates to the field of automatic driving technologies, and in particular, to a method, an apparatus, a computer device, a storage medium, and a computer program product for detecting a distance to an obstacle.
Background
With the development of the automatic driving technology, it is required to detect obstacles in the surrounding environment of the automatic driving vehicle and to obtain accurate distance information to plan a driving route and speed. The existing obstacle ranging usually detects obstacles through image data, but cannot accurately obtain the distance information of the obstacles; distance information can be obtained by detecting obstacles through a laser radar, but the problem of low accuracy of obstacle distance detection exists due to point cloud sparseness of small objects and long-distance objects.
Disclosure of Invention
In view of the above, it is necessary to provide an obstacle distance detection method, an apparatus, a computer device, a computer readable storage medium, and a computer program product, which can improve the accuracy of obstacle distance detection, in view of the above technical problems.
In a first aspect, the present application provides a method of obstacle distance detection. The method comprises the following steps:
acquiring original point cloud data and image data corresponding to the original point cloud data;
performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data;
detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to an obstacle contact line in the ground point cloud projection area;
and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
In a second aspect, the present application further provides an obstacle distance detection apparatus. The device comprises:
the acquisition module is used for acquiring original point cloud data and image data corresponding to the original point cloud data;
the ground detection module is used for carrying out ground point cloud detection on the basis of the original point cloud data to obtain ground point cloud data and generating a target ground point cloud area on the basis of the ground point cloud data;
the contact line detection module is used for detecting the contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
the projection module is used for projecting based on a target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to an obstacle contact line in the ground point cloud projection area;
and the calculation module is used for determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain the obstacle distance.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the following steps when executing the computer program:
acquiring original point cloud data and image data corresponding to the original point cloud data;
performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data;
detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to an obstacle contact line in the ground point cloud projection area;
and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
In a fourth aspect, the present application further provides a computer-readable storage medium. The computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring original point cloud data and image data corresponding to the original point cloud data;
performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data;
detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to an obstacle contact line in the ground point cloud projection area;
and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
In a fifth aspect, the present application further provides a computer program product. The computer program product comprising a computer program which when executed by a processor performs the steps of:
acquiring original point cloud data and image data corresponding to the original point cloud data;
performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data;
detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area;
and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
According to the obstacle distance detection method, the obstacle distance detection device, the computer equipment, the storage medium and the computer program product, the ground point cloud data are detected from the original point cloud data, and the target ground point cloud area is generated according to the ground point cloud data. And then detecting a contact line between the obstacle and the ground through image data, and projecting the target ground point cloud area to obtain a ground point cloud projection area, so that projection data corresponding to the obstacle contact line exist in the ground point cloud projection area. The obstacle projection contact line corresponding to the obstacle contact line can be accurately obtained according to the obstacle contact line through the ground point cloud projection area, accurate obstacle contact line point cloud data can be obtained through the obstacle projection contact line, and the accurate obstacle distance can be obtained through calculation according to the obstacle contact line point cloud data, so that the accuracy of obstacle distance detection is improved.
Drawings
FIG. 1 is a diagram of an exemplary environment for an obstacle distance detection method;
FIG. 2 is a schematic flow chart of a method for obstacle distance detection in one embodiment;
FIG. 3 is a schematic flow chart illustrating the calculation of a target obstacle distance in one embodiment;
FIG. 4 is a schematic illustration of a region demarcated by a ground point cloud in one embodiment;
FIG. 5 is a schematic flow diagram illustrating the generation of filled ground point cloud data in one embodiment;
FIG. 6 is a schematic illustration of an obstacle contact line in one embodiment;
FIG. 7 is a schematic flow chart of obstacle distance detection in one embodiment;
fig. 8 is a block diagram showing the structure of an obstacle distance detection apparatus according to an embodiment;
FIG. 9 is a diagram of the internal structure of a computer device in one embodiment;
FIG. 10 is a diagram showing an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for detecting the distance between the obstacles provided by the embodiment of the application can be applied to the application environment shown in fig. 1. Wherein the mobile carrier terminal 102 communicates with the server 104 over a network. The data storage system may store data that the server 104 needs to process. The data storage system may be integrated on the server 104 or may be placed on the cloud or other network server. A moving carrier terminal acquires original point cloud data and image data corresponding to the original point cloud data; the moving carrier terminal carries out ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and a target ground point cloud area is generated based on the ground point cloud data; the moving carrier terminal detects a contact line between the barrier and the ground based on the image data to obtain a barrier contact line; the method comprises the steps that a moving carrier terminal projects based on a target ground point cloud area to obtain a ground point cloud projection area, and an obstacle projection contact line corresponding to an obstacle contact line is determined in the ground point cloud projection area; and the moving carrier terminal determines obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performs distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance. The moving carrier terminal sends the obstacle distance to the server 104 and obtains a moving path, and moves according to the moving path. The terminal 102 may be, but not limited to, various personal computers, notebook computers, smart phones, tablet computers, internet of things devices and portable wearable devices, and the internet of things devices may be smart speakers, smart televisions, smart air conditioners, smart car-mounted devices, and the like. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, and the like. The server 104 may be implemented as a stand-alone server or a server cluster comprised of multiple servers.
In one embodiment, as shown in fig. 2, an obstacle distance detection method is provided, which is described by taking an example that the method is applied to the moving carrier terminal in fig. 1, it is to be understood that the method may also be applied to a server, and may also be applied to a system including a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the steps of:
step 202, obtaining original point cloud data and image data corresponding to the original point cloud data.
The original point cloud data refers to the acquired original point cloud data of the surrounding environment of the motion carrier, and the surrounding environment may include obstacles. The image data refers to the acquired original image of the environment surrounding the moving carrier. The motion carrier refers to a movable object, and the motion carrier can be an unmanned motion carrier or a manned motion carrier.
Specifically, the motion carrier is equipped with a point cloud data acquisition device and an image acquisition device, the point cloud data acquisition device and the image acquisition device perform a unified coordinate system in advance, and synchronously acquire data by using the same frame rate, that is, one frame of image data in the image data corresponds to one frame of point cloud data in the original point cloud data. The moving carrier terminal can acquire original point cloud data around the moving carrier through the point cloud data acquisition equipment, and acquire image data around the moving carrier through the image acquisition equipment. The moving carrier may be a vehicle, aircraft, robot, etc.
And 204, performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data.
The ground point cloud data refers to point cloud data representing the ground in the original point cloud data. The target ground point cloud area is ground point cloud data obtained by filling point cloud data into the ground area in the original point cloud data.
Specifically, the motion carrier terminal detects the original point cloud data by using a preset ground point classification algorithm to obtain ground point cloud data in the original point cloud data. And then the moving carrier terminal scans the ground point cloud data, and when a blank area exists between the ground point cloud data, the blank area is filled with the point cloud data according to the existing ground point cloud data to obtain a target ground point cloud area.
And step 206, detecting a contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line.
The obstacle contact line is a contact area between the obstacle and the ground, and is displayed as a line in the image data.
Specifically, the moving carrier terminal detects a contact area between image data and the ground by using a preset deep learning network model, and obtains an obstacle contact line output by the model.
And 208, projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area.
The projection refers to a process of projecting three-dimensional point cloud data of a target ground point cloud area to a two-dimensional plane to obtain point cloud projection data, the point cloud projection data refers to data of the point cloud data projected to the two-dimensional plane, and the point cloud projection data exists in the form of the two-dimensional data. In one embodiment, the point cloud data is projected onto the same two-dimensional coordinate system as the image data to obtain corresponding point cloud projection data. The ground point cloud projection area is a point cloud projection area obtained after projection is carried out on the target ground point cloud area. The obstacle projection contact line refers to point cloud projection data corresponding to the obstacle contact line in the ground point cloud projection area.
Specifically, the motion carrier terminal converts three-dimensional coordinates in a target ground point cloud area into horizontal plane coordinates according to preset calibration parameters to obtain point cloud projection data after projection of the target ground point cloud area, namely a ground point cloud projection area. And then the moving carrier terminal searches the corresponding barrier projection contact line in the ground point cloud projection area according to the coordinate information of the barrier contact line.
And step 210, determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
The obstacle contact line point cloud data is point cloud data corresponding to an obstacle projection contact line in a target ground point cloud area. The horizontal plane coordinate information refers to two-dimensional coordinates representing a horizontal plane in three-dimensional coordinates of the point cloud data. The obstacle distance refers to the distance between the moving carrier and the obstacle.
Specifically, the motion carrier terminal finds obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area according to the projection relationship between the target ground point cloud area and the ground point cloud projection area. And then acquiring horizontal plane coordinates in obstacle contact line point cloud data to calculate the distance so as to obtain the distance between the motion carrier and the obstacle.
In the obstacle distance detection method, ground point cloud data is detected from the original point cloud data, and a target ground point cloud area is generated according to the ground point cloud data. Then, a contact line between the obstacle and the ground is detected through the image data, the target ground point cloud area is projected to obtain a ground point cloud projection area, and the fact that projection data corresponding to the obstacle contact line exist in the ground point cloud projection area is guaranteed. The obstacle projection contact line corresponding to the obstacle contact line can be accurately obtained according to the obstacle contact line through the ground point cloud projection area, accurate obstacle contact line point cloud data can be obtained through the obstacle projection contact line, and the accurate obstacle distance can be obtained through calculation according to the obstacle contact line point cloud data, so that the accuracy of obstacle distance detection is improved.
In one embodiment, as shown in FIG. 3, a schematic flow chart for calculating a target obstacle distance is provided; the method further comprises the following steps:
step 302, acquiring vertical coordinate information corresponding to obstacle contact line point cloud data and coordinate information corresponding to an obstacle contact line;
step 304, performing point cloud coordinate calculation based on the vertical coordinate information and the coordinate information to obtain target horizontal plane coordinate information corresponding to the obstacle contact line point cloud data;
and step 306, performing distance calculation based on the coordinate information of the target horizontal plane to obtain the target obstacle distance.
The vertical coordinate information refers to a coordinate in a vertical direction in a three-dimensional coordinate of the point cloud data. The coordinate information is two-dimensional plane coordinates corresponding to the image data. The target horizontal plane coordinate information refers to horizontal plane coordinate information corresponding to obstacle contact line point cloud data obtained through point cloud coordinate calculation, and comprises horizontal coordinate information and longitudinal coordinate information corresponding to the point cloud data. The target obstacle distance refers to the distance between the moving carrier and the obstacle, which is obtained by performing distance calculation by using the coordinate information of the target horizontal plane.
Specifically, the motion carrier terminal scans the obstacle contact line point cloud data, and when the filled ground point cloud data exists in the obstacle contact line point cloud data, the vertical coordinate information corresponding to the obstacle contact line point cloud data is acquired. And then, the moving carrier terminal acquires coordinate information corresponding to the obstacle contact line, wherein the coordinate information corresponding to the obstacle contact line can be obtained when the moving carrier terminal detects a contact area between image data and the ground by using a preset deep learning network model. And the moving carrier terminal acquires a pre-stored point cloud coordinate calculation formula, and calculates according to the point cloud calculation formula by using the vertical coordinate information corresponding to the obstacle contact line point cloud data and the coordinate information corresponding to the obstacle contact line to obtain the horizontal plane coordinate information corresponding to the obstacle contact line point cloud data. And the moving carrier terminal takes the horizontal plane coordinate information corresponding to the calculated obstacle contact line point cloud data as target horizontal plane coordinate information. And then the moving carrier terminal uses the coordinate information of the target horizontal plane to calculate the distance to obtain the distance of the target obstacle.
When the moving carrier terminal detects that the filled ground point cloud data does not exist in the obstacle contact line point cloud data, the horizontal plane coordinate information corresponding to the ground point cloud data existing in the obstacle contact line point cloud data is used as target horizontal plane coordinate information, and distance calculation is carried out by using the target horizontal plane coordinate information to obtain the target obstacle distance.
In a specific embodiment, the point cloud data collecting device may be a laser radar, the image collecting device may be a monocular camera, and the internal and external parameter matrixes may be obtained in advance through calibration algorithms of the laser radar and the monocular camera. The point cloud coordinate calculation formula is obtained by deducing an internal and external parameter matrix, and the internal and external parameter matrix is obtained in advance through a calibration algorithm. The calculation formula for projecting the three-dimensional coordinates in the camera coordinate system into the image through the internal reference matrix is shown in formula (1):
wherein fx, fy is camera focal length, ox oy is origin offset, xc, yc, zc are three-dimensional points in camera coordinate system, and U, V are two-dimensional coordinates of each point in the obstacle contact line.
The calculation formula for transforming the three-dimensional points under the laser radar coordinate system into the camera coordinate system through the external reference matrix is shown as formula (2):
wherein M is a rotation matrix, tx, ty and tz are translation vectors, xw, yw and Zw are three-dimensional points under a laser radar coordinate system, and Xc, yc and Zc are three-dimensional points under a camera coordinate system.
The point cloud coordinate calculation formula is obtained by derivation by using the formula (1) and the formula (2), as shown in the formula (3),
Xw＝((M11-(V-oy)*(M21)/fy)*((U-ox)*(M22*Zw+tz)/fx-M02*Zw-tx)-(M01-(U-ox)*(M21)/fx)*((V-oy)*(M22*Zw+tz)/fy-M12*Zw-ty))/((M11-(V-oy)*(M21)/fy)*(M00-(U-ox)*(M20)/fx)-(M01-(U-ox)*(M21)/fx)*(M10-(V-oy)*(M20)/fy))；
yw = ((M10- (V-oy) × (M20)/fy) ((U-ox) × (M22 × Zw + tz)/fx-M02 × Zw-tx) - (M00- (U-ox) × (M20)/fx) ((V-oy) × (M22 × Zw + tz)/fy-M12 × Zw-ty))/((M10- (V-oy) ((M20)/fy) ((M01- (U-ox) × (M21)/fx) - (M00- (U-ox) ((M20)/fx) ((M11- (V-oy) ((M21)/fy)) formula (3),
wherein Xw represents transverse coordinate information corresponding to the obstacle contact line point cloud data; yw represents the longitudinal coordinate information corresponding to the obstacle contact line point cloud data. The motion carrier obtains corresponding vertical coordinate information Zw in the point cloud data of the contact line of the obstacle, obtains corresponding coordinate information (U, V) of the contact line of the obstacle, uses Zw and (U, V) to calculate according to a formula (3) to obtain corresponding template horizontal plane coordinate information (Xw, yw) of the point cloud number of the contact line of the obstacle, and then uses (Xw, yw) to calculate the distance of the target obstacle.
In the embodiment, when filled ground point cloud data exists in the obstacle contact line point cloud data, the point cloud coordinate calculation formula is used for calculating the horizontal plane coordinate information corresponding to the obstacle contact line point cloud data, so that the error of the filled ground point cloud data can be reduced, and the accuracy of obstacle distance detection is improved.
In one embodiment, step 204, generating a target ground point cloud region based on the ground point cloud data includes:
dividing the ground point cloud data based on a preset division specification to obtain a ground point cloud division area, wherein the ground point cloud division area comprises a ground point cloud area and an area to be filled;
and generating filling ground point cloud data corresponding to the area to be filled based on the area ground point cloud data in the ground point cloud area, and generating a target ground point cloud area based on the area ground point cloud data and the filling ground point cloud data.
The preset division specification refers to a preset specification for carrying out region division on the ground point cloud data. The ground point cloud dividing region is a dividing region obtained by dividing ground point cloud data, and the ground point cloud dividing region comprises the ground point cloud data. The ground point cloud area refers to an area in which ground point cloud data exists in the ground point cloud dividing area. The region to be filled refers to a region in which ground point cloud data needs to be filled in the ground point cloud division region. The ground point cloud data filling means ground point cloud data filled in an area to be filled. The regional ground point cloud data refers to ground point cloud data existing in a ground point cloud region.
Specifically, the moving carrier terminal divides the ground point cloud data into grids of fixed specification according to a preset division specification, for example, divides the ground point cloud data into 3 × 3 square grids according to a division specification of 3 meters. And then the moving carrier terminal searches for the grid with the ground point cloud data, scans the distribution state of the ground point cloud data in the searched grid, takes the area distributed with the ground point cloud data in the scanned grid as the ground point cloud area, and takes the area not distributed with the ground point cloud data in the scanned grid as the area to be filled.
And then, the motion carrier terminal estimates according to the ground point cloud data in the ground point cloud area, the ground point cloud data obtained through estimation is used as filling ground point cloud data, and the filling ground point cloud data is filled in the area to be filled. And the moving carrier terminal can scan each grid with the ground point cloud data again, and when detecting that the area to be filled does not exist, each grid with the ground point cloud data is used as a target ground point cloud area.
In one embodiment, as shown in FIG. 4, a schematic diagram of a cloud divided area of a surface point is provided; the frame A represents a ground point cloud division area obtained by division; box A-a represents a ground point cloud area; the boxes a-b represent the area to be filled.
In the embodiment, the ground point cloud data is divided according to the preset division specification to obtain each ground point cloud division area, and the area to be filled in the ground point cloud division area is filled with the point cloud data, so that complete ground point cloud data can be obtained, the three-dimensional coordinates corresponding to the contact line of the obstacle in the target ground point cloud area can be ensured, the condition of data loss in the projection of the target ground point cloud area is avoided, and the accuracy of obstacle distance detection is improved.
In one embodiment, as shown in FIG. 5, a schematic flow chart for generating filled-in ground point cloud data is provided; generating filling ground point cloud data corresponding to a region to be filled based on regional ground point cloud data in the ground point cloud region, wherein the filling ground point cloud data comprises the following steps:
step 502, establishing a regional point cloud coordinate relation based on regional ground point cloud data;
step 504, obtaining area horizontal plane coordinate information corresponding to the area ground point cloud data, and calculating filling horizontal plane coordinate information corresponding to an area to be filled based on the area horizontal plane coordinate information and preset horizontal plane coordinate interval information;
step 506, calculating according to the area point cloud coordinate relation based on the filling plane coordinate information to obtain filling vertical coordinate information corresponding to the area to be filled;
and step 508, generating filling ground point cloud data corresponding to the area to be filled based on the filling horizontal coordinate information and the filling vertical coordinate information.
The area point cloud coordinate relationship refers to an objective physical relationship existing between point clouds in a ground point cloud partition area. The area point cloud coordinate relations corresponding to different ground point cloud division areas are different. The region horizontal plane coordinate information refers to horizontal plane coordinate information corresponding to ground point cloud data in the ground point cloud region. The filling of the ground point cloud data refers to ground point cloud data estimated according to the regional ground point cloud data, and the filling of the ground point cloud data is used for filling the region to be filled. The preset horizontal plane coordinate interval information refers to preset interval values between horizontal plane coordinates used for estimating and filling ground point cloud data. The filling horizontal plane coordinate information refers to horizontal plane coordinate information corresponding to the filling ground point cloud data. The filling of the vertical coordinate information refers to filling of vertical coordinate information corresponding to the ground point cloud data.
Specifically, the moving carrier terminal randomly acquires at least two regional ground point cloud data, establishes a regional point cloud coordinate relationship according to the at least two regional ground point cloud data, and can establish the regional point cloud coordinate relationship by using a plane equation: ax + By + Cz + D =0, a, B, C, D represent coefficients of a plane equation, which can be estimated By using an algorithm such as the least square method, RANSAC, or the like. Then, the moving carrier terminal scans regional ground point cloud data in the ground point cloud region to obtain regional horizontal plane coordinate information corresponding to the regional ground point cloud data closest to the region to be filled, and then accumulates the regional horizontal plane coordinate information according to preset horizontal plane coordinate interval information to obtain a plurality of filling horizontal plane coordinate information corresponding to the region to be filled, for example, the regional horizontal plane coordinate information corresponding to the regional ground point cloud data is (1, 1), and the preset horizontal plane coordinate interval information is 0.1, and then the filling horizontal plane coordinate information corresponding to the filling ground point cloud data is (1.1 ), (1.2, 1.2), (1.3 ), and the like, or the filling horizontal plane coordinate information corresponding to the filling ground point cloud data is (1.1 ), (1.1, 1.2), (1.3, 1.2), (1.1.3, 1.4), and the like, or (1.1 ), (1.2, 1.1), (1.3, 1.2), (1.3, and the like) can be accumulated according to coordinates respectively. And the motion carrier terminal calculates according to the point cloud coordinate relationship by using the estimated filling horizontal plane coordinate information to obtain filling vertical coordinate information, then obtains filling ground point cloud data corresponding to the area to be filled according to the filling horizontal plane coordinate information and the filling vertical coordinate information, and marks the filling ground point cloud data so as to process the filling ground point cloud data subsequently.
In the embodiment, the filled ground point cloud data can be accurately obtained and the complete ground point cloud data can be obtained by estimating the existing ground point cloud data through the preset horizontal plane coordinate interval information and the area point cloud coordinate relationship, so that the three-dimensional coordinate corresponding to the barrier contact line in the target ground point cloud area can be ensured, the condition of data loss in the projection of the target ground point cloud area is avoided, and the accuracy of barrier distance detection is improved.
In one embodiment, step 208, determining an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area includes:
searching projection coordinate information which is the same as the contact line coordinate information in a ground point cloud projection area based on the contact line coordinate information corresponding to the barrier contact line to obtain target projection coordinate information;
and obtaining an obstacle projection contact line based on the target projection coordinate information.
The contact line coordinate information refers to two-dimensional coordinate information corresponding to the obstacle contact line in the acquired image data. The projection coordinate information refers to two-dimensional coordinate information in image data corresponding to the ground point cloud projection area.
Specifically, the motion carrier terminal scans projection coordinate information in a ground point cloud projection area according to contact line coordinate information corresponding to an obstacle contact line, obtains projection coordinate information identical to the contact line coordinate information in the ground point cloud projection area, and takes the obtained projection coordinate information as target projection coordinate information. And then the moving carrier terminal obtains the projection contact line of the barrier according to the target projection coordinate information. Specifically, the number of two-dimensional points in the obstacle contact line is determined by the number of pixels corresponding to the image data, the number of two-dimensional points in the obstacle projection contact line is determined by the number of two-dimensional points in the obstacle contact line, and further, the number of three-dimensional points in the obstacle contact line point cloud data is determined by the number of two-dimensional points in the obstacle projection contact line.
In one embodiment, as shown in FIG. 6, a schematic view of an obstacle contact line is provided; in the figure, a represents an obstacle in the acquired image data; b represents a ground area in the acquired image data; line L represents the line of contact of the obstacle with the ground.
In the embodiment, the target projection coordinate information which is the same as the contact line coordinate information is searched in the ground point cloud projection area, so that the barrier projection contact line is obtained, the coordinate accuracy of the barrier projection contact line can be improved, and the accuracy of barrier distance detection is improved.
In one embodiment, step 210, performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance, includes:
acquiring horizontal plane coordinate information corresponding to each three-dimensional point in the obstacle contact line point cloud data;
respectively performing distance calculation based on the horizontal plane coordinate information corresponding to each three-dimensional point to obtain a point obstacle distance corresponding to each three-dimensional point;
and taking the shortest point obstacle distance in the point obstacle distances corresponding to the three-dimensional points as the obstacle distance.
Wherein the three-dimensional points represent constituent units that constitute the point cloud data. Point-obstacle distance refers to the distance between the moving carrier and the three-dimensional point in the obstacle contact line.
Specifically, the moving carrier terminal acquires horizontal plane coordinate information corresponding to each three-dimensional point in the obstacle contact line point cloud data, wherein the horizontal plane coordinate information comprises transverse coordinate information and longitudinal coordinatesAnd (4) information. And respectively using the horizontal plane coordinate information corresponding to each three-dimensional point to calculate the distance to obtain the barrier distances of the plurality of points. The moving carrier terminal can calculate the point obstacle distance by using a triangle hypotenuse calculation formula:
d represents the obstacle distance.
And then the moving carrier terminal compares the barrier distances of all points, and the barrier distance of the point with the shortest distance is taken as the barrier distance.
And then the moving carrier takes the right front of the moving carrier as 0 degree and takes the anticlockwise direction as the positive direction, and the position of the obstacle is calculated according to the transverse coordinate information and the longitudinal coordinate information corresponding to the distance of the obstacle, so that the position and the direction of the obstacle relative to the moving carrier are obtained. The moving terminal carrier may calculate the position of the obstacle using the angle calculation formula atan2 (y, x). For example, the calculated obstacle position is +45 degrees, which indicates that the obstacle is at the front left of the moving carrier, and the calculated obstacle position is-45 degrees, which indicates that the obstacle is at the front right of the moving carrier.
In this embodiment, the accuracy of the barrier distance can be improved by calculating the point barrier distance of each three-dimensional point and taking the point barrier distance with the shortest distance as the barrier distance.
In one embodiment, as shown in fig. 7, a schematic flow chart of obstacle distance detection is provided; in the driving process of the automatic driving vehicle, the vehicle-mounted terminal acquires original point cloud data of a current frame in a range of 360 degrees from the laser radar, acquires image data of 360 degrees around the automatic driving vehicle from the 6 cameras, and calibrates internal and external parameters of the laser radar and the cameras.
The vehicle-mounted terminal searches out ground points in the original point cloud data by using ground point classification algorithms such as deep learning and traditional geometric algorithm to obtain ground point cloud data. The scene is then divided according to a coarse resolution, e.g. 3 meters per grid mesh, and the plane equation for the mesh is calculated for the mesh with the ground point cloud data. Then determining a ground point cloud data missing area in the grid, namely an area to be filled, estimating the missing ground point cloud data by the vehicle-mounted terminal according to the existing ground point cloud data closest to the ground point cloud data missing area, generating filling horizontal plane coordinate information x and y at certain intervals, such as 0.1, on an x plane and a y plane of the grid, calculating filling vertical coordinate information by the vehicle-mounted terminal according to the filling horizontal plane coordinate information x and y of the grid by using a plane equation corresponding to the grid to obtain filling ground point cloud data, and finishing ground point cloud estimation to obtain a target ground point cloud area.
The vehicle-mounted terminal carries out obstacle detection on image data acquired by image acquisition equipment in target detection models such as YOLO, SSD, centerNet and the like, including traffic participation obstacle targets such as vehicles, pedestrians, bicycles, cone barrels and the like, and outputs a contact line between an obstacle and the ground through the detection models.
The vehicle-mounted terminal projects the target ground point cloud area to obtain a ground point cloud projection area, then target projection coordinate information which is the same as coordinate information of the obstacle contact line is searched in the ground point cloud projection area to obtain an obstacle projection contact line, obstacle contact line point cloud data corresponding to the obstacle projection contact line is searched in the target ground point cloud area according to the projection relation, and distance calculation is carried out according to horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance. The vehicle-mounted terminal can re-plan the driving route and the driving speed according to the distance between the obstacles.
It should be understood that, although the steps in the flowcharts related to the embodiments as described above are sequentially displayed as indicated by arrows, the steps are not necessarily performed sequentially as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least a part of the steps in the flowcharts related to the embodiments described above may include multiple steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, and the execution order of the steps or stages is not necessarily sequential, but may be rotated or alternated with other steps or at least a part of the steps or stages in other steps.
Based on the same inventive concept, the embodiment of the application also provides an obstacle distance detection device for realizing the obstacle distance detection method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, so that specific limitations in one or more embodiments of the obstacle distance detection device provided below can be referred to the limitations on the obstacle distance detection method in the foregoing, and details are not described here.
In one embodiment, as shown in fig. 8, there is provided an obstacle distance detecting apparatus 800 including: an acquisition module 802, a ground detection module 804, a contact line detection module 806, a projection module 808, and a calculation module 810, wherein:
an obtaining module 802, configured to obtain original point cloud data and image data corresponding to the original point cloud data;
a ground detection module 804, configured to perform ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generate a target ground point cloud area based on the ground point cloud data;
a contact line detection module 806, configured to perform contact line detection on an obstacle and the ground based on the image data, to obtain an obstacle contact line;
the projection module 808 is configured to perform projection based on the target ground point cloud area to obtain a ground point cloud projection area, and determine an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area;
and the calculating module 810 is used for determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
In one embodiment, the obstacle distance detecting apparatus 800 further includes:
the target obstacle distance calculation unit is used for acquiring vertical coordinate information corresponding to the obstacle contact line point cloud data and coordinate information corresponding to the obstacle contact line; performing point cloud coordinate calculation based on the vertical coordinate information and the coordinate information to obtain target horizontal plane coordinate information corresponding to the obstacle contact line point cloud data; and calculating the distance based on the coordinate information of the target horizontal plane to obtain the distance of the target obstacle.
In one embodiment, the ground detection module 804 includes:
the area dividing unit is used for dividing the ground point cloud data based on a preset dividing specification to obtain a ground point cloud dividing area, and the ground point cloud dividing area comprises a ground point cloud area and an area to be filled; and generating filling ground point cloud data corresponding to the region to be filled based on the regional ground point cloud data in the ground point cloud region, and generating a target ground point cloud region based on the regional ground point cloud data and the filling ground point cloud data.
In one embodiment, the ground detection module 804 includes:
the filling point cloud unit is used for establishing a regional point cloud coordinate relation based on regional ground point cloud data; acquiring area horizontal plane coordinate information corresponding to the area ground point cloud data, and calculating filling horizontal plane coordinate information corresponding to an area to be filled based on the area horizontal plane coordinate information and preset horizontal plane coordinate interval information; calculating according to the area point cloud coordinate relation based on the filling plane coordinate information to obtain filling vertical coordinate information corresponding to the area to be filled; and generating filling ground point cloud data corresponding to the area to be filled based on the filling horizontal plane coordinate information and the filling vertical coordinate information.
In one embodiment, projection module 808, comprises:
the coordinate projection unit is used for searching projection coordinate information which is the same as the contact line coordinate information in the ground point cloud projection area based on the contact line coordinate information corresponding to the barrier contact line to obtain target projection coordinate information; and obtaining an obstacle projection contact line based on the target projection coordinate information.
In one embodiment, the calculation module 810 includes:
the distance calculation unit is used for acquiring horizontal plane coordinate information corresponding to each three-dimensional point in the obstacle contact line point cloud data; respectively performing distance calculation based on the horizontal plane coordinate information corresponding to each three-dimensional point to obtain a point obstacle distance corresponding to each three-dimensional point; and taking the shortest point obstacle distance in the point obstacle distances corresponding to the three-dimensional points as the obstacle distance.
Each module in the above obstacle distance detection apparatus may be wholly or partially implemented by software, hardware, or a combination thereof. The modules can be embedded in a hardware form or independent of a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 9. The computer device includes a processor, a memory, an Input/Output interface (I/O for short), and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing original point cloud data and image data. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The communication interface of the computer device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement an obstacle distance detection method.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 10. The computer apparatus includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input device. The processor, the memory and the input/output interface are connected by a system bus, and the communication interface, the display unit and the input device are connected by the input/output interface to the system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The input/output interface of the computer device is used for exchanging information between the processor and an external device. The communication interface of the computer device is used for communicating with an external terminal in a wired or wireless manner, and the wireless manner can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement an obstacle distance detection method. The display unit of the computer equipment is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device, the display screen can be a liquid crystal display screen or an electronic ink display screen, the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on a shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the configurations shown in fig. 9-10 are only block diagrams of some of the configurations relevant to the present application, and do not constitute a limitation on the computing devices to which the present application may be applied, and that a particular computing device may include more or less components than shown, or combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is further provided, which includes a memory and a processor, the memory stores a computer program, and the processor implements the steps of the above method embodiments when executing the computer program.
In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method embodiments.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, carries out the steps in the method embodiments described above.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the relevant laws and regulations and standards of the relevant country and region.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include a Read-Only Memory (ROM), a magnetic tape, a floppy disk, a flash Memory, an optical Memory, a high-density embedded nonvolatile Memory, a resistive Random Access Memory (ReRAM), a Magnetic Random Access Memory (MRAM), a Ferroelectric Random Access Memory (FRAM), a Phase Change Memory (PCM), a graphene Memory, and the like. Volatile Memory can include Random Access Memory (RAM), external cache Memory, and the like. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM), among others. The databases involved in the embodiments provided herein may include at least one of relational and non-relational databases. The non-relational database may include, but is not limited to, a block chain based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic devices, quantum computing based data processing logic devices, etc., without limitation.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present application. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, and these are all within the scope of protection of the present application. Therefore, the protection scope of the present application shall be subject to the appended claims.
Claims (10)
1. An obstacle distance detection method, characterized by comprising:
acquiring original point cloud data and image data corresponding to the original point cloud data;
performing ground point cloud detection based on the original point cloud data to obtain ground point cloud data, and generating a target ground point cloud area based on the ground point cloud data;
detecting a contact line of the obstacle and the ground based on the image data to obtain an obstacle contact line;
projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area;
and determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
2. The method of claim 1, further comprising:
acquiring vertical coordinate information corresponding to the obstacle contact line point cloud data and coordinate information corresponding to the obstacle contact line;
performing point cloud coordinate calculation based on the vertical coordinate information and the coordinate information to obtain target horizontal plane coordinate information corresponding to the obstacle contact line point cloud data;
and calculating the distance based on the coordinate information of the target horizontal plane to obtain the distance of the target obstacle.
3. The method of claim 1, wherein generating a target ground point cloud region based on the ground point cloud data comprises:
dividing the ground point cloud data based on a preset division specification to obtain a ground point cloud division area, wherein the ground point cloud division area comprises a ground point cloud area and an area to be filled;
and generating filling ground point cloud data corresponding to the area to be filled based on the area ground point cloud data in the ground point cloud area, and generating the target ground point cloud area based on the area ground point cloud data and the filling ground point cloud data.
4. The method of claim 3 wherein generating filled ground point cloud data corresponding to the area to be filled based on regional ground point cloud data in the ground point cloud region comprises:
establishing a regional point cloud coordinate relation based on the regional ground point cloud data;
acquiring area horizontal plane coordinate information corresponding to the area ground point cloud data, and calculating filling horizontal plane coordinate information corresponding to the area to be filled based on the area horizontal plane coordinate information and preset horizontal plane coordinate interval information;
calculating according to the area point cloud coordinate relation based on the filling plane coordinate information to obtain filling vertical coordinate information corresponding to the area to be filled;
and generating filling ground point cloud data corresponding to the area to be filled based on the filling horizontal plane coordinate information and the filling vertical coordinate information.
5. The method of claim 1, wherein determining the projected contact line of the obstacle corresponding to the contact line of the obstacle in the ground point cloud projection area comprises:
searching projection coordinate information which is the same as the contact line coordinate information in the ground point cloud projection area based on the contact line coordinate information corresponding to the obstacle contact line to obtain target projection coordinate information;
and obtaining the barrier projection contact line based on the target projection coordinate information.
6. The method of claim 1, wherein the distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance comprises:
acquiring horizontal plane coordinate information corresponding to each three-dimensional point in the obstacle contact line point cloud data;
respectively performing distance calculation based on the horizontal plane coordinate information corresponding to each three-dimensional point to obtain the barrier distance of the point corresponding to each three-dimensional point;
and taking the shortest point obstacle distance in the point obstacle distances corresponding to the three-dimensional points as the obstacle distance.
7. An obstacle distance detection apparatus, characterized in that the apparatus comprises:
the acquisition module is used for acquiring original point cloud data and image data corresponding to the original point cloud data;
the ground detection module is used for carrying out ground point cloud detection on the basis of the original point cloud data to obtain ground point cloud data and generating a target ground point cloud area on the basis of the ground point cloud data;
the contact line detection module is used for detecting the contact line between the obstacle and the ground based on the image data to obtain an obstacle contact line;
the projection module is used for projecting based on the target ground point cloud area to obtain a ground point cloud projection area, and determining an obstacle projection contact line corresponding to the obstacle contact line in the ground point cloud projection area;
and the calculation module is used for determining obstacle contact line point cloud data corresponding to the obstacle projection contact line in the target ground point cloud area, and performing distance calculation based on horizontal plane coordinate information in the obstacle contact line point cloud data to obtain an obstacle distance.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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| CN116993879A (en) * | 2023-07-03 | 2023-11-03 | 广州极点三维信息科技有限公司 | Method for automatically avoiding obstacle and distributing light, electronic equipment and storage medium |
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| CN116993879A (en) * | 2023-07-03 | 2023-11-03 | 广州极点三维信息科技有限公司 | Method for automatically avoiding obstacle and distributing light, electronic equipment and storage medium |
| CN116993879B (en) * | 2023-07-03 | 2024-03-12 | 广州极点三维信息科技有限公司 | Method for automatically avoiding obstacle and distributing light, electronic equipment and storage medium |
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