CN112985464A - Precision detection method of vehicle odometer, electronic device and storage medium - Google Patents
Precision detection method of vehicle odometer, electronic device and storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a precision detection method of a vehicle odometer, electronic equipment and a readable storage medium, which relate to the technical field of automation and can comprise the following steps: obtaining point cloud data of a test field, wherein the point cloud data of the test field is based on point cloud data under the test field of a measurement field coordinate system, and the test field is an overlapping area of areas covered by at least two laser radars; extracting vehicle outline point cloud data from the test field point cloud data; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; calculating a true pose value of the vehicle according to the coordinate values of the vehicle contour points; obtaining a measurement pose; and detecting the accuracy of the vehicle odometer based on the difference between the true pose value and the measurement pose. By the vehicle odometer precision detection method, the electronic device and the readable storage medium, automation of vehicle odometer precision detection can be realized, and precision of vehicle odometer performance detection is improved.
Description
Technical Field
The invention relates to the technical field of automation, in particular to a precision detection method of a vehicle odometer, electronic equipment and a storage medium.
Background
A vehicle odometer may be understood as a module or device installed in a vehicle for measuring the pose of the vehicle. The quality of the performance of the vehicle odometer, namely the accuracy of the vehicle pose output by the vehicle odometer, is an important index of the vehicle performance. At present, the performance of the odometer is often evaluated by adopting a manual measurement mode, and the manual measurement mode has the problem of large manual measurement error, so that the accuracy of detecting the performance of the vehicle odometer is low.
Disclosure of Invention
The embodiment of the invention aims to provide a precision detection method of a vehicle odometer, electronic equipment and a storage medium, so as to realize automation of precision detection of the vehicle odometer and improve precision of performance detection of the vehicle odometer. The specific technical scheme is as follows:
the embodiment of the invention provides a precision detection method of a vehicle odometer, which comprises the following steps:
obtaining test field point cloud data, wherein the test field point cloud data are point cloud data under a test field based on a measurement field coordinate system, the test field is an overlapping area of areas covered by at least two laser radars, the measurement field coordinate system is a coordinate system constructed based on the position of a main laser radar, and the main laser radar is one of the at least two laser radars;
extracting vehicle contour point cloud data from the test field point cloud data;
calculating a vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour;
calculating a true pose value of the vehicle according to the coordinate value of the vehicle contour point;
obtaining a measurement pose, wherein the measurement pose is a pose of a vehicle pose output by a vehicle odometer under the measurement field coordinate system;
and performing precision detection on the vehicle odometer based on the difference between the pose true value and the measurement pose.
Optionally, the obtaining test field point cloud data includes:
obtaining first point cloud data of the main laser radar in the test field, wherein the first point cloud data is point cloud data based on the measurement field coordinate system;
obtaining second point cloud data of other laser radars in the test field, wherein the second point cloud data is based on a measurement field coordinate system, and the other laser radars are laser radars except the main laser radar in the at least two laser radars;
and forming the test field point cloud data by the first point cloud data and the second point cloud data.
Optionally, the obtaining second point cloud data of other lidar in the test field includes:
acquiring point cloud data of other laser radars in the test field;
and converting the point cloud data of the other laser radars in the test field into second point cloud data based on the measurement field coordinate system based on the position relation between the other laser radars and the main laser radar.
Optionally, the calculating a vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour includes:
according to the vehicle contour point cloud data, calculating a circumscribed rectangle of the vehicle contour to obtain four vertex coordinates of the circumscribed rectangle;
the calculating the true pose value of the vehicle according to the coordinate value of the vehicle contour point comprises the following steps:
acquiring the ratio of the distance from the center of a rear shaft of the vehicle to the foremost end of the vehicle body to the vehicle length;
and calculating the position information and the head orientation angle of the vehicle relative to the initial moment according to the coordinates of the four vertexes of the circumscribed rectangle and the proportion, wherein the head orientation angle represents the axial head direction in the vehicle.
Optionally, the obtaining a measurement pose includes:
acquiring a vehicle pose output by a vehicle odometer, wherein the vehicle pose output by the vehicle odometer is a pose based on a vehicle coordinate system;
and converting the vehicle pose to a measurement pose based on the measurement field coordinate system based on a conversion relation between the vehicle coordinate system and the measurement field coordinate system.
Optionally, the performing accuracy detection on the vehicle odometer based on the difference between the pose true value and the measurement pose includes:
calculating errors between the pose true value and the measurement pose at each moment aiming at a plurality of moments in a test process; the test process represents a process of performing accuracy detection on the vehicle odometer;
counting the errors respectively corresponding to all the moments to obtain a statistical value;
and comparing the statistical value with a preset performance index, and performing precision detection on the vehicle odometer through a comparison result.
Optionally, the performing accuracy detection on the vehicle odometer based on the difference between the pose true value and the measurement pose includes:
displaying the pose true values and the measurement poses corresponding to a plurality of moments in a visualization mode, so that a tester can observe the difference between the pose true values and the measurement poses based on the displayed pose true values and the measurement poses corresponding to the plurality of moments, and can perform precision detection on the vehicle odometer.
Optionally, the statistical value includes a statistical histogram, a mean, a variance and/or a double variance.
In another aspect of the present invention, there is also provided an electronic device, including a processor, a communication interface, a memory and a communication bus, where the processor, the communication interface, and the memory complete communication with each other through the communication bus;
a memory for storing a computer program;
and the processor is used for realizing the method steps of the precision detection method of the vehicle odometer when executing the program stored in the memory.
In yet another aspect of the present invention, there is also provided a computer-readable storage medium having stored therein instructions, which when run on a computer, cause the computer to perform the method steps of the accuracy detection method of a vehicle odometer described above.
In yet another aspect of the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method steps of the accuracy detection method of a vehicle odometer described above.
The embodiment of the invention has the following beneficial effects:
according to the precision detection method of the vehicle odometer, the electronic device and the storage medium provided by the embodiment of the invention, vehicle contour point cloud data are extracted from the test field point cloud data by obtaining the test field point cloud data, namely the point cloud data of the overlapping area of the areas covered by at least two laser radars; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; and calculating the true value of the vehicle pose according to the coordinate values of the vehicle contour points, thus obtaining the true value of the vehicle pose and obtaining the measurement pose, namely the pose of the vehicle pose output by the vehicle odometer under the coordinate system of the measurement field. The precision of the point cloud data is high, and vehicle outline point cloud data are extracted from the point cloud data of the test field; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; the vehicle odometer is subjected to precision detection through the difference between the pose truth value and the measurement pose, and the precision of performance detection of the vehicle odometer can be improved.
Of course, not all of the advantages described above need to be achieved at the same time in the practice of any one product or method of the invention.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other embodiments can be obtained by referring to these drawings.
FIG. 1 is a flow chart of a method for accuracy detection of a vehicle odometer according to an embodiment of the present invention;
FIG. 2 is a flowchart of obtaining point cloud data of a test field according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a circumscribed rectangle of a vehicle outline extracted in an embodiment of the invention;
FIG. 4 is a flow chart of accuracy detection of a vehicle odometer based on a difference between a true pose value and a measured pose in an embodiment of the invention;
FIG. 5 is a schematic diagram of an application scenario of a method for detecting accuracy of a vehicle odometer according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an application of the method for detecting the accuracy of the vehicle odometer according to the embodiment of the invention;
FIG. 7 is a schematic structural diagram of an accuracy detection device of a vehicle odometer according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived from the embodiments given herein by one of ordinary skill in the art, are within the scope of the invention.
The accuracy detection method of the odometer provided by the embodiment of the invention can be applied to the environment of a GNSS (Global Navigation Satellite System), and particularly can be applied to the environment without the GNSS in a limited distance range, such as an indoor environment and the like.
The execution main body of the accuracy detection method of the odometer provided by the embodiment of the invention can be electronic equipment, such as a terminal, a server and the like.
The following describes in detail a method for detecting the accuracy of a vehicle odometer according to an embodiment of the present invention.
The embodiment of the invention provides a precision detection method of a vehicle odometer, which comprises the following steps:
obtaining test field point cloud data, wherein the test field point cloud data are point cloud data under a test field based on a measurement field coordinate system, the test field is an overlapping area of areas covered by at least two laser radars, the at least two laser radars can cover the area to be measured, the measurement field coordinate system is a coordinate system constructed based on the position of a main laser radar, and the main laser radar is one of the at least two laser radars;
extracting vehicle outline point cloud data from the test field point cloud data;
calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour;
calculating a true pose value of the vehicle according to the coordinate values of the vehicle contour points;
obtaining a measurement pose, wherein the measurement pose is the pose of the vehicle pose output by the vehicle odometer under a measurement field coordinate system;
and detecting the accuracy of the vehicle odometer based on the difference between the true pose value and the measurement pose.
In the embodiment of the invention, vehicle contour point cloud data are extracted from the test field point cloud data by obtaining the test field point cloud data, namely the point cloud data of the overlapping area of the areas covered by at least two laser radars; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; and calculating the true value of the vehicle pose according to the coordinate values of the vehicle contour points, thus obtaining the true value of the vehicle pose and obtaining the measurement pose, namely the pose of the vehicle pose output by the vehicle odometer under the coordinate system of the measurement field. The precision of the point cloud data is high, and vehicle outline point cloud data are extracted from the point cloud data of the test field; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; the vehicle odometer is subjected to precision detection through the difference between the pose truth value and the measurement pose, and the precision of performance detection of the vehicle odometer can be improved.
The embodiment of the invention provides a precision detection method of a vehicle odometer, which comprises the following steps of:
and S101, obtaining point cloud data of the test field.
And the point cloud data of the test field is based on the point cloud data under the test field of the coordinate system of the measurement field.
The test field is an overlapping area of areas covered by at least two laser radars, and the at least two laser radars can cover the area needing to be measured.
The number of the laser radars is at least two, and the specific number of the laser radars, the positions and the layout of the laser radars are not limited in the embodiment of the invention, as long as at least two laser radars can cover the area to be measured.
The number of the laser radars is determined by the area required to be measured, so that the area required to be measured is covered as the judgment basis of the required minimum number of the laser radars.
The area to be measured can be understood as the area where the vehicle is located when the vehicle odometer is accurately detected. In one embodiment, the vehicle may be driven in an area, such as an underground parking garage, where the area may be understood as the area where measurements are desired. In addition, in order to avoid the influence of other factors on the precision detection precision, the embodiment of the invention ensures that the area is open as much as possible.
The laser radar in the embodiment of the invention can be a multi-line laser radar, and the number of the required laser radars can be determined according to the coverage area of the multi-line laser radar and the range of the area required to be measured.
For example, the area to be measured is 200 meters, typically 16-line lidar covers 20 meters, 32-line lidar covers 50 meters, and 64-line lidar covers 100 meters, and if 16-line lidar is used, the number of lidar is 10, if 32-line lidar is used, the number of lidar is 4, and if 64-line lidar is used, the number of lidar is 2.
The measurement field coordinate system is a coordinate system constructed based on the position of the main laser radar, and the main laser radar is one of at least two laser radars.
In the embodiment of the invention, two laser radars (laser radar 1 and laser radar 2) are taken as an example for description, and an overlapping area of a coverage area of the laser radar 1 and a coverage area of the laser radar 2 is a test field. The test evaluation related to the embodiment of the invention, namely the precision detection of the vehicle odometer is completed in the test field.
The lidar is simply understood as a radar using a laser as a radiation source, and may possibly radiate to the other side of the object to be detected through one side of the object to be detected due to the existence of a shielding region and the like, or may also be understood as incapable of detecting the other side of the object to be detected through the lidar positioned on one side of the object to be detected. If through the in-process of a laser radar detection, to waiting to detect the object, if to the in-process of vehicle detection, probably only can detect one side of vehicle, and can't detect the opposite side of vehicle, can only acquire the point cloud data of vehicle one side promptly, so can make to wait to detect the detection range of object and have the limitation, the data of acquireing are incomplete. In order to comprehensively detect an object to be detected and acquire complete point cloud data, in the embodiment of the invention, the laser radar 1 and the laser radar 1 are distributed to ensure that the laser radar 1 and the laser radar 2 have an overlapping area, the laser radar 1 and the laser radar 2 are respectively positioned on different sides of the object to be detected, and preferably two laser radars are arranged on diagonal positions of the different sides of the object to be detected, so that the object to be detected can be detected from different sides, and the problem that the object to be detected cannot be completely and comprehensively detected due to the existence of a shielding area is avoided.
The laser radar 1 is used as a main laser radar, and a measurement field coordinate system is constructed based on the main laser radar, for example, the xy-axis two-dimensional plane of the laser radar 1 coordinate system is used as a measurement field coordinate system, and the measurement field coordinate system is a right-hand coordinate system.
For simplicity of understanding, in the embodiment of the invention, the coordinate axis of the laser radar 2 is parallel to the coordinate axis of the laser radar 1, the included angle between the x-axis is 180 degrees, and the two laser radars are in the same horizontal plane. The position of the lidar2 in the measurement field coordinate system is (xlidar 2, ylidar 2).
In the embodiment of the invention, the layout of the multiple laser radars is the same, and the layout positions influence the spatial synchronization of the radars, but have no uniqueness requirement. In the embodiment of the present invention, the positions and the layouts of the laser radar 1 and the laser radar 2 are not limited, as long as at least two laser radars can cover the area to be measured, for example, it is ensured that the overlapping area of the laser radar 1 and the laser radar 2 covers the area to be measured, and the area to be measured may include the driving range of the vehicle.
The method is simple to understand, the main laser radar is selected to establish a measurement field coordinate system according to the position of the main laser radar, so that point cloud data obtained by at least two laser radars are in the same coordinate system, and spatial synchronization of the point cloud data obtained by at least two laser radars is realized. In the embodiment of the invention, any one of at least two laser radars can be selected as the main laser radar.
In the embodiment of the invention, all point cloud data of each laser radar in the coverage area can be acquired respectively, and then the intersection of all point cloud data corresponding to each laser radar is calculated to obtain the point cloud data of the test field.
The intersection of the coverage areas of the laser radars can be obtained firstly, the overlapping areas of the coverage areas of all the laser radars, namely the test field, are obtained, the point cloud data of the laser radars in the test field are obtained, and the point cloud data of the laser radars in the test field are combined into the point cloud data of the test field.
In an alternative embodiment, as shown in fig. 2, S101 may include:
and S1011, obtaining first point cloud data of the main laser radar in the test field, wherein the first point cloud data is point cloud data based on a measurement field coordinate system.
And constructing a coordinate system based on the position of the main laser radar, namely constructing a measurement field coordinate system, and acquiring point cloud data of the main laser radar, namely first point cloud data, such as x-axis and y-axis coordinate values of multiple points acquired by the main laser radar in the measurement field coordinate system.
The point cloud data of the main laser radar in the test field can be directly obtained. Or all point cloud data of the main laser radar in the coverage area can be obtained first, and then the point cloud data in the test field can be screened out from all the point cloud data.
And S1012, obtaining second point cloud data of other laser radars in the test field, wherein the second point cloud data is based on the point cloud data of the measurement field coordinate system.
The other lidar is a lidar of the at least two lidar other than the primary lidar.
And point cloud data of other laser radars in the test field can be directly acquired. Or all point cloud data of other laser radars in the coverage area can be obtained first, and then the point cloud data in the test field can be screened out from all the point cloud data.
In one implementation mode, point cloud data of other laser radars in a test field is obtained; and converting the point cloud data of the other laser radars in the test field into second point cloud data based on a measurement field coordinate system based on the position relation between the other laser radars and the main laser radar.
And acquiring point cloud data of other laser radars in a coordinate system constructed based on the positions of the other laser radars, such as x-axis and y-axis coordinate values of multiple points acquired by the other laser radars in the coordinate system.
According to the position relation between other laser radars and the main laser radar, point cloud data of other laser radars are converted into a coordinate system of a measuring field, and coordinate values of multiple points in the coordinate system constructed based on the positions of the other laser radars can be converted into coordinate values in the coordinate system of the measuring field. Thus, the spatial synchronization of at least two laser radar point cloud data is realized.
For simplicity of description, two lidar are included in the embodiment of the present invention: the laser radar 1 and the laser radar 2 are described as an example, and the laser radar 1 is a main laser radar and the laser radar 2 is another laser radar.
The method comprises the steps of obtaining point cloud data, namely first point cloud data, of the laser radar 1 in a test field, obtaining point cloud data of the laser radar 2 in the test field, converting the point cloud data of the laser radar 2 in the test field into second point cloud data based on a measurement field coordinate system, namely converting the point cloud data of the laser radar 2 into the point cloud data which is in the same coordinate system with the point cloud data of the laser radar 1, and achieving spatial synchronization of the point cloud data.
And S1013, forming the first point cloud data and the second point cloud data into test field point cloud data.
The point cloud data of the test field are coordinate values under a measurement field coordinate system.
And S102, extracting vehicle contour point cloud data from the test field point cloud data.
And selecting a test field and placing the laser radar, and ensuring that the point cloud data of the test field contains a complete vehicle outline.
The test field may include other objects besides the vehicle, such as indicator lights in an underground parking lot, and thus the test field point cloud data may include data other than the point cloud data corresponding to the vehicle.
In order to subsequently position the vehicle and determine the pose of the vehicle, the vehicle contour point cloud data is extracted from the test field point cloud data. Vehicle contour point cloud data can be extracted from the test field point cloud data according to the contour features of the vehicle.
For example, when the vehicle is on the ground, the longitudinal axis coordinate of the vehicle is not too high, the longitudinal axis coordinate can be limited, and the point cloud data of which the longitudinal axis coordinate is smaller than the preset value in the point cloud data of the test field is extracted as the vehicle contour point cloud data. The preset value may be determined according to an empirical value, etc.
S103, calculating the vehicle contour based on the vehicle contour point cloud data to obtain the vehicle contour point coordinate value of the vehicle contour.
And extracting the vehicle contour point cloud data according to the point cloud data coordinate values to form a vehicle contour, wherein the vehicle contour point coordinate values are used for representing the vehicle contour.
The vehicle contour point coordinate values of the vehicle contour may be coordinate values in the measurement field coordinate system. When the obtained coordinate value of the vehicle contour point is not the coordinate value under the measurement field coordinate system, the coordinate value under the measurement field coordinate system can be converted into the coordinate value under the measurement field coordinate system through conversion between the coordinate systems.
In an alternative embodiment, a circumscribed rectangle of the vehicle contour can be calculated according to the vehicle contour point cloud data, and four vertex coordinates of the circumscribed rectangle are obtained.
The rectangle can be located by four vertexes of the rectangle, so that the outline of the vehicle is represented by coordinates of the four vertexes of the circumscribed rectangle in the embodiment of the invention. As shown in fig. 3, the coordinate values of four vertices A, B, C of the circumscribed rectangle and D: [ A (Axt, Ayt), B (Bxt, Byt), C (Cxt, Cyt), D (Dxt, Dyt) ], wherein A represents a point of a circumscribed rectangle near the upper left corner of the vehicle, B represents an upper right corner point, C represents a lower right corner point, and D represents a lower left corner.
The minimum circumscribed rectangle of the outline can be calculated according to a polygon formed by the point clouds on the outermost side of the outline of the vehicle. The embodiment of the invention does not limit the way of calculating the minimum circumscribed rectangle of the outline of the vehicle, and any way of calculating the minimum circumscribed rectangle of the outline is within the protection scope of the embodiment of the invention. For example, the minimum bounding rectangle of the outline may be calculated in an "rotational-shell-based" outside-rectangle calculation.
And S104, calculating a true pose value of the vehicle according to the coordinate values of the vehicle contour points.
In an optional implementation mode, when the calculated vehicle contour is a circumscribed rectangle, the proportion of the distance from the center of a rear axle of the vehicle to the foremost end of the vehicle body to the vehicle length can be obtained; and calculating the position information and the head orientation angle of the vehicle relative to the initial moment according to the coordinates and the proportion of the four vertexes of the circumscribed rectangle, wherein the head orientation angle represents the axial head direction in the vehicle.
For example, the ratio of the distance from the center of the rear axle of the vehicle to the foremost end of the vehicle body to the vehicle length is k, the coordinate values of the four vertexes A, B, C and D of the circumscribed rectangle are used for calculating the true position value of the vehicle at the time t: and the t moment vehicle pose truth values (Vgt _ xt, Vgt _ yt and Vgt _ yawt), wherein V (Vgt _ xt, Vgt _ yt) represents the position information of the vehicle at the t moment and Vgt _ yawt represents the heading angle.
V (Vgt _ xt, Vgt _ yt), Vgt _ xt = Axt-k (Axt-Dxt), Vgt _ yt = (Ayt + Byt)/2, gt represents the true value, and the heading angle Vgt _ yawt of the vehicle head at the time t is equal to the included angle between the straight line DA in the circumscribed rectangle and the x axis under the measurement field coordinates.
And S105, obtaining a measurement pose, wherein the measurement pose is the pose of the vehicle pose output by the vehicle odometer in a measurement field coordinate system.
The vehicle position and pose output by the vehicle odometer can be obtained, and the vehicle position and pose output by the vehicle odometer is based on a vehicle coordinate system; and converting the vehicle pose to a measurement pose based on the measurement field coordinate system based on the conversion relation between the vehicle coordinate system and the measurement field coordinate system.
The vehicle coordinate system takes the center of a rear axle of the vehicle as the origin of the coordinate system, the direction of the head of the middle axle of the vehicle is the positive direction of an X axis, the direction of the width of the vehicle is a y axis, and the vehicle coordinate system is a right-hand coordinate system. Odometer coordinate system: vehicle coordinate system at the starting time.
The automatic parking/passenger-replacing parking system is characterized by comprising an odometer module, namely a vehicle odometer outputs x and y coordinate values at t moment and a vehicle head orientation angle under an odometer coordinate system, wherein the vehicle head orientation yaw angle represents an included angle between an x axis of the vehicle coordinate system and an x axis of the odometer coordinate system at the t moment, and the anticlockwise direction is positive. The embodiment of the invention evaluates the performance of the odometer module.
Namely, the output result of the vehicle odometer at the current moment is obtained. For example, the initial time vehicle odometer outputs (0, 0, 0), and the time t vehicle odometer outputs (xt, yt, yawt). And transforming the odometer at the time t to a coordinate system of a measuring field: (Vxt, Vyt, Vyawt).
In one implementation, transformation of the vehicle coordinate system (xt, yt, yawt) to the measurement field coordinate system may be performed by translation (Vgt _ x0, Vgt _ y 0) along the measurement field coordinate axes and rotation of Vgt _ yaw0 about the z-axis, based on a transformation relationship between the vehicle coordinate system and the measurement field coordinate system.
And S106, detecting the accuracy of the vehicle odometer based on the difference between the true pose value and the measurement pose.
The smaller the difference between the true pose value and the measured position, the better the performance of the vehicle odometer.
According to the embodiment of the invention, the pose true value and the measurement pose corresponding to each moment can be respectively determined at a plurality of moments, and the vehicle odometer is subjected to precision detection based on the pose true value and the measurement pose corresponding to each moment.
Specifically, as shown in fig. 4, S106 may include:
s1061, calculating errors between the lower pose true values and the measurement poses at multiple moments in the test process.
The test process represents a process of performing accuracy detection on the vehicle odometer.
Calculating the error corresponding to each moment in the whole test process, wherein the error can also be understood as the difference between the true pose value corresponding to the moment and the measurement pose, for example, the error at the moment t is: dxt = Vgt _ xt-Vxt, dyt = Vgt _ yt-Vyt, dyawt = Vgt _ ywat-Vyawt.
And S1062, counting the errors corresponding to the multiple moments to obtain a statistical value.
The statistical values may include statistical histograms, mean, variance, and/or double variance, among others.
And S1063, comparing the statistical value with a preset performance index, and performing precision detection on the vehicle odometer through a comparison result.
The preset performance index can be determined according to actual requirements or empirical values and the like, the comparison result can be the difference between the statistical value and the preset performance index, and the smaller the difference between the statistical value and the preset performance index is, the better the performance of the vehicle odometer is represented.
In an alternative embodiment, different operations of the vehicle can be measured during the test process, so as to evaluate the performance of the vehicle odometer corresponding to the different operations of the vehicle.
Specifically, a plurality of corresponding errors under different operations can be counted according to different operations executed by the vehicle in the advancing process to obtain a statistical value; and comparing the statistical value with a preset performance index, and performing precision detection on the performance of the vehicle odometer under each operation through a comparison result. The operation means an operation performed by the vehicle, such as a vehicle changing a traveling direction, a vehicle backing up, or the like.
For example, for the result of measuring the pose of the vehicle in different operations in the test process for a plurality of times, for example, 100 times of measuring the point where the vehicle changes in the traveling direction, 100 pose true values and measurement poses can be obtained, the performance of the vehicle odometer in the operation (such as changing the traveling direction of the vehicle) can be evaluated by evaluating the statistical characteristics of the test sample, corresponding errors are calculated for the pose true values and the measurement poses corresponding to the 100 times of measurement results respectively, and the errors corresponding to the 100 times of measurement are counted to obtain a statistical value, so that the performance of the vehicle odometer can be evaluated according to the statistical value.
In an alternative embodiment, the embodiment of the present invention may also evaluate the performance of the vehicle odometer when the vehicle travels on different tracks.
Specifically, a plurality of corresponding errors in a preset track can be counted according to the preset track of the vehicle to obtain a statistical value; and comparing the statistical value with a preset performance index, and performing precision detection on the performance of the vehicle odometer based on a preset track through a comparison result. For example, the vehicle can travel a fixed track, 100 times of measurement is carried out, the terminal pose is recorded, and the performance indexes of different travels of the odometer can be evaluated by evaluating the statistical characteristics of the test sample.
In an optional embodiment, the pose true values and the measurement poses corresponding to multiple moments can be displayed in a visualization mode, so that a tester can observe the difference between the pose true values and the measurement poses based on the displayed pose true values and the displayed measurement poses corresponding to the multiple moments, and the vehicle odometer can be subjected to precision detection.
The curves of pose truth values corresponding to a plurality of moments and the curves of measurement poses corresponding to a plurality of moments can be displayed in a visual mode, so that a tester can intuitively evaluate the performance of the vehicle odometer by observing the difference between the two curves.
The embodiment of the invention can adopt any visualization mode. For example, visual presentation may be implemented based on the robot operating system ROS, or an existing software library such as visual QT.
The embodiment of the invention can realize the automation of the precision detection of the vehicle odometer. The precision of the point cloud data is high, and vehicle outline point cloud data are extracted from the point cloud data of the test field; calculating the vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour; the vehicle odometer is subjected to precision detection through the difference between the pose truth value and the measurement pose, and the precision of performance detection of the vehicle odometer can be improved. In addition, compared with evaluation by a manual measurement mode, the embodiment of the invention can improve the test efficiency and reduce the test cost.
In an optional embodiment, the method for detecting the accuracy of the vehicle odometer according to the embodiment of the present invention may be used in an automatic parking system or a valet parking system, for example, to detect the accuracy of the vehicle odometer of a vehicle in the automatic parking system or the valet parking system. The accuracy detection method of the vehicle odometer provided by the embodiment of the invention is exemplified by combining the specific application scenario.
Fig. 5 is a schematic view of an application scenario of the accuracy detection method of the vehicle odometer according to the embodiment of the present invention. Fig. 6 is an application schematic diagram of the accuracy detection method of the vehicle odometer provided by the embodiment of the invention. Referring to fig. 5 and 6, point cloud data of the laser radar 1 in the test field is acquired, which is based on the measurement field coordinate system. The method comprises the steps of obtaining point cloud data of a laser radar 2 in a test field, wherein the point cloud data are based on a coordinate system constructed by the laser radar 2, therefore, the point cloud data of the laser radar 2 in the test field need to be subjected to coordinate conversion, and the point cloud data of the laser radar 2 in the test field are converted into point cloud data based on a measurement field coordinate system based on the position relation of the laser radar 1 and the laser radar 2, so that the spatial synchronization of the point cloud data is realized. Based on the position relationship between the lidar 1 and the lidar2 shown in fig. 5, converting all the x-axis coordinate values and the y-axis coordinate values into the measurement coordinate system may include rotating the lidar2 data coordinate values by 180 ° around the z-axis, and translating (xlidar 2, ylidar 2) to the lidar along the x-axis and the y-axis of the lidar 1 coordinate system, respectively, to complete the original data spatial synchronization.
Thus, the original data of the measuring field, namely the point cloud data of the measuring field, is obtained.
And then, extracting vehicle outline point cloud data from the point cloud data of the test field, namely acquiring vehicle point cloud data of the measurement field from the original data of the measurement field.
And then, calculating a vehicle outline circumscribed rectangle based on the vehicle point cloud data of the measuring field, and calculating a true value of the vehicle pose of the measuring field.
According to the vehicle contour point cloud data, calculating a circumscribed rectangle of the vehicle contour to obtain four vertex coordinates of the circumscribed rectangle, and acquiring the proportion of the distance from the center of a rear axle of the vehicle to the foremost end of the vehicle body to the vehicle length; and calculating the position information and the head orientation angle of the vehicle relative to the initial moment according to the coordinates and the proportion of the four vertexes of the circumscribed rectangle, wherein the head orientation angle represents the axial head direction in the vehicle. And position information and a heading angle of the vehicle head are vehicle pose truth values.
And acquiring an output result of the vehicle odometer calculation module, namely a vehicle pose of the vehicle relative to the starting point coordinate system, and converting the output pose into a vehicle pose under a measurement field coordinate system, namely a measurement pose of the vehicle odometer based on the measurement field coordinate system.
And visualizing the obtained true pose value and the measurement pose, namely realizing the pose visualization, evaluating the error of the vehicle odometer by the displayed pose so as to perform precision detection on the performance of the vehicle odometer, wherein the smaller the error is, the better the performance of the vehicle odometer is.
In the embodiment of the invention, under the environment without GNSS, the vehicle odometer of the vehicle in the automatic parking system or the passenger-replacing parking system carries out precision detection and evaluates the precision of the real-time pose of the vehicle output by the vehicle odometer. According to the embodiment of the invention, the test field is determined by at least two laser radars, the vehicle contour point cloud data is extracted based on the midpoint cloud data of the laser radars in the test field, and the pose truth value of the vehicle is further obtained, so that a high-precision vehicle real-time pose result can be provided as a truth value, a reference is provided for vehicle positioning of an automatic parking system or a passenger-replacing parking system, the performance of the function is evaluated, and the method has the characteristics of high test result precision, high automation degree, high test efficiency and low cost.
Meanwhile, the method plays an important role in evaluating or verifying the performance of the positioning function in the automatic parking system or the passenger-replacing parking system, and can be applied to actual development and test tasks as a production tool. The method can provide convenience for an automatic parking system or a passenger-replacing parking system positioning function development manufacturer, a system demand receiver and the like, and has positive economic benefits.
Corresponding to the accuracy detection method of the vehicle odometer provided in the above embodiment, an embodiment of the present invention further provides an accuracy detection apparatus of the vehicle odometer, as shown in fig. 7, which may include:
the first obtaining module 701 is configured to obtain test field point cloud data, where the test field point cloud data is point cloud data under a test field based on a measurement field coordinate system, the test field is an overlapping area of areas covered by at least two laser radars, the measurement field coordinate system is a coordinate system established based on a position where a main laser radar is located, and the main laser radar is one of the at least two laser radars;
an extraction module 702, configured to extract vehicle contour point cloud data from the test field point cloud data;
the calculation module 703 is configured to calculate a vehicle contour based on the vehicle contour point cloud data, so as to obtain a vehicle contour point coordinate value of the vehicle contour; calculating a true pose value of the vehicle according to the coordinate values of the vehicle contour points;
a second obtaining module 704, configured to obtain a measurement pose, where the measurement pose is a pose of a vehicle pose output by the vehicle odometer in a measurement field coordinate system;
and the precision detection module 705 is used for detecting the precision of the vehicle odometer based on the difference between the true pose value and the measurement pose.
Corresponding to the accuracy detection method of the vehicle odometer provided in the above embodiment, an embodiment of the present invention further provides an electronic device, as shown in fig. 8, including a processor 801, a communication interface 802, a memory 803, and a communication bus 804, where the processor 801, the communication interface 802, and the memory 803 complete mutual communication through the communication bus 804.
A memory 803 for storing a computer program;
the processor 801 is configured to implement the method steps of the accuracy detection method for the vehicle odometer when executing the program stored in the memory 803.
The communication bus mentioned in the electronic device of the vehicle odometer may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The communication bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus.
The communication interface is used for communication between the electronic equipment of the vehicle odometer and other equipment.
The Memory may include a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as at least one disk Memory. Optionally, the memory may also be at least one memory device located remotely from the processor.
The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
In yet another embodiment provided by the present invention, there is also provided a computer-readable storage medium having stored therein a computer program which, when executed by a processor, implements the method steps of the accuracy detection method of the vehicle odometer described above.
In yet another embodiment provided by the present invention, there is also provided a computer program product containing instructions which, when run on a computer, cause the computer to perform the method steps of the accuracy detection method of a vehicle odometer described above.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the invention to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The computer instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website site, computer, server, or data center to another website site, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device, such as a server, a data center, etc., that incorporates one or more of the available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
All the embodiments in the present specification are described in a related manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the apparatus, device, computer-readable storage medium, and computer program product embodiments, the description is relatively simple as it is substantially similar to the method embodiments, and reference may be made to some descriptions of the method embodiments for relevant points.
The above description is only for the preferred embodiment of the present invention, and is not intended to limit the scope of the present invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention shall fall within the protection scope of the present invention.
Claims (10)
1. A method for detecting the accuracy of a vehicle odometer, comprising:
obtaining test field point cloud data, wherein the test field point cloud data are point cloud data under a test field based on a measurement field coordinate system, the test field is an overlapping area of areas covered by at least two laser radars, the measurement field coordinate system is a coordinate system constructed based on the position of a main laser radar, and the main laser radar is one of the at least two laser radars;
extracting vehicle contour point cloud data from the test field point cloud data;
calculating a vehicle contour based on the vehicle contour point cloud data to obtain a vehicle contour point coordinate value of the vehicle contour;
calculating a true pose value of the vehicle according to the coordinate value of the vehicle contour point;
obtaining a measurement pose, wherein the measurement pose is a pose of a vehicle pose output by a vehicle odometer under the measurement field coordinate system;
and performing precision detection on the vehicle odometer based on the difference between the pose true value and the measurement pose.
2. The method of claim 1, wherein the obtaining test field point cloud data comprises:
obtaining first point cloud data of the main laser radar in the test field, wherein the first point cloud data is point cloud data based on the measurement field coordinate system;
obtaining second point cloud data of other laser radars in the test field, wherein the second point cloud data is based on a measurement field coordinate system, and the other laser radars are laser radars except the main laser radar in the at least two laser radars;
and forming the test field point cloud data by the first point cloud data and the second point cloud data.
3. The method of claim 2, wherein the obtaining second point cloud data of other lidar in the test field comprises:
acquiring point cloud data of other laser radars in the test field;
and converting the point cloud data of the other laser radars in the test field into second point cloud data based on the measurement field coordinate system based on the position relation between the other laser radars and the main laser radar.
4. The method of claim 1, wherein said calculating a vehicle contour based on said vehicle contour point cloud data, resulting in vehicle contour point coordinate values for said vehicle contour, comprises:
according to the vehicle contour point cloud data, calculating a circumscribed rectangle of the vehicle contour to obtain four vertex coordinates of the circumscribed rectangle;
the calculating the true pose value of the vehicle according to the coordinate value of the vehicle contour point comprises the following steps:
acquiring the ratio of the distance from the center of a rear shaft of the vehicle to the foremost end of the vehicle body to the vehicle length;
and calculating the position information and the head orientation angle of the vehicle relative to the initial moment according to the coordinates of the four vertexes of the circumscribed rectangle and the proportion, wherein the head orientation angle represents the axial head direction in the vehicle.
5. The method according to claim 1, wherein the obtaining a measurement pose comprises:
acquiring a vehicle pose output by a vehicle odometer, wherein the vehicle pose output by the vehicle odometer is a pose based on a vehicle coordinate system;
and converting the vehicle pose to a measurement pose based on the measurement field coordinate system based on a conversion relation between the vehicle coordinate system and the measurement field coordinate system.
6. The method of claim 1, wherein the accuracy detecting the vehicle odometer based on the difference between the pose true value and the measurement pose comprises:
calculating errors between the pose true value and the measurement pose at each moment aiming at a plurality of moments in a test process; the test process represents a process of performing accuracy detection on the vehicle odometer;
counting the errors respectively corresponding to all the moments to obtain a statistical value;
and comparing the statistical value with a preset performance index, and performing precision detection on the vehicle odometer through a comparison result.
7. The method of claim 1, wherein the accuracy detecting the vehicle odometer based on the difference between the pose true value and the measurement pose comprises:
displaying the pose true values and the measurement poses corresponding to a plurality of moments in a visualization mode, so that a tester can observe the difference between the pose true values and the measurement poses based on the displayed pose true values and the measurement poses corresponding to the plurality of moments, and can perform precision detection on the vehicle odometer.
8. The method of claim 6, wherein the statistical values comprise a statistical histogram, a mean, a variance, and/or a double variance.
9. An electronic device is characterized by comprising a processor, a communication interface, a memory and a communication bus, wherein the processor and the communication interface are used for realizing mutual communication by the memory through the communication bus;
a memory for storing a computer program;
a processor for implementing the method steps of any one of claims 1 to 8 when executing a program stored in the memory.
10. A computer-readable storage medium, having stored thereon instructions which, when executed on a computer, cause the computer to perform the method steps of any of claims 1 to 8.
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