CN114488097A - External parameter calibration method of laser radar, computer equipment and computer storage medium - Google Patents
External parameter calibration method of laser radar, computer equipment and computer storage medium Download PDFInfo
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Abstract
The application discloses a laser radar external reference calibration method, computer equipment and a computer storage medium, wherein the method comprises the following steps: acquiring point cloud data acquired by a laser radar to be calibrated, wherein the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other; and respectively calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data, and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and parameters of a coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector. Therefore, the method and the device have the advantages that the planar point cloud data is adopted to calibrate the external parameters, the utilization rate of the point cloud data can be improved, the influence of point cloud sparsity is avoided or reduced, and the error of external parameter calibration is reduced.
Description
Technical Field
The invention relates to the technical field of radar calibration, in particular to an external parameter calibration method of a laser radar, computer equipment and a computer storage medium.
Background
The lidar is a radar system that emits a laser beam to detect characteristic quantities such as a position and a speed of a target, and is widely used in many fields, for example, a vehicle-mounted three-dimensional reconstruction system, a sensing system, and the like need to work based on detection data of the lidar. After the laser radar is installed, external parameters of the laser radar need to be calibrated so as to improve the accuracy of using detection data. In the related art, the external reference of the laser radar is generally calibrated and calculated through the angular points or the characteristic points of the calibration plate, but the point-based calculation mode is easily affected by the sparsity of the point cloud of the laser radar, so that the external reference obtained through calibration has a large error.
Disclosure of Invention
In view of the above technical problems, the present application provides a method, a computer device, and a computer storage medium for calibrating external parameters of a laser radar, which can avoid or reduce the influence of point cloud sparsity and reduce errors in calibrating the external parameters.
In order to solve the technical problem, the present application provides an external reference calibration method for a laser radar, including:
acquiring point cloud data acquired by a laser radar to be calibrated, wherein the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other;
calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data;
and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector.
Optionally, the calculating, according to the first point cloud data, the second point cloud data, and the third point cloud data, plane parameters of the first plane, the second plane, and the third plane, respectively, includes:
and respectively fitting plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data.
Optionally, the first plane is perpendicular to a first coordinate axis of a coordinate system where the laser radar is located, the second plane is perpendicular to a second coordinate axis of the coordinate system where the laser radar is located, the third plane is perpendicular to a third coordinate axis of the coordinate system where the laser radar is located, and the first coordinate axis, the second coordinate axis and the third coordinate axis are perpendicular to each other in pairs.
Optionally, the obtaining external parameters of the laser radar by calibrating according to the plane parameters of the first plane, the second plane, and the third plane and the parameters of the coordinate system where the laser radar is located includes:
respectively calculating the translation amounts of the first plane, the second plane and the third plane relative to the origin of a coordinate system where the laser radar is located according to the plane parameters of the first plane, the second plane and the third plane;
acquiring the vertical distance between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane;
and respectively calculating the difference value between the translation amount and the vertical distance corresponding to the first plane, the second plane and the third plane to obtain the translation vector of the laser radar.
Optionally, a vertical distance between an origin of the coordinate system where the laser radar is located and the first plane, the second plane, and the third plane is a preset value or an external input value.
Optionally, the obtaining external parameters of the laser radar by calibrating according to the plane parameters of the first plane, the second plane, and the third plane and the parameters of the coordinate system where the laser radar is located includes:
according to the plane parameters of the first plane, the second plane and the third plane, respectively calculating normal vectors of the first plane, the second plane and the third plane;
and calculating a rotation matrix of the laser radar according to the normal vectors of the first plane, the second plane and the third plane and the directions of a first coordinate axis, a second coordinate axis and a third coordinate axis of a coordinate system in which the laser radar is located.
Optionally, the calculating a rotation matrix of the laser radar according to the normal vectors of the first plane, the second plane, and the third plane and the directions of the first coordinate axis, the second coordinate axis, and the third coordinate axis of the coordinate system in which the laser radar is located includes:
respectively calculating included angles between a normal vector of each of the first plane, the second plane and the third plane and a direction of a first coordinate axis, a second coordinate axis and a third coordinate axis of a coordinate system where the laser radar is located, and obtaining rotation matrixes corresponding to the first plane, the second plane and the third plane;
and calculating the product of the rotation matrixes corresponding to the first plane, the second plane and the third plane to obtain the rotation matrix of the laser radar.
The application also provides a laser radar's external reference calibration device, its characterized in that includes:
the system comprises a point cloud data acquisition module, a calibration module and a calibration module, wherein the point cloud data acquisition module is used for acquiring point cloud data acquired by a laser radar to be calibrated, and the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other;
the plane parameter calculation module is used for calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data;
and the calibration calculation module is used for calibrating and obtaining external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector.
The present application further provides a computer device, comprising: a processor and a memory storing a computer program, wherein the processor implements the steps of the laser radar external reference calibration method as described above when running the computer program.
The present application further provides a computer storage medium storing a computer program, which when executed by a processor, implements the steps of the external reference calibration method for a laser radar as described above.
As described above, according to the external reference calibration method for the laser radar, the computer device and the computer storage medium of the application, point cloud data collected by the laser radar to be calibrated is obtained, wherein the point cloud data includes first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other; and respectively calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data, and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and parameters of a coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector. Therefore, the method and the device have the advantages that the planar point cloud data is adopted to calibrate the external parameters, the utilization rate of the point cloud data can be improved, the influence of point cloud sparsity is avoided or reduced, and the error of external parameter calibration is reduced.
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Fig. 1 is a schematic flow chart of an external reference calibration method for a laser radar according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a calibration scenario provided in an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an external reference calibration apparatus of a laser radar according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
It should be noted that, in this document, 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, the recitation of an element by the phrase "comprising an … …" does not exclude the presence of additional like elements in the process, method, article, or apparatus that comprises the element, and further, where similarly-named elements, features, or elements in different embodiments of the disclosure may have the same meaning, or may have different meanings, that particular meaning should be determined by their interpretation in the embodiment or further by context with the embodiment.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context. Also, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used in this specification, specify the presence of stated features, steps, operations, elements, components, items, species, and/or groups, but do not preclude the presence, or addition of one or more other features, steps, operations, elements, components, items, species, and/or groups thereof. The terms "or" and/or "as used herein are to be construed as inclusive or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a; b; c; a and B; a and C; b and C; A. b and C ". An exception to this definition will occur only when a combination of elements, functions, steps or operations are inherently mutually exclusive in some way.
It should be understood that, although the steps in the flowcharts in the embodiments of the present application are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, in different orders, and may be performed alternately or at least partially with respect to other steps or sub-steps of other steps.
It should be noted that step numbers such as S101 and S102 are used herein for the purpose of more clearly and briefly describing the corresponding contents, and do not constitute a substantial limitation on the sequence, and those skilled in the art may perform S102 first and then S101 in specific implementations, but these steps should be within the scope of the present application.
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.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for the convenience of description of the present application, and have no specific meaning in themselves. Thus, "module", "component" or "unit" may be used mixedly.
Fig. 1 is a schematic flow chart of an external reference calibration method for a laser radar according to an embodiment of the present invention. As shown in fig. 1, an external reference calibration method for a laser radar includes the following steps:
s101: the method comprises the steps of obtaining point cloud data collected by a laser radar to be calibrated, wherein the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other.
The laser radar to be calibrated is a laser radar installed on a target device, the target device may be a vehicle, a robot, or other devices that need to use the laser radar, and the present embodiment takes a calibration process of the laser radar installed on the vehicle as an example for explanation.
Referring to fig. 2, a schematic diagram of a calibration scenario after a laser radar (not shown) is installed on the vehicle 10 is shown. Before calibration, three planes which are not parallel to each other are firstly arranged, including a first plane 11, a second plane 12 and a third plane 13, and the first plane 11, the second plane 12 and the third plane 13 can be three flat plates. In actual implementation, the first plane 11, the second plane 12, and the third plane 13 may be arranged first, and then the vehicle 10 may be stopped at a predetermined position and orientation according to the positions of the first plane 11, the second plane 12, and the third plane 13, or the first plane 11, the second plane 12, and the third plane 13 may be arranged according to the position and orientation of the vehicle 10 after the vehicle 10 is stopped.
In this embodiment, the first plane 11, the second plane 12, and the third plane 13 are perpendicular to each other, preferably, the first plane 11 is perpendicular to a first coordinate axis of a coordinate system in which the laser radar is located, the second plane 12 is perpendicular to a second coordinate axis of the coordinate system in which the laser radar is located, the third plane 13 is perpendicular to a third coordinate axis of the coordinate system in which the laser radar is located, and the first coordinate axis, the second coordinate axis, and the third coordinate axis are perpendicular to each other, as illustrated in fig. 2, the first coordinate axis may be a z-axis (not shown in the figure), the second coordinate axis may be an x-axis, and the third coordinate axis may be a y-axis, so that scene arrangement and a subsequent calibration calculation process may be simplified. The coordinate system of the lidar is a coordinate system of a device in which the lidar is located, for example, a vehicle coordinate system, in the scenario shown in fig. 2, the vehicle coordinate system may select a rear axle center of the vehicle 10 as a coordinate origin, an x axis and a y axis are coordinate axes on a horizontal plane, and a z axis is a coordinate axis on a vertical plane (not shown in the figure), which may facilitate the arrangement of the first plane 11, the second plane 12, and the third plane 13. It will be appreciated that the choice of coordinate origin and coordinate axis is not limited thereto.
After the calibration scene is arranged, the laser radar to be calibrated is started for detection, and point cloud data corresponding to the first plane 11, the second plane 12 and the third plane 13 can be acquired, that is, the acquired point cloud data includes first point cloud data corresponding to the first plane 11, second point cloud data corresponding to the second plane 12 and third point cloud data corresponding to the third plane 13.
S102: calculating plane parameters of the first plane, the second plane and the third plane respectively according to the first point cloud data, the second point cloud data and the third point cloud data;
the plane parameters are parameters a, b, c, and d that make the plane equation aX + bY + cZ + d equal to 0. In this embodiment, plane parameters of the first plane, the second plane, and the third plane are respectively fitted based on the first point cloud data, the second point cloud data, the third point cloud data, and a RAndom SAmple Consensus (RAndom SAmple Consensus). Taking the plane parameter of the fitting first plane as an example, the specific process is as follows:
(1) randomly selecting three points in the first point cloud data: p1 ═ x1, y1, z1, P2 ═ x2, y2, z2, P3 ═ x2, y3, z 3;
(2) calculating plane parameters a, b, c and d through P1, P2 and P3, wherein the formula is as follows:
a＝[(y2-y1)(z3-z1)-(z2-z1)(y3-y2)]
b＝[(z2-z1)(x3-x1)-(x2-x1)(z3-z2)]
c＝[(x2-x1)(y3-y1)-(y2-y1)(x3-x2)]
d＝-(ax+by+cz)
(3) calculating the distance from all points in the first point cloud data to the plane of the three points, and assuming that the point is P4(x4, y4, z4), the distance from the point P4 to the plane of the three points is:
(4) if the distance is smaller than a set threshold value T, the point P4 is regarded as an inner point (inliers), otherwise, the point P4 is regarded as an outer point (outliers); the threshold T is a maximum allowable distance difference between a point in the first point cloud data and a plane determined based on the current plane parameter, and may be set according to an error requirement, and for example, may be 0.5 cm:
(5) counting the number of the interior points, and if the number of the interior points is greater than the maximum historical value, saving the plane parameters; for example, assuming that the number of the inner points of the ith iteration is Ni, and N1 to N10 are obtained after 10 iterations, the maximum value of N1 to N10 is taken as the historical maximum value;
(6) repeating the steps (1) - (5) until the algorithm converges, for example, the number of the interior points is more than a certain number, and obtaining the plane parameter of the first plane.
According to the method, when the plane parameters of the first plane, the second plane and the third plane are calculated, the point cloud data of the first plane, the second plane and the third plane are used for fitting a large amount of point cloud data of multiple planes, the utilization rate of the point cloud data is improved, and the influence of point cloud sparsity can be avoided or reduced. In addition, the calibration method can be completed without a specially customized calibration plate, and the calibration cost is reduced.
S103: and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector.
The plane parameters of the first plane, the second plane and the third plane can be used for representing the actual detection result of the laser radar. The parameters of the coordinate system where the laser radar is located correspond to the theoretical plane parameters of the first plane, the second plane and the third plane, and the parameters can be used for representing the theoretical detection result of the laser radar. The parameters of the coordinate system where the laser radar is located comprise the vertical distances between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane, and the directions of all coordinate axes of the coordinate system where the laser radar is located. Therefore, according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, the external parameters of the laser radar can be obtained through calibration, and in this embodiment, the external parameters include a rotation matrix and/or a translation vector.
Optionally, when calibrating the translation vector, calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane, and the third plane and the parameters of the coordinate system where the laser radar is located, including:
respectively calculating the translation amounts of the first plane, the second plane and the third plane relative to the origin of a coordinate system where the laser radar is located according to the plane parameters of the first plane, the second plane and the third plane;
acquiring the vertical distance between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane;
and respectively calculating the difference between the translation amount and the vertical distance corresponding to the first plane, the second plane and the third plane to obtain the translation vector of the laser radar.
And calculating to obtain an intersection point of the first plane and the first coordinate axis, an intersection point of the second plane and the second coordinate axis, and an intersection point of the third plane and the third coordinate axis according to the plane parameters of the first plane, the second plane and the third plane, wherein a coordinate value of the intersection point is also the translation amount of the corresponding plane. The vertical distance between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane is a preset value or an external input value, for example, the first plane, the second plane and the third plane are arranged at a first designated position, and after the vehicle stops at a second designated position corresponding to the first designated position according to a designated direction, the vertical distance can adopt the preset value; or after the vehicle stops, a laser pen or a ruler or other tools can be used for measuring the vertical distance between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane, and the measured value is input as an external input value.
Then, the difference between the translation amounts d1, d2 and d3 corresponding to the first plane, the second plane and the third plane and the vertical distances m1, m2 and m3 are respectively calculated, and the translation vector T of the laser radar is obtained as [ d1-m1, d2-m2 and d3-m3 ].
Optionally, when calibrating the rotation matrix of the laser radar, obtaining external parameters of the laser radar by calibration according to the plane parameters of the first plane, the second plane, and the third plane and the parameters of the coordinate system where the laser radar is located, including:
respectively calculating normal vectors of the first plane, the second plane and the third plane according to plane parameters of the first plane, the second plane and the third plane;
and calculating the rotation matrix of the laser radar according to the normal vectors of the first plane, the second plane and the third plane and the directions of the first coordinate axis, the second coordinate axis and the third coordinate axis of the coordinate system in which the laser radar is located.
Optionally, calculating a rotation matrix of the laser radar according to the normal vectors of the first plane, the second plane, and the third plane and the directions of the first coordinate axis, the second coordinate axis, and the third coordinate axis of the coordinate system in which the laser radar is located, where the calculating includes:
respectively calculating included angles between a normal vector of each of the first plane, the second plane and the third plane and the directions of a first coordinate axis, a second coordinate axis and a third coordinate axis of a coordinate system in which the laser radar is located, and obtaining rotation matrixes corresponding to the first plane, the second plane and the third plane;
and calculating the product of the rotation matrixes corresponding to the first plane, the second plane and the third plane to obtain the rotation matrix of the laser radar.
The normal vector of each plane in the first plane, the second plane and the third plane is a vector, the first coordinate axis, the second coordinate axis and the third coordinate axis of the coordinate system where the laser radar is located all correspond to a vector, and the rotation matrix between the two vectors can be calculated based on the following process:
(1) assuming that unit vectors corresponding to the two vectors are a and b, respectively, making v equal to a × b;
(2) let s ═ v | |, c ═ a · b;
(3) definition of
The rotation matrix is then:
the process of calculating the included angle between the normal vector of each of the first plane, the second plane, and the third plane and the direction of the first coordinate axis, the second coordinate axis, and the third coordinate axis of the coordinate system in which the laser radar is located to obtain the rotation matrix corresponding to the first plane, the second plane, and the third plane is well known to those skilled in the art, and is not described herein again. After rotation matrixes E1, E2 and E3 corresponding to the first plane, the second plane and the third plane are obtained, the product of E1, E2 and E3 is calculated, and then the rotation matrix of the laser radar can be obtained.
As described above, according to the external reference calibration method for the laser radar, point cloud data acquired by the laser radar to be calibrated is acquired, wherein the point cloud data includes first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane, and third point cloud data corresponding to a third plane, and the first plane, the second plane, and the third plane are not parallel to each other; and respectively calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data, and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and parameters of a coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector. Therefore, the method and the device have the advantages that the planar point cloud data is adopted to calibrate the external parameters, the utilization rate of the point cloud data can be improved, the influence of point cloud sparsity is avoided or reduced, and the error of external parameter calibration is reduced.
Fig. 3 is a schematic structural diagram of an external reference calibration apparatus for a laser radar according to an embodiment of the present invention. As shown in fig. 3, an external reference calibration apparatus for a laser radar includes:
the point cloud data acquisition module 301 is configured to acquire point cloud data acquired by a laser radar to be calibrated, where the point cloud data includes first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane, and third point cloud data corresponding to a third plane, and the first plane, the second plane, and the third plane are not parallel to each other;
the plane parameter calculating module 302 is configured to calculate plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data;
and the calibration calculation module 303 is configured to calibrate and obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane, and the third plane and the parameter of the coordinate system where the laser radar is located, where the external parameters include a rotation matrix and/or a translation vector.
The working process of the above module is described in detail in the above method embodiment, and is not described herein again.
Based on the same inventive concept as the foregoing embodiment, an embodiment of the present invention provides a computer apparatus, as shown in fig. 4, including: a processor 310 and a memory 311 storing computer programs; the processor 310 illustrated in fig. 4 is not used to refer to the number of the processors 310 as one, but is only used to refer to the position relationship of the processor 310 relative to other devices, and in practical applications, the number of the processors 310 may be one or more; similarly, the memory 311 shown in fig. 4 is also used in the same sense, i.e. only used to refer to the position relationship of the memory 311 relative to other devices, and in practical applications, the number of the memory 311 may be one or more. When the processor 310 runs the computer program, the method for external reference calibration of the lidar according to the above embodiment is implemented.
The computer device may further include: at least one network interface 312. The various components in the computer device are coupled together by a bus system 313. It will be appreciated that the bus system 313 is used to enable communications among the components connected. The bus system 313 includes a power bus, a control bus, and a status signal bus in addition to the data bus. For clarity of illustration, however, the various buses are labeled as bus system 313 in FIG. 4.
The memory 311 may be a volatile memory or a nonvolatile memory, or may include both volatile and nonvolatile memories. Among them, the nonvolatile Memory may be a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a magnetic random access Memory (FRAM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical disk, or a Compact Disc Read-Only Memory (CD-ROM); the magnetic surface storage may be disk storage or tape storage. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Synchronous Static Random Access Memory (SSRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic Random Access Memory (SDRAM), Double Data Rate Synchronous Dynamic Random Access Memory (DDRSDRAM), Enhanced Synchronous Dynamic Random Access Memory (ESDRAM), Enhanced Synchronous Dynamic Random Access Memory (Enhanced DRAM), Synchronous Dynamic Random Access Memory (SLDRAM), Direct Memory (DRmb Access), and Random Access Memory (DRAM). The memory 311 described in connection with the embodiments of the invention is intended to comprise, without being limited to, these and any other suitable types of memory.
The memory 311 in the embodiment of the present invention is used to store various types of data to support the operation of the external reference calibration method of the laser radar. Examples of such data include computer programs, such as operating systems and application programs. The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. The application programs may include various application programs such as a Media Player (Media Player) and the like for implementing various application services. Here, the program that implements the method of the embodiment of the present invention may be included in an application program.
Based on the same inventive concept of the foregoing embodiments, this embodiment further provides a computer storage medium, where a computer program is stored in the computer storage medium, where the computer storage medium may be a Memory such as a magnetic random access Memory (FRAM), a Read Only Memory (ROM), a Programmable Read Only Memory (PROM), an Erasable Programmable Read Only Memory (EPROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Flash Memory (Flash Memory), a magnetic surface Memory, an optical Disc, or a Compact Disc Read Only Memory (CD-ROM), and the like; or may be a variety of devices including one or any combination of the above memories, such as a mobile phone, computer, tablet device, personal digital assistant, etc. When the computer program stored in the computer storage medium is executed by the processor, the method for calibrating external parameters of the laser radar according to the above embodiment is implemented. Please refer to the description of the embodiment shown in fig. 1 for a specific step flow realized when the computer program is executed by the processor, which is not described herein again.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
As used herein, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, including not only those elements listed, but also other elements not expressly listed.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (10)
1. A method for calibrating external parameters of a laser radar is characterized by comprising the following steps:
acquiring point cloud data acquired by a laser radar to be calibrated, wherein the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other;
calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data;
and calibrating to obtain external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector.
2. The method of claim 1, wherein the calculating plane parameters of the first plane, the second plane, and the third plane from the first point cloud data, the second point cloud data, and the third point cloud data, respectively, comprises:
and respectively fitting plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data.
3. The method according to claim 1, wherein the first plane is perpendicular to a first coordinate axis of a coordinate system of the lidar, the second plane is perpendicular to a second coordinate axis of the coordinate system of the lidar, the third plane is perpendicular to a third coordinate axis of the coordinate system of the lidar, and the first coordinate axis, the second coordinate axis, and the third coordinate axis are perpendicular to each other.
4. The method according to claim 3, wherein the calibrating to obtain the external parameters of the lidar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the lidar is located comprises:
respectively calculating the translation amounts of the first plane, the second plane and the third plane relative to the origin of a coordinate system where the laser radar is located according to the plane parameters of the first plane, the second plane and the third plane;
acquiring the vertical distance between the origin of the coordinate system where the laser radar is located and the first plane, the second plane and the third plane;
and respectively calculating the difference value between the translation amount and the vertical distance corresponding to the first plane, the second plane and the third plane to obtain the translation vector of the laser radar.
5. The method according to claim 4, wherein a vertical distance between an origin of a coordinate system in which the laser radar is located and the first plane, the second plane, and the third plane is a preset value or an external input value.
6. The method according to claim 3, wherein the calibrating to obtain the external parameters of the lidar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the lidar is located comprises:
according to the plane parameters of the first plane, the second plane and the third plane, respectively calculating normal vectors of the first plane, the second plane and the third plane;
and calculating a rotation matrix of the laser radar according to the normal vectors of the first plane, the second plane and the third plane and the directions of a first coordinate axis, a second coordinate axis and a third coordinate axis of a coordinate system in which the laser radar is located.
7. The method according to claim 6, wherein the calculating the rotation matrix of the lidar according to the normal vectors of the first plane, the second plane and the third plane and the directions of the first coordinate axis, the second coordinate axis and the third coordinate axis of the coordinate system of the lidar comprises:
respectively calculating included angles between a normal vector of each of the first plane, the second plane and the third plane and a direction of a first coordinate axis, a second coordinate axis and a third coordinate axis of a coordinate system where the laser radar is located, and obtaining rotation matrixes corresponding to the first plane, the second plane and the third plane;
and calculating the product of the rotation matrixes corresponding to the first plane, the second plane and the third plane to obtain the rotation matrix of the laser radar.
8. The external reference calibration device of the laser radar is characterized by comprising the following components:
the system comprises a point cloud data acquisition module, a calibration module and a calibration module, wherein the point cloud data acquisition module is used for acquiring point cloud data acquired by a laser radar to be calibrated, and the point cloud data comprises first point cloud data corresponding to a first plane, second point cloud data corresponding to a second plane and third point cloud data corresponding to a third plane, and the first plane, the second plane and the third plane are not parallel to each other;
the plane parameter calculation module is used for calculating plane parameters of the first plane, the second plane and the third plane according to the first point cloud data, the second point cloud data and the third point cloud data;
and the calibration calculation module is used for calibrating and obtaining external parameters of the laser radar according to the plane parameters of the first plane, the second plane and the third plane and the parameters of the coordinate system where the laser radar is located, wherein the external parameters comprise a rotation matrix and/or a translation vector.
9. A computer device, comprising: a processor and a memory storing a computer program which, when executed by the processor, performs the steps of the method of external reference calibration for lidar according to any of claims 1 to 7.
10. A computer storage medium, characterized in that a computer program is stored which, when being executed by a processor, carries out the steps of the method for external reference calibration of a lidar according to any of claims 1 to 7.
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