CN113495256B - Method and device for determining accuracy of calibration result among multiple laser radars - Google Patents
Method and device for determining accuracy of calibration result among multiple laser radars Download PDFInfo
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- CN113495256B CN113495256B CN202010251300.2A CN202010251300A CN113495256B CN 113495256 B CN113495256 B CN 113495256B CN 202010251300 A CN202010251300 A CN 202010251300A CN 113495256 B CN113495256 B CN 113495256B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
Abstract
The invention discloses a method and a device for determining accuracy of calibration results among a plurality of laser radars, and relates to the field of sensors. One embodiment of the method comprises the steps of: acquiring point cloud data acquired by a plurality of laser radars respectively for a scene comprising a flat surface; converting point cloud data acquired by a plurality of laser radars into the same coordinate system by using a calibration result; fitting equations representing the flat surfaces based on the point cloud data of each laser radar respectively; and calculating a numerical value representing the accuracy of the calibration result using a plurality of equations. This embodiment achieves the effect of simply and intuitively expressing the accuracy of the calibration result by numerical values.
Description
Technical Field
The invention relates to the field of sensors, in particular to a method and a device for determining the accuracy of calibration results among a plurality of laser radars.
Background
In recent years, the application of the laser radar is becoming more and more widespread in the fields of transportation, national defense security and the like. For example, in the related art, a laser radar is installed on an automobile and external information is acquired using the laser radar to assist a driver in driving or to perform automatic driving.
Due to the shielding of the vehicle itself and the existence of the blind areas of the lidars, a single lidar sensor cannot usually complete the task, and a plurality of lidars are required to be installed on the automobile to compensate for each other. The coordinate relationship between different lidars is a key point of fusing point cloud data of a plurality of lidars, and a plurality of calibration methods exist at present. Calibration refers to a process of converting point cloud data acquired by a plurality of radars into the same coordinate system by coordinate conversion (using a rotation matrix and a translation vector or using a homogeneous matrix).
In the process of implementing the present invention, the inventor finds that at least the following problems exist in the prior art: the conventional calibration processing method and device cannot conveniently and accurately know the accuracy of the calibration result after the calibration is completed, and if the calibration result is inaccurate, the situation that even if the calibration result is used for converting the point cloud data acquired by a plurality of laser radars, the point cloud data cannot be well fused may occur.
Disclosure of Invention
In view of this, the embodiments of the present invention provide a method and an apparatus for determining the accuracy of a calibration result between a plurality of lidars, which can determine the accuracy of the calibration result by using a flat surface (ground) existing in a scene, without arranging special props for determining the accuracy of the calibration result in the scene, and simultaneously, because the accuracy of the calibration result of each lidar is represented in a numerical form, the method and the apparatus are simple and intuitive, so that a user can conveniently and quickly understand the accuracy of the calibration result, and the calculation amount is reduced.
To achieve the above object, according to one aspect of the embodiments of the present invention, there is provided a method for determining accuracy of calibration results between a plurality of lidars, comprising the steps of:
acquiring point cloud data acquired by a plurality of laser radars respectively for a scene comprising a flat surface;
converting the point cloud data acquired by a plurality of laser radars into the same coordinate system by using a calibration result;
respectively fitting equations representing the flat surfaces based on point cloud data of the laser radars after being converted into the same coordinate system; and
calculating a numerical value representing the accuracy of the calibration result using a plurality of the equations.
In the method of determining the accuracy of the calibration results between a plurality of lidars, preferably,
selecting one laser radar as a reference laser radar, taking a coordinate system of the laser radar as a reference coordinate system, and converting point cloud data based on a self coordinate system, which is acquired by non-reference laser radars except the reference laser radars, in a plurality of the laser radars into the reference coordinate system by utilizing the calibration result;
fitting a reference plane equation characterizing the planar surface based on the point cloud data of the reference lidar, fitting a non-reference plane equation characterizing the planar surface based on the converted point cloud data of a non-reference lidar, the reference plane equation indicating a reference fit plane corresponding to the planar surface measured by the reference lidar, the non-reference plane equation indicating a non-reference fit plane corresponding to the planar surface measured by the non-reference lidar.
In the method of determining the accuracy of the calibration result between the plurality of lidars, it is further preferable that,
calculating the distance from the point in the non-reference fitting plane to the reference fitting plane in the point cloud data acquired by the non-reference laser radar,
and utilizing the distance to represent the accuracy of the calibration result.
In the method of determining the accuracy of the calibration result between the plurality of lidars, it is further preferable that,
calculating the average distance between the points in the non-reference fitting plane and the distance between the points in the non-reference fitting plane in the point cloud data acquired by the non-reference laser radar,
and utilizing the average distance to represent the accuracy of the calibration result.
In the method of determining the accuracy of the calibration result between the plurality of lidars, it is further preferable that,
calculating an included angle between a normal of the non-reference fitting plane and a normal of the reference fitting plane,
and characterizing the accuracy of the calibration result by using the included angle.
In the method of determining the accuracy of the calibration results between a plurality of lidars, preferably,
acquiring a plurality of frames of point cloud data acquired by the laser radars, and fitting the reference plane equation and the non-reference plane equation representing the flat surface to each frame of point cloud data respectively;
the numerical value characterizing the accuracy of the calibration result is calculated using the reference plane equation and the non-reference plane equation derived from the point cloud data for each frame.
In the method of determining the accuracy of the calibration results between a plurality of lidars, preferably,
and selecting the laser radar with the highest position from a plurality of laser radars as the reference laser radar.
According to another aspect of an embodiment of the present invention, there is provided an apparatus for determining accuracy of calibration results between a plurality of lidars, characterized in that,
the device is provided with:
a data acquisition unit that acquires point cloud data acquired by a plurality of lidars for a scene including a flat surface, respectively;
the data conversion unit is used for converting the point cloud data acquired by the plurality of laser radars into the same coordinate system by using a calibration result;
a fitting unit for fitting equations representing the flat surfaces based on the point cloud data of the laser radars after being converted into the same coordinate system; and
a calculation unit that calculates a numerical value characterizing accuracy of the calibration result using a plurality of the equations.
According to another aspect of an embodiment of the present invention, there is also provided an electronic apparatus for determining accuracy of calibration results between a plurality of lidars, including:
one or more processors;
storage means for storing one or more programs,
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the methods described above.
According to another aspect of an embodiment of the present invention, there is also provided a computer readable medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements a method as described above.
One embodiment of the above invention has the following advantages or benefits: because the accuracy of the calibration result is determined by using the flat surface (ground) existing in the scene, special props for determining the accuracy of the calibration result are not required to be arranged in the scene, and meanwhile, the accuracy of the calibration result of each laser radar is represented in a numerical form, so that the method is simple and visual. The user can conveniently and rapidly know the accuracy of the calibration result, and meanwhile, the calculated amount is reduced.
Further effects of the above-described non-conventional alternatives are described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of the main steps of a first embodiment of a method of determining the accuracy of calibration results between a plurality of lidars according to the present invention;
FIG. 2 is a schematic diagram of the main steps of a second embodiment of a method of determining the accuracy of calibration results between a plurality of lidars according to the present invention;
FIG. 3 is a schematic diagram of the main modules of an apparatus for determining the accuracy of calibration results between multiple lidars according to an embodiment of the invention;
fig. 4 is a schematic diagram of a computer system suitable for use in implementing an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present invention are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
(first embodiment)
The method for determining the accuracy of the calibration result between the plurality of laser radars according to the embodiment of the invention is used for determining the accuracy of the calibration result between the plurality of vehicle-mounted multi-line laser radars.
Fig. 1 shows a method for determining accuracy of calibration results between a plurality of lidars according to an embodiment of the present invention, and as shown in fig. 1, the method for determining accuracy of calibration results between a plurality of lidars according to an embodiment of the present invention achieves the effect of simply and intuitively representing accuracy of calibration results by numerical values.
In the method for determining accuracy of calibration results between multiple lidars according to an embodiment of the present invention shown in fig. 1, a data acquisition step S101 is included, in which a vehicle mounted with multiple multi-line lidars is allowed to stand on a flat ground, and point cloud data acquired for a scene by three multi-line lidars is acquired. The point cloud data refers to data recorded in the form of points, each of which includes three-dimensional coordinates.
In this embodiment, the vehicle has three multi-line lidars, and thus three lidars are collected in total for point cloud data, but the number of lidars is not limited.
It is to be understood that in the present invention, it is not necessary to stand the vehicle on the ground, and the object of the present invention can be achieved in a scene having a flat surface. For example, a scene with a wall in front of the vehicle may be selected.
The method for determining the accuracy of the calibration result between the plurality of laser radars according to one embodiment of the present invention has a data conversion step S102 in which one laser radar with the highest height is selected as a reference laser radar, its coordinate system is used as a reference coordinate system, and point cloud data based on its own coordinate system acquired by the other two laser radars (non-reference laser radars) is converted to the reference coordinate system through the calibration result.
The specific form of the calibration result is a rotation matrix R and translation vectors (x, y, z).
(in the rotation matrix R, psi is roll (roll angle),Pitch, θ is yaw). With the rotation matrix and translation vector, the coordinates of a point in one coordinate system can be converted to coordinates in the other coordinate system. In the present embodiment, the coordinates of the point cloud data based on the own coordinate system acquired by the non-reference lidar are converted into the coordinate system of the reference lidar.
The calibration result can also be a homogeneous matrix M 1 (matrix of 4*4), the rotation and translation of the coordinates can be completed simultaneously by using the homogeneous matrix, so that the coordinates of the points in one coordinate system can be converted into other coordinate systems, and a specific calculation formula is as follows.
In the formula, the coordinates (X W ，Y W ，X W ) Is converted into the coordinates (X C ，Y C ，Z C ). The calculation process when the rotation matrix R and the translation vector are used is similar to this, and therefore, the description is omitted.
That is, the coordinates of the point cloud data based on the own coordinate system acquired by one laser radar can be converted into coordinates based on the coordinate system of the other laser radar by using the calibration result, and in the present embodiment, the coordinates are converted into coordinates in the coordinate system of the reference laser radar.
The accuracy of determining calibration results between a plurality of laser radars described in the present invention refers to determining whether parameters in these matrices (rotation matrix, translation vector or homogeneous matrix) are accurate. When the calibration result is found to be inaccurate, the operator performs recalibration according to the requirement.
In the embodiment of the present invention, a case where one lidar is selected as the reference lidar and the remaining lidars are non-reference lidars is described, but it is to be understood that this is merely illustrative and not restrictive. For example, the lidar may be numbered to be a first lidar, a second lidar, or the like without affecting the effect of the present invention.
In the fitting step S103, a ground is extracted for the point cloud data acquired by the reference lidar, and the ground is fitted using the RANSAC algorithm, resulting in a first plane equation (hereinafter referred to as "reference plane equation") denoted as a1x+b1y+c1z+d1=0. The reference plane equation represents a reference fitting plane, which is a fitting plane of point cloud data of the reference lidar to the ground.
Wherein A1, B1, C1, D1 are parameters of the first plane equation, respectively, i.e., a reference fitting plane is completely determined by the four parameters.
Next, a ground is extracted from the point cloud data acquired by the non-reference lidar which has been converted in the data conversion step S102, and the ground is fitted using the RANSAC algorithm, resulting in a non-reference plane equation expressed as a2x+b2y+c2z+d2=0 (second plane equation) and a3x+b3y+c3z+d3=0 (third plane equation). The non-reference plane equation represents a fitting plane to the ground by the point cloud data of the non-reference lidar, that is, a non-reference fitting plane (a second fitting plane and a third fitting plane). Wherein A2, B2, C2, D2 are parameters of the second plane equation, respectively, and a second fitting plane is completely determined by the four parameters; a3, B3, C3, D3 are parameters of the third plane equation, respectively, from which the third fitting plane is completely determined.
Here, since the vehicle has three lidars, one reference plane equation and two non-reference plane equations are obtained, but in the case where the vehicle has two or more lidars, the number of plane equations may also be changed. For example, with five lidars, one reference plane equation and four non-reference plane equations may be obtained.
The RANSAC algorithm is a random sample consensus algorithm (Random Sample Consensus), which is an algorithm that calculates mathematical model parameters of data from a sample data set containing outlier data to obtain valid sample data. The basic assumption of the RANSAC algorithm is that the samples contain correct data (data that can be described by a model) and also abnormal data (data that deviate far from the normal range and cannot adapt to a mathematical model), i.e. the data set contains noise. These anomalous data may be due to erroneous measurements, erroneous assumptions, erroneous calculations, etc.
In the calculation step S104, numerical processing is performed using the reference plane equation and the non-reference plane equation. Specifically, the included angles between the normals of the two non-reference fitting planes and the normals of the reference fitting planes are calculated respectively. In the present embodiment, since there are two non-reference lidars in common, the angles between the normals of the two non-reference fitting planes and the normals of the reference fitting planes are calculated in total. The calculation formula of the included angle between the normal line of the second fitting plane and the normal line of the reference fitting plane is as follows:
the angles between the normal of the third fitting plane and the normal of the reference fitting plane are calculated by replacing A2, B2, C2, D2 in the above formula with A3, B3, C3, D3.
It will be appreciated that in the present invention, it is not necessary to select the laser radar with the highest height as the reference laser radar, and any one of the laser radars may be selected as the reference laser radar to achieve the object of the present invention. In the embodiment of the present invention, the laser radar with the highest position may be automatically selected as the reference laser radar, or may be appropriately selected by the operator according to the actual situation.
In the present embodiment, the description has been made in terms of calculating the angle between the normal line of the non-reference fitting plane and the normal line of the reference fitting plane, but the angle between each fitting plane and the other fitting plane may be calculated. For example, in the case of three lidars in the present embodiment, the angle of each fitting plane relative to the other two fitting planes may be calculated separately.
In this embodiment, the method includes an alarm step S105, which judges whether each included angle is greater than a threshold value of 0.5 °, and when an included angle greater than 0.5 ° exists in the two included angles, an alarm is sent to the outside to remind the operator that the calibration results of the plurality of lidars are not qualified. The operator can recalibrate the calibration as required.
The threshold may be appropriately selected according to the required calibration accuracy and the flatness of the ground, and is not limited to 0.5 °, for example, when the required calibration accuracy is high, the threshold may be set to 0.2 °, that is, when an included angle greater than 0.2 ° exists in the two included angles, an alarm is given to the outside.
In addition, the calculated angle may be directly output to the outside without setting the threshold value, and the operator may determine whether the calibration result is acceptable.
The method of determining the accuracy of the calibration result between the plurality of lidars of the present embodiment does not require arranging special props for determining the accuracy of the calibration result in the scene, but uses a flat surface (ground) existing in the scene to determine the accuracy of the calibration result. Moreover, the difference of the fitting planes of the laser radars is represented in the form of an included angle, so that the method is simple and visual, the calculated amount is small, and the resources occupied in the calculation process are reduced. The user can conveniently and quickly know the quality of the calibration result.
Modification 1
The method has the advantages that the method has great errors when judging whether the calibration result is good or not according to the fitting plane fitted by the point cloud data in a single frame, is easily affected by unexpected conditions, and causes errors and the like on the accuracy of the determined calibration result.
As an improvement of the first embodiment of the present invention, in the data acquisition step, a plurality of frames of point cloud data acquired by a plurality of lidars are acquired, and one fitting plane is obtained by the same lidar according to each frame of point cloud data. I.e. each lidar is fitted with a plurality of fitting planes (an amount corresponding to the number of frames).
Since a plurality of fitting planes are fitted according to the point cloud data acquired by each lidar, two included angles are formed between the normal line of the two non-reference fitting planes and the normal line of the reference fitting plane for the content in each frame at this time.
In modification 1, it is set such that an alarm is given to the outside only when the value of the two included angles in the number of frames of more than 80% is more than 0.5 ° to alert the operator that the calibration results of the plurality of lidars are not acceptable. The ratio of the number of frames may be selected according to the need, or may be set such that the alarm is given to the outside only when the value of the two included angles in the number of frames of more than 50% (determined according to the actual situation) is more than 0.5 ° (not limited, and may be determined according to the situation).
According to the technical scheme of modification 1, the accuracy of the calibration result among the plurality of laser radars is determined by acquiring the multi-frame point cloud data acquired by the plurality of laser radars, so that the influence of accidental factors or errors can be avoided as much as possible.
(second embodiment)
The second embodiment of the present invention is different from the first embodiment in that, in the calculation step S204, the distance from the point located in the non-reference plane to the reference fitting plane in the point cloud data acquired by the non-reference lidar is calculated by using a point-to-plane distance formula, and the average distance of these distances is calculated. The magnitude of the average distance represents the magnitude of the difference between the non-reference fit plane and the reference fit plane, so the average distance is used to represent the accuracy of the calibration result. Other steps (data acquisition step S201, data conversion step S202, fitting step S203) other than these are the same as those of the first embodiment, and therefore, the description thereof is omitted.
In the calculation step of this embodiment, in the calculation step S204, the distances (laser radar range) between the points actually located in the second fitting plane (a2x+b2y+c2z+d2=0) (excluding the points not participating in the fitting plane) and the reference fitting plane (a1x+b1y+c1z+d1=0) which is the first fitting plane are calculated, and the average distance D1 is further calculated. And the average distance D2 from the point on the third fitting plane (a3x+b3y+c3z+d3=0) to the reference fitting plane (a1x+b1y+c1z+d1=0) was found in the same manner.
Since the RANSAC algorithm is used in the fitting step, in the calculation step, data that deviates too far from the normal range is not involved in calculation (i.e., points that do not participate in the fitting plane are culled) when the distance is calculated.
After the average distances d1 and d2 are obtained, it is determined whether or not the average distances d1 and d2 are larger than a threshold value of 0.05m. When the d1 and d2 are larger than 0.05m, an alarm is sent to the outside to remind an operator that the calibration results of the plurality of laser radars are not qualified. The threshold value can be appropriately selected according to the required calibration accuracy and the flatness of the ground, and is not limited to 0.05m. In addition, the calculated average distance may be directly output to the outside without setting the threshold value, and the operator may determine whether the calibration result is acceptable.
It will be appreciated that although the accuracy of the calibration results of the plurality of lidars is characterized by the average distance in the present embodiment, a distance such as the median may be selected to characterize the accuracy of the calibration results of the plurality of lidars from the distance from the point actually located in the non-reference fitting plane (a2x+b2y+c2z+d2=0) (excluding the point not participating in the fitting plane) to the reference fitting plane, i.e., the reference fitting plane (a1x+b1y+c1z+d1=0).
The second embodiment uses the form of distance to represent the difference of the fitting planes of the laser radars, so that the method is simple and visual. The user can conveniently and quickly know the quality of the calibration result.
Modification 2
Similar to modification 1, as a modification of the second embodiment of the present invention, in the data acquisition step, a plurality of frames of point cloud data acquired by a plurality of lidars are acquired, and one fitting plane is obtained by the same lidar based on each frame of point cloud data. I.e. each lidar is fitted with a plurality of fitting planes (an amount corresponding to the number of frames).
Since a plurality of fitting planes are fitted on the basis of the point cloud data acquired by each lidar, the distances from the points located on the non-reference fitting plane (excluding the points not participating in the fitting plane) to the reference fitting plane are calculated for the content in each frame at this time, and the average distances d1, d2 are calculated.
In modification 2, it is set such that only when the number of two distances in the number of frames larger than 80% is larger than 0.05m, an alarm is given to the outside to alert the operator that the calibration results of the plurality of lidars are not acceptable. The ratio of the number of frames is not limited, and the warning may be given to the outside only when the value of the average distance between two of the number of frames greater than 50% (determined according to the actual situation) is greater than 0.05m (not limited, and may be determined according to the situation).
Modification 2 determines the accuracy of the calibration result between the plurality of lidars by acquiring multi-frame point cloud data acquired by the plurality of lidars, so that the influence of accidental factors or errors can be avoided as much as possible.
(third embodiment)
As a third embodiment of the present invention, the angle between the normal line of the non-reference fitting plane and the normal line of the reference fitting plane and the distance from the point in the non-reference fitting plane to the reference fitting plane may be taken as the numerical value representing the accuracy of the calibration result at the same time.
In this case, since there are two kinds of data, the operator can more clearly determine the accuracy of the calibration result from two aspects.
(fourth embodiment)
A fourth embodiment of the present invention provides an apparatus for determining accuracy of calibration results between a plurality of lidars, comprising: a data acquisition unit 1, a data conversion unit 2, a fitting unit 3 and a calculation unit 4.
In the present embodiment, the data acquisition unit 1 acquires point cloud data acquired by three lidars for a scene including a flat surface, respectively.
The data conversion unit 2 selects the laser radar with the highest position from the three laser radars as a reference laser radar, and converts the point cloud data based on the self coordinate system acquired by the remaining two non-reference laser radars into a reference coordinate system through the acquired calibration result.
The fitting unit 3 fits a reference plane equation representing the ground and a non-reference plane equation indicating a reference fitting plane, and a non-reference plane equation indicating a non-reference fitting plane, based on the point cloud data of the reference lidar and the point cloud data of the converted non-reference lidar. Wherein a reference fit plane corresponds to the planar surface measured by the reference lidar and a non-reference fit plane corresponds to the planar surface measured by the non-reference lidar.
The calculation unit 4 performs numerical processing using the reference plane equation and the non-reference plane equation to obtain a numerical value representing the accuracy of the calibration result. Specifically, the calculating unit calculates the included angle between the normal line of the two non-reference fitting planes and the normal line of the reference fitting plane respectively, and the difference between the non-reference fitting planes and the reference fitting plane is represented by the included angle, so that the accuracy of the calibration results among the plurality of laser radars is determined.
The calculation unit can also calculate the distance from the point in the non-reference fitting plane to the reference fitting plane in the point cloud data acquired by the non-reference laser radar respectively, further calculate the average distance, and utilize the average distance to represent the difference between the non-reference fitting plane and the reference fitting plane, thereby determining the accuracy of the calibration result among the plurality of laser radars.
In this embodiment, the apparatus for determining the accuracy of the calibration result between the plurality of lidars further includes an output unit 5 for outputting the included angle or the average distance to the outside, so that the operator intuitively knows the accuracy of the calibration result.
In the present embodiment, the alarm unit 6 is provided, and the alarm unit 6 is provided with a threshold value, and when the included angle or the average distance is larger than the threshold value, the alarm unit 6 gives an alarm indicating that the calibration result is not acceptable to the outside. The threshold value may be set appropriately according to the required accuracy and the surrounding environment, and may be, for example, an angle value of 0.5 °, or an angle value of 0.2 °, or an average distance of 0.05m, in the case where higher accuracy is required. The alarm output to the outside can contain the excess of the included angle or average distance compared with the threshold value, or only a prompt that the calibration result is not qualified.
The apparatus for determining accuracy of a calibration result between a plurality of lidars of the fourth embodiment may make it unnecessary to arrange special props for determining accuracy of a calibration result in a scene, and determine accuracy of a calibration result using a flat surface (ground) existing in the scene. In addition, the accuracy of the calibration result of each laser radar can be expressed in the form of data, so that the method is simple and visual. The user can conveniently and quickly know the quality of the calibration result, and meanwhile, the calculated amount is reduced.
Although the method and apparatus for determining the accuracy of the calibration results between a plurality of lidars according to the present invention are described in the application to a vehicle-mounted multi-line lidar, the present invention is not limited to this, and may be applied to the fields of, for example, aircraft, ship, and the like.
Referring now to FIG. 4, there is illustrated a schematic diagram of a computer system 400 suitable for use in implementing an embodiment of the present invention. The terminal device shown in fig. 4 is only an example, and should not impose any limitation on the functions and the scope of use of the embodiment of the present invention.
As shown in fig. 4, the computer system 400 includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 402 or a program loaded from a storage section 408 into a Random Access Memory (RAM) 403. In RAM 403, various programs and data required for the operation of system 400 are also stored. The CPU 401, ROM 402, and RAM 403 are connected to each other by a bus 404. An input/output (I/O) interface 405 is also connected to bus 404.
The following components are connected to the I/O interface 405: an input section 406 including a keyboard, a mouse, and the like; an output portion 407 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker, and the like; a storage section 408 including a hard disk or the like; and a communication section 409 including a network interface card such as a LAN card, a modem, or the like. The communication section 409 performs communication processing via a network such as the internet. The drive 410 is also connected to the I/O interface 405 as needed. A removable medium 411 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 410 as needed, so that a computer program read therefrom is installed into the storage section 408 as needed.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method shown in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 409 and/or installed from the removable medium 411. The above-described functions defined in the system of the present invention are performed when the computer program is executed by a Central Processing Unit (CPU) 401.
The computer readable medium shown in the present invention may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units involved in the embodiments of the present invention may be implemented in software or in hardware. The described units may also be provided in a processor, for example, described as: a processor comprising: the device comprises a data acquisition unit, a data conversion unit, a fitting unit and a calculation unit. The names of these units do not in any way limit the units themselves, for example, the data acquisition unit may also be described as "unit for acquiring point cloud data acquired by a lidar".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be present alone without being fitted into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to include the steps of:
acquiring point cloud data acquired by a plurality of laser radars respectively for a scene comprising a flat surface;
converting the point cloud data acquired by a plurality of laser radars into the same coordinate system by using a calibration result;
fitting equations characterizing the planar surfaces based on the point cloud data of each of the lidars, respectively; and
calculating a numerical value representing the accuracy of the calibration result using a plurality of the equations.
According to the technical scheme of the embodiment of the invention, special props for determining the accuracy of the calibration result are not required to be arranged in the scene, and the accuracy of the calibration result is determined by utilizing the flat surface (ground) existing in the scene. Moreover, the accuracy of the fitting result of each laser radar is shown in a numerical form, so that the method is simple and visual, the calculated amount is small, and the resources occupied in the calculation process are reduced. The user can conveniently and quickly know the quality of the calibration result.
The above embodiments do not limit the scope of the present invention. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives can occur depending upon design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of the present invention.
Claims (8)
1. A method of determining the accuracy of a calibration result between a plurality of lidars, comprising the steps of:
acquiring point cloud data acquired by a plurality of laser radars respectively for a scene comprising a flat surface;
converting the point cloud data acquired by the laser radars into the same coordinate system by using a calibration result, wherein the method comprises the following steps of: selecting one laser radar as a reference laser radar, taking a coordinate system of the laser radar as a reference coordinate system, and converting point cloud data based on a self coordinate system, which is acquired by non-reference laser radars except the reference laser radars, in a plurality of the laser radars into the reference coordinate system by utilizing the calibration result;
respectively fitting equations representing the flat surfaces based on point cloud data of the laser radars after being converted into the same coordinate system; the method comprises the steps of fitting a reference plane equation representing the flat surface based on point cloud data of the reference laser radar, fitting a non-reference plane equation representing the flat surface based on converted point cloud data of a non-reference laser radar, wherein the reference plane equation indicates a reference fitting plane; and
calculating a value characterizing the accuracy of the calibration result using a plurality of the equations, comprising:
calculating the distance between a point in a non-reference fitting plane and a reference fitting plane in point cloud data acquired by the non-reference laser radar, and representing the accuracy of the calibration result by using the distance;
or,
and calculating an included angle between the normal line of the non-reference fitting plane and the normal line of the reference fitting plane, and representing the accuracy of the calibration result by using the included angle.
2. The method of determining the accuracy of a calibration result between a plurality of lidars as claimed in claim 1,
the reference fit plane corresponds to the planar surface measured by the reference lidar, and the non-reference plane equation indicates a non-reference fit plane corresponding to the planar surface measured by the non-reference lidar.
3. The method of determining the accuracy of a calibration result between a plurality of lidars as claimed in claim 1,
calculating the average distance between the points in the non-reference fitting plane and the distance between the points in the non-reference fitting plane in the point cloud data acquired by the non-reference laser radar,
and utilizing the average distance to represent the accuracy of the calibration result.
4. The method of determining the accuracy of a calibration result between a plurality of lidars as claimed in claim 1,
acquiring a plurality of frames of point cloud data acquired by the laser radars, and fitting the reference plane equation and the non-reference plane equation representing the flat surface to each frame of point cloud data respectively;
the numerical value characterizing the accuracy of the calibration result is calculated using the reference plane equation and the non-reference plane equation derived from the point cloud data for each frame.
5. The method of determining the accuracy of a calibration result between a plurality of lidars as claimed in claim 1,
and selecting the laser radar with the highest position from a plurality of laser radars as the reference laser radar.
6. An apparatus for determining accuracy of a calibration result between a plurality of lidars, comprising:
a data acquisition unit that acquires point cloud data acquired by a plurality of lidars for a scene including a flat surface, respectively;
the data conversion unit converts the point cloud data acquired by the laser radars into the same coordinate system by using a calibration result, and comprises the following steps: selecting one laser radar as a reference laser radar, taking a coordinate system of the laser radar as a reference coordinate system, and converting point cloud data based on a self coordinate system, which is acquired by non-reference laser radars except the reference laser radars, in a plurality of the laser radars into the reference coordinate system by utilizing the calibration result;
a fitting unit for fitting equations representing the flat surfaces based on the point cloud data of the laser radars after being converted into the same coordinate system; the method comprises the steps of fitting a reference plane equation representing the flat surface based on point cloud data of the reference laser radar, fitting a non-reference plane equation representing the flat surface based on converted point cloud data of a non-reference laser radar, wherein the reference plane equation indicates a reference fitting plane; and
a calculation unit that calculates a numerical value characterizing accuracy of the calibration result using a plurality of the equations, comprising:
calculating the distance between a point in a non-reference fitting plane and a reference fitting plane in point cloud data acquired by the non-reference laser radar, and representing the accuracy of the calibration result by using the distance;
or,
and calculating an included angle between the normal line of the non-reference fitting plane and the normal line of the reference fitting plane, and representing the accuracy of the calibration result by using the included angle.
7. An electronic device for determining accuracy of a calibration result between a plurality of lidars, comprising:
one or more processors;
storage means for storing one or more programs,
when executed by the one or more processors, causes the one or more processors to implement the method of any of claims 1-5.
8. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the method according to any of claims 1-5.
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