CN114593751A - External parameter calibration method, device, medium and electronic equipment - Google Patents
External parameter calibration method, device, medium and electronic equipment Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
- G01C25/005—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass initial alignment, calibration or starting-up of inertial devices
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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 embodiment of the disclosure provides an external parameter calibration method, an external parameter calibration device, an external parameter calibration medium and electronic equipment, and relates to the technical field of automatic driving. The method comprises the following steps: extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation; determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames; determining search external parameters of each hierarchy in a preset search range through multi-hierarchy iterative search; and determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each hierarchy, and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance. According to the technical scheme of the embodiment of the disclosure, the calibration external parameter has higher calibration precision, and the balance between the search speed and the search granularity is realized.
Description
Technical Field
The disclosure relates to the technical field of automatic driving, and particularly relates to an external parameter calibration method, an external parameter calibration device, a computer readable medium and an electronic device.
Background
In the field of automatic driving, a multiline laser radar and a combined Inertial Navigation System (GNSS), for example, an Inertial Measurement Unit (IMU), are commonly used sensor configurations for high-precision mapping, unmanned vehicle pose positioning, and point cloud object detection tasks. Therefore, the external reference between the laser radar and the combined inertial navigation is accurately calibrated, and the method has important significance.
At present, in a technical scheme, a relative pose between multi-line laser radar frames is calculated by using a laser radar odometer or a SLAM (Simultaneous Localization And Mapping) technology, And then, the pose information provided by the combined inertial navigation is combined to perform extrinsic parameter solution based on methods such as hand-eye calibration And the like.
However, in the technical scheme, some prior assumptions or approximations need to be made on the scene or pose information, and when the actual scene is different from the prior assumptions, the calibration accuracy is difficult to guarantee.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
An object of the embodiments of the present disclosure is to provide an external reference calibration method, an external reference calibration apparatus, a computer-readable medium, and an electronic device, so as to obtain a calibration external reference with a higher calibration accuracy at least to a certain extent.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the disclosure.
According to a first aspect of the embodiments of the present disclosure, there is provided an external reference calibration method for lidar and combined inertial navigation, the method including: extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation; determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames; determining search external parameters of each hierarchy in a preset search range through multi-hierarchy iterative search; and determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each level, and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
According to the first aspect, in some example embodiments, the determining search arguments of respective levels within a predetermined search range by a multi-level iterative search includes: determining the searching step length and the searching range of the current level in the preset searching range in a mode of reducing the step length layer by layer; and determining a search external parameter corresponding to the current level based on the search step length and the search range of the current level.
According to the first aspect, in some example embodiments, the multi-level iterative search is an alternating angle element and line element iterative search, and the determining search arguments of respective levels within a predetermined search range by the multi-level iterative search includes: determining angle element search external parameters of each level in a predetermined angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a preset line element search range through line element multi-level iterative search.
According to the first aspect, in some example embodiments, the determining a calibration external parameter of the lidar and combined inertial navigation based on the distance includes: determining a loss function corresponding to each key frame matching pair based on the distance, wherein the loss function is an average distance measurement function of a target three-dimensional point between two key frames in the key frame matching pair; and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the loss function.
According to the first aspect, in some example embodiments, said extracting a plurality of point cloud key frames of the lidar from the acquired pose trajectories of the combined inertial navigation comprises: extracting a corresponding point cloud key frame of the laser radar according to a preset condition according to the collected pose track of the combined inertial navigation, wherein the preset condition comprises the following steps: the first frame or the last frame of the point cloud corresponding to the pose track is a key frame of the point cloud; the current frame which passes through the last key frame and has the accumulated track length larger than a preset length threshold value is a point cloud key frame; and the current frame with the variation of the yaw angle between the current frame and the last key frame being larger than the preset angle threshold value is a point cloud key frame.
According to the first aspect, in some example embodiments, the determining a plurality of key frame matching pairs according to the relative pose information between the point cloud key frames comprises: determining two frames which are adjacent in front and back in time as a key frame matching pair according to the relative pose information between the point cloud key frames; and/or determining two frames adjacent in space as a key frame matching pair according to the relative pose information between the point cloud key frames.
According to the first aspect, in some example embodiments, the method further comprises: before searching, a certain proportion of key frame matching pairs are extracted from a plurality of key frame matching pairs in an equal probability random sampling mode to form a key frame matching pair subset so as to search the key frame matching pair subset.
According to a second aspect of the embodiments of the present disclosure, there is provided an external reference calibration apparatus for lidar and combined inertial navigation, the apparatus including: the frame extraction module is used for extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation; the matching pair determining module is used for determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames; the search module is used for determining search external parameters of each level in a preset search range through multi-level iterative search; and the external parameter determining module is used for determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each level and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
According to the second aspect, in some example embodiments, the search module is further configured to: determining the search step length and the search range of the current level in the preset search range in a mode of reducing the step length layer by layer; and determining a search external parameter corresponding to the current level based on the search step length and the search range of the current level.
According to the second aspect, in some example embodiments, the multi-level iterative search is an alternating angular element and line element iterative search, the search module further to: determining angle element search external parameters of each level in a predetermined angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a preset line element search range through line element multi-level iterative search.
According to the second aspect, in some example embodiments, the external parameter determination module is further configured to: determining a loss function corresponding to each key frame matching pair based on the distance, wherein the loss function is an average distance measurement function of a target three-dimensional point between two key frames in the key frame matching pair; and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the loss function.
According to the second aspect, in some example embodiments, the frame extraction module is further configured to: extracting a corresponding point cloud key frame of the laser radar according to the collected pose track of the combined inertial navigation and preset conditions, wherein the preset conditions comprise: the first frame or the last frame of the point cloud corresponding to the pose track is a key frame of the point cloud; the current frame which passes through the last key frame and has the accumulated track length larger than a preset length threshold value is a point cloud key frame; and the current frame with the variation of the yaw angle between the current frame and the last key frame being larger than the preset angle threshold value is a point cloud key frame.
According to the second aspect, in some example embodiments, the matching pair determination module is further configured to: determining two frames which are adjacent in front and back in time as a key frame matching pair according to the relative pose information between the point cloud key frames; and/or determining two frames adjacent in space as a key frame matching pair according to the relative pose information between the point cloud key frames.
According to a second aspect, in some example embodiments, the apparatus further comprises: and the sampling module is used for extracting a certain proportion of key frame matching pairs from the plurality of key frame matching pairs in an equal probability random sampling mode before searching to form a key frame matching pair subset so as to search the key frame matching pair subset.
According to a third aspect of the embodiments of the present disclosure, there is provided a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements the external reference calibration method as described in the first aspect of the embodiments above.
According to a fourth aspect of the embodiments of the present disclosure, there is provided an electronic apparatus including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement the method of external reference calibration as described in the first aspect of the embodiments above.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
in some embodiments of the present disclosure, on one hand, a point cloud key frame is extracted according to a pose track of the combined inertial navigation, and a plurality of key frame matching pairs are determined according to relative pose information between the point cloud key frames, so that key frames with consistent spatial distribution characteristics can be accurately acquired; on the other hand, search external parameters of all levels in a preset search range are determined through multi-level iterative search, and calibration external parameters of the laser radar and the combined inertial navigation are determined based on the distance between the key frames, so that the calibration external parameters have high calibration precision, the balance between the search speed and the search granularity is realized, and the accuracy and the robustness of a calibration result are guaranteed.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:
FIG. 1 is a schematic diagram illustrating an application scenario of an external reference calibration method in an exemplary embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram of an external reference calibration method according to some example embodiments of the present disclosure;
FIG. 3 shows a schematic flow diagram of an external reference calibration method according to further example embodiments of the present disclosure;
FIG. 4 shows a schematic diagram of two data acquisition modes in some example embodiments according to the present disclosure;
FIG. 5 illustrates a schematic diagram of hierarchical iterative search in some example embodiments according to the present disclosure;
FIG. 6 shows a schematic structural diagram of an external reference calibration apparatus according to another embodiment of the present disclosure;
fig. 7 shows a schematic structural diagram of an electronic device in an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known methods, devices, implementations, or operations have not been shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
In order to clearly explain technical solutions in the embodiments of the present disclosure, before specifically developing and explaining the embodiments of the present disclosure, some terms applied in the embodiments are first described.
Hereinafter, the external reference calibration method in the exemplary embodiment of the present disclosure will be described in detail with reference to the accompanying drawings.
Fig. 1 illustrates a schematic diagram of an application scenario provided in accordance with some embodiments of the present disclosure.
Fig. 1 illustrates a schematic diagram of an application scenario provided in accordance with some embodiments of the present disclosure. In the high-precision map acquisition system shown in fig. 1, the laser radar 110 is horizontally placed on the roof of the vehicle to obtain a 360-degree unobstructed sensing range, and the combined inertial navigation device 120 is horizontally placed right below the laser, so as to calculate the relative pose between the two.
In an exemplary embodiment of the present disclosure, point cloud key frames of the laser radar 110 are extracted according to the collected pose trajectory of the combined inertial navigation device 120, and matching frames satisfying a certain condition around each key frame are extracted according to the relative pose change between the point cloud key frames, so as to obtain a key frame matching pair (Keyframe-pair) set of the whole area. The method is based on the assumption that the same local space laser point cloud sensed at different moments and positions has consistent spatial distribution characteristics, and the average distance between the nearest neighboring points between two frames is used as a measurement index for calibrating the reliability of parameters. On the basis of the initial values of the external parameters and the field search range which are given in advance, the method takes the nearest neighbor distance among all frames in the minimized Keyframe-pair set as a target, and obtains external parameter calibration results through a multi-scale hierarchical search and an alternating iterative search strategy of angle elements and line elements.
According to the technical scheme in the example embodiment, based on the assumption that the same local space laser point cloud sensed at different moments and positions has consistent spatial distribution characteristics, the balance of the search speed and the search granularity is realized through two parameter space search strategies of layering and alternate iteration of angle elements and line elements, and the accuracy and the robustness of a calibration result are guaranteed.
FIG. 2 illustrates a flow diagram of an external reference calibration method, according to some example embodiments of the present disclosure. The execution subject of the external reference calibration method provided by the embodiment of the disclosure may be a computing device with a computing processing function, such as a desktop computer or a server. The external reference calibration method includes steps S210 to S240, and the external reference calibration method in the example embodiment is described in detail below with reference to the drawings.
Referring to fig. 2, in step S210, a plurality of point cloud key frames of the lidar are extracted according to the collected pose trajectory of the combined inertial navigation.
In an example embodiment, the combined inertial navigation is a GNSS and an IMU. It should be noted that the combined inertial navigation system may also be in other suitable forms such as GPS and IMU, which is also within the scope of the present disclosure. The pose track data of the vehicle body is collected through the combined inertial navigation carried by the vehicle body, and the laser point cloud is collected through the laser radar carried by the vehicle body. For example, body positioning data is acquired via GNSS, acceleration and rotational motion data is acquired via IMU. And acquiring a point cloud key frame of the laser point cloud at corresponding time according to the time corresponding to the collected pose track of the combined inertial navigation.
Further, in an example embodiment, according to the collected pose trajectory of the combined inertial navigation, extracting a corresponding point cloud key frame of the lidar according to a predetermined condition, where the predetermined condition includes: the first frame or the last frame of the point cloud corresponding to the pose track is a key frame; the current frame which passes through the last key frame and has the accumulated track length larger than a preset length threshold value is a point cloud key frame; and the current frame with the variation of the yaw angle between the current frame and the last key frame being larger than the preset angle threshold value is a point cloud key frame.
In step S220, a plurality of key frame matching pairs are determined according to the relative pose information between the point cloud key frames.
In an example embodiment, because the same local space laser point cloud sensed at different moments and positions has consistent spatial distribution characteristics, two frames adjacent to each other in time are determined as a key frame matching pair according to the relative pose information between the key frames of the point cloud; and/or determining two frames adjacent in space as a key frame matching pair according to the relative pose information between the point cloud key frames.
In step S230, search arguments of respective hierarchies within a predetermined search range are determined through multi-hierarchy iterative search.
In an example embodiment, the search step length and the search range of the current level within the predetermined search range are determined by reducing the step length level by level; and determining the search external parameters corresponding to the current level based on the search step length and the search range of the current level.
For example, if the initial calibration parameter value is 20 and the initial search step is 10, the search range of the first level is [10, 30 ]; the search step size of the second level is 5, the search range is [5, 15], the search step size of the third level is 2.5, and the search range is [2.5, 7.5], and corresponding search external parameters are determined based on the search step size and the search range of each level.
In step S240, a distance between two keyframes in each keyframe matching pair corresponding to the search external parameters of each hierarchy is determined, and a calibration external parameter of the lidar and the combined inertial navigation is determined based on the distance.
In an example embodiment, the average distance of all nearest three-dimensional points between two key frames after coordinate transformation is determined based on current calibration parameters, a loss function corresponding to each key frame matching pair is determined based on the average distance, the loss function is an average distance measurement function of a target three-dimensional point between two key frames in the key frame matching pair, and calibration external parameters of the laser radar and the combined inertial navigation are determined based on the loss function.
In some exemplary embodiments, the same local spatial laser point cloud sensed based on different time and position has consistent spatial distribution characteristics, and on the basis of external parameter initial values and a domain search range which are given in advance, the external parameter calibration result is obtained by taking the minimum nearest neighbor distance among all frames in a key frame matching pair set as a target through multi-scale hierarchical search and an angle element and line element alternating iterative search strategy.
According to the technical scheme in the example embodiment of fig. 2, on one hand, point cloud key frames are extracted according to the pose track of the combined inertial navigation, a plurality of key frame matching pairs are determined according to the relative pose information between the point cloud key frames, and the key frames with consistent spatial distribution characteristics can be accurately acquired; on the other hand, search external parameters of all levels in a preset search range are determined through multi-level iterative search, and calibration external parameters of the laser radar and the combined inertial navigation are determined based on the distance between the key frames, so that the calibration external parameters have high calibration precision, the balance between the search speed and the search granularity is realized, and the accuracy and the robustness of a calibration result are guaranteed.
FIG. 3 shows a flow diagram of an external reference calibration method according to further example embodiments of the present disclosure.
Referring to fig. 3, in step S310, data acquisition is performed.
In an example embodiment, the point cloud data is collected by a lidar and the positioning data of the vehicle is collected by a combined inertial navigation, e.g., GNSS/IMU. In the calibration data acquisition process, two basic principles need to be followed, and firstly, the GNSS signals of an acquisition site are ensured to be good, so that the combined inertial navigation can acquire accurate pose information; secondly, the arrangement of the acquisition route should fully activate each angular axis and each movement direction as much as possible to obtain the effective constraint of each external parameter.
In an example embodiment, the data acquisition is performed with the following two acquisition schemes of fig. 4. As shown in fig. 4, the first acquisition scheme (a) is an 8-line scheme, the second acquisition scheme (b) is a cross-line scheme, and the clockwise and counterclockwise directions of the crossing loops should be opposite in the cross-line scheme.
In step S320, key frame extraction is performed.
In an example embodiment, after calibration data acquisition is completed, based on track pose information recorded by the combined inertial navigation, extraction of a laser point cloud key frame is performed according to the following three criteria, where a track recorded by the combined inertial navigation is set as S, and a current frame of the laser point cloud is set as fi: 1) if it is presentFrame fiThe first frame or the last frame of the track S is marked as a point cloud key frame as shown in the formula (1); 2) if the current frame fiAnd the last key frame kprevThe accumulated track length of the cross-over is greater than the length threshold thpathThen the frame is marked as a key frame as shown in formula (2); 3) if the current frame fiAnd the last key frame kprevThe variation of yaw angle yaw between is greater than the angle threshold thyawThen it is marked as a key frame, as shown in equation (3).
i＝1||i＝size(S) (1)
||path(fi,kprev)||>thpath (2)
||yaw(fi,kprev)||>thyaw (3)
Wherein size (S) is the total number of frames contained in the trace, and path (f)i,kprev) A function of cumulative track length metric passed between two frames, yaw (f)i,kprev) Is a function of the measure of the amount of yaw variation between two frames.
In step S330, a set of key frame matching pairs is constructed.
In an example embodiment, a set of Keyframe matching pairs (Keyframe-pair) is constructed from the relative pose information between the keyframes. The set of key frame matching pairs consists of two types of key frame matching pairs, Keyframe-pair. The first is temporally adjacent Keyframe-pair, and the second is spatially adjacent Keyframe-pair.
In an example embodiment, for the second class of Keyframe-pair, it should satisfy the following two conditions: one is the Euclidean distance dist (k) between two key framesi,kj) Less than threshold
As shown in the following formula (4); the second is the cumulative track length of two key frames | | | path (k)i,kj) | | is greater than a threshold value
As shown in formula (5).
In step S340, random sampling is performed to obtain a subset of matching pairs of keyframes.
In an example embodiment, before each iterative search, a certain proportion of Keyframe-pair is extracted from the key frame matching pair set in an equal probability random sampling manner to form a Keyframe-pair subset, and the extrinsic parameters which minimize the loss of the subset are searched out. Then, the results of each iteration are compared with each other with the goal of minimizing the loss of the Keyframe-pair corpus, and the extrinsic parameter which minimizes the loss of the Keyframe-pair corpus is screened as the final calibration result.
In step S350, a corner element multi-level search is performed.
In an example embodiment, the corner elements in the outer parameters are decoupled from the line elements and the 6 degree of freedom search range is reduced to two 3 degree of freedom search ranges by alternating iterative searches. For example, the line elements may be kept unchanged, and the diagonal elements may be searched iteratively in multiple levels.
In the search process of the angle element and the line element, a multi-scale coarse-to-fine hierarchical search strategy as shown in fig. 5 is adopted, as shown in fig. 5. Specifically, let the given initial calibration parameter value be θ0Initial search step size of thetaσAnd the set final calibration precision is thetaεThen, according to the present invention, the search range of the first level is [ theta ]0-θσ,θ0+θσ]Search step of thetaσIth (i)>1) The search range of the hierarchy is
The search step size is
When in use
The secondary hierarchical search is stopped. Referring to FIG. 5, the initial calibration parameter value is 20, the initial search step is 10, and the search range of the first level is [10, 30]](ii) a The search step size of the second level is 5, and the search range is [5, 15]]The search step size of the third level is 2.5, and the search range is [2.5, 7.5]]。
In step S360, a line element multi-level search is performed.
In an example embodiment, the corner elements are kept unchanged, and a multi-level iterative search is performed on the line elements. When the search step size is smaller than a predetermined angular precision threshold, the hierarchical search is stopped.
In step S370, it is determined whether the search is ended.
In an example embodiment, a loss function corresponding to a hierarchical search result is determined, and if the value of the loss function is smaller than a predetermined threshold, it is determined that the search is ended.
In an example embodiment, the optimal external parameter θ is performed by means of a parameter space search*And solving, namely combining the 6-degree-of-freedom external parameters with the minimum loss function value into the final target calibration parameters, as shown in the following formula (6).
Wherein P is the Keyframe-pair set obtained in the previous section, (k)i,kj) For a pair of key frames in the set, N is the total number of Keyframe-pair contained in the set P, Avg _ dist (k)i,kj) And performing coordinate transformation on the basis of the current calibration parameter theta to obtain an average distance measurement function of all nearest three-dimensional points between the two key frames.
In step S380, the calibration result is output.
According to the technical scheme in the example embodiment of fig. 3, on one hand, based on the assumption that the same local space laser point cloud sensed at different moments and positions has consistent spatial distribution characteristics, the balance between the search speed and the search granularity is realized through two parameter space search strategies of layering and alternate iteration, and the accuracy and robustness of the calibration result are guaranteed; on the other hand, the angle elements and the line elements in the external parameters are decoupled, the search range of 6 degrees of freedom is reduced into two search ranges of 3 degrees of freedom in an alternating iterative search mode, and high calibration precision can be obtained with fewer search times.
It is noted that the above-mentioned figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the present disclosure and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Embodiments of the disclosed apparatus are described below that may be used to perform the above-described external reference calibration method of the present disclosure.
Fig. 6 shows a schematic structural diagram of an external reference calibration apparatus according to an embodiment of the present disclosure.
Referring to fig. 6, there is provided an external reference calibration apparatus 600 for lidar and combined inertial navigation, where the apparatus 600 includes: a frame extraction module 610, configured to extract a plurality of point cloud key frames of the lidar according to the collected pose trajectory of the combined inertial navigation; a matching pair determining module 620, configured to determine a plurality of matching pairs of key frames according to the relative pose information between the point cloud key frames; a searching module 630, configured to determine, through multi-level iterative search, search arguments of respective levels within a predetermined search range; and the external parameter determining module 640 is configured to determine a distance between two key frames in each key frame matching pair corresponding to the search external parameters of each hierarchy, and determine the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
According to the second aspect, in some example embodiments, the search module 630 is further configured to: determining the search step length and the search range of the current level in the preset search range in a mode of reducing the step length layer by layer; and determining a search external parameter corresponding to the current level based on the search step length and the search range of the current level.
According to the second aspect, in some example embodiments, the multi-level iterative search is an alternating angular element and line element iterative search, and the search module 630 is further configured to: determining angle element search external parameters of each level in a predetermined angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a preset line element search range through line element multi-level iterative search.
According to the second aspect, in some example embodiments, the external parameter determination module 640 is further configured to: determining a loss function corresponding to each key frame matching pair based on the distance, wherein the loss function is an average distance measurement function of a target three-dimensional point between two key frames in the key frame matching pair; and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the loss function.
According to the second aspect, in some example embodiments, the frame extraction module 610 is further configured to: extracting a corresponding point cloud key frame of the laser radar according to a preset condition according to the collected pose track of the combined inertial navigation, wherein the preset condition comprises the following steps: the first frame or the last frame of the point cloud corresponding to the pose track is a key frame of the point cloud; the current frame which passes through the last key frame and has the accumulated track length larger than a preset length threshold value is a point cloud key frame; and the current frame with the variation of the yaw angle between the current frame and the last key frame being larger than the preset angle threshold value is a point cloud key frame.
According to the second aspect, in some example embodiments, the matching pair determination module 620 is further configured to: determining two frames which are adjacent in front and back in time as a key frame matching pair according to the relative pose information between the point cloud key frames; and/or determining two frames adjacent in space as a key frame matching pair according to the relative pose information between the point cloud key frames.
According to the second aspect, in some example embodiments, the apparatus 600 further comprises: and the sampling module is used for extracting a certain proportion of key frame matching pairs from the plurality of key frame matching pairs in an equal probability random sampling mode before searching to form a key frame matching pair subset so as to search the key frame matching pair subset.
Since the functional modules of the external reference calibration apparatus 600 of the exemplary embodiment of the present disclosure correspond to the steps of the exemplary embodiment of the external reference calibration method described above, for details that are not disclosed in the embodiment of the apparatus of the present disclosure, please refer to the embodiment of the external reference calibration method described above of the present disclosure.
It should be noted that although in the above detailed description several modules or units of the device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Moreover, although the steps of the methods of the present disclosure are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken into multiple step executions, etc.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer storage medium capable of implementing the above method. On which a program product capable of implementing the above-described method of the present specification is stored. In some possible embodiments, various aspects of the present disclosure may also be implemented in the form of a program product including program code for causing a terminal device to perform the steps according to various exemplary embodiments of the present disclosure described in the "exemplary methods" section above of this specification when the program product is run on the terminal device.
The program product may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present disclosure is not limited thereto, and in this document, a 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.
The program product described above may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, 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.
A computer readable signal medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable signal medium may also be any readable medium that is not a 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 readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Having described the methods, apparatus, and media of the exemplary embodiments of the present disclosure, a computing device in accordance with another exemplary embodiment of the present disclosure is next described.
As will be appreciated by one skilled in the art, aspects of the present disclosure may be embodied as a system, method or program product. Accordingly, various aspects of the present disclosure may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
In some possible embodiments, a computing device according to embodiments of the present disclosure may include at least one processor, and at least one memory. Wherein the memory stores program code that, when executed by the processor, causes the processor to perform the steps in the voice authentication method according to various exemplary embodiments of the present disclosure described in the "exemplary methods" section above in this specification. For example, the processor may perform the steps as shown in fig. 2: step S210, extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation; step S220, determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames; step S230, determining search external parameters of each hierarchy in a preset search range through multi-hierarchy iterative search; step S240, determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each hierarchy, and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
An electronic device 700 according to an example embodiment of the present disclosure is described below with reference to fig. 7. The electronic device 700 shown in fig. 7 is only an example and should not bring any limitations to the functionality and scope of use of the embodiments of the present disclosure.
As shown in fig. 7, electronic device 700 is embodied in the form of a general purpose computing device. The components of the electronic device 700 may include, but are not limited to: the at least one processing unit 710, the at least one memory unit 720, and a bus 730 that couples various system components including the memory unit 720 and the processing unit 710.
Bus 730 represents one or more of any of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.
The storage unit 720 may include a readable medium in the form of a volatile Memory, such as a RAM (Random Access Memory) 721 and/or a cache Memory 722, and may further include a ROM (Read-Only Memory) 723.
The storage unit 720 may also include a program/utility 725 having a set (at least one) of program modules 724, such program modules 724 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 700 may also communicate with one or more external devices 740 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 700, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 700 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 750. Also, the electronic device 700 may communicate with one or more networks (e.g., a local area network, a wide area network, and/or a public network, such as the Internet) via the network adapter 760. As shown, the network adapter 760 communicates with the other modules of the electronic device 700 via the bus 730. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 700, including but not limited to: microcode, device drivers, Redundant processing units, external disk drive Arrays, RAID (Redundant array of Independent Disks) systems, tape drives, and data backup storage systems, among others.
It should be noted that although in the above detailed description, several units or sub-units of the voice verification apparatus are mentioned, such division is merely exemplary and not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
Further, while the operations of the disclosed methods are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
While the spirit and principles of the present disclosure have been described with reference to several particular embodiments, it is to be understood that the present disclosure is not limited to the particular embodiments disclosed, nor is the division of aspects, which is for convenience only as the features in such aspects may not be combined to benefit. The disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (10)
1. An external reference calibration method for a laser radar and a combined inertial navigation is characterized by comprising the following steps:
extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation;
determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames;
determining search external parameters of each hierarchy in a preset search range through multi-hierarchy iterative search;
and determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each level, and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
2. The method of claim 1, wherein determining search arguments for respective levels within a predetermined search range via a multi-level iterative search comprises:
determining the search step length and the search range of the current level in the preset search range in a mode of reducing the step length layer by layer;
and determining a search external parameter corresponding to the current level based on the search step length and the search range of the current level.
3. The method according to claim 1 or 2, wherein the multi-level iterative search is an alternating iterative search of angle elements and line elements, and the determining search parameters of each level in the predetermined search range by the multi-level iterative search comprises:
determining angle element search external parameters of each level in a predetermined angle element search range through angle element multi-level iterative search; and
and determining line element search external parameters of each level in a preset line element search range through line element multi-level iterative search.
4. The method of claim 1, wherein determining a calibration external reference for the lidar and combined inertial navigation based on the distance comprises:
determining a loss function corresponding to each key frame matching pair based on the distance, wherein the loss function is an average distance measurement function of a target three-dimensional point between two key frames in the key frame matching pair;
and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the loss function.
5. The method of claim 1, wherein extracting a plurality of point cloud key frames of the lidar from the acquired pose trajectories of the combined inertial navigation comprises:
extracting a corresponding point cloud key frame of the laser radar according to a preset condition according to the collected pose track of the combined inertial navigation, wherein the preset condition comprises the following steps:
the first frame or the last frame of the point cloud corresponding to the pose track is a key frame of the point cloud;
the current frame which passes through the last key frame and has the accumulated track length larger than a preset length threshold value is a point cloud key frame;
and the current frame with the variation of the yaw angle between the current frame and the last key frame being larger than the preset angle threshold value is a point cloud key frame.
6. The method of claim 1, wherein determining a plurality of key frame matching pairs from relative pose information between the point cloud key frames comprises:
determining two frames which are adjacent in front and back in time as a key frame matching pair according to the relative pose information between the point cloud key frames; and/or the presence of a gas in the gas,
and determining two frames adjacent in space as a key frame matching pair according to the relative pose information between the point cloud key frames.
7. The method of claim 1, further comprising:
before searching, a certain proportion of key frame matching pairs are extracted from a plurality of key frame matching pairs in an equal probability random sampling mode to form a key frame matching pair subset so as to search the key frame matching pair subset.
8. An external reference calibration device for laser radar and combined inertial navigation is characterized by comprising:
the frame extraction module is used for extracting a plurality of point cloud key frames of the laser radar according to the collected pose track of the combined inertial navigation;
the matching pair determining module is used for determining a plurality of key frame matching pairs according to the relative pose information among the point cloud key frames;
the search module is used for determining search external parameters of each level in a preset search range through multi-level iterative search;
and the external parameter determining module is used for determining the distance between two key frames in each key frame matching pair corresponding to the search external parameters of each level and determining the calibration external parameters of the laser radar and the combined inertial navigation based on the distance.
9. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the extrinsic calibration method according to any one of claims 1 to 7.
10. An electronic device, comprising:
one or more processors;
storage means for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to carry out the extrinsic calibration method as claimed in any one of claims 1 to 7.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106996795A (en) * | 2016-01-22 | 2017-08-01 | 腾讯科技（深圳）有限公司 | Join scaling method and device outside a kind of vehicle-mounted laser |
| US20200041623A1 (en) * | 2018-02-05 | 2020-02-06 | Centre Interdisciplinaire De Developpement En Cartographie Des Oceans (Cidco) | METHOD AND APPARATUS FOR AUTOMATIC CALIBRATION OF MOBILE LiDAR SYSTEMS |
| CN110849362A (en) * | 2019-11-28 | 2020-02-28 | 湖南率为控制科技有限公司 | Laser radar and vision combined navigation algorithm based on vehicle-mounted inertia |
| US20210181745A1 (en) * | 2019-12-17 | 2021-06-17 | Motional Ad Llc | Automated object annotation using fused camera/lidar data points |
| CN113674399A (en) * | 2021-08-16 | 2021-11-19 | 杭州图灵视频科技有限公司 | Mobile robot indoor three-dimensional point cloud map construction method and system |
| CN113671530A (en) * | 2021-08-06 | 2021-11-19 | 北京京东乾石科技有限公司 | Pose determination method and device, storage medium and electronic equipment |
| CN113781582A (en) * | 2021-09-18 | 2021-12-10 | 四川大学 | Synchronous positioning and map creating method based on laser radar and inertial navigation combined calibration |
| CN113933818A (en) * | 2021-11-11 | 2022-01-14 | 阿波罗智能技术(北京)有限公司 | Method, device, storage medium and program product for calibrating laser radar external parameter |
| CN113985464A (en) * | 2021-11-01 | 2022-01-28 | 中国人民解放军火箭军工程大学 | Zero calibration method and system for vehicle-mounted satellite communication-in-motion |
-
2022
- 2022-03-11 CN CN202210238284.2A patent/CN114593751A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106996795A (en) * | 2016-01-22 | 2017-08-01 | 腾讯科技（深圳）有限公司 | Join scaling method and device outside a kind of vehicle-mounted laser |
| US20200041623A1 (en) * | 2018-02-05 | 2020-02-06 | Centre Interdisciplinaire De Developpement En Cartographie Des Oceans (Cidco) | METHOD AND APPARATUS FOR AUTOMATIC CALIBRATION OF MOBILE LiDAR SYSTEMS |
| CN110849362A (en) * | 2019-11-28 | 2020-02-28 | 湖南率为控制科技有限公司 | Laser radar and vision combined navigation algorithm based on vehicle-mounted inertia |
| US20210181745A1 (en) * | 2019-12-17 | 2021-06-17 | Motional Ad Llc | Automated object annotation using fused camera/lidar data points |
| CN113671530A (en) * | 2021-08-06 | 2021-11-19 | 北京京东乾石科技有限公司 | Pose determination method and device, storage medium and electronic equipment |
| CN113674399A (en) * | 2021-08-16 | 2021-11-19 | 杭州图灵视频科技有限公司 | Mobile robot indoor three-dimensional point cloud map construction method and system |
| CN113781582A (en) * | 2021-09-18 | 2021-12-10 | 四川大学 | Synchronous positioning and map creating method based on laser radar and inertial navigation combined calibration |
| CN113985464A (en) * | 2021-11-01 | 2022-01-28 | 中国人民解放军火箭军工程大学 | Zero calibration method and system for vehicle-mounted satellite communication-in-motion |
| CN113933818A (en) * | 2021-11-11 | 2022-01-14 | 阿波罗智能技术(北京)有限公司 | Method, device, storage medium and program product for calibrating laser radar external parameter |
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