CN114593751B - External parameter calibration method, device, medium and electronic equipment - Google Patents
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Abstract
The embodiment of the disclosure provides an external parameter calibration method, an external parameter calibration device, a 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 key frames of each point cloud; determining search external parameters of each level in a preset search range through multi-level 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 technical scheme of the embodiment of the disclosure, the calibration external parameters can have higher calibration precision, and the balance of the search speed and the search granularity is realized.
Description
Technical Field
The disclosure relates to the technical field of automatic driving, in particular to an external parameter calibration method, an external parameter calibration device, a computer readable medium and electronic equipment.
Background
In the field of autopilot, multi-line lidar and combined inertial navigation such as GNSS (Global Navigation SATELLITE SYSTEM )/IMU (Inertial Measurement Unit, inertial measurement unit) are commonly used sensor configurations in high-precision mapping, unmanned vehicle pose location, and point cloud object detection tasks. Therefore, the external parameter between the accurate calibration laser radar and the combined inertial navigation has important significance.
At present, in a technical scheme, a laser radar odometer or SLAM (Simultaneous Localization AND MAPPING, instant positioning and map building) technology is utilized to calculate the relative pose between frames of the multi-line laser radar, then pose information provided by combined inertial navigation is combined, and external parameter solving is carried out based on methods such as hand-eye calibration and the like.
However, in this technical solution, some prior assumptions or approximations need to be performed on the scene or pose information, and when the actual scene and the prior assumptions are different, the calibration accuracy is difficult to ensure.
It should be noted that the information disclosed in the above background section is only for enhancing 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 parameter calibration method, an external parameter calibration device, a computer readable medium, and an electronic apparatus, so as to obtain a calibrated external parameter with higher calibration accuracy at least to a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to a first aspect of embodiments of the present disclosure, there is provided a method for calibrating an external parameter of a lidar and combined inertial navigation, the method comprising: 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 level in a preset search range through multi-level 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 a first aspect, in some example embodiments, the determining search arguments for each level 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 level by level; 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 a first aspect, in some example embodiments, the multi-level iterative search is an alternating iterative search of corner elements and line elements, the determining search arguments for each level within a predetermined search range by the multi-level iterative search includes: determining angle element search external parameters of each level in a preset angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a predetermined line element search range through line element multi-level iterative search.
According to a first aspect, in some example embodiments, the determining calibration parameters of 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 a calibration external parameter of the laser radar and combined inertial navigation based on the loss function.
According to a first aspect, in some example embodiments, the extracting a plurality of point cloud keyframes of the lidar according to the collected pose trajectories of the combined inertial navigation includes: extracting a point cloud key frame of the corresponding 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 point cloud 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; the current frame with the variation of the navigation deviation 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 a first aspect, in some example embodiments, the determining a plurality of key frame matching pairs according to the relative pose information between the key frames of the point cloud includes: determining two frames adjacent to each other in time as key frame matching pairs according to the relative pose information among the key frames of the point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of the point cloud.
According to a 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 that the key frame matching pair subset is searched.
According to a second aspect of embodiments of the present disclosure, there is provided an external parameter calibration device of a lidar and combined inertial navigation, the device 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 tracks 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 a second aspect, in some example embodiments, the search module is further to: 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 level by level; 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 a second aspect, in some example embodiments, the multi-level iterative search is an alternating iterative search of corner elements and line elements, the search module further being for: determining angle element search external parameters of each level in a preset angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a predetermined line element search range through line element multi-level iterative search.
According to a second aspect, in some example embodiments, the extrinsic determination module is further 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 a calibration external parameter of the laser radar and combined inertial navigation based on the loss function.
According to a second aspect, in some example embodiments, the frame extraction module is further to: extracting a point cloud key frame of the corresponding 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 point cloud 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; the current frame with the variation of the navigation deviation 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 a second aspect, in some example embodiments, the matching pair determination module is further to: determining two frames adjacent to each other in time as key frame matching pairs according to the relative pose information among the key frames of the point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of the point cloud.
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, and forming a key frame matching pair set so as to search the key frame matching pair set.
According to a third aspect of the embodiments of the present disclosure, there is provided a computer readable medium having stored thereon a computer program which, when executed by a processor, implements the method of calibrating a parameter as described in the first aspect of the embodiments described above.
According to a fourth aspect of embodiments of the present disclosure, there is provided an electronic device, comprising: one or more processors; and the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the external parameter calibration method according to the first aspect of the embodiment.
The technical scheme provided by the embodiment of the disclosure can comprise the following beneficial effects:
In some embodiments of the present disclosure, on the one hand, a point cloud keyframe is extracted according to a pose track of combined inertial navigation, and a plurality of keyframe matching pairs are determined according to relative pose information between the point cloud keyframes, so that keyframes with consistent spatial distribution characteristics can be accurately acquired; on the other hand, the search external parameters of each level in the preset search range are determined through multi-level iterative search, and the calibration external parameters of the laser radar and the combined inertial navigation are determined based on the distance between key frames, so that the calibration external parameters have higher calibration precision, the balance of the search speed and the search granularity is realized, and the accuracy and the robustness of the calibration result are ensured.
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 disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort. In the drawings:
FIG. 1 shows a schematic diagram of an application scenario of a method for calibrating an external parameter in an exemplary embodiment of the present disclosure;
FIG. 2 illustrates a flow diagram of a method of extrinsic calibration according to some example embodiments of the present disclosure;
FIG. 3 illustrates a flow diagram of a method of calibrating an external parameter according to further example embodiments of the present disclosure;
FIG. 4 illustrates a schematic diagram of two data acquisition approaches in some example embodiments according to this disclosure;
FIG. 5 illustrates a schematic diagram of hierarchical iterative searching in some example embodiments according to this disclosure;
FIG. 6 shows a schematic structural diagram of an external reference calibration device 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. However, the exemplary embodiments may be embodied in many 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 the 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 disclosed aspects may be practiced without one or more of the specific details, or with other methods, components, devices, steps, etc. In other instances, well-known methods, devices, implementations, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams depicted in the figures are merely functional entities and do not necessarily correspond to physically separate entities. That is, the functional entities may be implemented in software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor devices and/or microcontroller devices.
The flow diagrams depicted in the figures are exemplary only, and do not necessarily include all of the elements and operations/steps, nor must they 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 order of actual execution may be changed according to actual situations.
In order to clearly illustrate the technical solutions in the embodiments of the present disclosure, before the embodiments of the present disclosure are specifically explained, some terms applied to the embodiments will be explained first.
The external parameter calibration method in the exemplary embodiments 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 according to some embodiments of the present disclosure.
Fig. 1 illustrates a schematic diagram of an application scenario provided according to 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 120 is horizontally placed directly under the laser to calculate the relative pose between the two.
In an example embodiment of the present disclosure, point cloud keyframes of the lidar 110 are extracted according to the collected pose tracks of the combined inertial navigation 120, and matching frames satisfying a certain condition around each keyframe are extracted according to the relative pose changes among the point cloud keyframes, so as to obtain a keyframe matching pair (Keyframe-pair) set of the whole area. The same local space laser point cloud perceived by different moments and positions has consistent space distribution characteristics, and the average distance of the nearest neighbors between two frames is used as a measurement index of the reliability of calibration parameters. Based on a preset external parameter initial value and a preset field searching range, taking the minimum Keyframe-pair set of all inter-frame nearest neighbor distances as targets, and obtaining an external parameter calibration result through multi-scale hierarchical searching and an angle element and line element alternating iterative searching strategy.
According to the technical scheme in the example embodiment, based on the assumption that the same local space laser point cloud perceived by different moments and positions has consistent space distribution characteristics, the balance of search speed and search granularity is realized through layering and alternate iteration of angle elements and line elements, and the accuracy and the robustness of a calibration result are ensured.
FIG. 2 illustrates a flow diagram of a method of extrinsic calibration according to some example embodiments of the present disclosure. The execution subject of the external parameter calibration method provided by the embodiment of the present disclosure may be a computing device having a computing processing function, such as a desktop computer or a server. The external parameter calibration method includes steps S210 to S240, and the external parameter calibration method in the exemplary embodiment is described in detail below with reference to the accompanying drawings.
Referring to fig. 2, in step S210, a plurality of point cloud keyframes of the lidar are extracted according to the collected pose tracks of the combined inertial navigation.
In an example embodiment, the combined inertial navigation is a GNSS and IMU. It should be noted that the combined inertial navigation may take other suitable forms, such as GPS and IMU, as well, which are 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, vehicle body positioning data is acquired by GNSS, and acceleration and rotational motion data is acquired by IMU. And acquiring a point cloud key frame of the laser point cloud at the corresponding time according to the time corresponding to the acquired pose track of the combined inertial navigation.
Further, in an example embodiment, according to the collected pose track of the combined inertial navigation, the point cloud keyframes of the corresponding lidar are extracted according to predetermined conditions, where the predetermined conditions include: 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; the current frame with the variation of the navigation deviation 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 key frames of each point cloud.
In the example embodiment, since the same local space laser point cloud perceived by different moments and positions has consistent space distribution characteristics, two frames adjacent to each other in time are determined as key frame matching pairs according to the relative pose information among key frames of each point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of each point cloud.
In step S230, search arguments for each level within the predetermined search range are determined by multi-level iterative search.
In an example embodiment, the search step size and the search range of the current level within the predetermined search range are determined by means of a level-by-level narrowing step size; 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.
For example, let the initial calibration parameter value be 20, and the initial search step be 10, the search range of the first level be [10, 30]; the second level has a search step size of 5, a search range of [5, 15], the third level has a search step size of 2.5, a search range of [2.5,7.5], and corresponding search external parameters are determined based on the search step sizes and the search ranges of the respective levels.
In step S240, a distance between two keyframes in each keyframe matching pair corresponding to the search extrinsic parameters of each hierarchy is determined, and a calibration extrinsic parameter of the lidar and the combined inertial navigation is determined based on the distance.
In an example embodiment, an average distance of all nearest three-dimensional points between two key frames after coordinate transformation is determined based on current calibration parameters, loss functions corresponding to each key frame matching pair are determined based on the average distance, the loss functions are average distance measurement functions of target three-dimensional points between two key frames in the key frame matching pair, and calibration external parameters of the laser radar and combined inertial navigation are determined based on the loss functions.
In some example embodiments, based on the fact that the same local space laser point cloud perceived by different moments and positions has consistent space distribution characteristics, on the basis of a preset external parameter initial value and a preset field searching range, the minimum key frame matching pair is used as a target for minimizing the nearest neighbor distance between all frames in the set, and external parameter calibration results are obtained through multi-scale hierarchical searching and an angle element and line element alternating iterative searching strategy.
According to the technical scheme in the example embodiment of fig. 2, on one hand, the point cloud keyframes are extracted according to the pose tracks of the combined inertial navigation, and a plurality of keyframe matching pairs are determined according to the relative pose information among the point cloud keyframes, so that the keyframes with consistent spatial distribution characteristics can be accurately acquired; on the other hand, the search external parameters of each level in the preset search range are determined through multi-level iterative search, and the calibration external parameters of the laser radar and the combined inertial navigation are determined based on the distance between key frames, so that the calibration external parameters have higher calibration precision, the balance of the search speed and the search granularity is realized, and the accuracy and the robustness of the calibration result are ensured.
FIG. 3 shows a flow diagram of a method of calibrating an external parameter according to further example embodiments of the present disclosure.
Referring to fig. 3, in step S310, data acquisition is performed.
In an example embodiment, point cloud data is acquired by lidar and positioning data of the vehicle is acquired by combined inertial navigation, such as GNSS/IMU. In the process of calibration data acquisition, two basic principles need to be followed, namely, the acquisition site GNSS signals are guaranteed to be good, so that the combined inertial navigation can acquire accurate pose information; secondly, the arrangement of the acquisition route should enable each angular axis and each movement direction to be fully activated as much as possible so as to obtain effective constraint of each external parameter.
In an example embodiment, data acquisition is performed by the following two acquisition schemes of FIG. 4. As shown in fig. 4, the first acquisition scheme (a) is an 8-way scheme, the second acquisition scheme (b) is a cross-way scheme, and the clockwise and counterclockwise directions of the two crossing loops are opposite in the cross-way scheme.
In step S320, key frame extraction is performed.
In an example embodiment, after calibration data acquisition is completed, based on track pose information of the combined inertial navigation record, laser point cloud key frame extraction is performed according to the following three criteria, and the track of the combined inertial navigation record is set as S, and the current frame of the laser point cloud is set as f i: 1) If the current frame f i is the first frame or the last frame of the track S, marking the current frame as a point cloud key frame as shown in a formula (1); 2) If the accumulated track length passing between the current frame f i and the last key frame k prev is greater than the length threshold th path, the accumulated track length is recorded as a key frame, as shown in formula (2); 3) If the variation of the yaw angle yaw between the current frame f i and the previous key frame k prev is greater than the angle threshold th yaw, the key frame is recorded as a key frame, as shown in the formula (3).
i＝1||i＝size(S) (1)
||path(fi,kprev)||>thpath (2)
||yaw(fi,kprev)||>thyaw (3)
Where size (S) is the total number of frames contained in the track, path (f i,kprev) is the cumulative track length measure function passed between two frames, and yaw (f i,kprev) is the yaw angle variation measure function between two frames.
In step S330, a set of key frame matching pairs is constructed.
In an example embodiment, a set of key frame matching pairs (Keyframe-pairs) is constructed from relative pose information between key frames. The keyframe matching pair set consists of two types of keyframe matching pairs Keyframe-pairs. The first is a Keyframe-pair that is temporally contiguous and the second is a Keyframe-pair that is spatially contiguous.
In an example embodiment, for the second class Keyframe-pair, it should satisfy the following two conditions: one is that the Euclidean distance dist (k i,kj) between two key frames is less than the thresholdThe following formula (4); the second is that the cumulative track length between two key frames is greater than the threshold/>, path (k i,kj)As shown in formula (5).
In step S340, random sampling is performed to obtain a key frame matching pair.
In an example embodiment, a proportion Keyframe of the pair components Keyframe-pair subset is extracted from the set of key frame matching pairs in an equi-probability random sampling manner prior to each iterative search, and outliers are searched that minimize the subset loss. Thereafter, the iteration results are compared with the aim of minimizing the Keyframe-pair corpus loss, and the external parameters minimizing the Keyframe-pair corpus loss are screened as final calibration results.
In step S350, a multi-level search of corner elements 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 means of an alternating iterative search. For example, the line elements may be kept unchanged, and a multi-level iterative search may be performed on the diagonal elements.
In the searching process of the angle element and the line element, a multi-scale coarse-to-fine hierarchical searching strategy shown in fig. 5 is adopted, and the hierarchical searching strategy is shown in fig. 5. Specifically, if a given initial calibration parameter value is θ 0, an initial search step length is θ σ, and a final calibration accuracy is θ ε, according to the present invention, the search range of the first level is [ θ 0-θσ,θ0+θσ ], the search step length is θ σ, and the search range of the i (i > 1) th level isSearch step size is/>When/>The sub-level search is stopped. Referring to fig. 5, the initial calibration parameter value is 20, the initial search step length is 10, and the search range of the first level is [10, 30]; the search step length of the second level is 5, the search range is [5, 15], the search step length 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 angle element is kept unchanged, and a multi-level iterative search is performed on the line element. The hierarchical search is stopped when the search step size is less than a predetermined angle accuracy threshold.
In step S370, it is determined whether the search is ended.
In an example embodiment, a loss function corresponding to the hierarchical search result is determined, and if the value of the loss function is smaller than a predetermined threshold, the search is determined to be ended.
In an example embodiment, the optimal extrinsic parameters θ * are solved by using a parameter space searching method, that is, the 6-degree-of-freedom extrinsic parameters with the minimum loss function value are combined into a final target calibration parameter, as shown in the following formula (6).
Wherein P is Keyframe-pair set obtained in the previous section, (k i,kj) is a pair of key frames in the set, N is the total number of Keyframe-pairs contained in the set P, and Avg_dist (k i,kj) is an average distance measurement function of all nearest three-dimensional points between two key frames after coordinate transformation based on the current calibration parameter theta.
In step S380, a 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 perceived by different moments and positions has consistent space distribution characteristics, the balance of search speed and search granularity is realized through layering and alternate iteration of two parameter space search strategies, and the accuracy and robustness of a calibration result are ensured; on the other hand, the angular elements and the line elements in the external parameters are decoupled, and the search range with 6 degrees of freedom is reduced to be two search ranges with 3 degrees of freedom in an alternate iterative search mode, so that higher calibration precision can be obtained with fewer search times.
It is noted that the above-described figures are merely schematic illustrations of processes involved in a method according to exemplary embodiments of the present disclosure, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
The following describes embodiments of the apparatus of the present disclosure that may be used to perform the above-described external parameter calibration methods of the present disclosure.
FIG. 6 shows a schematic structural diagram of an external parameter calibration device according to an embodiment of the present disclosure.
Referring to fig. 6, there is provided a laser radar and combined inertial navigation external reference calibration apparatus 600, the apparatus 600 comprising: a frame extraction module 610, configured to extract a plurality of point cloud keyframes of the lidar according to the collected pose track of the combined inertial navigation; a matching pair determining module 620, configured to determine a plurality of key frame matching pairs according to the relative pose information between the key frames of the point cloud; a search module 630, configured to determine search arguments of each level within a predetermined search range through multi-level iterative search; and the external parameter determining module 640 is used for determining the distance between two key frames in each key frame matching pair corresponding to each level of search external parameters, and determining the calibrated external parameters of the laser radar and the combined inertial navigation based on the distance.
According to a second aspect, in some example embodiments, the search module 630 is further to: 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 level by level; 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 a second aspect, in some example embodiments, the multi-level iterative search is an alternating iterative search of corner elements and line elements, the search module 630 further being configured to: determining angle element search external parameters of each level in a preset angle element search range through angle element multi-level iterative search; and determining line element search external parameters of each level in a predetermined line element search range through line element multi-level iterative search.
According to a second aspect, in some example embodiments, the extrinsic 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 a calibration external parameter of the laser radar and combined inertial navigation based on the loss function.
According to a second aspect, in some example embodiments, the frame extraction module 610 is further configured to: extracting a point cloud key frame of the corresponding 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 point cloud 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; the current frame with the variation of the navigation deviation 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 a second aspect, in some example embodiments, the matching pair determination module 620 is further configured to: determining two frames adjacent to each other in time as key frame matching pairs according to the relative pose information among the key frames of the point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of the point cloud.
According to a 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, and forming a key frame matching pair set so as to search the key frame matching pair set.
Since each functional module of the external reference calibration device 600 of the exemplary embodiment of the present disclosure corresponds to a step of the exemplary embodiment of the external reference calibration method described above, for details not disclosed in the embodiment of the device of the present disclosure, please refer to the embodiment of the external reference calibration method described above in the present disclosure.
It should be noted that although in the above detailed description several modules or units of a 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 in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order, or that all illustrated steps be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, 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 (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer storage medium capable of implementing the above method is also provided. On which a program product is stored which enables the implementation of the method described above in the present specification. In some possible embodiments, the various aspects of the present disclosure may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the disclosure as described in the "exemplary methods" section of this specification, when the program product is run on the terminal device.
The program product may take the form of a portable compact disc read-only memory (CD-ROM) and comprises 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 take the form of any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is 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 (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with 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 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 of 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, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, 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., connected via the Internet using an Internet service provider).
Having described the methods, apparatus, and media of exemplary embodiments of the present disclosure, next, a computing device according to another exemplary embodiment of the present disclosure is described.
Those skilled in the art will appreciate that the various aspects of the present disclosure may be implemented as a system, method, or program product. Accordingly, various aspects of the disclosure may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may 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 verification method according to various exemplary embodiments of the present disclosure described in the above section of the "exemplary method" of the present 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 tracks of the combined inertial navigation; step S220, determining a plurality of key frame matching pairs according to the relative pose information among the key frames of each point cloud; step S230, determining search external parameters of each level in a preset search range through multi-level 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 level, 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 merely an example and should not be construed as limiting the functionality and scope of use of the disclosed embodiments.
As shown in fig. 7, the electronic device 700 is embodied in the form of a general purpose computing device. Components of 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 connecting the different system components, including the memory unit 720 and the processing unit 710.
Bus 730 represents one or more 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 or some combination of which may include 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.), one or more devices that enable a user to interact with the electronic device 700, and/or any device (e.g., router, modem, etc.) that enables the electronic device 700 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 750. Also, electronic device 700 may communicate with one or more networks such as a local area network, a wide area network, and/or a public network such as the Internet through network adapter 760. As shown, network adapter 760 communicates with other modules of electronic device 700 over bus 730. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 700, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID (Redundant Arrays of INDEPENDENT DISKS, redundant array of independent disks) systems, tape drives, data backup storage systems, and the like.
It should be noted that although several units or sub-units of the voice verification apparatus are mentioned in the above detailed description, this 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 in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the operations of the methods of the present disclosure are depicted in the drawings in a particular order, this is not required or suggested that these operations must be performed in this particular order or that all of the illustrated operations must be performed in order to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform.
While the spirit and principles of the present disclosure have been described with reference to several particular embodiments, it is to be understood that this disclosure is not limited to the particular embodiments disclosed nor does it imply that features in these aspects are not to be combined to benefit from this division, which is done for convenience of description only. The disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.
Claims (7)
1. The external parameter calibration method for the laser radar and the combined inertial navigation is characterized by comprising the following steps of:
extracting a point cloud key frame of the corresponding 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 point cloud 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; the current frame with the variation of the navigation deflection angle between the current frame and the previous key frame being larger than a preset angle threshold value is a point cloud key frame;
Determining two frames adjacent to each other in time as key frame matching pairs according to the relative pose information among the key frames of the point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of the point cloud;
keeping line elements unchanged, and determining angle element search external parameters of each level in a preset angle element search range through angle element multi-level iterative search; and maintaining the angle element unchanged, and determining line element search external parameters of each level in a predetermined line element search range through line element multi-level 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 each level within a predetermined search range by a multi-level iterative search comprises:
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 level by level;
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 of claim 1, wherein the determining a calibration external parameter of 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 a calibration external parameter of the laser radar and combined inertial navigation based on the loss function.
4. The method according to claim 1, wherein 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 that the key frame matching pair subset is searched.
5. An external parameter calibration device for laser radar and combined inertial navigation, which is characterized by comprising:
The frame extraction module is used for extracting the point cloud key frame of the corresponding laser radar according to the acquired 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 point cloud 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; the current frame with the variation of the navigation deflection angle between the current frame and the previous key frame being larger than a preset angle threshold value is a point cloud key frame;
The matching pair determining module is used for determining two frames which are adjacent to each other in time as key frame matching pairs according to the relative pose information among the key frames of the point cloud; and/or determining two frames which are adjacent in space as key frame matching pairs according to the relative pose information among the key frames of the point cloud;
the searching module is used for keeping the line elements unchanged, and determining angle element searching external parameters of each level in a preset angle element searching range through angle element multi-level iterative searching; and maintaining the angle element unchanged, and determining line element search external parameters of each level in a predetermined line element search range through line element 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.
6. A computer readable medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the external parameter calibration method according to any one of claims 1 to 4.
7. 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 implement the method of external parameter calibration as claimed in any one of claims 1 to 4.
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