CN116105716A - High-precision map heterogeneous information synchronization method and device and electronic equipment - Google Patents

High-precision map heterogeneous information synchronization method and device and electronic equipment Download PDF

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CN116105716A
CN116105716A CN202310110069.9A CN202310110069A CN116105716A CN 116105716 A CN116105716 A CN 116105716A CN 202310110069 A CN202310110069 A CN 202310110069A CN 116105716 A CN116105716 A CN 116105716A
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gnss
data
speed
sampling data
group
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陈胜通
王涛
石磊
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Zhejiang Geely Holding Group Co Ltd
Ningbo Geely Automobile Research and Development Co Ltd
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Zhejiang Geely Holding Group Co Ltd
Ningbo Geely Automobile Research and Development Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/005—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 with correlation of navigation data from several sources, e.g. map or contour matching
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/38—Electronic maps specially adapted for navigation; Updating thereof
    • G01C21/3804—Creation or updating of map data
    • G01C21/3833—Creation or updating of map data characterised by the source of data
    • G01C21/3848—Data obtained from both position sensors and additional sensors
    • 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
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position

Abstract

The application relates to a high-precision map heterogeneous information synchronization method and device and electronic equipment. The method comprises the following steps: based on GNSS data and VO data of a global positioning navigation system of a vehicle, a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data are obtained respectively; sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve; analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain the time offset between the GNSS data and the VO data; and synchronizing the GNSS data and the VO data according to the time offset. Based on the method, synchronization of the GNSS data time stamp and the VO data time stamp can be achieved, synchronization time consumption is reduced, and synchronization efficiency is improved.

Description

High-precision map heterogeneous information synchronization method and device and electronic equipment
Technical Field
The application relates to the technical field of intelligent driving, in particular to a high-precision map heterologous information synchronization method and device and electronic equipment.
Background
Visual Odometer (VO) is a common method for dealing with positioning problems of mobile devices equipped with Visual sensors, and is widely used in the fields of autopilot, mobile robots, AR (augmented reality)/VR (virtual reality) and the like. The visual odometer can be used for reconstruction of high-precision maps in intelligent driving. The map reconstructed by the camera and the sensor such as IMU (Inertial Measurement Unit ) often needs to be fused with GNSS (Global Navigation Satellite System ) data to obtain the absolute position and scale of the map. However, the accuracy of the reconstructed high-precision map is often directly affected by different sources of map data and GNSS data reconstructed by the camera and the sensor such as the IMU, and by asynchronous time stamps.
Disclosure of Invention
The application provides a high-precision map heterogeneous information synchronization method, device and electronic equipment, which are used for realizing synchronization of GNSS data time stamps and VO data time stamps, reducing synchronization time consumption and improving synchronization efficiency.
In a first aspect, the present application provides a high-precision map heterologous synchronization method, the method comprising:
based on GNSS data of a global positioning navigation system of a vehicle and VO data of a visual odometer, a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data are respectively obtained;
sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve, wherein N is an integer greater than 1;
analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain time offset between the GNSS data and the VO data, wherein the time offset represents time deviation between the GNSS speed curve and the VO speed curve;
and synchronizing the GNSS data and the VO data according to the time offset.
In one possible design, the obtaining, by the vehicle-based global positioning navigation system GNSS data and the visual odometer VO data, a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data respectively includes: acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of the vehicle; according to the GNSS three-dimensional position, the VO three-dimensional position and the moments, calculating GNSS instantaneous speeds of the GNSS receiver at the moments and VO instantaneous speeds of the VO camera optical center at the moments; the GNSS speed curve is obtained according to the GNSS instantaneous speeds at all the moments, and the VO instantaneous speeds at all the moments are obtained.
In one possible design, the sampling the GNSS speed curve and the VO speed curve for N times respectively, to obtain N sets of GNSS speed sampling data corresponding to the GNSS speed curve and N sets of VO speed sampling data corresponding to the VO speed curve, includes: respectively acquiring a preset number of speed data from the GNSS speed curve and the VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of VO speed sampling data corresponding to the VO speed curve; taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, respectively carrying out downsampling according to preset multiples based on the GNSS original sampling data and the VO original sampling data for N-1 times to obtain the GNSS speed sampling data of the N groups and the VO speed sampling data of the N groups, wherein the quantity of the GNSS speed sampling data of each group in the GNSS speed sampling data of the N groups is sequentially reduced from the preset quantity of the GNSS speed sampling data of the 1 st group, and the quantity of the VO speed sampling data of each group in the VO speed sampling data of the N groups is sequentially reduced from the preset quantity of the VO speed sampling data of the 1 st group.
In one possible design, the analyzing correlations between the N sets of GNSS speed sample data and the N sets of VO speed sample data to obtain a time offset between the GNSS data and the VO data includes: analyzing the correlation between the N group of GNSS speed sampling data and the N group of VO speed sampling data from a first preset offset, and obtaining an actual first time offset between the N group of GNSS speed sampling data and the N group of VO speed sampling data; dividing the actual first time offset by the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data to obtain a second preset offset, and analyzing the correlation between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data from the second preset offset to obtain the actual second time offset between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data; and until the actual N time offset between the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group is obtained through analysis, taking the actual N time offset as the time offset.
In one possible design, the synchronizing the GNSS data and the VO data according to the time offset includes: adding or subtracting the time offset to or from the time stamp of the GNSS data, and synchronizing the time stamp of the GNSS data with the time stamp of the VO data; or adding or subtracting the time offset to or from the time stamp of the VO data, and synchronizing the time stamp of the GNSS data and the time stamp of the VO data.
In a second aspect, the present application provides a high-precision map heterologous information synchronization device, the device comprising:
the acquisition module is used for respectively obtaining a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data based on the GNSS data of the vehicle and the VO data of the visual odometer;
the sampling module is used for sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve, wherein N is an integer greater than 1;
the analysis module is used for analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain time offset between the GNSS data and the VO data, wherein the time offset represents the time offset between the GNSS speed curve and the VO speed curve;
and the synchronization module is used for synchronizing the GNSS data and the VO data according to the time offset.
In one possible design, the acquisition module is specifically configured to: acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of the vehicle; according to the GNSS three-dimensional position, the VO three-dimensional position and the moments, calculating GNSS instantaneous speeds of the GNSS receiver at the moments and VO instantaneous speeds of the VO camera optical center at the moments; the GNSS speed curve is obtained according to the GNSS instantaneous speeds at all the moments, and the VO instantaneous speeds at all the moments are obtained.
In one possible design, the sampling module is specifically configured to: respectively acquiring a preset number of speed data from the GNSS speed curve and the VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of VO speed sampling data corresponding to the VO speed curve; taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, respectively downsampling the GNSS original sampling data and the VO original sampling data for N-1 times according to preset multiples to obtain the GNSS speed sampling data of the N groups and the VO speed sampling data of the N groups, wherein the quantity of the GNSS speed sampling data of each group in the GNSS speed sampling data of the N groups is sequentially reduced from the preset quantity of the GNSS speed sampling data of the 1 st group, and the quantity of the VO speed sampling data of each group in the VO speed sampling data of the N groups is sequentially reduced from the preset quantity of the VO speed sampling data of the 1 st group.
In one possible design, the analysis module is specifically configured to: analyzing the correlation between the N group of GNSS speed sampling data and the N group of VO speed sampling data from a first preset offset, and obtaining an actual first time offset between the N group of GNSS speed sampling data and the N group of VO speed sampling data; dividing the actual first time offset by the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data to obtain a second preset offset, and analyzing the correlation between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data from the second preset offset to obtain the actual second time offset between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data; and until the actual N time offset between the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group is obtained through analysis, taking the actual N time offset as the time offset.
In one possible design, the synchronization module is specifically configured to: adding or subtracting the time offset to or from the time stamp of the GNSS data, and synchronizing the time stamp of the GNSS data with the time stamp of the VO data; or adding or subtracting the time offset to or from the time stamp of the VO data, and synchronizing the time stamp of the GNSS data and the time stamp of the VO data.
In a third aspect, the present application provides an electronic device, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the high-precision map heterogeneous information synchronization method when executing the computer program stored in the memory.
In a fourth aspect, the present application provides a computer readable storage medium having a computer program stored therein, which when executed by a processor, implements a high-precision map heterologous information synchronization method step as described above.
The technical effects of each of the second to fourth aspects and the technical effects that may be achieved by each aspect are referred to above for the technical effects that may be achieved by the first aspect or each possible aspect in the first aspect, and the detailed description is not repeated here.
Drawings
Fig. 1 is a flowchart of a high-precision map heterologous information synchronization method provided in the present application;
fig. 2 is a schematic diagram of a high-precision map heterogeneous information synchronization device provided in the present application;
fig. 3 is a schematic diagram of a structure of an electronic device provided in the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings. The specific method of operation in the method embodiment may also be applied to the device embodiment or the system embodiment.
In the description of the present application "a plurality of" is understood as "at least two". "and/or", describes an association relationship of an association object, and indicates that there may be three relationships, for example, a and/or B, and may indicate: a exists alone, A and B exist together, and B exists alone. A is connected with B, and can be represented as follows: both cases of direct connection of A and B and connection of A and B through C. In addition, in the description of the present application, the words "first," "second," and the like are used merely for distinguishing between the descriptions and not be construed as indicating or implying a relative importance or order.
Referring to fig. 1, a flow chart of a high-precision map heterogeneous information synchronization method provided in an embodiment of the present application is shown, and a specific implementation flow of the method is as follows:
step 101: based on GNSS data and VO data of a global positioning navigation system of a vehicle, a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data are obtained respectively;
in the embodiment of the application, a GNSS receiver and a visual odometer camera are installed on a vehicle. Acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of a vehicle; and according to the GNSS three-dimensional position, the VO three-dimensional position and each moment, calculating the GNSS instantaneous speed of the GNSS receiver at each moment and the VO instantaneous speed of the VO camera optical center at each moment.
Concrete embodimentsThe calculation formula of the instantaneous speed is as follows: v= ||p ti+1 -p ti ||/(t i+1 -t i ) Wherein p is ti At t i 3D position of time, p ti+1 At t i+1 3D position of time of day.
After obtaining the GNSS instantaneous speed of the GNSS receiver at each moment and the VO instantaneous speed of the VO camera optical center at each moment, obtaining a GNSS speed curve according to the GNSS instantaneous speed at each moment, and obtaining a VO speed curve according to the VO instantaneous speed at each moment.
For example, a speed schedule of a GNSS may be constructed from GNSS instantaneous speeds of a GNSS receiver at various times as shown in Table 1 below; the velocity schedule of the VO at each instant in time from the VO camera's optical center can be constructed as shown in table 2 below.
Figure BDA0004076492010000071
TABLE 1
Figure BDA0004076492010000072
TABLE 2
In this embodiment of the present application, a corresponding GNSS speed profile may be obtained according to the speed schedule of the GNSS, and a corresponding VO speed profile may be obtained according to the speed schedule of the VO.
Step 102: sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve;
in the embodiment of the present application, N is an integer greater than 1, and the sampling manner of the GNSS speed curve and the VO speed curve may be downsampling.
Specifically, firstly, respectively acquiring a preset number of speed data of a GNSS speed curve and a VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of speed sampling data corresponding to the VO speed curve.
For example, 240 GNSS speed data are collected on the GNSS speed curve, and the time stamps of the collected 240 GNSS speed data are 1ms, 3ms, 5ms, 7ms, and 9ms … …, respectively, and the 240 VO speed data are also collected on the VO speed curve, and the time stamps of the collected 240 VO speed data are 1ms, 3ms, 5ms, 7ms, and 9ms … …. The 240 GNSS velocity data form group 1 GNSS velocity sample data, and the 240 VO velocity data form group 1 VO velocity sample data.
After obtaining the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group, taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, and respectively carrying out downsampling for N-1 times according to a preset multiple based on the GNSS original sampling data and the VO original sampling data to obtain N groups of GNSS speed sampling data and N groups of VO speed sampling data. In this embodiment of the present application, the number of each set of GNSS speed sample data in the N sets of GNSS speed sample data decreases sequentially from the preset number of the 1 st set of GNSS speed sample data, and the number of each set of VO speed sample data in the N sets of VO speed sample data decreases sequentially from the preset number of the 1 st set of VO speed sample data.
Specifically, based on the original GNSS sample data (i.e., the 1 st set of GNSS speed sample data), the first downsampling is performed to obtain the 2 nd set of GNSS speed sample data, the number of the 2 nd set of GNSS speed sample data is 1/m of the number (preset number) of the 1 st set of GNSS speed sample data, and m is an integer greater than 1. And performing second downsampling based on the GNSS original sampling data to obtain the GNSS speed sampling data of the 3 rd group, wherein the number of the GNSS speed sampling data of the 3 rd group is 1/m of the number of the GNSS speed sampling data of the 2 nd group. And continuing to perform downsampling based on the GNSS original sampling data until the downsampling is performed for N-1 times to obtain N groups of GNSS speed sampling data.
For example, if the number of the GNSS speed sample data of the 1 st set is 240, based on the GNSS speed sample data of the 1 st set, 240× (1/2) =120 speed sample data is resampled as the GNSS speed sample data of the 2 nd set; resampling 120× (1/2) =60 speed sample data based on the group 1 GNSS speed sample data as group 3 GNSS speed sample data; and continuing to sample until sampling is carried out for 4 times, and finally obtaining 5 groups of GNSS speed sampling data.
Similarly, based on the original VO sampling data (i.e. the 1 st group of VO speed sampling data), performing first downsampling to obtain the 2 nd group of VO speed sampling data, wherein the number of the 2 nd group of VO speed sampling data is 1/m of the number (preset number) of the 1 st group of VO speed sampling data. And performing second downsampling based on the VO original sampling data to obtain 3 groups of VO speed sampling data, wherein the number of the 3 groups of VO speed sampling data is 1/m of the number of the 2 groups of VO speed sampling data. And continuing downsampling based on the VO original sampling data until sampling is performed for N-1 times, so as to obtain N groups of VO speed sampling data.
In the embodiment of the application, when the downsampling is performed based on the original sampled data (including the GNSS original sampled data and the OV original sampled data), interpolation and resampling are required to be performed in the original sampled data, and in order to ensure the downsampling accuracy, each interpolation is performed on the original sampled data. For example, the original sampled data are instantaneous speeds corresponding to time stamps of 1ms, 3ms, 5ms, 7ms, 9ms and 11ms respectively, downsampling is performed based on the original sampled data, the instantaneous speeds corresponding to the acquisition time stamps of 3ms, 6ms and 9ms respectively are required, and the instantaneous speed of 6ms does not exist in the original acquired data, and the instantaneous speed of 6ms is obtained through the instantaneous speed corresponding to 5ms and the instantaneous speed corresponding to 7ms in the original acquired data, so that the 2 nd group of sampled data is obtained.
It should be noted that the GNSS speed sampling data and the VO speed sampling data with the same sequence number group number have the same time stamp. For example, the time stamps of the group 1 GNSS speed sampling data are 1ms, 4ms, 7ms, 10ms, 13ms, 16ms, 19ms, and 22ms, respectively, and the time stamps of the group 1 VO speed sampling data are 1ms, 4ms, 7ms, 10ms, 13ms, 16ms, 19ms, and 22ms, respectively; the time stamps of the group 2 GNSS speed sample data are respectively 4ms, 10ms, 16ms and 22ms, and the time stamps of the group 2 VO speed sample data are respectively 4ms, 10ms, 16ms and 22ms.
Step 103: analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain the time offset between the GNSS data and the VO data;
in the embodiment of the application, the time offset represents the time deviation between the GNSS speed profile and the VO speed profile.
In this embodiment of the present application, the correlation between the nth set of GNSS speed sample data and the nth set of VO speed sample data is analyzed from the first preset offset bit, so as to obtain an actual first time offset between the nth set of GNSS speed sample data and the nth set of VO speed sample data.
Specifically, the correlation is analyzed starting from the group with the least number of N groups of velocity sample data, i.e. the correlation between the nth group of GNSS velocity sample data and the nth group of VO velocity sample data is analyzed first. Starting from a first preset offset bit, for example, starting from bit 0, the correlation between the nth set of GNSS speed sampling data and the nth set of VO speed sampling data is analyzed one by one, and the result of multiplying the offset step corresponding to the highest correlation coefficient by the time stamp interval between each adjacent nth set of speed sampling data is used as the actual first time offset between the nth set of GNSS speed sampling data and the nth set of VO speed sampling data.
For example, if the time stamp interval between each adjacent sample data is 4ms and the first preset offset is 0, the correlation between the nth set of GNSS speed sample data and the nth set of VO speed sample data is analyzed from the 0 th bit as shown in table 3 below.
Figure BDA0004076492010000101
TABLE 3 Table 3
When the offset step length of the nth set of GNSS speed sample data is-1, i.e. the nth set of GNSS speed sample data is shifted left by 1 step, the speed sequence of the nth set of GNSS speed sample data at 1ms, 5ms, 9ms, 13ms becomes 1, 2, 1, and is the same as the speed sequence of the nth set of VO speed sample data at 1ms, 5ms, 9ms, 13ms of 1, 2, 1, as shown in table 4 below, at this time, the correlation between the nth set of GNSS speed sample data and the nth set of VO speed sample data is the highest, so that the actual first time offset between the nth set of GNSS speed sample data and the nth set of VO speed sample data is the time stamp interval multiplied by the offset step length: 4ms× (-1) = -4ms.
Figure BDA0004076492010000102
TABLE 4 Table 4
When the actual first time offset is obtained, dividing the actual first time offset by the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data to obtain a second preset offset, for example, the actual first time offset is-4 ms, and the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data is 2ms, then the second preset offset is: -4 ms/2 ms= -2. And starting from the second preset offset, analyzing the correlation between the GNSS speed sampling data of the N-1 group and the VO speed sampling data of the N-1 group to obtain the actual second time offset between the GNSS speed sampling data of the N-1 group and the VO speed sampling data of the N-1 group.
According to the analysis mode, until the actual N time offset between the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group is obtained through analysis, the actual N time offset is taken as the time offset.
Step 104: and synchronizing the GNSS data and the VO data according to the time offset.
In the embodiment of the application, after obtaining the time offset, adding or subtracting the time offset to or from the time stamp of the GNSS data, and synchronizing the time stamp of the GNSS data and the time stamp of the VO data; alternatively, the time offset is added to or subtracted from the time stamp of the VO data, and the time stamp of the GNSS data and the time stamp of the VO data are synchronized.
In summary, the sampling method can ensure the sampling precision and the accuracy of the sampling data by respectively downsampling the GNSS speed data and the VO speed data for N times according to a preset multiple to obtain N groups of GNSS speed sampling data and N groups of VO speed data with the same time stamp in each group; the correlation between each sampling data set is analyzed in sequence from the sampling data set with the minimum number, and finally the time offset between the GNSS speed data and the VO speed data is obtained, so that the GNSS data and the VO data are synchronized based on the time offset.
Based on the same inventive concept, the present application further provides a high-precision map heterogeneous information synchronization device, which is used for implementing synchronization of a GNSS data timestamp and a VO data timestamp, reducing synchronization time consumption, and improving synchronization efficiency, and referring to fig. 2, the device includes:
the acquisition module 201 is used for respectively obtaining a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data based on the GNSS data and the VO data of the vehicle;
the sampling module 202 samples the GNSS speed curve and the VO speed curve for N times, to obtain N sets of GNSS speed sampling data corresponding to the GNSS speed curve and N sets of VO speed sampling data corresponding to the VO speed curve, where N is an integer greater than 1;
the analysis module 203 is configured to analyze correlations between the N sets of GNSS speed sampling data and the N sets of VO speed sampling data, and obtain a time offset between the GNSS data and the VO data, where the time offset characterizes a time offset between the GNSS speed curve and the VO speed curve;
and a synchronization module 204, configured to synchronize the GNSS data and the VO data according to the time offset.
In one possible design, the obtaining module 201 is specifically configured to: acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of the vehicle; according to the GNSS three-dimensional position, the VO three-dimensional position and the moments, calculating GNSS instantaneous speeds of the GNSS receiver at the moments and VO instantaneous speeds of the VO camera optical center at the moments; the GNSS speed curve is obtained according to the GNSS instantaneous speeds at all the moments, and the VO instantaneous speeds at all the moments are obtained.
In one possible design, the sampling module 202 is specifically configured to: respectively acquiring a preset number of speed data from the GNSS speed curve and the VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of VO speed sampling data corresponding to the VO speed curve; taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, respectively downsampling the GNSS original sampling data and the VO original sampling data for N-1 times according to preset multiples to obtain the GNSS speed sampling data of the N groups and the VO speed sampling data of the N groups, wherein the quantity of the GNSS speed sampling data of each group in the GNSS speed sampling data of the N groups is sequentially reduced from the preset quantity of the GNSS speed sampling data of the 1 st group, and the quantity of the VO speed sampling data of each group in the VO speed sampling data of the N groups is sequentially reduced from the preset quantity of the VO speed sampling data of the 1 st group.
In one possible design, the analysis module 203 is specifically configured to: analyzing the correlation between the N group of GNSS speed sampling data and the N group of VO speed sampling data from a first preset offset, and obtaining an actual first time offset between the N group of GNSS speed sampling data and the N group of VO speed sampling data; dividing the actual first time offset by the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data to obtain a second preset offset, and analyzing the correlation between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data from the second preset offset to obtain the actual second time offset between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data; and until the actual N time offset between the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group is obtained through analysis, taking the actual N time offset as the time offset.
In one possible design, the synchronization module 204 is specifically configured to: adding or subtracting the time offset to or from the time stamp of the GNSS data, and synchronizing the time stamp of the GNSS data with the time stamp of the VO data; or adding or subtracting the time offset to or from the time stamp of the VO data, and synchronizing the time stamp of the GNSS data and the time stamp of the VO data.
Based on the device, the GNSS speed data and the VO speed data are respectively downsampled for N times according to preset multiples to obtain N groups of GNSS speed sampling data and N groups of VO speed data with the same time stamp, and the sampling mode can ensure the sampling precision and the accuracy of the sampling data; the correlation between each sampling data set is analyzed in sequence from the sampling data set with the minimum number, and finally the time offset between the GNSS speed data and the VO speed data is obtained, so that the synchronization of the GNSS data and the VO data is realized based on the time offset.
Based on the same inventive concept, the embodiment of the present application further provides an electronic device, where the electronic device may implement the function of the foregoing high-precision map heterologous information synchronization device, and referring to fig. 3, the electronic device includes:
at least one processor 301, and a memory 302 connected to the at least one processor 301, in this embodiment of the present application, a specific connection medium between the processor 301 and the memory 302 is not limited, and in fig. 3, the connection between the processor 301 and the memory 302 through the bus 300 is taken as an example. Bus 300 is shown in bold lines in fig. 3, and the manner in which the other components are connected is illustrated schematically and not by way of limitation. The bus 300 may be divided into an address bus, a data bus, a control bus, etc., and is represented by only one thick line in fig. 3 for convenience of illustration, but does not represent only one bus or one type of bus. Alternatively, the processor 301 may be referred to as a controller, and the names are not limited.
In the embodiment of the present application, the memory 302 stores instructions executable by the at least one processor 301, and the at least one processor 301 may execute the high-precision map heterologous information synchronization method described above by executing the instructions stored in the memory 302. Processor 301 may implement the functions of the various modules in the apparatus shown in fig. 2.
The processor 301 is a control center of the apparatus, and may connect various parts of the entire control device using various interfaces and lines, and by executing or executing instructions stored in the memory 302 and invoking data stored in the memory 302, various functions of the apparatus and processing data, thereby performing overall monitoring of the apparatus.
In one possible design, processor 301 may include one or more processing units, and processor 301 may integrate an application processor and a modem processor, where the application processor primarily processes operating systems, user interfaces, application programs, and the like, and the modem processor primarily processes wireless communications. It will be appreciated that the modem processor described above may not be integrated into the processor 301. In some embodiments, processor 301 and memory 302 may be implemented on the same chip, and in some embodiments they may be implemented separately on separate chips.
The processor 301 may be a general purpose processor such as a Central Processing Unit (CPU), digital signal processor, application specific integrated circuit, field programmable gate array or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, which may implement or perform the methods, steps and logic blocks disclosed in embodiments of the present application. The general purpose processor may be a microprocessor or any conventional processor or the like. The steps of the high-precision map heterologous information synchronization method disclosed in connection with the embodiment of the application can be directly embodied as the execution completion of a hardware processor or the execution completion of the combination execution of hardware and software modules in the processor.
The memory 302 serves as a non-volatile computer-readable storage medium that can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The Memory 302 may include at least one type of storage medium, which may include, for example, flash Memory, hard disk, multimedia card, card Memory, random access Memory (Random Access Memory, RAM), static random access Memory (Static Random Access Memory, SRAM), programmable Read-Only Memory (Programmable Read Only Memory, PROM), read-Only Memory (ROM), charged erasable programmable Read-Only Memory (Electrically Erasable Programmable Read-Only Memory), magnetic Memory, magnetic disk, optical disk, and the like. Memory 302 is any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 302 in the present embodiment may also be circuitry or any other device capable of implementing a memory function for storing program instructions and/or data.
By programming the processor 301, the code corresponding to the high-precision map heterogeneous information synchronization method described in the foregoing embodiment may be cured into the chip, so that the chip can execute the steps of the high-precision map heterogeneous information synchronization method in the embodiment shown in fig. 1 during operation. How to design and program the processor 301 is a technology well known to those skilled in the art, and will not be described in detail herein.
Based on the same inventive concept, the embodiments of the present application also provide a storage medium storing computer instructions that, when executed on a computer, cause the computer to perform the high-precision map heterologous information synchronization method described in the foregoing.
In some possible embodiments, the aspects of the high-precision map heterologous information synchronization method provided herein may also be implemented in the form of a program product comprising program code for causing the control apparatus to perform the steps in the high-precision map heterologous information synchronization method according to the various exemplary embodiments of the present application as described herein above when the program product is run on a device.
It will be apparent to those skilled in the art that embodiments of the present application may be provided as a method, apparatus, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It will be apparent to those skilled in the art that various modifications and variations can be made in the present application without departing from the spirit or scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims and the equivalents thereof, the present application is intended to cover such modifications and variations.

Claims (10)

1. A high-precision map heterogeneous information synchronization method, characterized in that the method comprises the following steps:
based on GNSS data of a global positioning navigation system of a vehicle and VO data of a visual odometer, a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data are respectively obtained;
sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve, wherein N is an integer greater than 1;
analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain time offset between the GNSS data and the VO data, wherein the time offset represents time deviation between the GNSS speed curve and the VO speed curve;
and synchronizing the GNSS data and the VO data according to the time offset.
2. The method of claim 1, wherein the obtaining GNSS speed curves corresponding to the GNSS data and VO speed curves corresponding to the VO data based on the GNSS data and the VO data, respectively, comprises:
acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of the vehicle;
according to the GNSS three-dimensional position, the VO three-dimensional position and the moments, calculating GNSS instantaneous speeds of the GNSS receiver at the moments and VO instantaneous speeds of the VO camera optical center at the moments;
the GNSS speed curve is obtained according to the GNSS instantaneous speeds at all the moments, and the VO instantaneous speeds at all the moments are obtained.
3. The method of claim 1, wherein sampling the GNSS speed profile and the VO speed profile N times to obtain N sets of GNSS speed sample data corresponding to the GNSS speed profile and N sets of VO speed sample data corresponding to the VO speed profile, respectively, comprises:
respectively acquiring a preset number of speed data from the GNSS speed curve and the VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of VO speed sampling data corresponding to the VO speed curve;
taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, respectively carrying out downsampling according to preset multiples based on the GNSS original sampling data and the VO original sampling data for N-1 times to obtain the GNSS speed sampling data of the N groups and the VO speed sampling data of the N groups, wherein the quantity of the GNSS speed sampling data of each group in the GNSS speed sampling data of the N groups is sequentially reduced from the preset quantity of the GNSS speed sampling data of the 1 st group, and the quantity of the VO speed sampling data of each group in the VO speed sampling data of the N groups is sequentially reduced from the preset quantity of the VO speed sampling data of the 1 st group.
4. The method of claim 1, wherein said analyzing correlations between the N sets of GNSS speed sample data and the N sets of VO speed sample data to obtain a time offset between the GNSS data and the VO data comprises:
analyzing the correlation between the N group of GNSS speed sampling data and the N group of VO speed sampling data from a first preset offset, and obtaining an actual first time offset between the N group of GNSS speed sampling data and the N group of VO speed sampling data;
dividing the actual first time offset by the timestamp interval between each adjacent speed sampling data of the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data to obtain a second preset offset, and analyzing the correlation between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data from the second preset offset to obtain the actual second time offset between the N-1 group of GNSS speed sampling data and the N-1 group of VO speed sampling data;
and until the actual N time offset between the GNSS speed sampling data of the 1 st group and the VO speed sampling data of the 1 st group is obtained through analysis, taking the actual N time offset as the time offset.
5. The method of claim 1, wherein synchronizing the GNSS data and the VO data according to the time offset comprises:
adding or subtracting the time offset to or from the time stamp of the GNSS data, and synchronizing the time stamp of the GNSS data with the time stamp of the VO data; or alternatively
And adding or subtracting the time offset to the time stamp of the VO data, and synchronizing the time stamp of the GNSS data and the time stamp of the VO data.
6. A high-precision map heterogeneous information synchronization device, the device comprising:
the acquisition module is used for respectively obtaining a GNSS speed curve corresponding to the GNSS data and a VO speed curve corresponding to the VO data based on the GNSS data of the vehicle and the VO data of the visual odometer;
the sampling module is used for sampling the GNSS speed curve and the VO speed curve for N times respectively to obtain N groups of GNSS speed sampling data corresponding to the GNSS speed curve and N groups of VO speed sampling data corresponding to the VO speed curve, wherein N is an integer greater than 1;
the analysis module is used for analyzing the correlation between the N groups of GNSS speed sampling data and the N groups of VO speed sampling data to obtain time offset between the GNSS data and the VO data, wherein the time offset represents the time offset between the GNSS speed curve and the VO speed curve;
and the synchronization module is used for synchronizing the GNSS data and the VO data according to the time offset.
7. The apparatus of claim 6, wherein the acquisition module is specifically configured to:
acquiring a GNSS three-dimensional position of a GNSS receiver and a VO three-dimensional position of a VO camera optical center corresponding to each moment of the vehicle;
according to the GNSS three-dimensional position, the VO three-dimensional position and the moments, calculating GNSS instantaneous speeds of the GNSS receiver at the moments and VO instantaneous speeds of the VO camera optical center at the moments;
the GNSS speed curve is obtained according to the GNSS instantaneous speeds at all the moments, and the VO instantaneous speeds at all the moments are obtained.
8. The apparatus of claim 6, wherein the sampling module is specifically configured to:
respectively acquiring a preset number of speed data from the GNSS speed curve and the VO speed curve at the same time stamp to obtain a 1 st group of GNSS speed sampling data corresponding to the GNSS speed curve and a 1 st group of VO speed sampling data corresponding to the VO speed curve;
taking the GNSS speed sampling data of the 1 st group as GNSS original sampling data, taking the VO speed sampling data of the 1 st group as VO original sampling data, respectively downsampling the GNSS original sampling data and the VO original sampling data for N-1 times according to preset multiples to obtain the GNSS speed sampling data of the N groups and the VO speed sampling data of the N groups, wherein the quantity of the GNSS speed sampling data of each group in the GNSS speed sampling data of the N groups is sequentially reduced from the preset quantity of the GNSS speed sampling data of the 1 st group, and the quantity of the VO speed sampling data of each group in the VO speed sampling data of the N groups is sequentially reduced from the preset quantity of the VO speed sampling data of the 1 st group.
9. An electronic device, comprising:
a memory for storing a computer program;
a processor for carrying out the method steps of any one of claims 1-5 when executing a computer program stored on said memory.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored therein a computer program which, when executed by a processor, implements the method steps of any of claims 1-5.
CN202310110069.9A 2023-02-09 2023-02-09 High-precision map heterogeneous information synchronization method and device and electronic equipment Pending CN116105716A (en)

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Application Number Priority Date Filing Date Title
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Application Number Priority Date Filing Date Title
CN202310110069.9A CN116105716A (en) 2023-02-09 2023-02-09 High-precision map heterogeneous information synchronization method and device and electronic equipment

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