CN110533718A - A kind of navigation locating method of the auxiliary INS of monocular vision artificial landmark - Google Patents
A kind of navigation locating method of the auxiliary INS of monocular vision artificial landmark Download PDFInfo
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- G—PHYSICS
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- 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
- G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
- G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
- G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
- G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
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- 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
- G01C21/20—Instruments for performing navigational calculations
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Abstract
The present invention is the navigation locating method of the auxiliary INS of monocular vision artificial landmark a kind of, comprising the following steps: design artificial landmark；Demarcate scale factor；Establish vision road sign library；The estimation of interframe pose is carried out to camera position and posture based on road sign library；Monocular vision artificial landmark assists INS positioning.The invention has the advantages that the position of camera and posture information when calculating acquisition current manual's road sign image using known vision road sign library information, camera current location and INS data are merged using Kalman filtering algorithm, accumulated error in traditional INS localization method can be reduced, make to position more acurrate, at low cost, easy to operate.
Description
Technical field
The invention belongs to the navigation of positioning and navigation field more particularly to a kind of auxiliary INS of monocular vision artificial landmark are fixed
Position method.
Background technique
Traditional localization method mainly includes satellite, inertial navigation positioning etc., and satellite navigation and positioning is widely used, precision
Height, but be highly susceptible to the influence of environment, have occlusion area all without satellite-signal and satellite-signal indoors and will be unable to using.
Inertial navigation system is a kind of navigation system of autonomous type, its advantage is that can provide continuous navigation information, short-term positioning accurate
Degree and stability are good, but since navigation information is generated by integral, position error increases at any time, cannot long-term independent work
Make.
In recent years, vision guided navigation is got growing concern for as new localization method.Visual odometry (visual
Odometer, VO) concept be by Nist é r propose, it is to estimate to carry by the variation of adjacent image matching characteristic point coordinate
The pose situation of change of body.Because VO is the motion conditions for estimating camera by a series of comparison of before and after frames, can not
What is avoided will cause the accumulative of error.Positioning and map structuring technology (visual simultaneous while view-based access control model
Localization and mapping, VSLAM), the several part groups of figure are detected and built by the front end VO, rear end optimization, winding
At being played an important role in robot autonomous localization and path planning.VSLAM is greatly improved compared to VO calculation amount, right
Data processing terminal computing capability has very high requirement, difficult to realize to position in real time and build figure.
Summary of the invention
It the problem of increasing as the time increases present invention mainly solves traditional indoor orientation method position error, mentions
The navigation locating method of the auxiliary INS of monocular vision artificial landmark at low cost out, easy to operate, accuracy is high.
The technical solution adopted by the present invention to solve the technical problems is a kind of auxiliary INS of monocular vision artificial landmark
Navigation locating method, comprising the following steps:
S1: design artificial landmark；
S2: calibration scale factor；
S3: vision road sign library is established；
S4: monocular vision estimation is carried out to camera position and posture based on road sign library；
S5: monocular vision artificial landmark assists INS positioning.
Artificial landmark image is arranged in known location in the present invention, vision road sign library is established, according to image in vision road sign library
With the relationship of current acquired image, the camera position and posture when obtaining in conjunction with known road sign library image are to obtain current phase
The position of machine and posture carry out error correction to INS location data using the location information of camera, to reduce the error of INS
Accumulation, makes to position more accurate.
As a kind of above-mentioned preferred embodiment, the step S1 artificial landmark Outside Dimensions are R, and center, which is equipped with, is used for road sign mark
Number two dimensional code, the region of two dimensional code to artificial landmark edge is equipped with identification pattern.Identification pattern can be such that artificial landmark has
Enough ORB characteristic points.
As a kind of above-mentioned preferred embodiment, the step S2 acceptance of the bid dimensioning factor, comprising the following steps:
S21: it is shot using camera in known distance D face artificial landmark；
S22: the Pixel Dimensions r of artificial landmark is obtained；
S23: according to pinhole imaging system principle, scale factor f is obtained
F=D*r/R.
As a kind of above-mentioned preferred embodiment, vision road sign library is established in the step S3, comprising the following steps:
S31: multiple artificial landmarks are arranged on the shiftable haulage line of the carrier with camera；
S32: shooting camera in known location face artificial landmark, records camera position, posture；
S33: road sign region and Pixel Dimensions in detection shooting image obtain road sign to camera according to scale factor
Distance, and the unartificial road sign region in shooting image is filled；
S34: camera position, posture, the distance of camera to road sign and filled image correspondence are deposited into vision road sign
In library.
As a kind of above-mentioned preferred embodiment, interframe position is carried out to camera position and posture based on road sign library in the step S4
Appearance estimation, comprising the following steps:
S41: according to the distance of the Pixel Dimensions acquisition camera of artificial landmark in image shot by camera to artificial landmark；
S42: the two dimensional code in identification shooting image in artificial landmark finds corresponding artificial landmark in vision road sign library
Data；
S43: unartificial road sign region in shooting image is filled, carries out feature extraction with correspondence image in road sign library
And matching；
S44: matching characteristic in road sign image is obtained according to the distance of matched characteristic point pixel coordinate and camera to road sign
Three-dimensional point set P={ p of the point under camera coordinates system1..., pnAnd present image in matching characteristic point in camera coordinates
Three-dimensional point set P '={ p ' under system1..., p 'n}；
S45: meeting European variation between matched three-dimensional point, so that
pi=Rp 'i+t
Above formula is solved, spin matrix R and translation vector t is obtained；
S46: the position of camera, posture information when being obtained in conjunction with spin matrix R and translation vector t and known library image,
Position and posture information when acquisition camera shooting present image.
As a kind of above-mentioned preferred embodiment, the three-dimensional point set of match point is obtained in the step S44 by the following method:
In camera imaging as establishing pixel coordinate system in plane, by origin of camera photocentre three-dimensional camera coordinate system is established, it is known that figure
As upper characteristic point p ' under pixel coordinate system coordinate (u, v), obtain fact characteristic point p on three-dimensional camera coordinate system coordinate (X,
Y, Z)
(cx, cy) it is optical center in the coordinate fastened as the subpoint in plane in pixel coordinate, with optical center on as plane
Subpoint is that origin is established as coordinate system, and characteristic point p ' is (x ', y ') in the coordinate as coordinate system on image, according to as coordinate system
It can be obtained with the relationship of pixel coordinate system
Simultaneously
It can finally obtain
Wherein f1For camera focus, α f1=fx, β f1=fy, α is that the pixel coordinate system abscissa of characteristic point p ' on image exists
As the scaling multiple on coordinate system axis of abscissas, the pixel coordinate system ordinate that β is characteristic point p ' on image is as coordinate system is vertical
Scaling multiple in reference axis.
As a kind of above-mentioned preferred embodiment, in the step S45 by the method for singular value decomposition obtain spin matrix R and
Translation vector t: calculating centroid position p, the p ' of match point in present image and library image, then calculate each point go center-of-mass coordinate
qi=pi- p, q 'i=p 'i-p′
Calculate spin matrix R and translation vector t
Translation vector t is sought according to spin matrix R
t*=p-Rp '.
As a kind of above-mentioned preferred embodiment, monocular vision artificial landmark auxiliary INS positioning in the S5: pushed away with INS boat position
Calculating formula is that prediction model establishes state equation
Observational equation is established using monocular vision artificial landmark positioning method as observation model
Yk=HXk+v(k)
Wherein, Xk、Xk-1Corresponding state vector, X at the time of adjacent for trolleyk=[xk, yk, zk], (xk, yk, zk) it is small
Coordinate of the vehicle current time on three-dimensional navigation coordinate system, three-dimensional navigation coordinate system are the coordinate system of activity space locating for carrier；A
For state-transition matrix；W (k) is system noise error；YkFor observation, i.e. artificial vision's rout marking allocation result；H is observation square
Battle array；V (k) is the noise error in observation process；Obtain state renewal equation
KkFor Kalman gain；It is the moment state estimator obtained by state equation；To be obtained by observational equation
The observed quantity at the moment arrived；As fused location information.
The invention has the advantages that camera when calculating acquisition current manual's road sign image using known vision road sign library information
Position and posture information, camera current location and INS data are merged using Kalman filtering algorithm, biography can be reduced
Accumulated error in system INS localization method, makes to position more acurrate, at low cost, easy to operate.
Detailed description of the invention
Fig. 1 is a kind of flow diagram of the invention.
Fig. 2 is a kind of structural schematic diagram of artificial landmark in the present invention.
Fig. 3 is a kind of flow diagram that the factor is dimensioned in the present invention.
Fig. 4 is a kind of flow diagram that vision road sign library is established in the present invention.
Fig. 5 is that a kind of process for carrying out the estimation of interframe pose to camera position and posture based on road sign library in the present invention is illustrated
Figure.
Fig. 6 is camera coordinates system model in the present invention.
Fig. 7 is inter frame motion estimation figure in the present invention.
Specific embodiment
Below with reference to the embodiments and with reference to the accompanying drawing further description of the technical solution of the present invention.
Embodiment:
A kind of monocular vision artificial landmark of the present embodiment auxiliary INS navigation locating method, as shown in Figure 1, include with
Lower step:
S1: design artificial landmark；As shown in Fig. 2, artificial landmark is the circle of known outermost radius R, it is easy to use Hough
Circle transformation detects round road sign；The two dimensional code of setting road sign label in circle, convenient for the identification of road sign.In round road sign
Various identification patterns are designed in region so that there is enough ORB characteristic points in road sign region, for later feature extraction and
Matching, different road signs need to only replace the label two dimensional code of intermediate region.
S2: calibration scale factor, as shown in Figure 3, comprising the following steps:
S21: it is shot using camera in known distance D face artificial landmark；
S22: it uses hough-circle transform to detect the pixel radius of round road sign the image of shooting, obtains the picture of artificial landmark
Plain radius r, it is known that artificial landmark real radius R；
S23: according to pinhole imaging system principle
R/r=D/f
, obtain scale factor f
F=D*r/R
According to scale factor, when the pixel radius for detecting people's road sign is r ', it is known that the distance of camera to road sign is
D=f*R/r '.
S3: vision road sign library is established, as shown in Figure 4, comprising the following steps:
S31: all artificial landmarks being separately positioned on the wall of the trolley shiftable haulage line with camera, height and camera
Height apart from ground is identical；
S32: making camera in known location face, successively artificial landmark is shot, and records camera position, posture；
S33: road sign region and pixel radius in detection shooting image are detected using hough-circle transform, according in S23
Scale factor obtain road sign to camera distance, and to shooting image in unartificial road sign region be filled with black；
S34: camera position, posture, the distance of camera to road sign and filled image correspondence are deposited into vision road sign
In library；
S4: the estimation of interframe pose is carried out to camera position and posture based on road sign library, as shown in Figure 5, comprising the following steps:
S41: according to the distance of the Pixel Dimensions acquisition camera of artificial landmark in image shot by camera to artificial landmark；
S42: the two dimensional code in identification shooting image in artificial landmark finds corresponding artificial landmark in vision road sign library
Data；
S43: correspondence image in filled black, with road sign library is carried out to unartificial road sign region in shooting image and carries out ORB
Feature extraction and matching；
S44: matching characteristic in road sign image is obtained according to the distance of matched characteristic point pixel coordinate and camera to road sign
Three-dimensional point set P={ p of the point under camera coordinates system1..., pnAnd present image in matching characteristic point in camera coordinates
Three-dimensional point set P '={ p ' under system1..., p 'n}.Three-dimensional point set acquisition methods are as follows: as shown in Figure 6 in camera imaging
As establishing pixel coordinate system o "-uv in plane, three-dimensional camera coordinate system o-xyz is established by origin of camera photocentre, it is known that image
Upper characteristic point p ' coordinate (u, v) under pixel coordinate system, obtain fact characteristic point p on three-dimensional camera coordinate system coordinate (X, Y,
Z)
(cx, cy) it is optical center in the coordinate fastened as the subpoint in plane in pixel coordinate, with optical center on as plane
Subpoint is that origin is established as coordinate system o '-x ' y ', and characteristic point p ' is (x ', y ') in the coordinate as coordinate system on image, according to
As the relationship of coordinate system and pixel coordinate system can obtain
Simultaneously
It can finally obtain
Wherein f1For camera focus, α f1=fx, β f1=fy, α is that the pixel coordinate system abscissa of characteristic point p ' on image exists
As the scaling multiple on coordinate system axis of abscissas, the pixel coordinate system ordinate that β is characteristic point p ' on image is as coordinate system is vertical
Scaling multiple in reference axis.
S45: meeting European variation between matched three-dimensional point, so that
pi=Rp 'i+t
By the method solution above formula of singular value decomposition, obtains spin matrix R and translation vector t, solution procedure is as follows:
Centroid position p, the p ' of match point in present image and library image are calculated, then calculate each point go center-of-mass coordinate
qi=pi- p, q 'i=p 'i-p′
Calculate spin matrix R and translation vector t
Translation vector t is sought according to spin matrix R
t*=p-Rp '.
S46: as shown in fig. 7, obtaining spin matrix R and translation vector t and known in conjunction with by singular value decomposition (SVD) method
Position and posture information when obtaining camera shooting present image of library image position of camera when obtaining, posture information；
S5: monocular vision artificial landmark assists INS positioning, using INS/ odometer as in a manner of the prime navaid of trolley, and
Using the positioning method of view-based access control model artificial landmark as auxiliary, error correction is carried out to INS/ odometer location data.Because serving as reasons
The attitudes vibration that vision solves is more accurate, the course angle directly obtained here with vision to inertial navigation to accumulated error into
Row amendment, and then use the mode of Kalman filter to merge location information: using INS dead reckoning formula as prediction model
Establish state equation
Observational equation is established using monocular vision artificial landmark positioning method as observation model
Yk=HXk+v(k)
Wherein, Xk、Xk-1Corresponding state vector, X at the time of adjacent for trolleyk=[xk, yk, zk], (xk, yk, zk) it is small
Coordinate of the vehicle current time on three-dimensional navigation coordinate system, navigation three-dimensional coordinate system are the coordinate system of activity space locating for trolley；A
For state-transition matrix；W (k) is system noise error；YkFor observation, i.e. artificial vision's rout marking allocation result；H is observation square
Battle array；V (k) is the noise error in observation process；
Obtain state renewal equation
Wherein, Kk is Kalman gain；It is the moment state estimator obtained by state equation；For by observing
The observed quantity at the moment that equation obtains；As fused location information.
Specific embodiment described herein is only an example for the spirit of the invention.The neck of technology belonging to the present invention
The technical staff in domain can make various modifications or additions to the described embodiments or replace by a similar method
In generation, however, it does not deviate from the spirit of the invention or beyond the scope of the appended claims.
Claims (8)
1. the navigation locating method of the auxiliary INS of monocular vision artificial landmark a kind of, it is characterized in that: the following steps are included:
S1: design artificial landmark；
S2: calibration scale factor；
S3: vision road sign library is established；
S4: the estimation of interframe pose is carried out to camera position and posture based on road sign library；
S5: monocular vision artificial landmark assists INS positioning.
2. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 1 a kind of, feature
Be: the step S1 artificial landmark Outside Dimensions are R, and center is equipped with the two dimensional code for road sign label, two dimensional code to artificial road
The region for marking edge is equipped with identification pattern.
3. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 1 a kind of, feature
It is: the step S2 acceptance of the bid dimensioning factor, comprising the following steps:
S21: it is shot using camera in known distance D face artificial landmark；
S22: the Pixel Dimensions r of artificial landmark is obtained；
S23: according to pinhole imaging system principle, scale factor f is obtained
F=D*r/R.
4. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 1 a kind of, feature
It is: establishes vision road sign library in the step S3, comprising the following steps:
S31: multiple artificial landmarks are arranged on the shiftable haulage line of the carrier with camera；
S32: shooting camera in known location face artificial landmark, records camera position, posture；
S33: road sign region and Pixel Dimensions in detection shooting image, according to scale factor obtain road sign to camera away from
From, and the unartificial road sign region in shooting image is filled；
S34: camera position, posture, the distance of camera to road sign and filled image correspondence are deposited into vision road sign library.
5. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 1 a kind of, feature
It is: the estimation of interframe pose is carried out to camera position and posture based on road sign library in the step S4, comprising the following steps:
S41: according to the distance of the Pixel Dimensions acquisition camera of artificial landmark in image shot by camera to artificial landmark；
S42: the two dimensional code in identification shooting image in artificial landmark finds corresponding artificial landmark number in vision road sign library
According to；
S43: to shooting image in unartificial road sign region be filled, in road sign library correspondence image carry out feature extraction and
Match；
S44: matching characteristic point in road sign image is obtained according to the distance of matched characteristic point pixel coordinate and camera to road sign and is existed
Three-dimensional point set P={ p under camera coordinates system1..., pnAnd present image in matching characteristic point under camera coordinates system
Three-dimensional point set P '={ p '1..., p 'n}；
S45: meeting European variation between matched three-dimensional point, so that
pi=Rp 'i+t
Above formula is solved, spin matrix R and translation vector t is obtained；
S46: the position of camera, posture information when obtaining in conjunction with spin matrix R and translation vector t and known library image obtain
Position and posture information when camera shooting present image.
6. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 5 a kind of, feature
It is: obtains the three-dimensional point set of match point in the step S44 by the following method: in camera imaging as establishing picture in plane
Plain coordinate system establishes three-dimensional camera coordinate system by origin of camera photocentre, it is known that characteristic point p ' is under pixel coordinate system on image
Coordinate (u, v) obtains coordinate (X, Y, Z) of the fact characteristic point p on three-dimensional camera coordinate system
(cx, cy) it is optical center in the coordinate fastened as the subpoint in plane in pixel coordinate, with optical center in as the projection in plane
Point is that origin is established as coordinate system, and characteristic point p ' is (x ', y ') in the coordinate as coordinate system on image, according to as coordinate system and picture
The relationship of plain coordinate system can obtain
Simultaneously
It can finally obtain
Wherein f1For camera focus, α f1=fx, β f1=fy, the pixel coordinate system abscissa that α is characteristic point p ' on image is as sitting
Scaling multiple on mark system axis of abscissas, the pixel coordinate system ordinate that β is characteristic point p ' on image is as coordinate system ordinate
Scaling multiple on axis.
7. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 5 a kind of, feature
It is: spin matrix R and translation vector t is obtained by the method for singular value decomposition in the step S45: calculates present image and library
Centroid position p, the p ' of match point in image, then calculate each point go center-of-mass coordinate
qi=pi- p, q 'i=p 'i-p′
Calculate spin matrix R and translation vector t
Translation vector t is sought according to spin matrix R
t*=p-Rp '.
8. the navigation locating method of the auxiliary INS of monocular vision artificial landmark according to claim 1 a kind of, feature
It is: monocular vision artificial landmark auxiliary INS positioning in the S5: establishes state side using INS dead reckoning formula as prediction model
Journey
Observational equation is established using monocular vision artificial landmark positioning method as observation model
Yk=HXk+v(k)
Wherein, Xk、Xk-1Corresponding state vector, X at the time of adjacent for trolleyk=[xk, yk, zk], (xk, yk, zk) work as trolley
Coordinate of the preceding moment on three-dimensional navigation coordinate system, three-dimensional navigation coordinate system are the coordinate system of activity space locating for carrier；A is shape
State transfer matrix；W (k) is system noise error；YkFor observation, i.e. artificial vision's rout marking allocation result；H is observing matrix；v
It (k) is the noise error in observation process；Obtain state renewal equation
KkFor Kalman gain；It is the moment state estimator obtained by state equation；It is obtained by observational equation
The observed quantity at the moment；As fused location information.
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Application publication date: 20191203 |