CN105551032B - The shaft tower image capturing system and its method of a kind of view-based access control model servo - Google Patents

The shaft tower image capturing system and its method of a kind of view-based access control model servo Download PDF

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CN105551032B
CN105551032B CN201510907446.7A CN201510907446A CN105551032B CN 105551032 B CN105551032 B CN 105551032B CN 201510907446 A CN201510907446 A CN 201510907446A CN 105551032 B CN105551032 B CN 105551032B
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tower
image
real
shaft tower
holder
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CN105551032A (en
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刘越
王万国
刘俍
李宗谕
张方正
雍军
慕世友
孟瑜
傅孟潮
李华东
魏传虎
李建祥
赵金龙
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State Grid Intelligent Technology Co Ltd
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State Grid Corp of China SGCC
Electric Power Research Institute of State Grid Shandong Electric Power Co Ltd
Shandong Luneng Intelligence Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D3/00—Control of position or direction
    • G05D3/12—Control of position or direction using feedback

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Theoretical Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Closed-Circuit Television Systems (AREA)
  • Image Analysis (AREA)
  • Studio Devices (AREA)
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Abstract

The invention discloses the shaft tower image capturing system and its method of view-based access control model servo, and the method comprising the steps of (1)：According to inspection requirement, the video information of shaft tower is obtained using the video camera on head and a frame realtime graphic is intercepted from video；Step (2)：Identify and position position of the shaft tower in the realtime graphic of interception；Step (3)：Whether shaft tower is judged positioned at the middle position of the realtime graphic intercepted, if so, then entering step (5)；Otherwise, it determines deviation of the shaft tower relative to the middle position of the realtime graphic of interception；Step (4)：The rotation direction of head is determined by the position of shaft tower in the picture, the deviation then obtained according to step (3) determines the amount of spin of head；After adjusting head, the shaft tower realtime graphic of current position is obtained again, is transferred to and is performed step (2)；Step (5)：Since a certain angle of shaft tower, with " S " type path adjustment head position, while shaft tower image is acquired using the camera on head.

Description

Tower image acquisition system and method based on visual servo
Technical Field
The invention relates to the field of digital image processing, in particular to a tower image acquisition system and a tower image acquisition method based on visual servo.
Background
Towers are important components of overhead transmission lines and function to support overhead line conductors and overhead ground wires and to provide adequate safety distances between conductors, between conductors and overhead ground wires, between conductors and towers, and between conductors to the ground and cross-over spans. As the tower is exposed in the natural environment for a long time and is influenced by natural or artificial factors, the problems of loosening and falling of screws, deflection of the tower, exposure of a tower foundation and the like exist. If regular inspection and maintenance are not performed on the towers with problems, the normal operation of the whole power grid is affected, and even serious safety accidents can be caused.
Carry on visible light, infrared equipment through unmanned aerial vehicle and patrol and examine and image information gathers the shaft tower, the problem that discovery shaft tower that can be timely exists has compensatied the manual work effectively and has patrolled and examined the not enough that exists. However, in the existing tower image information acquisition mode based on the unmanned aerial vehicle, an operator observes video information returned by the ground station and adjusts the airborne cradle head to complete information acquisition of the tower, so that the operator is required to observe feedback information of the ground station in real time, and the labor intensity is high. It is very important how to automatically complete tower information acquisition by using a tower identification technology and a visual servo technology.
In the existing system based on visual servo, the visual servo-based power transmission line unmanned aerial vehicle inspection tripod head control (patent number: CN 1029292880a) proposed by the Shandong province electric academy is designed to adjust the tripod head to realize the tracking of the power transmission line by using the visual servo technology, but the patent only realizes the tracking function of the line by using the visual servo technology, and does not describe the key technology of how to acquire high-quality images for towers.
Disclosure of Invention
In order to solve the defects of the prior art, the invention provides a tower image acquisition system based on visual servo and a method thereof. The method utilizes a pole tower identification technology to identify and position the position of a pole tower in a video; then, the position of the airborne cloud deck is adjusted through a visual servo technology, and the high-definition camera is positioned on a tower; and finally, photographing is carried out to complete information acquisition of the tower, so that the accuracy of tower information acquisition and the quality of acquired images are improved.
In order to achieve the purpose, the invention adopts the following technical scheme:
a tower image acquisition system based on visual servo comprises:
the system comprises an unmanned aerial vehicle, a camera and a video camera, wherein the unmanned aerial vehicle is provided with a cloud deck on which the camera and the video camera are arranged; the camera is used for acquiring video information of the tower;
the image intercepting module is used for intercepting a frame of real-time image from the video information of the tower;
the tower identification and positioning module is used for identifying and positioning the position of the tower in the intercepted real-time image;
the pole tower position judging module is used for judging whether the pole tower is positioned in the center of the intercepted real-time image;
the holder control module is used for controlling the holder to rotate in a visual servo mode based on the image when the tower is not positioned at the central position of the intercepted real-time image, and the rotating direction of the holder is determined according to the position of the tower in the image;
and the image acquisition module determines the rotation amount of the holder according to the obtained deviation, adjusts the position of the holder by an S-shaped path from a certain angle of the tower when the tower is positioned at the central position of the intercepted real-time image, and simultaneously acquires the image of the tower by adopting a camera on the holder.
The camera and the video camera are in a coaxial position on the cloud deck.
The camera is a monocular camera.
The pole tower identification and positioning module comprises:
the line detection module is used for performing line detection on the acquired real-time image by using an LSD line detection algorithm;
and the tower positioning module is used for dividing the real-time image into a plurality of image blocks, counting the number of straight lines in each image block, and further judging whether a tower exists or not and determining the position of the tower.
A tower image acquisition method of a tower image acquisition system based on visual servo comprises the following steps:
step (1): according to the inspection requirement, a camera on a holder is adopted to obtain the video information of the tower and a frame of real-time image is intercepted from the video;
step (2): identifying and positioning the position of the tower in the intercepted real-time image;
and (3): judging whether the tower is located at the central position of the intercepted real-time image, if so, entering the step (5); otherwise, determining the deviation of the tower relative to the central position of the intercepted real-time image, and entering the next step;
and (4): controlling the rotation of the cradle head in an image-based visual servo mode, determining the rotation direction of the cradle head through the position of the tower in the image, and then determining the rotation quantity of the cradle head according to the deviation obtained in the step (3); after the cradle head is adjusted, acquiring the real-time image of the tower at the current position again, and executing the step (2);
and (5): and starting from a certain angle of the tower, adjusting the position of the cradle head by an S-shaped path, and simultaneously acquiring images of the tower by a camera on the cradle head.
The specific process of the step (2) is as follows:
firstly, carrying out line detection by using an LSD (least squares-based) line detection algorithm to obtain a real-time image;
then, the real-time image is divided into a plurality of image blocks, the number of straight lines in each image block is counted, and then whether a tower exists or not is judged, and the position of the tower is determined.
The specific process of controlling the rotation of the holder by adopting the visual servo mode based on the image in the step (4) is as follows:
step (4.1): positioning the image block containing the upper right corner of the tower component, and extracting SURF (speeded up robust features) F of the image block1；
Step (4.2): determining the rotation direction of the holder according to the position of the image block, wherein the rotation direction of the holder is the direction which enables the tower to deviate towards the center of the image; then, the cradle head is rotated by the minimum unit to obtain the tower image at the current position, and the SURF characteristic F of the tower image is extracted2；
Step (4.3): matching feature F1And F2And calculate F1And F2The offset of the matching point pair at the pixel level;
step (4.4): and obtaining the rotation quantity of the holder according to the linear mapping relation between the characteristic offset and the rotation quantity of the holder.
In the step (4.3), RANSAC random sampling is used to eliminate the mismatching feature pairs, a matching matrix H of the features is obtained, and the matching equation of the two features obtained from the corresponding relationship is as follows: f2＝HF1。
In the step (4.4), a linear mapping matrix between the characteristic offset and the holder rotation amount is a Jacobian matrix of the current image.
The invention has the beneficial effects that:
(1) the invention realizes the automatic acquisition of the image of the tower mast in the process of the unmanned aerial vehicle inspection, greatly reduces the labor intensity of inspection personnel, adopts a visual servo control mode based on the image to realize the control of the pan-tilt, and describes the corresponding relation between the image pixel information and the pan-tilt control quantity by calculating the Jacobian matrix;
(2) the invention also sets an S-shaped path photographing mode according to the characteristics of the tower, thereby ensuring the integrity of the tower information;
(3) the tower image acquisition is completed based on the monocular camera, the requirement on equipment is low, and the whole system is simple.
Drawings
FIG. 1 is a flow chart of a tower image acquisition method based on visual servoing according to the present invention;
FIG. 2 is a real-time image captured from the tower video information;
FIG. 3 is a real-time image of a tower obtained after a pan-tilt is adjusted;
FIG. 4a) is a first turret image acquired for this embodiment;
FIG. 4b) is a second turret image acquired for this embodiment;
FIG. 4c) is a third turret image acquired for this embodiment;
FIG. 4d) is a fourth turret image acquired for this example;
FIG. 4e) is a fifth turret image acquired for this embodiment;
FIG. 4f) is a sixth turret image acquired for the present embodiment;
FIG. 4g) is a seventh turret image acquired for this example;
FIG. 4h) is an eighth turret image acquired for this embodiment;
fig. 4i) is a ninth turret image acquired for this example.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
the invention discloses a tower image acquisition system based on visual servo, which comprises:
the system comprises an unmanned aerial vehicle, a camera and a video camera, wherein the unmanned aerial vehicle is provided with a cloud deck on which the camera and the video camera are arranged; the camera is used for acquiring video information of the tower;
the image intercepting module is used for intercepting a frame of real-time image from the video information of the tower;
the tower identification and positioning module is used for identifying and positioning the position of the tower in the intercepted real-time image;
the pole tower position judging module is used for judging whether the pole tower is positioned in the center of the intercepted real-time image;
the holder control module is used for controlling the holder to rotate in a visual servo mode based on the image when the tower is not positioned at the central position of the intercepted real-time image, and the rotating direction of the holder is determined according to the position of the tower in the image;
an image acquisition module: determining the rotation quantity of the holder according to the obtained deviation; when the tower is located at the central position of the intercepted real-time image, the position of the holder is adjusted by an S-shaped path from a certain angle of the tower, and meanwhile, the image of the tower is collected by a camera on the holder.
Wherein the camera and the video camera are in coaxial positions on the holder.
The camera may be a monocular camera.
Further, shaft tower discernment location module includes:
the line detection module is used for carrying out line detection on a real-time image acquired by using an LSD line detection algorithm;
and the tower positioning module is used for dividing the real-time image into a plurality of image blocks, counting the number of straight lines in each image block, and further judging whether a tower exists or not and determining the position of the tower.
When the visual servo mode based on the image is adopted to control the rotation of the pan-tilt, an eye-in-hand mode is adopted, the pan-tilt has m degrees of freedom, and the angular speed of the rotation of the pan-tilt is q ═ q [ [ q ] q [1,…,qp]The linear velocity of the tip is r ═ r1,…,rm]The two have the following relationship:
r＝Jr·q
wherein,
and converting the position transformation of the holder into the change of image parameters through a camera perspective projection matrix, thereby obtaining the transformation relation between the image characteristic space and the holder tail end position space.
Assuming that the coordinates of the current image are (x, y), the final transformation relationship is:
wherein,f is the focal length of the camera;
u＝[νx,νy,νz,ωx,ωy,ωz]T，vx，vy，vzrepresenting the linear velocity, omega, of the camera rotation along the x, y and z axes, respectivelyx，ωy，ωzRepresenting the angular velocity of the camera rotation along the x, y and z axes, respectively.
JImageFor the Jacobian matrix of the image, the relationship between the rate of change of the image characteristic and the pan-tilt velocity is represented by the composite Jacobian matrix available J ═ JImage·JrAnd (4) showing.
As shown in fig. 1, the tower image acquisition method of the tower image acquisition system based on visual servo according to the present invention includes:
step (1): according to the inspection requirement, a camera on a cloud deck is adopted to obtain video information of a tower and a frame of real-time image is intercepted from the video, as shown in figure 2;
step (2): identifying and positioning the position of the tower in the intercepted real-time image;
and (3): judging whether the tower is located at the central position of the intercepted real-time image, if so, entering the step (5); otherwise, determining the deviation of the tower relative to the central position of the intercepted real-time image, and entering the next step;
and (4): controlling the rotation of the cradle head in an image-based visual servo mode, determining the rotation direction of the cradle head through the position of the tower in the image, and then determining the rotation quantity of the cradle head according to the deviation obtained in the step (3); after the cradle head is adjusted, acquiring the real-time image of the tower at the current position again, and executing the step (2);
and (5): starting from a certain angle of the tower, the position of the cradle head is adjusted by an S-shaped path, meanwhile, a camera on the cradle head is adopted to collect images of the tower, and the obtained images are shown in figures 4a) -4 i).
Further, the specific process of identifying and positioning the position of the tower in the intercepted real-time image in the step (2) is as follows:
firstly, carrying out line detection by using an LSD (least squares-based) line detection algorithm to obtain a real-time image;
then, the real-time image is divided into a plurality of image blocks, the number of straight lines in each image block is counted, and then whether a tower exists or not is judged, and the position of the tower is determined.
When the invention is used for visual servo, the invention can be completed by adopting two forms of visual servo control based on position and visual servo control based on image, the visual servo control based on position needs to calculate the position and the orientation of an object in real time, and the track of the manipulator end effector is predicted according to the information. In this way, in the presence of noise, a phenomenon in which the feature point deviates from the field of view is likely to occur. And the image-based visual servo is insensitive to quantization errors and measurement errors, mainly because when the manipulator moves towards the direction in which the error of the image characteristic point is reduced, the probability that the characteristic point is separated from the visual field is very low, so the image-based visual servo control is adopted in the servo control process of the step (4).
And (4) acquiring the holder information and the relative information of the tower in the video when the unmanned aerial vehicle is suspended, and enabling the shooting condition to be met at the moment through the adjustment in the step (4).
Wherein, the specific process of controlling the rotation of the holder by adopting the visual servo mode based on the image in the step (4) is as follows:
and (4).1): locating an image block containing a certain corner of a tower component, and extracting SURF (speeded up robust feature) F of the image block1；
Step (4.2): determining the rotation direction of the holder according to the position of the image block, wherein the rotation direction of the holder is the direction which enables the tower to deviate towards the center of the image; then, the cradle head is rotated by the minimum unit to obtain the tower image at the current position, and the SURF characteristic F of the tower image is extracted2；
Step (4.3): matching feature F1And F2And calculate F1And F2The offset of the matching point pair at the pixel level;
step (4.4): and obtaining the rotation quantity of the holder according to the linear mapping relation between the characteristic offset and the rotation quantity of the holder.
Further, in the step (4.3), the RANSAC random sampling is used to eliminate the mismatching feature pairs, and a matching matrix H of the features is obtained, and the matching equation of the two features obtained from the corresponding relationship is: f2＝HF1。
Further, in step (4.4), the linear mapping matrix between the characteristic offset and the pan-tilt rotation amount is a jacobian matrix of the current image.
F is calculated in step (4.3)1And F2Is aligned to the offset (P) at the pixel levelx,Py) Comprises the following steps:
(Px,Py)＝JImage*u。
in the embodiment, the real-time image is divided into 7 × 9 image blocks, and firstly, the cradle head is adjusted to adjust the position of the upper right corner of the tower in the real-time acquired image to the central position of the whole image;
secondly, taking 2 image blocks in the horizontal direction and 1.5 image blocks in the vertical direction as rotation step lengths, and converting the rotation step length of the pixel level into the direction and the angle of holder adjustment through an image Jacobian matrix;
and finally, starting from a certain angle of the tower, carrying out pan-tilt adjustment in an S shape and starting the camera to shoot, wherein 9 images are shot by each tower, as shown in figures 4a) to 4 i).
The real-time image can be divided into other image blocks, and the corresponding step length of the rotation of the holder in the horizontal direction and the vertical direction can be adjusted according to the actual situation.
Although the embodiments of the present invention have been described with reference to the accompanying drawings, it is not intended to limit the scope of the present invention, and it should be understood by those skilled in the art that various modifications and variations can be made without inventive efforts by those skilled in the art based on the technical solution of the present invention.

Claims (4)

1. A tower image acquisition method of a tower image acquisition system based on visual servo is characterized by comprising the following steps:
step (1): according to the inspection requirement, a camera on a holder is adopted to obtain the video information of the tower and a frame of real-time image is intercepted from the video;
step (2): identifying and positioning the position of the tower in the intercepted real-time image;
and (3): judging whether the tower is located at the central position of the intercepted real-time image, if so, entering the step (5); otherwise, determining the deviation of the tower relative to the central position of the intercepted real-time image, and entering the next step;
and (4): controlling the rotation of the cradle head in an image-based visual servo mode, determining the rotation direction of the cradle head through the position of the tower in the image, and then determining the rotation quantity of the cradle head according to the deviation obtained in the step (3); after the cradle head is adjusted, acquiring the real-time image of the tower at the current position again, and executing the step (2);
and (5): adjusting the position of a cradle head by an S-shaped path from a certain angle of the tower, and simultaneously acquiring images of the tower by a camera on the cradle head;
the specific process of controlling the rotation of the holder by adopting the visual servo mode based on the image in the step (4) is as follows:
step (4.1): locating an image block containing a certain corner of a tower component, and extracting SURF (speeded up robust feature) F of the image block1；
Step (4.2): determining the rotation direction of the holder according to the position of the image block, wherein the rotation direction of the holder is the direction which enables the tower to deviate towards the center of the image; then, the cradle head is rotated by the minimum unit to obtain the tower image at the current position, and the SURF characteristic F of the tower image is extracted2；
Step (4.3): matching feature F1And F2And calculate F1And F2The offset of the matching point pair at the pixel level;
step (4.4): and obtaining the rotation quantity of the holder according to the linear mapping relation between the characteristic offset and the rotation quantity of the holder.
2. The tower image acquisition method as claimed in claim 1, wherein the specific process of the step (2) is as follows:
firstly, carrying out line detection by using an LSD (least squares-based) line detection algorithm to obtain a real-time image;
then, the real-time image is divided into a plurality of image blocks, the number of straight lines in each image block is counted, and then whether a tower exists or not is judged, and the position of the tower is determined.
3. The tower image acquisition method as claimed in claim 1, wherein in the step (4.3), RANSAC random sampling is used to eliminate mismatching feature pairs, a matching matrix H of features is obtained, and a matching equation of two features obtained from a corresponding relationship is as follows: f2＝HF1。
4. The tower image acquisition method according to claim 1, wherein in the step (4.4), the linear mapping matrix between the characteristic offset and the pan-tilt rotation amount is a Jacobian matrix of the current image.
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