CN109993763B - Detector positioning method and system based on image recognition and force feedback fusion - Google Patents

Detector positioning method and system based on image recognition and force feedback fusion Download PDF

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CN109993763B
CN109993763B CN201910243779.2A CN201910243779A CN109993763B CN 109993763 B CN109993763 B CN 109993763B CN 201910243779 A CN201910243779 A CN 201910243779A CN 109993763 B CN109993763 B CN 109993763B
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CN109993763A (en
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段星光
田焕玉
靳励行
潘月
温浩
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Beijing Institute of Technology BIT
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    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G06T7/13—Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G—PHYSICS
    • G21—NUCLEAR PHYSICS; NUCLEAR ENGINEERING
    • G21C—NUCLEAR REACTORS
    • G21C17/00—Monitoring; Testing ; Maintaining
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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Abstract

The embodiment of the invention discloses a detector positioning method and a detector positioning system based on image recognition and force feedback fusion, wherein the method comprises the following steps: the method comprises the steps of carrying out image preprocessing on collected image data, obtaining contour information of a detector in the image data, carrying out primary position fitting on the detector based on the contour information, positioning the position information of the detector, controlling a mechanical arm to grab the detector according to the position information, and adjusting the grabbing state by combining feedback of a force sensor when the mechanical arm grabs the detector. By adopting the invention, the position of the detector is initially determined through image recognition, and then the grabbing state is adjusted along with the force feedback when the detector is grabbed, so that the aim of accurately and automatically replacing the detector can be realized.

Description

Detector positioning method and system based on image recognition and force feedback fusion
Technical Field
The invention relates to the technical field of automatic control, in particular to a detector positioning method and system based on image recognition and force feedback fusion.
Background
In the field of nuclear power robots, detectors are usually replaced by manual alignment and by semi-automatic tools. In this way, operators are not protected from low-dose radiation, and the residual radiation in the body after daily and monthly accumulation seriously affects the physical health of workers. Therefore, an unmanned operation on the biological shielding plate is a research focus in the field of the current nuclear power robot.
Disclosure of Invention
The embodiment of the invention provides a detector positioning method and system based on image recognition and force feedback fusion.
The first aspect of the embodiments of the present invention provides a detector positioning method based on image recognition and force feedback fusion, which may include:
carrying out image preprocessing on the acquired image data to acquire contour information of a detector in the image data;
performing primary position fitting on the detector based on the contour information, and positioning the position information of the detector;
and controlling the mechanical arm to grab the detector according to the position information.
In one possible design, the image data includes at least four detectors, and the positioning method further includes:
sequencing and numbering the detectors according to the distance between the positioned positions of the detectors and the mechanical arm;
and controlling the mechanical arm to grab the detectors at the corresponding numbers according to the sequencing numbers.
In one possible design, the positioning method further includes:
performing primary position fitting by adopting a circle or ellipse detection algorithm;
when four circles or ellipses are fit in the image data, the process of determining the primary position fit ends.
In one possible design, the positioning method further includes:
acquiring grabbing parameters when the mechanical arm grabs the detector based on the force sensor, and judging whether the mechanical arm enters a blocking state or not according to the grabbing parameters, wherein the grabbing parameters comprise the grabbing force and the grabbing direction;
when the mechanical arm enters a blocking state, performing position fitting on the detector again to obtain the relative position and the relative angle between the detector and the mechanical arm;
and adjusting the mechanical arm to exit the blocking state according to the relative position and the relative angle.
In one possible design, the positioning method further includes:
and filtering information noise points in the contour information by adopting a noise point filtering algorithm.
A second aspect of the embodiments of the present invention provides a detector positioning system based on image recognition and force feedback fusion, which may include:
the contour information acquisition module is used for carrying out image preprocessing on the acquired image data to acquire contour information of the detector in the image data;
the position fitting module is used for performing primary position fitting on the detector based on the contour information and positioning the position information of the detector;
and the grabbing control module is used for controlling the mechanical arm to grab the detector according to the position information.
In one possible design, the image data includes at least four detectors, and the positioning system further includes:
the sequencing numbering module is used for sequencing and numbering the detectors according to the distance between the positioned positions of the detectors and the mechanical arm;
and the grabbing control module is also used for controlling the mechanical arm to grab the detector at the corresponding number according to the sequencing number.
In one possible design, the positioning system further includes:
the position fitting module is also used for performing primary position fitting by adopting a circle or ellipse detection algorithm;
and the fitting end determining module is used for determining that the process of fitting the primary position is ended when four circles or ellipses are fitted in the image data.
In one possible design, the positioning system further includes:
the state judgment module is used for acquiring a grabbing parameter when the mechanical arm grabs the detector based on the force sensor, and judging whether the mechanical arm enters a blocking state or not according to the grabbing parameter, wherein the grabbing parameter comprises the grabbing force and the grabbing direction;
the position fitting module is also used for performing position fitting on the detector again when the mechanical arm enters a blocking state to obtain the relative position and the relative angle between the detector and the mechanical arm;
and the state adjusting module is used for adjusting the mechanical arm to exit the blocking state according to the relative position and the relative angle.
In one possible design, the positioning system further includes:
and the noise filtering module is used for filtering the information noise in the contour information by adopting a noise filtering algorithm.
In the embodiment of the invention, the position of the detector is initially determined through image recognition, and then the grabbing state is adjusted along with the force feedback when the detector is grabbed, so that the aim of accurately and automatically replacing the detector is fulfilled.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below.
FIG. 1 is a schematic flow chart of a detector positioning method based on image recognition and force feedback fusion according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a position fitting effect provided by an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a detector positioning system based on image recognition and force feedback fusion according to an embodiment of the present invention.
Detailed Description
The technical solution in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.
The following describes in detail a method for positioning a detector based on image recognition and force feedback fusion according to an embodiment of the present invention with reference to fig. 1 and 2.
Referring to fig. 1, a schematic flow chart of a detector positioning method based on image recognition and force feedback fusion is provided for an embodiment of the present invention. As shown in fig. 1, the method of the embodiment of the present invention may include the following steps S101 to S103.
S101, image preprocessing is carried out on the acquired image data, and outline information of the detector in the image data is obtained.
It should be noted that the positioning system may employ a monocular vision camera to scan the working area of the robot along with the movement of the robot, and obtain image data including the detector, where the image data may be a color picture.
Specifically, the positioning system may perform image preprocessing on the acquired image data to obtain profile information of the detector in the image data. It will be appreciated that the image pre-processing process described above may be a process that trains filter parameters using a convolutional neural network. The convolutional neural network can be a convolutional neural network comprising a convolutional-pooling-full-connection three-layer network, and the filtering parameters can be applied to subsequent operation of fitting the position of the detector through a circle or an ellipse. Further, the strong corresponding points of the edge of the detector can be obtained through edge detection, and the contour information of the detector can be obtained through binarization processing of the strong corresponding points.
In an alternative embodiment, the positioning system may use a noise filtering algorithm to filter information noise in the profile information. Preferably, a method of first opening operation and then closing operation can be adopted to filter noise in the binarization threshold value parameter.
And S102, performing primary position fitting on the detector based on the contour information, and positioning the position information of the detector.
Specifically, the positioning system may perform a first position fitting on the detector by using the contour information, and position the position information of the detector, where it is understood that the position information may indicate the position of the detector in the current working area.
In alternative embodiments, the positioning system may use a circle or ellipse detection algorithm to perform the fitting operation of the primary position fitting described above. The image data may include 4 detectors, or may include other numbers of detectors, which are determined according to the working environment of the field or the working mode of the robot, where the number of detectors is a preferred number. It should be noted that after the position information and the radius information of the circle are obtained by performing circle or ellipse fitting, a circle with an appropriate size may be screened out, and the number may be counted. In a specific implementation, when four circles or ellipses are fitted to the image data, the detector in the image data may be considered to be successfully identified (for example, the identification result diagram shown in fig. 2), and the process of determining the initial position fitting may be ended.
In a specific implementation manner of the embodiment of the invention, the positioning system can adopt a hough circle detection algorithm to fit a circle or an ellipse. The HoughCallices function in the algorithm can be mainly used, and particularly, the detection range of the circle can be in the range of 15mm-40 mm.
And S103, controlling the mechanical arm to grab the detector according to the position information.
Specifically, the positioning system can control the mechanical arm to grab the detector according to the position information.
In an alternative embodiment, when there are 4 detectors in the image data, the positioning system may sequence and number the detectors according to the distance between the position of each positioned detector and the mechanical arm, for example, in the order from the near to the far before performing the capture control. Furthermore, the mechanical arm can be controlled to grab the detectors at the corresponding serial numbers according to the sequencing serial numbers.
In an optional embodiment, the positioning system may obtain a grabbing parameter when the mechanical arm grabs the detector based on the force sensor, and determine whether the mechanical arm enters a jamming state according to the grabbing parameter, where it is understood that the grabbing parameter may include a grabbing force and a grabbing direction, and the jamming state may be a state where a gripper of the mechanical arm is not sleeved in the detector. Further, when the mechanical arm enters the blocking state, the detector can be subjected to position fitting again, the relative position and the relative angle between the detector and the mechanical arm are obtained, and the mechanical arm is adjusted to exit the blocking state according to the relative position and the relative angle.
In the embodiment of the invention, the position of the detector is initially determined through image recognition, and then the grabbing state is adjusted along with the force feedback when the detector is grabbed, so that the aim of accurately and automatically replacing the detector is fulfilled.
In a specific implementation manner of the embodiment of the invention, the attitude and the position of the detector can be solved through circle image recognition.
Figure BDA0002010452810000051
Wherein the content of the first and second substances,
Figure BDA0002010452810000052
representing a rotation matrix in the world coordinate system W to the camera coordinate system I.
Figure BDA0002010452810000053
Is the vector corresponding to the maximum distance from the origin of the identified ellipse to the locus of the ellipse in the image coordinate system { I }.
Figure BDA0002010452810000054
Is the corresponding vector of the minimum distance from the origin of the identified ellipse to the locus of the ellipse under the image coordinate system { I }.
At this time, the detector pose corresponds to the transfer matrix:
Figure BDA0002010452810000055
converting the conversion matrix estimator into corresponding quaternion by coordinate conversion
Figure BDA0002010452810000056
The following governing equation in cartesian coordinates can be introduced:
Figure BDA0002010452810000057
wherein the content of the first and second substances,
Figure BDA0002010452810000058
is the ideal attitude quaternion of the sensor under the { W } coordinate system, the actual value of which is the unit quaternion in the vertical direction,
Figure BDA0002010452810000059
corresponding to actual quaternion
Figure BDA00020104528100000510
qcommandIs an increment which guides the motor to move to realize control. Alternatively, the motor may be a servo motor based on CANopoen bus control.
The following describes in detail a detector positioning system based on image recognition and force feedback fusion according to an embodiment of the present invention with reference to fig. 3. It should be noted that the positioning system shown in fig. 3 is used for executing the method of the embodiment of the present invention shown in fig. 1 and fig. 2, and for convenience of description, only the portion related to the embodiment of the present invention is shown, and details of the specific technology are not disclosed, please refer to the embodiment of the present invention shown in fig. 1 and fig. 2.
Referring to fig. 3, a schematic structural diagram of a detector positioning system based on image recognition and force feedback fusion is provided for an embodiment of the present invention. As shown in fig. 3, the positioning system 10 of the embodiment of the present invention may include: the system comprises a contour information acquisition module 101, a position fitting module 102, a grabbing control module 103, a sequencing numbering module 104, a fitting end determination module 105, a state judgment module 106, a state adjustment module 107 and a noise filtering module 108.
The contour information acquiring module 101 is configured to perform image preprocessing on the acquired image data to acquire contour information of the detector in the image data.
It should be noted that the positioning system 10 can scan the working area of the robot with the monocular vision camera as the robot moves, and obtain the image data including the detector, which may be a color picture.
In a specific implementation, the contour information obtaining module 101 may perform image preprocessing on the acquired image data to obtain contour information of the detector in the image data. It will be appreciated that the image pre-processing process described above may be a process that trains filter parameters using a convolutional neural network. The convolutional neural network can be a convolutional neural network comprising a convolutional-pooling-full-connection three-layer network, and the filtering parameters can be applied to subsequent operation of fitting the position of the detector through a circle or an ellipse. Further, the strong corresponding points of the edge of the detector can be obtained through edge detection, and the contour information of the detector can be obtained through binarization processing of the strong corresponding points.
In an alternative embodiment, noise filtering module 108 can use a noise filtering algorithm to filter the information noise in the contour information. Preferably, a method of first opening operation and then closing operation can be adopted to filter noise in the binarization threshold value parameter.
And the position fitting module 102 is configured to perform primary position fitting on the detector based on the contour information, and locate position information of the detector.
In a specific implementation, the position fitting module 102 may perform primary position fitting on the detector by using the contour information, and position the position information of the detector, where it is understood that the position information may indicate the position of the detector in the current working area.
In alternative embodiments, the position fitting module 102 may perform the fitting operation of the primary position fitting using a circle or ellipse detection algorithm. The image data may include 4 detectors, or may include other numbers of detectors, which are determined according to the working environment of the field or the working mode of the robot, where the number of detectors is a preferred number. It should be noted that, after performing circle or ellipse fitting to obtain the position information and radius information of the circle, the positioning system 10 may screen out the circle with a suitable size and count the number. In a specific implementation, when four circles or ellipses are fitted to the image data, the fitting end determination module 105 may consider that the detector in the image data is successfully identified (for example, the identification result diagram shown in fig. 2), and may determine that the process of fitting the primary position is ended.
In a specific implementation manner of the embodiment of the invention, the positioning system can adopt a hough circle detection algorithm to fit a circle or an ellipse. The HoughCallices function in the algorithm can be mainly used, and particularly, the detection range of the circle can be in the range of 15mm-40 mm.
And the grabbing control module 103 is used for controlling the mechanical arm to grab the detector according to the position information.
In a specific implementation, the grabbing control module 103 may control the mechanical arm to grab the detector according to the position information.
In an alternative embodiment, when there are 4 detectors in the image data, the sequence numbering module 104 may sequence and number the detectors according to the distance between the position of the positioned detector and the mechanical arm, for example, in the order from the near to the far before performing the capture control. Further, the grabbing control module 103 may control the mechanical arm to grab the detectors at the corresponding numbers according to the above sorting numbers.
In an alternative embodiment, the state determining module 106 may obtain a grabbing parameter when the mechanical arm grabs the detector based on the force sensor, and determine whether the mechanical arm enters a jamming state according to the grabbing parameter, where it is understood that the grabbing parameter may include a grabbing force and a grabbing direction, and the jamming state may be a state where a gripper of the mechanical arm is not sleeved in the detector. Further, when the mechanical arm enters the jamming state, the position fitting module 102 may perform position fitting on the detector again to obtain a relative position and a relative angle between the detector and the mechanical arm, and the state adjusting module 107 may adjust the mechanical arm to exit the jamming state according to the relative position and the relative angle.
In the embodiment of the invention, the position of the detector is initially determined through image recognition, and then the grabbing state is adjusted along with the force feedback when the detector is grabbed, so that the aim of accurately and automatically replacing the detector is fulfilled.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
The above disclosure is only for the purpose of illustrating the preferred embodiments of the present invention, and it is therefore to be understood that the invention is not limited by the scope of the appended claims.

Claims (8)

1. A detector positioning method based on image recognition and force feedback fusion is characterized by comprising the following steps:
carrying out image preprocessing on the acquired image data to acquire contour information of a detector in the image data;
performing primary position fitting on the detector based on the contour information, and positioning position information of the detector;
controlling a mechanical arm to grab the detector according to the position information;
the method further comprises the following steps:
acquiring grabbing parameters when the mechanical arm grabs the detector based on a force sensor, and judging whether the mechanical arm enters a blocking state or not according to the grabbing parameters, wherein the grabbing parameters comprise the grabbing force and the grabbing direction;
when the mechanical arm enters a blocking state, performing position fitting on the detector again to obtain the relative position and the relative angle between the detector and the mechanical arm;
and adjusting the mechanical arm to exit the blocking state according to the relative position and the relative angle.
2. The method of claim 1, wherein the image data includes at least four detectors, the method further comprising:
sequencing and numbering the detectors according to the distance between the positioned positions of the detectors and the mechanical arm;
and controlling the mechanical arm to grab the detector at the corresponding number according to the sequencing number.
3. The method of claim 2, further comprising:
performing the primary position fitting by using a circle or ellipse detection algorithm;
when four circles or ellipses are fit in the image data, the process of determining the primary position fit ends.
4. The method of claim 1, further comprising:
and filtering information noise points in the contour information by adopting a noise point filtering algorithm.
5. A detector positioning system based on image recognition and force feedback fusion, comprising:
the contour information acquisition module is used for carrying out image preprocessing on the acquired image data to acquire contour information of the detector in the image data;
the position fitting module is used for performing primary position fitting on the detector based on the contour information and positioning the position information of the detector;
the grabbing control module is used for controlling the mechanical arm to grab the detector according to the position information;
the system further comprises:
the state judgment module is used for acquiring a grabbing parameter when the mechanical arm grabs the detector based on the force sensor, and judging whether the mechanical arm enters a blocking state or not according to the grabbing parameter, wherein the grabbing parameter comprises grabbing force and grabbing direction;
the position fitting module is further used for performing position fitting on the detector again when the mechanical arm enters a blocking state to obtain the relative position and the relative angle between the detector and the mechanical arm;
and the state adjusting module is used for adjusting the mechanical arm to exit the blocking state according to the relative position and the relative angle.
6. The system of claim 5, wherein the image data includes at least four detectors, the system further comprising:
the sequencing numbering module is used for sequencing and numbering the detectors according to the distance between the positioned positions of the detectors and the mechanical arm;
and the grabbing control module is also used for controlling the mechanical arm to grab the detectors at the corresponding numbers according to the sequencing numbers.
7. The system of claim 6, further comprising:
the position fitting module is also used for performing the primary position fitting by adopting a circle or ellipse detection algorithm;
and the fitting end determining module is used for determining that the process of fitting the primary position is ended when four circles or ellipses are fitted in the image data.
8. The system of claim 5, further comprising:
and the noise filtering module is used for filtering the information noise in the contour information by adopting a noise filtering algorithm.
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