CN114119764A - Automatic guard board target positioning and aligning algorithm - Google Patents
Automatic guard board target positioning and aligning algorithm Download PDFInfo
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- CN114119764A CN114119764A CN202111125334.8A CN202111125334A CN114119764A CN 114119764 A CN114119764 A CN 114119764A CN 202111125334 A CN202111125334 A CN 202111125334A CN 114119764 A CN114119764 A CN 114119764A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/80—Analysis of captured images to determine intrinsic or extrinsic camera parameters, i.e. camera calibration
- G06T7/85—Stereo camera calibration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/60—Analysis of geometric attributes
- G06T7/66—Analysis of geometric attributes of image moments or centre of gravity
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- 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
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
- G06T7/75—Determining position or orientation of objects or cameras using feature-based methods involving models
Abstract
The invention discloses an automatic guard board target positioning and aligning algorithm, which comprises the following steps: acquiring a three-dimensional distance image of a target related in the installation process of the guardrail plate and a training image limited by the three-dimensional distance image with model characteristics by using a CCD (charge coupled device) camera; image dithering processing; estimating an error; selecting, by the vision processor: analyzing at least one training area of a training image having model features and determining a distribution of surface normal vectors within the at least one training area; and selecting at least one three-dimensional alignment algorithm from a plurality of available three-dimensional alignment algorithms based on the characteristics of the distribution to align features of the model with features of the runtime object. The invention replaces the observation of human eyes, is more accurate compared with the human eyes, adopts a conventional image processing mode, does not need to adopt a learning algorithm, has small calculated amount and real-time error estimation, provides a basis for real-time parameter correction of the controller and overcomes the image shaking interference under the CCD motion state.
Description
Technical Field
The invention relates to the technical field of intelligent construction sites, in particular to an automatic guard board target positioning and aligning algorithm.
Background
At present, the highway guardrail plate is installed by manual operation, and the labor intensity of the manual operation is high. The installation of the guard rail is carried out by a person (or persons) lifting the guard rail (usually a standard three-wave plate weighing 102 Kg) from the ground, leaning on the guard rail piles and then screwing the screws.
Because the side of the guardrail plate opposite to the guardrail pile is upward on the ground, the guardrail plate can be turned over to lean against the guardrail pile when being lifted in a mechanical mode, and then the screw is screwed, however, the aim of positioning and aligning the target cannot be provided in the moving process of the guardrail plate mounting equipment, and the aim of automatic mounting cannot be realized.
Disclosure of Invention
Based on the technical problems in the background art, the invention provides an automatic guard board target positioning and aligning algorithm.
The invention provides an automatic guard board target positioning and aligning algorithm, which comprises the following steps:
s1, acquiring a three-dimensional distance image of a target related in the installation process of the guard rail plate and a training image defined by the three-dimensional distance image with model characteristics by using a CCD camera;
s2 image dithering process:
generating a jitter matrix configuration file by software simulation according to the requirement of jitter processing;
writing the generated jitter matrix configuration file into the storage unit through an external main control unit in a form of software interface or hardware programming;
the content written into the storage unit and the image jitter overcoming algorithm circuit act together to realize image jitter processing;
the image is subjected to dithering and display to observe whether the processing effect accords with the software simulation effect; if the configuration meets the requirements, the configuration is finished; if the requirements are not met, processing is carried out again until the requirements are met;
s3 error estimation:
determining a target for the processed image, acquiring a coordinate origin of the target, and providing an error range estimation value for a controller in real time by adopting an estimation value of points and straight line points within a certain range and a fitting straight line;
s4 is selected by the vision processor: analyzing at least one training area of a training image having model features and determining a distribution of surface normal vectors within the at least one training area; and selecting at least one three-dimensional alignment algorithm from a plurality of available three-dimensional alignment algorithms based on the characteristics of the distribution to align features of the model with features of the runtime object.
Preferably, the target of step S1 includes: the edge and the gradient of the road surface, the height of the guardrail pile and the position of the screw hole, and the edge and the center line position of the movable guardrail plate.
Preferably, the "within certain range" and "point and straight line" estimated values and error range estimated values in step S3 all refer to: the relative error under standard illumination is 1%.
Preferably, the CCD camera comprises a plurality of discrete cameras at spaced apart locations to capture a scene of a plurality of angular objects.
Preferably, the training image is provided as a composite image acquired by a CCD being a camera, and the training is performed by locating at least one training area within the training image.
Preferably, the step S3 adopts an error estimation algorithm to obtain the estimation error.
Preferably, the step S3 obtains coordinates of the road surface edge in the target, a distance between the road surface edge and the guardrail pile, and a horizontal slope of the installation equipment; the height of the guardrail pile horizontal to the installation equipment, the position distance of the screw hole from the top of the guardrail pile and whether the three guardrail piles are parallel or not are judged; whether the edge of the guardrail plate is parallel to the central line and whether the edge of the guardrail plate is parallel to the guardrail pile in the moving process.
According to the automatic guardrail plate target positioning and aligning algorithm, observation of human eyes is replaced, the algorithm is more accurate compared with the human eyes, a conventional image processing mode is adopted, a learning algorithm is not needed, the calculated amount is small, real-time error estimation is achieved, a basis is provided for real-time parameter correction of a controller, and image shaking interference is overcome under the CCD motion state.
Drawings
Fig. 1 is a schematic flow chart of an automatic guard rail target positioning and aligning algorithm according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments.
Referring to fig. 1, an automated guardrail plate target positioning and alignment algorithm includes the steps of:
s1, acquiring a three-dimensional distance image of a target related in the installation process of the guard rail plate and a training image defined by the three-dimensional distance image with model characteristics by using a CCD camera;
s2 image dithering process:
generating a jitter matrix configuration file by software simulation according to the requirement of jitter processing;
writing the generated jitter matrix configuration file into the storage unit through an external main control unit in a form of software interface or hardware programming;
the content written into the storage unit and the image jitter overcoming algorithm circuit act together to realize image jitter processing;
the image is subjected to dithering and display to observe whether the processing effect accords with the software simulation effect; if the configuration meets the requirements, the configuration is finished; if the requirements are not met, processing is carried out again until the requirements are met;
s3 error estimation:
determining a target for the processed image, acquiring a coordinate origin of the target, and providing an error range estimation value for a controller in real time by adopting an estimation value of points and straight line points within a certain range and a fitting straight line;
s4 is selected by the vision processor: analyzing at least one training area of a training image having model features and determining a distribution of surface normal vectors within the at least one training area; and selecting at least one three-dimensional alignment algorithm from a plurality of available three-dimensional alignment algorithms based on the characteristics of the distribution to align features of the model with features of the runtime object.
In the present invention, the target of step S1 includes: the edge and the gradient of the road surface, the height of the guardrail pile and the position of the screw hole, and the edge and the center line position of the movable guardrail plate.
In the present invention, the "within certain range" and "point and straight line" estimated values and error range estimated values in step S3 all refer to: the relative error under standard illumination is 1%.
In the present invention, the CCD camera includes a plurality of dispersed cameras at spaced apart locations to capture a scene of a plurality of angular objects.
In the invention, the training image is provided by synthesizing images acquired by a CCD camera, and at least one training area is positioned in the training image to perform training.
In the present invention, the step S3 uses an error estimation algorithm to obtain the estimation error.
In the invention, the step S3 is to obtain the coordinates of the road surface edge in the target, the distance between the road surface edge and the guardrail pile and the horizontal gradient of the installation equipment; the height of the guardrail pile horizontal to the installation equipment, the position distance of the screw hole from the top of the guardrail pile and whether the three guardrail piles are parallel or not are judged; whether the edge of the guardrail plate is parallel to the central line and whether the edge of the guardrail plate is parallel to the guardrail pile in the moving process.
The invention comprises the following steps: acquiring a three-dimensional distance image of a target related in the installation process of the guardrail plate and a training image limited by the three-dimensional distance image with model characteristics by using a CCD (charge coupled device) camera; image dithering processing: generating a jitter matrix configuration file by software simulation according to the requirement of jitter processing; writing the generated jitter matrix configuration file into the storage unit through an external main control unit in a form of software interface or hardware programming; the content written into the storage unit and the image jitter overcoming algorithm circuit act together to realize image jitter processing; the image is subjected to dithering and display to observe whether the processing effect accords with the software simulation effect; if the configuration meets the requirements, the configuration is finished; if the requirements are not met, processing is carried out again until the requirements are met; and (3) error estimation: determining a target for the processed image, acquiring a coordinate origin of the target, and providing an error range estimation value for a controller in real time by adopting an estimation value of points and straight line points within a certain range and a fitting straight line; selecting, by the vision processor: analyzing at least one training area of a training image having model features and determining a distribution of surface normal vectors within the at least one training area; and selecting at least one three-dimensional alignment algorithm from a plurality of available three-dimensional alignment algorithms based on the characteristics of the distribution to align features of the model with features of the runtime object.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (7)
1. An automated guardrail plate target positioning and alignment algorithm, comprising the steps of:
s1, acquiring a three-dimensional distance image of a target related in the installation process of the guard rail plate and a training image defined by the three-dimensional distance image with model characteristics by using a CCD camera;
s2 image dithering process:
generating a jitter matrix configuration file by software simulation according to the requirement of jitter processing;
writing the generated jitter matrix configuration file into the storage unit through an external main control unit in a form of software interface or hardware programming;
the content written into the storage unit and the image jitter overcoming algorithm circuit act together to realize image jitter processing;
the image is subjected to dithering and display to observe whether the processing effect accords with the software simulation effect; if the configuration meets the requirements, the configuration is finished; if the requirements are not met, processing is carried out again until the requirements are met;
s3 error estimation:
determining a target for the processed image, acquiring a coordinate origin of the target, and providing an error range estimation value for a controller in real time by adopting an estimation value of points and straight line points within a certain range and a fitting straight line;
s4 is selected by the vision processor: analyzing at least one training area of a training image having model features and determining a distribution of surface normal vectors within the at least one training area; and selecting at least one three-dimensional alignment algorithm from a plurality of available three-dimensional alignment algorithms based on the characteristics of the distribution to align features of the model with features of the runtime object.
2. The automated guardrail board target positioning and alignment algorithm of claim 1 wherein the targets of step S1 comprise: the edge and the gradient of the road surface, the height of the guardrail pile and the position of the screw hole, and the edge and the center line position of the movable guardrail plate.
3. The automated balustrade target positioning and aligning algorithm of claim 1, wherein the "within range", "point and line" point estimates, error range estimates of step S3 are: the relative error under standard illumination is 1%.
4. The automated guardrail target positioning and alignment algorithm of claim 1 wherein the CCD cameras comprise a plurality of discrete cameras at spaced apart locations to capture a scene of a plurality of angular objects.
5. The automated guardrail board target positioning and alignment algorithm of claim 1 wherein the training images are provided as composite images captured by a CCD camera, and wherein training is performed to position at least one training area within the training images.
6. The automated balustrade target positioning and aligning algorithm of claim 1, wherein step S3 uses an error estimation algorithm to obtain the estimated error.
7. The automated guardrail board target positioning and alignment algorithm of claim 1 wherein step S3 obtains the coordinates of the road edges, the distance from the guardrail posts, and the slope from the installation equipment level in the target; the height of the guardrail pile horizontal to the installation equipment, the position distance of the screw hole from the top of the guardrail pile and whether the three guardrail piles are parallel or not are judged; whether the edge of the guardrail plate is parallel to the central line and whether the edge of the guardrail plate is parallel to the guardrail pile in the moving process.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111125334.8A CN114119764A (en) | 2021-09-26 | 2021-09-26 | Automatic guard board target positioning and aligning algorithm |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111125334.8A CN114119764A (en) | 2021-09-26 | 2021-09-26 | Automatic guard board target positioning and aligning algorithm |
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| CN114119764A true CN114119764A (en) | 2022-03-01 |
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| CN202111125334.8A Withdrawn CN114119764A (en) | 2021-09-26 | 2021-09-26 | Automatic guard board target positioning and aligning algorithm |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117532624A (en) * | 2024-01-10 | 2024-02-09 | 南京东奇智能制造研究院有限公司 | Automatic positioning and aligning method and system for guardrail plate installation |
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2021
- 2021-09-26 CN CN202111125334.8A patent/CN114119764A/en not_active Withdrawn
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117532624A (en) * | 2024-01-10 | 2024-02-09 | 南京东奇智能制造研究院有限公司 | Automatic positioning and aligning method and system for guardrail plate installation |
| CN117532624B (en) * | 2024-01-10 | 2024-03-26 | 南京东奇智能制造研究院有限公司 | Automatic positioning and aligning method and system for guardrail plate installation |
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Application publication date: 20220301 |