CN103336282A - Automatic cabin positioning device and positioning method thereof - Google Patents
Automatic cabin positioning device and positioning method thereof Download PDFInfo
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- CN103336282A CN103336282A CN2013102384035A CN201310238403A CN103336282A CN 103336282 A CN103336282 A CN 103336282A CN 2013102384035 A CN2013102384035 A CN 2013102384035A CN 201310238403 A CN201310238403 A CN 201310238403A CN 103336282 A CN103336282 A CN 103336282A
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Abstract
The invention discloses an automatic cabin positioning device and a positioning method thereof. The positioning device is mounted on a bulkhead wall mobile type ship loader. The positioning method comprises the following steps: 1, shrinking a cantilever of the ship loader, lifting the cantilever to form a 70-degree angle with the ground, operating a cart to one side of the head of a ship, and operating the cart from the head of the ship to the tail of the ship; 2, operating the automatic cabin positioning device and scanning the ship to acquire the two-dimensional coordinate information of the ship; 3, preprocessing by using an industrial person computer to acquire the adaptive gray-level image value of the ship; 4, extracting the two-dimensional gray-level image characteristics of the ship by using the industrial personal computer to obtain the edge, near the sea, of the ship; and 5, performing binarization processing on the two-dimensional gray-level image of the ship by using the industrial personal computer to obtain the cabin position of the ship. The automatic cabin positioning device and the positioning method thereof are not influenced by environment and temperature, can detect the position and the related information of the ship effectively and accurately, and can monitor the whole process real-timely. The automatic cabin positioning device is simple in structure, simple to operate and low in cost.
Description
Technical field
The present invention relates to a kind of cabin locating device and method, be specifically related to a kind of automatic cabin locating device and localization method thereof.
Background technology
Nowadays, increasing harbour is turning to unmanned intelligent harbour from the artificial mechanism harbour.Along with the sustainable development of international carriage and bulk goods logistics, the automatic improving of bulk cargo terminals also will be inexorable trend.The available technology adopting digital camera head need be fixed on a standardized marking image on the control target in advance as imageing sensor.By assisting of mark, can use vision system to calculate the three-dimensional coordinate of target.The method of digital camera head is applicable to machine itself.But for the automatic control of bulk cargo terminals machinery, this method is restricted.Dry bulk cargo and bulk freighter installation code marking image are very difficult, and the bulk cargo terminals environment is very abominable, adopt digital camera head and standard marking image can reduce the reliability of digital video camcorder vision system.
Summary of the invention
The object of the present invention is to provide a kind of automatic cabin locating device and localization method thereof, be not subjected to environment, Temperature Influence, can detect position and the relevant information of cabin efficiently and accurately, and whole process monitored in real time, apparatus structure is simple, and is simple to operate, with low cost.
In order to achieve the above object, the present invention is achieved through the following technical solutions: a kind of automatic cabin locating device, be installed on the bulkhead wall moving type ship loader, and be characterized in, comprise: two-dimensional laser radar and industrial computer;
Above-mentioned two-dimensional laser radar is installed on the square maintenance platform of slide bucket of ship loader;
Between above-mentioned two-dimensional laser radar and the industrial computer by optical fiber and Shielded Twisted Pair Data transmission;
Above-mentioned two-dimensional laser radar is transferred to industrial computer as vision sensor with scan image data;
Above-mentioned industrial computer carries out Treatment Analysis to scan image;
Above-mentioned industrial computer also is connected with the display that can show current scanning picture in real time.
A kind of localization method for above-mentioned automatic cabin locating device,
Above-mentioned localization method comprises:
Step 2, the automatic cabin locating device of operation, the two-dimensional laser radar is started working, and boats and ships are scanned, and obtains the two-dimensional coordinate information of boats and ships;
Step 4, industrial computer extract the two dimensional gray characteristics of image of boats and ships, obtain boats and ships by the edge of extra large side;
Step 5, industrial computer carry out binary conversion treatment to the two dimensional gray image of boats and ships, obtain the cabin position of boats and ships.
Above-mentioned step 2 also comprises following steps:
Step 2.1, above-mentioned two-dimensional laser radar are done a seashore side direction scanning every the boats and ships of 20ms, and each cross section is corresponding to a value of cart position coder;
Step 2.2, set up two-dimentional rectangular coordinate system;
Step 2.3, industrial computer obtain the two-dimensional laser radar to the cloud data of the air line distance formation of boats and ships analyzing spot;
Step 2.4, industrial computer are converted into the two-dimensional coordinate information corresponding with the cross section, place with cloud data.
Two-dimentional rectangular coordinate system in the above-mentioned step 2.2 is to be true origin with two-dimensional laser radar position, is the Y-axis positive dirction straight down, and the seashore side is that the X-axis positive dirction is set up.
Above-mentioned step 3 also comprises following steps:
Step 3.1, industrial computer obtain the self-adaptation gray-scale pixel values according to boats and ships number of contours strong point to the distance of two-dimensional laser radar;
Step 3.2, industrial computer obtain the distance of adjacent scanning cross-section according to the travelling speed information of cart;
Step 3.3, the industrial computer cross-section data that two-dimensional laser radar scanning is all carry out spatial recomposition, do interpolation every the 10cm pair cross-section, remove unnecessary cross-section data;
Step 3.4, industrial computer are rebuild the two dimensional gray image of boats and ships, and the two dimensional gray image are carried out filtering and noise reduction handle.
Boats and ships number of contours strong point obtains by following method in the above-mentioned step 3.1;
The self-defined gray-scale pixels threshold value of industrial computer k is as y〉during k, the point that expression is swept to this moment is boats and ships cabin inside or the water surface, define this pixel this moment is 0; When y＜=k, represent that this point is boats and ships number of contours strong point.
Above-mentioned step 4 also comprises following steps:
Step 4.1, when boats and ships pull in to shore, industrial computer is demarcated the seashore side;
The image array of step 4.2, the self-defined reconstruction of industrial computer is
, i wherein, j is the row and column of corresponding two dimensional gray image array respectively;
Step 4.3, the self-defined scan matrix P of industrial computer, the row of matrix P is according to on-site actual situations and require value, and the row of matrix P are taken as j;
Step 4.4, scan matrix P be scanning from top to bottom in image array H, obtains the profile of boats and ships;
Step 4.4, industrial computer are according to the gray pixels point distribution density ρ of the profile Ship ' of boats and ships;
Step 4.5, industrial computer obtain boats and ships by the edge of extra large side according to the variation of ρ value.
The gray pixels point distribution density ρ of the boats and ships in the above-mentioned step 4.4 obtains by following method:
Each element among the scan matrix P is corresponding to the pixel in the current scanning position of image array H, element
The time represent that this point is black, illustrate that this point is not the boats and ships profile; ρ is the ratio that the number of black color dots element in the current scanning area accounts for all elements among the scan matrix P.
Above-mentioned step 5 comprises:
Step 5.1, the self-defined square scan matrix T of industrial computer;
Step 5.2, scan matrix T begin from the image array H upper left corner with the interval of 1 or 2 pixel according to from left to right, order traversing graph from top to bottom is as matrix H, ρ in current T is during less than set-point, and the end of scan obtains the four edges edge of contiguous boats and ships cabin;
Step 5.3, industrial computer calculate position and the size of boats and ships cabin according to the four edges edge of boats and ships;
Step 5.4, industrial computer are corresponding with the value of cart position coder with the position of boats and ships cabin;
Step 5.5, cart moved to the boats and ships cabin of appointment.
During the end of scan, the middle point coordinate of scan matrix T is drawn the level of two illusions and the straight line of vertical direction thus in the boats and ships cabin in the above-mentioned step 5.2, when non-zero pixels point occurring for the first time separately, obtains the four edges edge of the boats and ships cabin that is close to.
A kind of automatic cabin locating device of the present invention and localization method thereof compared with prior art have the following advantages: owing to be provided with the two-dimensional laser radar, and two dimensional image that can the real time scan boats and ships; Owing to be provided with scan matrix P, can conveniently find boats and ships to lean on the edge of extra large side; Owing to be provided with square scan matrix T, the station keeping ship freight space is put fast.
Description of drawings
Fig. 1 is the automatic cabin locating device of the present invention synoptic diagram.
Fig. 2 is the automatic cabin localization method of the present invention process flow diagram.
Fig. 3 is the automatic cabin locating device of the present invention cabin two-dimension image rebuild and feature extraction synoptic diagram.
Embodiment
Below in conjunction with accompanying drawing, by describing a preferable specific embodiment in detail, the present invention is further elaborated.
As shown in Figure 1, a kind of automatic cabin locating device is installed on the bulkhead wall moving type ship loader, comprises: two-dimensional laser radar 1 and industrial computer; Two-dimensional laser radar 1 is installed on the square maintenance platform of slide bucket of ship loader, the vision sensor part that is used as boats and ships 3 cabins location, obtain the outline data of boats and ships 3 cargo holds and pass to industrial computer, two-dimensional laser radar 1 sector scanning broad covered area, scanning angle reaches 270 degree; By optical fiber and Shielded Twisted Pair Data transmission, industrial computer has display between industrial computer and the two-dimensional laser radar 1, can show current scanning picture in real time.
As Fig. 2, shown in Figure 3, a kind of process flow diagram of the localization method for above-mentioned automatic cabin locating device, localization method comprises:
Step 2, the automatic cabin locating device of operation, two-dimensional laser radar 1 is started working, and boats and ships 3 are scanned, and obtains the two-dimensional coordinate information of boats and ships 3;
Step 2.1, two-dimensional laser radar 1 are done seashore side 4 scanning directions one time every the boats and ships 3 of 20ms, and each cross section is corresponding to a value of cart 2 position coders;
Step 2.2, being true origin with two-dimensional laser radar 1 position, is the Y-axis positive dirction straight down, and seashore side 4 is set up two-dimentional rectangular coordinate system for the X-axis positive dirction;
Step 2.3, industrial computer obtain two-dimensional laser radar 1 to the cloud data of the air line distance formation of boats and ships 3 analyzing spots;
Step 2.4, industrial computer are converted into the two-dimensional coordinate information corresponding with the cross section, place with cloud data.
Step 3.1, industrial computer obtain the self-adaptation gray-scale pixel values according to boats and ships 3 number of contours strong points to the distance of two-dimensional laser radar 1, the self-defined gray-scale pixels threshold value of industrial computer k, as y〉during k, the point that expression is swept to this moment is boats and ships 3 cabin inside or the waters surface, define this pixel this moment is 0; When y＜=k, represent that this point is boats and ships 3 number of contours strong points;
Step 3.2, industrial computer obtain the distance of adjacent scanning cross-section according to the travelling speed information of cart 2;
Step 3.3, industrial computer carry out spatial recomposition with all cross-section datas of two-dimensional laser radar 1 scanning, do interpolation every the 10cm pair cross-section, remove unnecessary cross-section data;
Step 3.4, industrial computer are rebuild the two dimensional gray image of boats and ships 3, and the two dimensional gray image are carried out filtering and noise reduction handle.
As shown in Figure 3, step 4, industrial computer extract the two dimensional gray characteristics of image of boats and ships 3, obtain boats and ships 3 by the edge of extra large side;
Step 4.1, when boats and ships 3 pull in to shore, industrial computer is demarcated seashore side 4;
The image array of step 4.2, the self-defined reconstruction of industrial computer is
, i wherein, j is the row and column of corresponding two dimensional gray image array respectively;
Step 4.3, the self-defined scan matrix P of industrial computer, the row of matrix P is according to on-site actual situations and require value, and the row of matrix P are taken as j;
Step 4.4, scan matrix P be scanning from top to bottom in image array H, obtains the profile of boats and ships 3, and each element among the scan matrix P is corresponding to the pixel in the current scanning position of image array H, element
The time represent that this point is black, illustrate that this point is not boats and ships 3 profiles; ρ is the ratio that the number of black color dots element in the current scanning area accounts for all elements among the scan matrix P.；
Step 4.4, industrial computer are according to the gray pixels point distribution density ρ of the profile Ship ' 3 of boats and ships 3;
Step 4.5, industrial computer obtain boats and ships 3 by the edge of extra large side according to the variation of ρ value.
Step 5, industrial computer carry out binary conversion treatment to the two dimensional gray image of boats and ships 3, obtain the cabin position of boats and ships 3;
Step 5.1, the self-defined square scan matrix T of industrial computer;
Step 5.2, scan matrix T begin from the image array H upper left corner with the interval of 1 or 2 pixel according to from left to right, order traversing graph from top to bottom is as matrix H, ρ in current T is during less than set-point, the end of scan, when obtaining the four edges edge end of scan of contiguous boats and ships 3 cabins, the middle point coordinate of scan matrix T is in boats and ships 3 cabins, draw the level of two illusions and the straight line of vertical direction thus, when non-zero pixels point occurring for the first time separately, obtain the four edges edge of contiguous boats and ships 3 cabins;
Step 5.3, industrial computer calculate position and the size of boats and ships 3 cabins according to the four edges edge of boats and ships;
Step 5.4, industrial computer are corresponding with the value of cart 2 position coders with the position of boats and ships 3 cabins;
Step 5.5, cart 2 moved to boats and ships 3 cabins of appointment.
Although content of the present invention has been done detailed introduction by above preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple modification of the present invention with to substitute all will be apparent.Therefore, protection scope of the present invention should be limited to the appended claims.
Claims (10)
1. an automatic cabin locating device is installed on the bulkhead wall moving type ship loader, it is characterized in that, comprises: two-dimensional laser radar (1) and industrial computer;
Described two-dimensional laser radar (1) is installed on the square maintenance platform of slide bucket of ship loader;
Between described two-dimensional laser radar (1) and the industrial computer by optical fiber and Shielded Twisted Pair Data transmission;
Described two-dimensional laser radar (1) is transferred to industrial computer as vision sensor with scan image data;
Described industrial computer carries out Treatment Analysis to scan image;
Described industrial computer also is connected with the display that can show current scanning picture in real time.
2. localization method that is used for above-mentioned automatic cabin locating device is characterized in that described localization method comprises:
Step 1, ship loader cantilever shrink and rise, and rise to ground to be 70 degree angles, and cart (2) is moved to boats and ships (3) fore one side, and cart (2) moves to boats and ships (3) stern with given speed from boats and ships (3) fore;
Step 2, the automatic cabin locating device of operation, two-dimensional laser radar (1) is started working, and boats and ships (3) are scanned, and obtains the two-dimensional coordinate information of boats and ships (3);
Step 3, industrial computer carry out pre-service, obtain the self-adaptation grayscale image values of boats and ships (3);
Step 4, industrial computer extract the two dimensional gray characteristics of image of boats and ships (3), obtain boats and ships (3) by the edge of extra large side;
Step 5, industrial computer carry out binary conversion treatment to the two dimensional gray image of boats and ships (3), obtain the cabin position of boats and ships (3).
3. automatic cabin localization method as claimed in claim 2 is characterized in that described step 2 also comprises following steps:
Step 2.1, described two-dimensional laser radar (1) are done a seashore side (4) scanning direction every the boats and ships of 20ms (3), and each cross section is corresponding to a value of cart (2) position coder;
Step 2.2, set up two-dimentional rectangular coordinate system;
Step 2.3, industrial computer obtain two-dimensional laser radar (1) to the cloud data of the air line distance formation of boats and ships (3) analyzing spot;
Step 2.4, industrial computer are converted into the two-dimensional coordinate information corresponding with the cross section, place with cloud data.
4. automatic cabin localization method as claimed in claim 3, it is characterized in that, two-dimentional rectangular coordinate system in the described step 2.2 is to be true origin with two-dimensional laser radar (1) position, is the Y-axis positive dirction straight down, and seashore side (4) is that the X-axis positive dirction is set up.
5. automatic cabin localization method as claimed in claim 2 is characterized in that described step 3 also comprises following steps:
Step 3.1, industrial computer obtain the self-adaptation gray-scale pixel values according to boats and ships (3) number of contours strong point to the distance of two-dimensional laser radar (1);
Step 3.2, industrial computer obtain the distance of adjacent scanning cross-section according to the travelling speed information of cart (2);
Step 3.3, industrial computer scan all cross-section datas with two-dimensional laser radar (1) and carry out spatial recomposition, do interpolation every the 10cm pair cross-section, remove unnecessary cross-section data;
Step 3.4, industrial computer are rebuild the two dimensional gray image of boats and ships (3), and the two dimensional gray image are carried out filtering and noise reduction handle.
6. automatic cabin localization method as claimed in claim 5 is characterized in that, boats and ships in the described step 3.1 (3) number of contours strong point obtains by following method;
The self-defined gray-scale pixels threshold value of industrial computer k is as y〉during k, the point that expression is swept to this moment is boats and ships (3) cabin inside or the water surface, define this pixel this moment is 0; When y＜=k, represent that this point is boats and ships (3) number of contours strong point.
7. automatic cabin localization method as claimed in claim 2 is characterized in that described step 4 also comprises following steps:
Step 4.1, boats and ships (3) are when pulling in to shore, and industrial computer is demarcated seashore side (4);
The image array of step 4.2, the self-defined reconstruction of industrial computer is, i wherein, and j is the row and column of corresponding two dimensional gray image array respectively;
Step 4.3, the self-defined scan matrix P of industrial computer, the row of matrix P is according to on-site actual situations and require value, and the row of matrix P are taken as j;
Step 4.4, scan matrix P be scanning from top to bottom in image array H, obtains the profile of boats and ships (3);
Step 4.4, industrial computer are according to the gray pixels point distribution density ρ of the profile Ship ' (3) of boats and ships (3);
Step 4.5, industrial computer obtain boats and ships (3) by the edge of extra large side according to the variation of ρ value.
8. automatic cabin localization method as claimed in claim 7 is characterized in that, the gray pixels point distribution density ρ of the boats and ships in the described step 4.4 (3) obtains by following method:
Each element among the scan matrix P represents during element that corresponding to the pixel in the current scanning position of image array H this point is black, illustrates that this point is not boats and ships (3) profiles; ρ is the ratio that the number of black color dots element in the current scanning area accounts for all elements among the scan matrix P.
9. automatic cabin localization method as claimed in claim 2 is characterized in that described step 5 comprises:
Step 5.1, the self-defined square scan matrix T of industrial computer;
Step 5.2, scan matrix T begin from the image array H upper left corner with the interval of 1 or 2 pixel according to from left to right, order traversing graph from top to bottom is as matrix H, ρ in current T is during less than set-point, and the end of scan obtains the four edges edge of contiguous boats and ships (3) cabin;
Step 5.3, industrial computer calculate position and the size of boats and ships (3) cabin according to the four edges edge of boats and ships;
Step 5.4, industrial computer are corresponding with the value of cart (2) position coder with the position of boats and ships (3) cabin;
Step 5.5, cart (2) moved to boats and ships (3) cabin of appointment.
10. automatic cabin localization method as claimed in claim 9, it is characterized in that, in the described step 5.2 during the end of scan, the middle point coordinate of scan matrix T is in boats and ships (3) cabin, draw the level of two illusions and the straight line of vertical direction thus, when non-zero pixels point occurring for the first time separately, obtain the four edges edge of contiguous boats and ships (3) cabin.
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103696711A (en) * | 2013-12-25 | 2014-04-02 | 青岛杰瑞自动化有限公司 | Robot for drilling operation |
| CN106933232A (en) * | 2017-04-27 | 2017-07-07 | 上海大学 | A kind of context aware systems and method based on collaboration unmanned boat group |
| CN107309619A (en) * | 2017-06-23 | 2017-11-03 | 福建宝中海洋工程股份有限公司 | A kind of ship mount point is to position detecting system |
| CN107514167A (en) * | 2017-07-18 | 2017-12-26 | 武汉智象机器人有限公司 | Vehicle identification system and storage method based on fixed radar and movable radar |
| CN110329907A (en) * | 2019-06-14 | 2019-10-15 | 上海驭矩信息科技有限公司 | The design of telescopic rod about a adjustable in length |
| CN112113506A (en) * | 2020-08-31 | 2020-12-22 | 天津蓝鳍海洋工程有限公司 | Underwater moving object measuring device and method based on deep learning |
| CN112529958A (en) * | 2020-12-10 | 2021-03-19 | 神华天津煤炭码头有限责任公司 | Single laser radar bulk cargo ship hatch position identification method |
| CN112859087A (en) * | 2020-12-31 | 2021-05-28 | 上海外高桥造船海洋工程有限公司 | Positioning method for ship floating state |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201004172Y (en) * | 2007-01-11 | 2008-01-09 | 上海港机重工有限公司 | Three-dimension material position detection device for harbor loading automated job |
| US20120033851A1 (en) * | 2010-04-22 | 2012-02-09 | Shen-En Chen | Spatially integrated aerial photography for bridge, structure, and environmental monitoring |
| US20120261516A1 (en) * | 2011-04-15 | 2012-10-18 | Patrick Gilliland | Ladar sensor for landing, docking and approach |
| CN202886922U (en) * | 2012-09-21 | 2013-04-17 | 天津港中煤华能煤码头有限公司 | A bucket wheel material taking system capable of automatically controlling material taking flow |
-
2013
- 2013-06-17 CN CN201310238403.5A patent/CN103336282B/en not_active Expired - Fee Related
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201004172Y (en) * | 2007-01-11 | 2008-01-09 | 上海港机重工有限公司 | Three-dimension material position detection device for harbor loading automated job |
| US20120033851A1 (en) * | 2010-04-22 | 2012-02-09 | Shen-En Chen | Spatially integrated aerial photography for bridge, structure, and environmental monitoring |
| US20120261516A1 (en) * | 2011-04-15 | 2012-10-18 | Patrick Gilliland | Ladar sensor for landing, docking and approach |
| CN202886922U (en) * | 2012-09-21 | 2013-04-17 | 天津港中煤华能煤码头有限公司 | A bucket wheel material taking system capable of automatically controlling material taking flow |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103696711A (en) * | 2013-12-25 | 2014-04-02 | 青岛杰瑞自动化有限公司 | Robot for drilling operation |
| CN103696711B (en) * | 2013-12-25 | 2016-04-06 | 青岛杰瑞工控技术有限公司 | A kind of drilling rod manipulation robot |
| CN106933232A (en) * | 2017-04-27 | 2017-07-07 | 上海大学 | A kind of context aware systems and method based on collaboration unmanned boat group |
| CN107309619A (en) * | 2017-06-23 | 2017-11-03 | 福建宝中海洋工程股份有限公司 | A kind of ship mount point is to position detecting system |
| CN107309619B (en) * | 2017-06-23 | 2018-12-28 | 福建宝中海洋工程股份有限公司 | A kind of ship installation point is to position detecting system |
| CN107514167A (en) * | 2017-07-18 | 2017-12-26 | 武汉智象机器人有限公司 | Vehicle identification system and storage method based on fixed radar and movable radar |
| CN110329907A (en) * | 2019-06-14 | 2019-10-15 | 上海驭矩信息科技有限公司 | The design of telescopic rod about a adjustable in length |
| CN112113506A (en) * | 2020-08-31 | 2020-12-22 | 天津蓝鳍海洋工程有限公司 | Underwater moving object measuring device and method based on deep learning |
| CN112529958A (en) * | 2020-12-10 | 2021-03-19 | 神华天津煤炭码头有限责任公司 | Single laser radar bulk cargo ship hatch position identification method |
| CN112529958B (en) * | 2020-12-10 | 2022-08-26 | 神华天津煤炭码头有限责任公司 | Single laser radar bulk cargo ship hatch position identification method |
| CN112859087A (en) * | 2020-12-31 | 2021-05-28 | 上海外高桥造船海洋工程有限公司 | Positioning method for ship floating state |
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