CN111899145A - Three-dimensional warehouse inventory method and system based on machine vision - Google Patents

Three-dimensional warehouse inventory method and system based on machine vision Download PDF

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CN111899145A
CN111899145A CN202010535788.1A CN202010535788A CN111899145A CN 111899145 A CN111899145 A CN 111899145A CN 202010535788 A CN202010535788 A CN 202010535788A CN 111899145 A CN111899145 A CN 111899145A
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inventory
machine vision
information
goods
stacker
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陶培胜
刀荣贵
张玉彬
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Hongta Tobacco Group Co Ltd
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Hongta Tobacco Group Co Ltd
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Abstract

The invention discloses a machine vision-based three-dimensional warehouse inventory method and a machine vision-based three-dimensional warehouse inventory system, wherein the method comprises the following steps: 1) the WMS issues a stock inventory command; 2) traversing the goods space by the industrial camera; 3) triggering an industrial camera to take a picture; 4) transmitting the picture and the position information to a computer; 5) processing the photo identification bar code; 6) generating a machine vision and WMS inventory information comparison table; 7) checking whether the positions of the inventory information materials and the bar codes are consistent or not; 8) and outputting an inventory report. Compared with the prior art, the invention has the beneficial effects that: the bar code information of the box body can be effectively identified, and the method has the advantages of high speed, high accuracy and the like. The bar codes of different varieties and different specifications can be identified, the stacker and the unmanned aerial vehicle are accurately positioned, and the upper WMS generates a report form to integrate two source information, so that accurate inventory information is obtained.

Description

Three-dimensional warehouse inventory method and system based on machine vision
Technical Field
The invention belongs to a three-dimensional warehouse inventory method, and particularly relates to a three-dimensional warehouse inventory method and a three-dimensional warehouse inventory system based on machine vision.
Background
Under the new trend that intelligent manufacturing 2025 is continuously promoted, the industrial field gradually develops towards the direction of unmanned workshops in order to solve the pressure problem caused by the continuously rising labor cost, and higher requirements are put forward on the automation degree of production equipment. In the aspect of three-dimensional warehouse management with higher automation degree, due to the existence of machine faults or human handling errors and other conditions, inventory information is inconsistent with a real object, warehouse checking operation needs to be carried out regularly or irregularly, an original operation mode is that a worker holds a printed goods location information list to be checked by a stacker near a goods location of the real object, and the operation method has the following problems:
1. security risk: at present, most of stacking machines on the market are designed aiming at cargo carrying, personal safety guarantee measures are not included in the design, the designed safety level can not meet the requirement of carrying people, and people can face huge high-altitude falling risks when riding to a stock room;
2. the workload is large: generally, the goods space corresponding to one tunnel of the stacker has more than thousands of orders of magnitude, and if people approach to check one by one, a great deal of time and energy are consumed;
3. the production efficiency is low: the application scene of the automatic three-dimensional warehouse is generally that the warehouse is in a production field warehouse with high turnover rate or a logistics hub warehouse, the requirement on warehouse entry and exit efficiency is extremely high, if manual warehouse entry is adopted, the existing warehouse entry and exit operation must be stopped, and the whole production process is stopped before the warehouse entry is finished.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide an intelligent, efficient, safe and accurate three-dimensional warehouse inventory method and system based on machine vision.
In order to achieve the purpose, the invention is realized by the following technical scheme: the machine vision-based three-dimensional library inventory method comprises the following steps:
1) the WMS issues a stock inventory command;
2) traversing the goods space by the industrial camera;
3) triggering an industrial camera to take a picture;
4) transmitting the picture and the position information to a computer;
5) processing the photo identification bar code;
6) generating a machine vision and WMS inventory information comparison table;
7) checking whether the positions of the inventory information materials and the bar codes are consistent or not;
8) and outputting an inventory report.
Preferably, the step 2) comprises the following steps:
21) calling the TDCS to respectively drive each stacker loading platform to traverse the goods space of the three-dimensional gallery of the roadway, wherein the operation sequence is from 1 row to 1 layer to the last row to finish the traversal of the goods space of 1 layer;
22) rising one layer to reach the last 2 layers, and returning to the 1 row 2 layers to complete the traversal of the 2 layers of cargo space;
23) by analogy, all cargo spaces are completed by using an S-shaped motion track.
3. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 3) comprises the following steps:
31) the precise positioning of a stacker cargo carrying platform (together with an industrial camera mounted on the stacker cargo carrying platform) is realized by using a laser range finder and a running and lifting encoder;
32) and controlling an output electric signal by using a stacker onboard PLC at the moment of reaching the accurate position, and triggering an industrial camera to take a picture.
Preferably, the step 5) comprises the following steps:
51) removing image noise by using low-pass filtering to carry out image blurring processing;
52) using the histogram with limited contrast to equalize the brightness characteristic and the edge characteristic of the image to enhance the image;
53) distinguishing crack characteristics of the image and a background for threshold segmentation;
54) and performing morphological operation on the black characteristic region and the white characteristic region of the image by using expansion operation and corrosion operation.
Preferably, the step 6) comprises the following steps:
61) determining a bar code characteristic region capable of distinguishing material varieties according to the coding specification;
62) extracting feature region codes by using a filter algorithm;
63) and comparing the obtained characteristic region codes with a BOM list table of the materials for operation, finding out matching items and determining the variety of the materials.
Preferably, the step 7) comprises the following steps:
71) acquiring the position information of the current cargo carrying platform of the stacker by using a TDCS system through an NPORT technology, wherein the position is defined as a visual identification position;
72) using a WMS system to obtain corresponding goods position information and material information stored in the goods position;
73) comparing the material variety information and the position information obtained in the steps 63) and 71) with the material variety information and the position information obtained in the step 72), if the material variety information stored in the same goods space is consistent, writing the material variety information into a comparison information consistent table of a inventory result report, otherwise, writing the material variety information into a comparison information inconsistent table, and taking the two tables as an inventory to generate a report.
Preferably, the three-dimensional warehouse inventory system based on machine vision includes an upper management system, a communication system and a stacker, and the upper management system includes: the system comprises a WMS, a TDCS, a database and a photo processing system, wherein the photo processing system comprises a Python, an Opencv, a Pyzbar, a visual resource library and a bar code decoder; the communication system preferably selects Ethernet, wherein the Ethernet preferably selects Nport, and the stacker comprises a PLC, an I/O module, a cargo carrying platform, a cargo space, a traveling system and a lifting system. Wherein, the cargo platform is provided with an industrial camera; the goods space comprises the position of the goods space and materials placed on the goods space, a photographic region of interest (ROI) is arranged in the materials, and the ROI comprises a bar code; the walking system comprises a walking frequency converter, a walking motor and a walking encoder; the lifting system comprises a lifting frequency converter, a lifting motor and a lifting encoder.
Preferably, the operation mode of the disc library system is as follows: the upper dispatching system TDCS transmits the inventory command to a PLC of a stacker through an Ethernet Nport communication mode, the PLC transmits the command to a walking frequency converter and a lifting frequency converter, the walking frequency converter drives a walking motor to move to a row of a goods position, meanwhile, the lifting frequency converter drives the lifting motor to move a goods carrying platform to a layer of the goods position, the goods position is reached through the positioning of an encoder, at the moment, the PLC transmits a photographing command to an industrial camera on the goods carrying platform through an I/O module, the ROI of materials is photographed, then the position and the corresponding ROI are uploaded to a database of an upper system through the Ethernet Nport communication mode, and the photo processing system recognizes a bar code and then places the bar code in the corresponding goods position.
The invention has the beneficial effects that:
the bar code information of the box body can be effectively identified, and the method has the advantages of high speed, high accuracy and the like. The bar codes of different varieties and different specifications can be identified, the stacker and the unmanned aerial vehicle are accurately positioned, and the upper WMS generates a report form to integrate two source information, so that accurate inventory information is obtained.
Drawings
FIG. 1 is a flow chart of a method of the present invention;
FIG. 2 is a system block diagram of the present invention;
1 upper management system, 11 WMS, 12 TDCS, 13 database, 14 photo processing system, 141 Python, 142Opencv, 143 Pyzbar, 144 visual resource library, 145 bar code decoder, 2 communication system, 21 Ethernet, 211Nport, 3 stacker, 31 PLC, 32I/O module, 33 cargo carrying platform, 331 industrial camera, 34 cargo space, 341 position, 342 material, 3421 ROI, 34211 bar code, 35 walking system, 351 walking transducer, 352 walking motor, 353 walking encoder, 36 lifting system, 361 lifting transducer, 362 lifting motor, 363 lifting encoder.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the accompanying drawings and examples, which are not intended to limit the present invention.
The method comprises the following steps:
1) the WMS issues a stock inventory command;
2) traversing the goods space by the industrial camera;
3) triggering an industrial camera to take a picture;
4) transmitting the picture and the position information to a computer;
5) processing the photo identification bar code;
6) generating a machine vision and WMS inventory information comparison table;
7) checking whether the positions of the inventory information materials and the bar codes are consistent or not;
8) and outputting an inventory report.
The step 2) comprises the following steps:
21) calling the TDCS to respectively drive each stacker loading platform to traverse the goods space of the three-dimensional gallery of the roadway, wherein the operation sequence is from 1 row to 1 layer to the last row to finish the traversal of the goods space of 1 layer;
22) rising one layer to reach the last 2 layers, and returning to the 1 row 2 layers to complete the traversal of the 2 layers of cargo space;
23) by analogy, all goods positions are moved by using an S-shaped motion track;
the step 3) comprises the following steps:
31) the precise positioning of a stacker cargo carrying platform (together with an industrial camera mounted on the stacker cargo carrying platform) is realized by using a laser range finder and a running and lifting encoder;
32) and controlling an output electric signal by using a stacker onboard PLC at the moment of reaching the accurate position, and triggering an industrial camera to take a picture.
The step 5) comprises the following steps:
51) removing image noise by using low-pass filtering to carry out image blurring processing;
52) using the histogram with limited contrast to equalize the brightness characteristic and the edge characteristic of the image to enhance the image;
53) distinguishing crack characteristics of the image and a background for threshold segmentation;
54) and performing morphological operation on the black characteristic region and the white characteristic region of the image by using expansion operation and corrosion operation.
The step 6) comprises the following steps:
61) determining a bar code characteristic region capable of distinguishing material varieties according to the coding specification;
62) extracting feature region codes by using a filter algorithm;
using a string interception algorithm:
Substring（param1，param2）
the first parameter is the start position, which is the initial position of the original string: note that: is taken from that location, but does not include this point,
the second parameter is the ending position, which can be omitted, if omitted, the starting position is taken to the end, if not omitted, the specified length is taken, if the length exceeds the length of the original character string, the error is reported, and this is considered to be a Bug. For example:
"abcdefg". Substring (3,2) "results: de
"abcdefg". Substring (3,12) results: error report
"abcdefg". Substring (3) "results: defg
Using string interception algorithms the following results can be obtained
String code32=” 913159131232030104120400001070720”
code32.Substring(2,6)= “315913”
Finally, obtaining a material characteristic region code: 315913
63) Comparing the obtained characteristic region codes with a BOM list table of the materials, finding out matching items and determining the variety of the materials;
631) fetching BOM inventory tables from database
DataTable dtItem=new DataTable();
632) Cyclically fetched data is compared with the intercepted character string
For(int i=0;i<dtItem.Rows.count;i++){
If(dtItem.row[i][“BARCODE”].tostring()==code32){
Return true;/
}else{
Return fase;//
}
}
The stereoscopic library inventory method based on machine vision according to claim 1, wherein the step 7) comprises the following steps:
71) acquiring the position information of the current cargo carrying platform of the stacker by using a TDCS system through an NPORT technology, wherein the position is defined as a visual identification position;
72) using a WMS system to obtain corresponding goods position information and material information stored in the goods position;
73) comparing the material variety information and the position information obtained in the steps 63) and 71) with the material variety information and the position information obtained in the step 72), if the material variety information stored in the same goods space is consistent, writing the material variety information into a comparison information consistent table of a inventory result report, otherwise, writing the material variety information into a comparison information inconsistent table, and taking the two tables as an inventory to generate a report.
The system comprises: upper management system, communication system, stacker.
The upper management system comprises: WMS, TDCS, database, photo processing system. The photo processing system comprises Python, Opencv, Pyzbar, a visual resource library and a bar code decoder.
The communication system is preferably an ethernet, wherein the ethernet is preferably Nport.
The stacker comprises a PLC, an I/O module, a cargo carrying platform, a cargo space, a traveling system and a lifting system. Wherein, the cargo platform is provided with an industrial camera; the goods space comprises the position of the goods space and materials placed on the goods space, a photographic region of interest (ROI) is arranged in the materials, and the ROI comprises a bar code; the walking system comprises a walking frequency converter, a walking motor and a walking encoder; the lifting system comprises a lifting frequency converter, a lifting motor and a lifting encoder.
The working mode of the disc library system is as follows: the upper dispatching system TDCS transmits the inventory command to a PLC of a stacker through an Ethernet Nport communication mode, the PLC transmits the command to a walking frequency converter and a lifting frequency converter, the walking frequency converter drives a walking motor to move to a row of a goods position, meanwhile, the lifting frequency converter drives the lifting motor to move a goods carrying platform to a layer of the goods position, the goods position is reached through the positioning of an encoder, at the moment, the PLC transmits a photographing command to an industrial camera on the goods carrying platform through an I/O module, the ROI of materials is photographed, then the position and the corresponding ROI are uploaded to a database of an upper system through the Ethernet Nport communication mode, and the photo processing system recognizes a bar code and then places the bar code in the corresponding goods position.
The working mode of the disc library system is as follows: the upper dispatching system TDCS12 transmits a inventory command to a PLC31 of the stacker 3 through an Ethernet 21Nport211 communication mode, the PLC31 transmits the command to a walking frequency converter 35 and a lifting frequency converter 36, the walking frequency converter 351 drives a walking motor 352 to move to the row of the goods position 341, the lifting frequency converter 361 drives a lifting motor 362 to move the goods carrying table 33 to the layer of the goods position 341, the goods position 341 is located through encoders 353 and 363, at the moment, the PLC31 transmits a photographing command to an industrial camera 331 on the goods carrying table 33 through an I/O module 32, a picture of an ROI3421 of the material is taken, the position 341 and the corresponding ROI3421 are uploaded to a database 13 of the upper system 1 through the Ethernet 21Nport211 communication mode, and the picture processing system 14 recognizes 34211 and places the barcode in the corresponding goods position 341.
The above embodiments are merely intended to illustrate the technical solution of the present invention and not to limit the same, and although the present invention has been described in detail by the above embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the scope of the invention defined by the appended claims.

Claims (9)

1. A three-dimensional warehouse inventory method and a system based on machine vision are characterized in that: the machine vision-based three-dimensional library inventory method comprises the following steps:
1) the WMS issues a stock inventory command;
2) traversing the goods space by the industrial camera;
3) triggering an industrial camera to take a picture;
4) transmitting the picture and the position information to a computer;
5) processing the photo identification bar code;
6) generating a machine vision and WMS inventory information comparison table;
7) checking whether the positions of the inventory information materials and the bar codes are consistent or not;
8) and outputting an inventory report.
2. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 2) comprises the following steps:
21) calling the TDCS to respectively drive each stacker loading platform to traverse the goods space of the three-dimensional gallery of the roadway, wherein the operation sequence is from 1 row to 1 layer to the last row to finish the traversal of the goods space of 1 layer;
22) rising one layer to reach the last 2 layers, and returning to the 1 row 2 layers to complete the traversal of the 2 layers of cargo space;
23) by analogy, all cargo spaces are completed by using an S-shaped motion track.
3. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 3) comprises the following steps:
31) the precise positioning of a stacker cargo carrying platform (together with an industrial camera mounted on the stacker cargo carrying platform) is realized by using a laser range finder and a running and lifting encoder;
32) and controlling an output electric signal by using a stacker onboard PLC at the moment of reaching the accurate position, and triggering an industrial camera to take a picture.
4. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 5) comprises the following steps:
51) removing image noise by using low-pass filtering to carry out image blurring processing;
52) using the histogram with limited contrast to equalize the brightness characteristic and the edge characteristic of the image to enhance the image;
53) distinguishing crack characteristics of the image and a background for threshold segmentation;
54) and performing morphological operation on the black characteristic region and the white characteristic region of the image by using expansion operation and corrosion operation.
5. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 6) comprises the following steps:
61) determining a bar code characteristic region capable of distinguishing material varieties according to the coding specification;
62) extracting feature region codes by using a filter algorithm;
63) and comparing the obtained characteristic region codes with a BOM list table of the materials for operation, finding out matching items and determining the variety of the materials.
6. The stereoscopic library inventory method and system based on machine vision according to claim 1, wherein the step 7) comprises the following steps:
71) acquiring the position information of the current cargo carrying platform of the stacker by using a TDCS system through an NPORT technology, wherein the position is defined as a visual identification position;
72) using a WMS system to obtain corresponding goods position information and material information stored in the goods position;
73) comparing the material variety information and the position information obtained in the steps 63) and 71) with the material variety information and the position information obtained in the step 72), if the material variety information stored in the same goods space is consistent, writing the material variety information into a comparison information consistent table of a inventory result report, otherwise, writing the material variety information into a comparison information inconsistent table, and taking the two tables as an inventory to generate a report.
7. A three-dimensional warehouse inventory method and a system based on machine vision are characterized in that: the three-dimensional warehouse inventory system based on machine vision comprises an upper management system, a communication system and a stacker, wherein the upper management system comprises: the system comprises a WMS, a TDCS, a database and a photo processing system, wherein the photo processing system comprises a Python, an Opencv, a Pyzbar, a visual resource library and a bar code decoder; the communication system preferably selects Ethernet, wherein the Ethernet preferably selects Nport, and the stacker comprises a PLC, an I/O module, a cargo carrying platform, a cargo space, a traveling system and a lifting system.
8. Wherein, the cargo platform is provided with an industrial camera; the goods space comprises the position of the goods space and materials placed on the goods space, a photographic region of interest (ROI) is arranged in the materials, and the ROI comprises a bar code; the walking system comprises a walking frequency converter, a walking motor and a walking encoder; the lifting system comprises a lifting frequency converter, a lifting motor and a lifting encoder.
9. The machine vision based stereoscopic library inventory method and system as claimed in claim 7, wherein: the working mode of the disc library system is as follows: the upper dispatching system TDCS transmits the inventory command to a PLC of a stacker through an Ethernet Nport communication mode, the PLC transmits the command to a walking frequency converter and a lifting frequency converter, the walking frequency converter drives a walking motor to move to a row of a goods position, meanwhile, the lifting frequency converter drives the lifting motor to move a goods carrying platform to a layer of the goods position, the goods position is reached through the positioning of an encoder, at the moment, the PLC transmits a photographing command to an industrial camera on the goods carrying platform through an I/O module, the ROI of materials is photographed, then the position and the corresponding ROI are uploaded to a database of an upper system through the Ethernet Nport communication mode, and the photo processing system recognizes a bar code and then places the bar code in the corresponding goods position.
CN202010535788.1A 2020-06-12 2020-06-12 Three-dimensional warehouse inventory method and system based on machine vision Pending CN111899145A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113516617A (en) * 2021-04-02 2021-10-19 云南省烟草质量监督检测站 Flue-cured tobacco grade identification modeling method based on machine vision and AI deep learning
CN114751121A (en) * 2022-03-01 2022-07-15 红塔烟草(集团)有限责任公司 Automatic control system for visual inventory of three-dimensional warehouse

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113516617A (en) * 2021-04-02 2021-10-19 云南省烟草质量监督检测站 Flue-cured tobacco grade identification modeling method based on machine vision and AI deep learning
CN114751121A (en) * 2022-03-01 2022-07-15 红塔烟草(集团)有限责任公司 Automatic control system for visual inventory of three-dimensional warehouse

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