CN111099342A - Fuzzy grabbing method and device based on machine vision - Google Patents
Fuzzy grabbing method and device based on machine vision Download PDFInfo
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- CN111099342A CN111099342A CN201911417497.6A CN201911417497A CN111099342A CN 111099342 A CN111099342 A CN 111099342A CN 201911417497 A CN201911417497 A CN 201911417497A CN 111099342 A CN111099342 A CN 111099342A
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- shell
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B65—CONVEYING; PACKING; STORING; HANDLING THIN OR FILAMENTARY MATERIAL
- B65G—TRANSPORT OR STORAGE DEVICES, e.g. CONVEYORS FOR LOADING OR TIPPING, SHOP CONVEYOR SYSTEMS OR PNEUMATIC TUBE CONVEYORS
- B65G47/00—Article or material-handling devices associated with conveyors; Methods employing such devices
- B65G47/74—Feeding, transfer, or discharging devices of particular kinds or types
- B65G47/90—Devices for picking-up and depositing articles or materials
- B65G47/905—Control arrangements
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Abstract
The invention discloses a fuzzy grabbing method based on machine vision.A manipulator moves above a material cache region to hover, a 3D camera photographs and identifies the posture of a shell, the posture of the shell is compared with a built-in picture of a system, and a correction amount is automatically calculated and fed back to a robot; the robot revises the manipulator position according to the calculated result in order to adapt to the actual gesture of casing, and the manipulator snatchs the casing downwards, moves to and sweeps a position, with the fixed yard rifle of sweeping of casing two-dimensional code alignment, carries out model mistake proofing discernment, moves to the production line initial point after the model mistake proofing discernment, loosens behind the locating point on each fabrication hole alignment tray of casing, accomplishes the single and snatchs the action. The fault tolerance to the casing gesture is big, and the manipulator can the position of self-adaptation work piece in millimeter level error range, revises suitable position of snatching from the work position, prevents to snatch failure or striking casing scheduling problem and take place.
Description
Technical Field
The invention belongs to the technical field of automatic gearbox control, and particularly relates to a fuzzy grabbing method and device based on machine vision.
Background
With the rapid development of computer technology and digital image processing, machine vision technology is widely applied in the fields of automobile and automobile part manufacturing industry, machining industry and the like. At present, the traditional industrial robot can complete material handling and assembly on a production line only through point-by-point teaching, but field workpieces are often randomly placed, so that the industrial robot cannot complete operation tasks.
In the assembly process in the past, the transmission shell is manually carried to be on-line, and the shell shields the sight, so that the shell inevitably slightly collides with a tool positioning point. If the manipulator is used for grabbing, accurate positioning of the shell before the shell is on line needs to be guaranteed, otherwise, the manipulator cannot complete grabbing action 100% and even collides with the shell.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a fuzzy grabbing method and device based on machine vision, which overcome the defects of the existing control method, and after the control method is adopted, the problem of low fault tolerance of the manipulator for the position before the shell is automatically grabbed on the line is solved, and when the shell is roughly positioned (the positioning precision is in millimeter level), the position of the manipulator can be automatically corrected, and 100% automatic grabbing is realized.
In order to solve the technical problems, the technical scheme of the invention is as follows: a fuzzy grasping method based on machine vision is characterized by comprising the following steps:
the manipulator moves to the material cache region 1-A or the material cache region 1-B to hover, the 3D camera photographs and recognizes the posture of the shell, the photographed posture is compared with a built-in picture of the system, and the correction amount is automatically calculated and fed back to the robot;
the robot revises the manipulator position according to the calculated result in order to adapt to the actual gesture of casing, and the manipulator snatchs the casing downwards, moves to and sweeps the code position, and the fixed yard rifle of sweeping is aimed at to casing two-dimensional code, carries out the mistake proofing discernment of model.
An optimization scheme, further comprising:
moving to the initial point of the production line after correct identification, and loosening each process hole of the shell after aligning to a positioning point on the tray to complete single grabbing action, placing the shell at the initial point of the production line, and then entering the production line of the gearbox;
if the shell is not correctly identified, the shell is placed in a shell repair area to wait for being carried off line.
An optimization scheme, further comprising: after each layer of grabbing is finished, the manipulator automatically grabs the black blister tray to the left empty material area.
Based on the fuzzy capture method, the device for implementing the fuzzy capture method comprises the following steps:
the device comprises a material cache area, a 3D camera, a manipulator, a fixed code scanning gun, a PLC control system, a material vehicle, a guide rail and a shell repair area;
the material buffer area comprises a material buffer area 1-A, a material buffer area 1-B and a material buffer area 1-C, and the material buffer area 1-C is an empty material area.
The utility model provides an in the blister supporting plate that optimization scheme, the manipulator is installed at industrial robot front end, and the 3D camera is installed on the manipulator, and the casing is placed on the material car.
An optimized scheme is a shell repair area used for placing the shell two-dimensional code in the area when the two-dimensional code of the shell is not correctly identified.
By adopting the technical scheme, compared with the prior art, the invention has the following advantages: the postures of the shells in the blister tray are different, and the shells can translate, rotate or deviate in a small range; by adopting the fuzzy grabbing method, the fault tolerance to the posture of the shell is high, the manipulator can be self-adapted to the position of the workpiece within the millimeter-scale error range, and the position of the workpiece can be corrected from the working position to the proper grabbing position, so that the problems of grabbing failure or shell collision and the like are prevented.
Drawings
FIG. 1 is a schematic structural diagram of a fuzzy grabbing unit machine tool in the embodiment of the invention;
FIG. 2 is a top view of a fuzzy grasping unit machine tool in an embodiment of the present invention;
FIG. 3 is a right side view of a fuzzy grasping unit machine tool in an embodiment of the present invention;
figure 4 is a position diagram of a material cart, a guide rail and an industrial robot according to an embodiment of the invention.
In the figure, the position of the upper end of the main shaft,
1-a material buffer area, 2-a 3D camera, 3-a manipulator, 4-a fixed code scanning gun, 5-a PLC control unit, 6-an industrial robot, 7-a material vehicle, 8-a guide rail, 9-a production line starting point and 10-a shell repair area.
Detailed Description
In order to more clearly understand the technical features, objects and effects of the present invention, the embodiments of the present invention will be described with reference to the accompanying drawings, and it will be understood by those skilled in the art that the following should not be construed as limiting the scope of the present invention.
In an embodiment, as shown in fig. 1, fig. 2, fig. 3, and fig. 4, an apparatus for implementing a fuzzy grasping method based on machine vision includes:
the whole equipment mainly comprises a material cache region 1, a 3D camera 2, a manipulator 3, a fixed code scanning gun 4, a PLC control system 5, a material vehicle 7, a guide rail 8 and a shell repair region 10.
The material cache region 1 comprises a material cache region 1-A, a material cache region 1-B and a material cache region 1-C, and the material cache region 1-C is an empty material region; and once one of the material buffer areas 1-A and 1-B is short of materials and the skip car is not replaced in time, the manipulator automatically grabs the shell from the other buffer area.
The manipulator 3 is installed at the front end of the industrial robot 6, the 3D camera 2 is installed on the manipulator 3, the shell is placed in a plastic uptake tray on the material trolley 7, and the line edge material cache region 1-A and the material cache region 1-B are manually pushed into the two mutually standby cache regions and lock the material trolley 7.
The shell repair area 10 is placed in the area once the two-dimension code of the shell is not correctly identified, and is manually carried and offline.
Because a certain gap amount exists between the material trolley 7 and the guide rail 8 and between the shell and the black blister tray, the position of the material trolley 7 relative to the manipulator 3 and the position and the posture of the shell relative to the black blister tray after being locked each time have randomness in a certain range.
The fuzzy capture method comprises the following steps:
the working process is as follows: the mechanical arm 3 moves to the material cache region 1-A or the material cache region 1-B to hover, the 3D camera 2 photographs and recognizes the posture of the shell, the images are compared with the built-in images of the system, the correction amount is automatically calculated and fed back to the robot, the robot corrects the position of the mechanical arm 3 according to the calculation result to adapt to the actual posture of the shell, the mechanical arm 3 grips the shell downwards, the shell moves to the code scanning position, the two-dimensional code of the shell is aligned to the fixed code scanning gun 4 to perform the error-proof recognition of the model, the shell moves to the initial point 9 of the production line after the correct recognition, each process hole of the shell is aligned to the positioning point on the tray and then released to complete the single gripping action, the shell is placed at the initial point 9; if not, the shell is placed in the shell rework area 10 and awaits handling off-line. After each layer of grabbing is finished, the manipulator 3 automatically grabs the black blister tray to the left empty material area; after each vehicle finishes grabbing, the material vehicle is manually replaced.
The foregoing is illustrative of the best mode of the invention and details not described herein are within the common general knowledge of a person of ordinary skill in the art. The scope of the present invention is defined by the appended claims, and any equivalent modifications based on the technical teaching of the present invention are also within the scope of the present invention.
Claims (6)
1. A fuzzy grasping method based on machine vision is characterized by comprising the following steps:
the manipulator (3) moves to the position above the material buffer area (1) to hover, the 3D camera (2) photographs and identifies the shell posture, the photographed posture is compared with a built-in picture of the system, the correction amount is automatically calculated, and the correction amount is fed back to the robot;
the robot revises manipulator (3) position according to the calculated result in order to adapt to the actual gesture of casing, and manipulator (3) snatch the casing downwards, moves to and sweeps a position, with casing two-dimensional code alignment fixed sweep yard rifle (4), carries out the wrong discernment of model mistake proofing.
2. The machine-vision-based blurred capture method of claim 1, further comprising:
after correct identification, moving to a production line starting point (9), aligning each process hole of the shell to a positioning point on the tray, then loosening to complete a single grabbing action, placing the shell on the production line starting point (9), and then entering a gearbox production line;
if not, the shell is placed in a shell repair area (10) and waits for being carried off-line.
3. The machine-vision-based blurred capture method of claim 1, further comprising: after each layer of grabbing is finished, the manipulator (3) automatically grabs the black blister tray to the left empty material area.
4. An apparatus for implementing the machine vision-based blur capture method according to claim 1, comprising:
the device comprises a material cache region (1), a 3D camera (2), a mechanical arm (3), a fixed code scanning gun (4), a PLC control system (5), a material vehicle (7), a guide rail (8) and a shell repair region (10);
the material buffer area (1) comprises a material buffer area (1-A), a material buffer area (1-B) and a material buffer area (1-C), and the material buffer area (1-C) is an empty material area.
5. The apparatus of claim 4, wherein:
the manipulator (3) is installed at the front end of the industrial robot (6), the 3D camera (2) is installed on the manipulator (3), and the shell is placed in a plastic suction tray on the material trolley (7).
6. The apparatus of claim 4, wherein:
and the shell repair area (10) is used for placing the shell two-dimensional code in the area when the shell two-dimensional code is not correctly identified.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201911417497.6A CN111099342A (en) | 2019-12-31 | 2019-12-31 | Fuzzy grabbing method and device based on machine vision |
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| CN201911417497.6A CN111099342A (en) | 2019-12-31 | 2019-12-31 | Fuzzy grabbing method and device based on machine vision |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112340435A (en) * | 2020-10-23 | 2021-02-09 | 哈尔滨工程大学 | Grabbing sensing and controlling method of logistics carrying robot |
| CN114435827A (en) * | 2021-12-24 | 2022-05-06 | 北京无线电测量研究所 | Wisdom warehouse system |
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| CN114435827A (en) * | 2021-12-24 | 2022-05-06 | 北京无线电测量研究所 | Wisdom warehouse system |
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Application publication date: 20200505 |