CN113213340B - Method, system, equipment and storage medium for unloading collection card based on lockhole identification - Google Patents
Method, system, equipment and storage medium for unloading collection card based on lockhole identification Download PDFInfo
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/18—Control systems or devices
- B66C13/48—Automatic control of crane drives for producing a single or repeated working cycle; Programme control
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C1/00—Load-engaging elements or devices attached to lifting or lowering gear of cranes or adapted for connection therewith for transmitting lifting forces to articles or groups of articles
- B66C1/10—Load-engaging elements or devices attached to lifting or lowering gear of cranes or adapted for connection therewith for transmitting lifting forces to articles or groups of articles by mechanical means
- B66C1/101—Load-engaging elements or devices attached to lifting or lowering gear of cranes or adapted for connection therewith for transmitting lifting forces to articles or groups of articles by mechanical means for containers
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C1/00—Load-engaging elements or devices attached to lifting or lowering gear of cranes or adapted for connection therewith for transmitting lifting forces to articles or groups of articles
- B66C1/10—Load-engaging elements or devices attached to lifting or lowering gear of cranes or adapted for connection therewith for transmitting lifting forces to articles or groups of articles by mechanical means
- B66C1/12—Slings comprising chains, wires, ropes, or bands; Nets
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B66—HOISTING; LIFTING; HAULING
- B66C—CRANES; LOAD-ENGAGING ELEMENTS OR DEVICES FOR CRANES, CAPSTANS, WINCHES, OR TACKLES
- B66C13/00—Other constructional features or details
- B66C13/18—Control systems or devices
- B66C13/46—Position indicators for suspended loads or for crane elements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
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- G06N3/00—Computing arrangements based on biological models
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Abstract
The invention provides a method, a system, equipment and a storage medium for unloading a set card based on lockhole identification, wherein the method comprises the following steps: horizontally calibrating a container spreader having a camera assembly; the method comprises the steps that pictures of lock holes are shot through each camera, a local picture area occupied by the lock holes is obtained through a neural network, a plane coordinate system is established, alignment error information is obtained according to errors of preset lifting positioning points, a container lifting tool is rotated according to the alignment error information and moves along a Y axis, when a lock head combination of the container lifting tool is overlapped with the lock hole combination in the Y axis direction, the alignment error information is sent to a container card, the container is moved through front and back running of the container card, when the lock head combination of the container lifting tool is overlapped with the lock hole combination in the X axis direction, the container lifting tool descends, and the lock head is lifted by the lock hole. The invention can realize the cooperation loading and unloading operation of the unmanned collecting card and the unmanned crane, well meet the aligning function of the collecting card and greatly improve the unmanned loading and unloading precision and efficiency of the collecting card container.
Description
Technical Field
The invention relates to the field of alignment of a collection card, in particular to a collection card box unloading method, a system, equipment and a storage medium based on lockhole identification in a crane container operation scene.
Background
The bridge crane business of the yard bridge and the quay bridge is the core mechanical operation of the container terminal, wherein the speed and the safety of the lifting appliance for loading and unloading containers from the collection truck directly affect the operation efficiency of the whole terminal. The conventional method needs to make the truck driver repeatedly move the truck back and forth through visual inspection to finish alignment of the truck and the lifting appliance. However, with economic lifting, the area of the container terminal is enlarged, the workload is increased sharply, the operation fatigue and negligence of a driver are increased, and meanwhile, the collision among a lifting appliance, a container and a collector is difficult to avoid completely, equipment is damaged, and a plurality of potential safety hazards are brought. Meanwhile, the manual alignment reduces the container loading and unloading speed, greatly influences the operation efficiency, and a simple and effective automatic alignment technology for the collection card, which is suitable for all-condition operation and does not depend on manual judgment, is urgently needed.
Therefore, the invention provides a method, a system, equipment and a storage medium for unloading a set card based on lockhole identification.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a method, a system, equipment and a storage medium for unloading a collection card based on lockhole identification, which overcome the difficulties in the prior art, can realize the cooperation loading and unloading operation of an unmanned collection card and an unmanned crane, well satisfy the alignment function of the collection card, and greatly improve the unmanned loading and unloading precision and efficiency of a collection card container.
The embodiment of the invention provides a method for unloading a container by using a collection card based on lockhole identification, which adopts at least one container identification component integrated with a lifting appliance positioning device and an image acquisition device, and comprises the following steps:
s110, horizontally calibrating a container lifting appliance with a camera assembly;
s120, shooting pictures of lock holes through each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and obtaining alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card;
s130, rotating the container spreader according to the alignment error information and moving the container spreader along the Y axis, judging whether the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y axis direction, if so, executing the step S150, otherwise, returning to the step S120;
s150, transmitting alignment error information to the collector card, moving the container through front and back running of the collector card, judging whether projection of a lock head combination of the container lifting tool based on the ground and projection of the lock hole combination based on the ground overlap in the X-axis direction, if so, executing the step S160, otherwise, returning to the step S150; and
and S160, the container lifting tool descends, and the lock head lifts the lock hole.
Preferably, in step S110, each lock of the container spreader is provided with a corresponding camera, and the container spreader is calibrated so that all cameras are located at the same level.
Preferably, in the step S110, the container spreader maintains a preset height with the ground;
the neural network is trained at the preset height and used for carrying out lockhole image recognition based on pictures.
Preferably, in the step S120, the method includes the following steps:
s121, shooting pictures of lock holes to be hoisted below the corresponding lock heads through each camera;
s122, performing picture identification through a trained neural network for identifying lock holes, and obtaining local picture areas occupied by the corresponding lock holes in the picture;
s123, establishing a plane coordinate system in each picture, and obtaining the distance difference between the center of each local picture area in the plane coordinate system and a preset hoisting positioning point on an X axis and a Y axis;
s124, generating alignment error information according to the distance difference of all cameras of the camera assembly.
Preferably, in the step S130, the method includes the following steps:
s131, enabling two sides of the projection based on the ground of the lock head combination to be parallel to two sides of the projection based on the ground of the lock hole combination by rotating the container lifting appliance;
and S132, moving the container lifting tool along the Y axis to enable two sides of the projection based on the ground of the lock head combination to overlap with the projection based on the ground of the lock hole combination in the Y axis direction.
Preferably, after the step S130, the step S150 further includes the following steps:
s140, shooting pictures of lock holes to be hoisted of the lock heads corresponding to the cameras, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and updating alignment error information according to the distance difference between the centers of the local picture areas and the Y axis of a preset hoisting positioning point.
The embodiment of the invention also provides a collecting card box unloading system based on the lockhole identification, which is used for realizing the collecting card box unloading method based on the lockhole identification, and comprises the following steps:
the horizontal calibration module is used for horizontally calibrating the container lifting appliance with the camera component;
the first detection module is used for shooting pictures of the lock holes through each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and obtaining alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card;
the first alignment module rotates according to the alignment error information and moves the container spreader along the Y axis, judges whether the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y axis direction, if so, executes the second alignment module, and if not, returns to the first alignment module;
the second alignment module is used for sending alignment error information to the collector card, moving the container through the front and back running of the collector card, judging whether the projection of the lock head combination of the container lifting tool is overlapped with the projection of the lock hole combination in the X-axis direction, if so, executing the lifting tool lifting module, and if not, returning to the second alignment module; and
and the lifting appliance lifting module is used for lifting the lock hole when the container lifting appliance descends.
Preferably, the device further comprises a second detection module, each camera is used for shooting pictures of lock holes to be hoisted of the corresponding lock heads, a local picture area occupied by the lock holes is obtained through a neural network, a plane coordinate system is established in each picture, and alignment error information is updated according to the distance difference between the center of the local picture area and the Y axis of a preset hoisting positioning point.
The embodiment of the invention also provides a collecting card box unloading device based on the lockhole identification, which comprises:
a processor;
a memory having stored therein executable instructions of a processor;
the processor is configured to execute the steps of the set card unloading method based on the lock hole identification through executing the executable instructions.
The embodiment of the invention also provides a computer readable storage medium for storing a program, and the program is executed to realize the steps of the method for unloading the integrated card based on the lock hole identification.
The method, the system, the equipment and the storage medium for unloading the collector card based on the lockhole identification can realize the cooperation loading and unloading operation of the unmanned collector card and the unmanned crane, well meet the alignment function of the collector card, and greatly improve the unmanned loading and unloading precision and efficiency of the collector card container.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, made with reference to the following drawings.
FIG. 1 is a flow chart of the method for unloading the integrated card based on the lock hole identification.
Fig. 2 to 5 are schematic views of an implementation process of the method for unloading the integrated card based on the lock hole identification.
FIG. 6 is a schematic structural view of the card collecting and unloading system based on the lock hole identification of the invention
Fig. 7 is a schematic structural diagram of the card collecting and unloading device based on the lock hole identification. And
Fig. 8 is a schematic structural view of a computer-readable storage medium according to an embodiment of the present invention.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the example embodiments may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus a repetitive description thereof will be omitted.
FIG. 1 is a flow chart of the method for unloading the integrated card based on the lock hole identification. As shown in fig. 1, an embodiment of the present invention provides a method for unloading a card from a box, wherein a lifting appliance in the embodiment is an unmanned gantry crane, and the card is an unmanned card, but not limited thereto, and the method includes the following steps:
s110, horizontally calibrating the container spreader with the camera assembly.
S120, shooting pictures of the lock holes through each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and obtaining alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card.
And S130, rotating the container spreader according to the alignment error information and moving the container spreader along the Y axis, judging whether the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y axis direction, if so, executing the step S150, and if not, returning to the step S120.
S150, since the unmanned gantry crane does not have the movement capability based on the X axis, the alignment error information is sent to the collector card, and the collector card is driven to adjust in the X axis direction. And (3) moving the container by the front and back running of the container truck, judging whether the projection of the lock head combination of the container lifting tool based on the ground and the projection of the lock hole combination based on the ground overlap in the X-axis direction, if so, executing the step S160, and if not, returning to the step S150.
S160, the container lifting appliance descends, and the lock head lifts the lock hole.
In a preferred embodiment, in step S110, each lock of the container spreader is provided with a corresponding camera, and the container spreader is calibrated so that all cameras are located at the same level, but not limited to this.
In a preferred embodiment, in step S110, the container spreader and the ground are kept at a preset height, and the neural network is trained at the preset height and performs keyhole image recognition based on the pictures, so that the scene of on-site recognition of the pictures is ensured to be the same as that of training of the neural network, and the recognition success rate is increased.
In a preferred embodiment, step S120 includes the steps of:
s121, shooting pictures of lock holes to be hoisted below the corresponding lock heads through each camera.
S122, performing picture identification through a trained neural network with lock hole identification, and obtaining a local picture area occupied by a corresponding lock hole in the picture.
S123, establishing a plane coordinate system in each picture, and obtaining the distance difference between the center of each local picture area in the plane coordinate system and a preset hoisting positioning point on the X axis and the Y axis.
S124, generating alignment error information according to the distance difference of all cameras of the camera assembly. By the picture identification based on the lock hole, the function of the lock hole can be accurately positioned, so that an error can be obtained.
In a preferred embodiment, step S130 includes the steps of:
s131, enabling two sides of the projection of the lock head combination based on the ground to be parallel to two sides of the projection of the lock hole combination based on the ground respectively by rotating the container lifting appliance.
And S132, moving the container lifting tool along the Y axis to enable two sides of the projection based on the ground of the lock head combination to overlap with the projection based on the ground of the lock hole combination in the Y axis direction.
In a preferred embodiment, after step S130, before step S150, the following steps are further included: s140, shooting pictures of lock holes to be hoisted of the lock heads corresponding to each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and updating alignment error information according to the distance difference between the centers of the local picture areas and the Y axis of a preset hoisting positioning point, wherein the X axis is aligned, so that S140 mainly detects errors of the Y axis.
According to the invention, each lock head is provided with a camera through the camera component arranged on the lifting appliance, so that the position of a lock hole can be accurately detected at the visual angle of the lock head, and the vertical positioning of each lock head and the lock hole is realized through the two detection by combining the self-adjusting operation of the lifting appliance (the lifting appliance is used as a rotation shaft to perform horizontal rotation and the advancing and retreating of the Y-axis direction) and the adjusting operation of the collection card (the advancing and retreating of the X-axis direction).
Fig. 2 to 5 are schematic views of an implementation process of the method for unloading the integrated card based on the lock hole identification. As shown in fig. 2 to 5, the implementation process of the method for unloading the integrated card based on the lock hole identification of the invention is as follows:
referring to fig. 2 and 3, the crane 4 has a hanger suspended by slings 45, four corners of the hanger are respectively provided with a locking head 41, a camera 42 is provided on each locking head 41, the pallet 1 is loaded with the container 21 and the container 22 and driven under the crane 4, locking holes 31, 32, 33 and 34 are provided on the upper surfaces of the container 21 and the container 22, respectively, and the container 22 is first unloaded. First, the container spreader with the camera assembly is horizontally calibrated, which positions all cameras 42 at the same level.
Then, referring to fig. 4, a picture of the lock hole is taken by each camera 42, a local picture area occupied by the lock hole is obtained by a neural network, a plane coordinate system is established in each picture, and alignment error information is obtained according to a distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the set card 1. The container spreader needs to keep a preset height with the ground, and the neural network is a trained neural network which performs lockhole image recognition based on pictures at the same preset height, so that the scene of on-site recognition pictures is ensured to be the same as that of training of the neural network, and the recognition success rate is increased. A picture of the lock hole to be hoisted below the respective lock head 41 is taken by each camera 42. Referring to fig. 5, a picture 421 taken by the camera 42 of the crane 4 located on the front left of the container 22 is taken as an example, and the picture is identified by the trained neural network for identifying the lock hole, so as to obtain a local picture area occupied by the corresponding lock hole in the picture. And establishing a plane coordinate system in each picture, and obtaining the distance difference a between the center Z of each local picture area C in the plane coordinate system and the preset hoisting positioning point O on the X axis and the distance difference b between the center Z and the preset hoisting positioning point O on the Y axis. The position error information is generated from the distance differences of all cameras 42 of the camera assembly. By the picture identification based on the lock hole, the function of the lock hole can be accurately positioned, so that an error can be obtained.
And rotating the container spreader according to the alignment error information and moving the container spreader along the Y-axis until the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y-axis direction. The container lifting tool can be rotated to enable two sides of the projection based on the ground of the lock head combination to be parallel to two sides of the projection based on the ground of the lock hole combination respectively, and then the container lifting tool is moved along the Y axis to enable two sides of the projection based on the ground of the lock head combination to be overlapped with the projection based on the ground of the lock hole combination in the Y axis direction. Then, each camera 42 is used for shooting pictures of the lock hole to be hoisted of the corresponding lock head 41, a local picture area occupied by the lock hole is obtained through a neural network, a plane coordinate system is established in each picture, and alignment error information is updated according to the distance difference between the center of the local picture area and the Y axis of a preset hoisting positioning point, and because the X axis is already aligned, S140 is mainly used for detecting errors of the Y axis. And the alignment error information is sent to the container truck 1, and the container is moved by the front and back running of the container truck 1 until the projection of the lock head combination of the container lifting tool based on the ground and the projection of the lock hole combination based on the ground are overlapped in the X-axis direction, so that the container lifting tool descends, and the lock head 41 lifts the lock hole.
Fig. 6 is a schematic structural diagram of a card-collecting and box-unloading system based on keyhole recognition according to the present invention as shown in fig. 6, and an embodiment of the present invention further provides a card-collecting and box-unloading system 5 based on keyhole recognition, for implementing the card-collecting and box-unloading method based on keyhole recognition, where the card-collecting and box-unloading system based on keyhole recognition includes:
a horizontal calibration module 51 horizontally calibrates the container spreader with the camera assembly.
The first detection module 52 shoots pictures of the lock holes through each camera, obtains local picture areas occupied by the lock holes through a neural network, establishes a plane coordinate system in each picture, and obtains alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card.
The first alignment module 53 rotates and moves the container spreader along the Y axis according to the alignment error information, determines whether the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y axis direction, if so, executes the second alignment module, and if not, returns to the first alignment module.
The second detection module 54 shoots pictures of the lock holes to be hoisted of the lock heads corresponding to the cameras respectively, obtains local picture areas occupied by the lock holes through a neural network, establishes a plane coordinate system in each picture, and updates alignment error information according to the distance difference between the centers of the local picture areas and the Y axis of the preset hoisting positioning points.
The second alignment module 55 sends the alignment error information to the collector card, and the container is moved by the front and back running of the collector card, so as to judge whether the projection of the lock head combination of the container lifting tool and the projection of the lock hole combination overlap in the X-axis direction, if yes, the lifting tool lifting module is executed, and if not, the second alignment module is returned.
And a lifting module 56 for lifting the container, wherein the container lifting device descends, and the lock head lifts the lock hole.
The collecting card box unloading system based on lockhole identification can realize the cooperation loading and unloading operation of the unmanned collecting card and the unmanned crane, well meets the aligning function of the collecting card, and greatly improves the unmanned loading and unloading precision and efficiency of the collecting card container.
The embodiment of the invention also provides a set card box unloading device based on the lock hole identification, which comprises a processor. A memory having stored therein executable instructions of a processor. Wherein the processor is configured to execute the steps of the method for card-unloading based on keyhole identification via execution of the executable instructions.
As above, the container unloading equipment for the collection card based on the lockhole identification can realize the cooperation loading and unloading operation of the unmanned collection card and the unmanned crane, well meets the alignment function of the collection card, and greatly improves the unmanned loading and unloading precision and efficiency of the collection card container.
Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the invention may be embodied in the following forms, namely: an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects may be referred to herein as a "circuit," module "or" platform.
Fig. 7 is a schematic structural diagram of the card collecting and unloading device based on the lock hole identification. An electronic device 600 according to this embodiment of the invention is described below with reference to fig. 7. The electronic device 600 shown in fig. 7 is merely an example, and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 7, the electronic device 600 is in the form of a general purpose computing device. Components of electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one memory unit 620, a bus 630 connecting the different platform components (including memory unit 620 and processing unit 610), a display unit 640, etc.
Wherein the storage unit stores program code executable by the processing unit 610 such that the processing unit 610 performs the steps according to various exemplary embodiments of the present invention described in the above-described electronic prescription flow processing method section of the present specification. For example, the processing unit 610 may perform the steps as shown in fig. 1.
The storage unit 620 may include readable media in the form of volatile storage units, such as Random Access Memory (RAM) 6201 and/or cache memory unit 6202, and may further include Read Only Memory (ROM) 6203.
The storage unit 620 may also include a program/utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment.
Bus 630 may be a local bus representing one or more of several types of bus structures including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or using any of a variety of bus architectures.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and/or any device (e.g., router, modem, etc.) that enables the electronic device 600 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 650. Also, electronic device 600 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 over the bus 630. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with electronic device 600, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage platforms, and the like.
The embodiment of the invention also provides a computer readable storage medium for storing a program, and the method for unloading the integrated card based on the lock hole identification is realized when the program is executed. In some possible embodiments, the aspects of the present invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the electronic prescription stream processing method section of this specification, when the program product is run on the terminal device.
As described above, when the program of the computer readable storage medium of the embodiment is executed, the cooperation loading and unloading operation of the unmanned truck and the unmanned crane can be realized, the truck alignment function can be well satisfied, and the unmanned loading and unloading precision and efficiency of the truck container can be greatly improved.
Fig. 8 is a schematic structural view of a computer-readable storage medium of the present invention. Referring to fig. 8, a program product 800 for implementing the above-described method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a data signal propagated in baseband or as part of a carrier wave, with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable storage medium may also be any readable medium that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., connected via the Internet using an Internet service provider).
In summary, the method, the system, the equipment and the storage medium for unloading the collection card based on the lockhole identification can realize the cooperation loading and unloading operation of the unmanned collection card and the unmanned crane, well meet the alignment function of the collection card, and greatly improve the unmanned loading and unloading precision and efficiency of the collection card container.
The foregoing is a further detailed description of the invention in connection with the preferred embodiments, and it is not intended that the invention be limited to the specific embodiments described. It will be apparent to those skilled in the art that several simple deductions or substitutions may be made without departing from the spirit of the invention, and these should be considered to be within the scope of the invention.
Claims (8)
1. The method for unloading the collection card based on the lock hole identification is characterized by comprising the following steps of:
s110, horizontally calibrating a container lifting appliance with a camera assembly;
s120, shooting pictures of lock holes through each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and obtaining alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card;
s130, enabling two sides of the projection based on the ground of the lock head combination to be parallel to two sides of the projection based on the ground of the lock hole combination by rotating the container spreader, moving the container spreader along a Y axis to enable two sides of the projection based on the ground of the lock head combination to overlap with the projection based on the ground of the lock hole combination in the Y axis direction, judging whether the projection based on the ground of the lock head combination of the container spreader overlaps with the projection based on the ground of the lock hole combination in the Y axis direction or not, if yes, executing step S140, otherwise returning to step S120;
s140, shooting pictures of lock holes to be hoisted of the lock heads corresponding to the cameras respectively, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and updating alignment error information according to the distance difference between the centers of the local picture areas and the Y axis of a preset hoisting positioning point;
s150, transmitting alignment error information to the collector card, moving the container through front and back running of the collector card, judging whether projection of a lock head combination of the container lifting tool based on the ground and projection of the lock hole combination based on the ground overlap in the X-axis direction, if so, executing the step S160, otherwise, returning to the step S150; and
and S160, the container lifting tool descends, and the lock head lifts the lock hole.
2. The method for unloading the container according to claim 1, wherein in step S110, each lock of the container spreader is provided with a corresponding camera, and the container spreader is calibrated such that all cameras are located at the same level.
3. The method for unloading the container based on the keyhole recognition according to claim 1, wherein in the step S110, the container spreader and the ground are kept at a predetermined height;
the neural network is trained at the preset height and used for carrying out lockhole image recognition based on pictures.
4. The method for unloading the card set based on the lock hole identification as set forth in claim 1, wherein the step S120 includes the steps of:
s121, shooting pictures of lock holes to be hoisted below the corresponding lock heads through each camera;
s122, performing picture identification through a trained neural network for identifying lock holes, and obtaining local picture areas occupied by the corresponding lock holes in the picture;
s123, establishing a plane coordinate system in each picture, and obtaining the distance difference between the center of each local picture area in the plane coordinate system and a preset hoisting positioning point on an X axis and a Y axis;
s124, generating alignment error information according to the distance difference of all cameras of the camera assembly.
5. A lock hole identification based card unloading system, for implementing the lock hole identification based card unloading method as defined in claim 1, comprising:
the horizontal calibration module is used for horizontally calibrating the container lifting appliance with the camera component;
the first detection module is used for shooting pictures of the lock holes through each camera, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, and obtaining alignment error information according to the distance difference between the center of the local picture area and a preset hoisting positioning point on an X axis and a Y axis, wherein the X axis is parallel to the running direction of the collector card;
the first alignment module rotates according to the alignment error information and moves the container spreader along the Y axis, judges whether the projection of the lock head combination of the container spreader based on the ground and the projection of the lock hole combination based on the ground overlap in the Y axis direction, if so, executes the second alignment module, and if not, returns to the first alignment module;
the second alignment module is used for sending alignment error information to the collector card, moving the container through the front and back running of the collector card, judging whether the projection of the lock head combination of the container lifting tool is overlapped with the projection of the lock hole combination in the X-axis direction, if so, executing the lifting tool lifting module, and if not, returning to the second alignment module; and
and the lifting appliance lifting module is used for lifting the lock hole when the container lifting appliance descends.
6. The lock hole identification-based set card box unloading system according to claim 5, further comprising a second detection module, wherein pictures of lock holes to be hoisted of the lock heads corresponding to the cameras are shot through each camera, local picture areas occupied by the lock holes are obtained through a neural network, a plane coordinate system is established in each picture, and alignment error information is updated according to distance differences between the centers of the local picture areas and Y axes of preset hoisting positioning points.
7. The utility model provides a collection card unloads case equipment based on lockhole discernment which characterized in that includes:
a processor;
a memory having stored therein executable instructions of a processor;
wherein the processor is configured to perform the steps of the lock hole identification based header removal method of any one of claims 1 to 4 via execution of executable instructions.
8. A computer-readable storage medium storing a program, wherein the program when executed implements the steps of the lock hole identification-based header card unpacking method according to any one of claims 1 to 4.
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| CN115180512B (en) * | 2022-09-09 | 2023-01-20 | 湖南洋马信息有限责任公司 | Automatic loading and unloading method and system for container truck based on machine vision |
| CN115849189B (en) * | 2022-11-16 | 2024-01-30 | 上海西井科技股份有限公司 | Point cloud-based lifting appliance secondary anchoring method, system, equipment and storage medium |
| CN115849195B (en) * | 2022-11-16 | 2023-12-19 | 上海西井科技股份有限公司 | Self-adaptive alignment calibration method, system, equipment and storage medium for transportation equipment |
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