CN113213340A - Method, system, equipment and storage medium for unloading container truck based on lockhole identification - Google Patents
Method, system, equipment and storage medium for unloading container truck based on lockhole identification Download PDFInfo
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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
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Abstract
The invention provides a method, a system, equipment and a storage medium for unloading a container truck based on keyhole 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 hoisting positioning points, the container spreader is rotated and moved along a Y axis according to the alignment error information, when a lock head combination of the container spreader is overlapped with a lock hole combination in the Y axis direction, the alignment error information is sent to a container truck, the container is moved through front and back running of the container truck, when the lock head combination of the container spreader is overlapped with the lock hole combination in the X axis direction, the container spreader descends, and the lock head hoists the lock holes. The invention can realize the matching loading and unloading operation of the unmanned container truck and the unmanned crane, well meet the alignment function of the container truck and greatly improve the precision and efficiency of unmanned loading and unloading of the container truck.
Description
Technical Field
The invention relates to the field of container truck alignment, in particular to a container truck unloading method, a system, equipment and a storage medium based on lockhole identification in a crane container operation scene.
Background
The bridge crane operation of the yard and shore bridges is the core mechanical operation of the container terminal, in which the speed and safety of the loading and unloading of containers by the spreader from the trucks directly affect the operational efficiency of the whole terminal. In the traditional method, a truck driver needs to repeatedly move the truck back and forth through visual inspection to complete the alignment of the truck and the lifting appliance. However, with economic improvement, the area of the container terminal is enlarged, the workload is increased rapidly, the operation fatigue and negligence of drivers are increased, and meanwhile, the collision among the lifting appliance, the container and the container truck and the equipment damage are difficult to be avoided completely, so that a plurality of potential safety hazards are brought. Meanwhile, the loading and unloading speed of the container is reduced by artificial alignment, the operation efficiency is greatly influenced, and a simple and effective automatic alignment technology which is not dependent on artificial judgment and is suitable for all-condition operation is urgently needed.
Therefore, the invention provides a method, a system, equipment and a storage medium for unloading a container truck based on keyhole identification.
Disclosure of Invention
Aiming at the problems in the prior art, the invention aims to provide a container truck unloading method, a container truck unloading system, equipment and a storage medium based on lockhole identification, which overcome the difficulties in the prior art, can realize the matched loading and unloading operation of an unmanned container truck and an unmanned crane, well meet the function of truck alignment and greatly improve the precision and efficiency of unmanned loading and unloading of container trucks.
The embodiment of the invention provides a container truck unloading method based on lockhole identification, which adopts at least one container identification component integrating a hanger positioning device and an image acquisition device, and comprises the following steps:
s110, horizontally calibrating a container spreader with a camera assembly;
s120, shooting pictures of the lockholes through each camera, obtaining local picture areas occupied by the lockholes 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 each 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 driving direction of the container truck;
s130, rotating and moving the container spreader along the Y axis according to the alignment error information, 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 are overlapped in the Y axis direction, if so, executing the step S150, otherwise, returning to the step S120;
s150, sending the alignment error information to the container truck, moving the container through the forward and backward driving of the container truck, judging whether the projection of the lock head combination of the container spreader based on the ground is overlapped with the projection of the lock hole combination based on the ground in the X-axis direction, if so, executing the step S160, and if not, returning to the step S150; and
and S160, the container lifting appliance descends, and the lock head lifts the lock hole.
Preferably, in step S110, each lock head of the container spreader is provided with a corresponding camera, and the container spreader is calibrated such that all the cameras are located at the same horizontal height.
Preferably, in step S110, the container spreader maintains a preset height with respect to the ground;
the neural network is trained at the preset height and used for identifying the keyhole image based on the picture.
Preferably, the step S120 includes the steps of:
s121, shooting pictures of the lock holes to be hoisted below the lock heads corresponding to the cameras through the cameras;
s122, carrying out picture identification through a trained lockhole identification neural network to obtain a local picture area occupied by a corresponding lockhole 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 and a preset hoisting positioning point in the plane coordinate system on the X axis and the Y axis;
and S124, generating alignment error information according to the distance differences of all the cameras of the camera assembly.
Preferably, the step S130 includes the following steps:
s131, rotating the container spreader to enable 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;
s132, moving the container lifting appliance along the Y axis to enable two sides of the projection of the lock head combination based on the ground to be overlapped with the projection of the lock hole combination based on the ground in the Y axis direction.
Preferably, after the step S130, the step S150 further includes the following steps:
s140, shooting pictures of the lock holes to be hoisted of the lock heads corresponding to the cameras through 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 center of each local picture area and the Y axis of a preset hoisting positioning point.
The embodiment of the invention also provides a container truck unloading system based on keyhole identification, which is used for realizing the container truck unloading method based on keyhole identification, and the container truck unloading system based on keyhole identification comprises the following steps:
a horizontal calibration module for horizontally calibrating a spreader having a camera assembly;
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 each 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 driving direction of the truck container;
the first alignment module rotates and moves the container spreader along the Y axis according to the alignment error information, 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 are overlapped in the Y axis direction, executes the second alignment module if the projection is overlapped in the Y axis direction, and returns to the first alignment module if the projection is not overlapped in the Y axis direction;
the second alignment module is used for sending alignment error information to the container truck, judging whether the projection of the lock head combination of the container lifting appliance and the projection of the lock hole combination are overlapped in the X-axis direction or not by moving the container through the forward and backward running of the container truck, executing the lifting appliance lifting module if the projection is overlapped in the X-axis direction, and returning to the second alignment module if the projection is not overlapped in the X-axis direction; and
and the container lifting appliance descends, and the lock head lifts the lock hole.
Preferably, the lock hole lifting device further comprises a second detection module, each camera shoots a picture of a lock hole to be lifted of a corresponding lock head, 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 lifting positioning point.
The embodiment of the invention also provides a container truck unloading device based on keyhole identification, which comprises:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the above-described lockhole identification based hopper unloading method via execution of executable instructions.
Embodiments of the present invention further provide a computer-readable storage medium for storing a program, where the program is executed to implement the steps of the above-mentioned method for unloading a container truck based on keyhole identification.
The container truck unloading method, the container truck unloading system, the container truck unloading equipment and the storage medium based on the lockhole identification can realize the matched loading and unloading operation of the unmanned container truck and the unmanned crane, well meet the alignment function of the container truck, and greatly improve the unmanned loading and unloading precision and efficiency of the container truck.
Drawings
Other features, objects and advantages of the present invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, with reference to the accompanying drawings.
FIG. 1 is a flow chart of a method for unloading a container truck based on keyhole identification according to the present invention.
Fig. 2 to 5 are schematic diagrams illustrating an implementation process of the truck box unloading method based on keyhole identification according to the present invention.
FIG. 6 is a schematic structural diagram of a container truck unloading system based on keyhole identification according to the present invention
Fig. 7 is a schematic structural diagram of the truck box unloading device based on keyhole identification according to the present invention. And
fig. 8 is a schematic structural diagram 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. Example embodiments may, however, 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 example embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar structures, and thus their repetitive description will be omitted.
FIG. 1 is a flow chart of a method for unloading a container truck based on keyhole identification according to the present invention. As shown in fig. 1, an embodiment of the present invention provides a truck-based box unloading method based on keyhole identification, where a spreader in this embodiment is an unmanned gantry crane, and a truck is an unmanned truck, but not limited thereto, the method of the present invention includes the following steps:
and S110, horizontally calibrating the container spreader with the camera assembly.
S120, shooting pictures of the lockholes through each camera, obtaining local picture areas occupied by the lockholes 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 each 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 driving direction of the container truck.
S130, rotating and moving the container spreader along the Y axis according to the alignment error information, 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 are overlapped in the Y axis direction, if so, executing the step S150, and if not, returning to the step S120.
And S150, since the unmanned gantry crane does not have the moving capability based on the X axis, the alignment error information is sent to the truck, and the truck is driven to adjust the X axis direction. And (3) moving the container through the forward and backward driving of the container truck, 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 are overlapped in the X-axis direction, if so, executing the step (S160), and if not, returning to the step (S150).
And 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 such that all the cameras are located at the same horizontal height, but not limited thereto.
In a preferred embodiment, in step S110, the container spreader maintains a preset height with respect to the ground, and the neural network is trained at the preset height and performs keyhole image recognition based on pictures, so as to ensure that the scene of field recognition pictures is the same as the scene of neural network training, and increase the recognition success rate.
In a preferred embodiment, step S120 includes the following steps:
and S121, shooting pictures of the lock holes to be hoisted below the corresponding lock heads through each camera.
And S122, carrying out picture identification through the trained neural network for identifying the lockholes to obtain a local picture area occupied by the corresponding lockholes 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 and a preset hoisting positioning point in the plane coordinate system on the X axis and the Y axis.
And S124, generating alignment error information according to the distance differences of all the cameras of the camera assembly. Through picture identification based on the lockhole, the work of the lockhole can be accurately positioned, and therefore the error is obtained.
In a preferred embodiment, step S130 includes the following steps:
s131, by rotating the container lifting appliance, two sides of the projection of the lock head combination based on the ground are respectively parallel to two sides of the projection of the lock hole combination based on the ground.
S132, moving the container lifting appliance along the Y axis to enable two sides of the projection of the lock combination based on the ground to be overlapped with the projection of the lock hole combination based on the ground in the Y axis direction.
In a preferred embodiment, after step S130, step S150 further comprises the following steps: s140, shooting pictures of lock holes to be hoisted of lock heads corresponding to the cameras respectively through the cameras, obtaining local picture areas occupied by the lock holes through a neural network, establishing a plane coordinate system in each picture, updating alignment error information according to the distance difference between the center of the local picture area and the Y axis of a preset hoisting positioning point, and performing error detection on the Y axis in S140 mainly because the X axis is aligned.
According to the container truck unloading method based on the lock hole identification, the position of the lock hole can be accurately detected at the visual angle of the lock head by matching a camera assembly arranged on the lifting appliance with each lock head, and the vertical positioning of each lock head and the lock hole is realized through two times of detection by combining the adjustment operation (horizontal rotation and advancing and retreating in the Y-axis direction by taking a sling as a rotating shaft) of the lifting appliance and the adjustment operation (advancing and retreating in the X-axis direction) of the container truck, so that the accuracy of the alignment is ensured.
Fig. 2 to 5 are schematic diagrams illustrating an implementation process of the truck box unloading method based on keyhole identification according to the present invention. As shown in fig. 2 to 5, the truck unloading method based on keyhole identification according to the present invention is implemented as follows:
referring to fig. 2 and 3, the crane 4 has a hanger suspended by a suspension wire 45, four corners of the hanger are provided with a locking head 41 respectively, a camera 42 is provided at an edge of each locking head 41, the container 21 and the container 22 loaded by the container truck 1 travel below the crane 4, locking holes 31, 32, 33, 34 are provided on upper surfaces of the container 21 and the container 22, respectively, and the container 22 is first unloaded. First, the spreader with the camera assembly is calibrated horizontally, which aligns the spreader with all of the cameras 42 at the same level.
Then, referring to fig. 4, a picture of the keyhole is taken by each camera 42, a local picture area occupied by the keyhole is obtained through 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 driving direction of the container truck 1. The container spreader needs to keep a preset height with the ground, and the neural network is also a trained neural network for identifying the keyhole image based on the picture at the same preset height, so that the scene of field identification picture and the scene of neural network training are the same, and the identification success rate is increased. And a picture of the lock hole to be hoisted below the corresponding lock head 41 is shot through each camera 42. Referring to fig. 5, a picture 421 taken by the camera 42 of the crane 4 located above the left front of the container 22 is taken as an example, and the picture is identified through a trained keyhole identification neural network, so as to obtain a local picture area occupied by a corresponding keyhole 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 and the preset hoisting positioning point O in the plane coordinate system on the X axis and the distance difference b on the Y axis. The registration error information is generated from the distance differences of all the cameras 42 of the camera assembly. Through picture identification based on the lockhole, the work of the lockhole can be accurately positioned, and therefore the error is obtained.
And rotating and moving the container spreader along the Y axis according to the alignment error information until the projection of the lock head combination of the container spreader based on the ground is overlapped with the projection of the lock hole combination based on the ground in the Y axis direction. The two sides of the projection of the lock head combination based on the ground and the two sides of the projection of the lock hole combination based on the ground can be parallel to each other by rotating the container lifting appliance, and then the container lifting appliance is moved along the Y axis to enable the two sides of the projection of the lock head combination based on the ground and the projection of the lock hole combination based on the ground to be overlapped in the Y axis direction. Then, each camera 42 shoots a picture of a 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 planar coordinate system is established in each picture, 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 S140 mainly detects errors of the Y axis because the X axis is aligned. The alignment error information is sent to the container truck 1, the container is moved through the front and back running of the container truck 1 until the projection of the lock combination of the container hanger based on the ground is overlapped with the projection of the lock hole combination based on the ground in the X-axis direction, the container hanger descends, and the lock 41 hoists the lock hole.
Fig. 6 is a schematic structural diagram of a truck box unloading system based on keyhole identification according to the present invention, as shown in fig. 6, an embodiment of the present invention further provides a truck box unloading system 5 based on keyhole identification, for implementing the above-mentioned truck box unloading method based on keyhole identification, where the truck box unloading system based on keyhole identification includes:
the horizontal calibration module 51 horizontally calibrates the spreader with the camera assembly.
The first detection module 52 takes a picture of the keyhole through each camera, obtains a local picture area occupied by the keyhole through a neural network, establishes a planar coordinate system in each picture, and obtains alignment error information 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 truck driving direction.
And 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 are overlapped 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 takes pictures of the lock holes to be hoisted of the lock heads corresponding to each camera, obtains a local picture area occupied by the lock holes through a neural network, establishes a planar coordinate system in each picture, and updates alignment error information according to the distance difference between the center of the local picture area and the Y axis of a preset hoisting positioning point.
And the second alignment module 55 sends the alignment error information to the container truck, moves the container through the forward and backward driving of the container truck, judges whether the projection of the lock combination of the container spreader and the projection of the lock hole combination are overlapped in the X-axis direction, executes the spreader hoisting module if the projection is overlapped, and returns to the second alignment module if the projection is not overlapped.
And the lifting appliance lifting module 56 is used for lowering the container lifting appliance and lifting the lock hole by the lock head.
The container collecting and unloading system based on lockhole identification can realize the matching loading and unloading operation of an unmanned collecting card and an unmanned crane, well meet the function of aligning the collecting card and greatly improve the accuracy and efficiency of unmanned loading and unloading of the container collecting card.
The embodiment of the invention also provides a container truck unloading device based on keyhole identification, which comprises a processor. A memory having stored therein executable instructions of the processor. Wherein the processor is configured to perform the steps of the lockhole identification based hopper unloading method via execution of the executable instructions.
As described above, the container truck unloading equipment based on lockhole identification can realize the matching loading and unloading operation of the unmanned container truck and the unmanned crane, well meet the function of positioning the container truck, and greatly improve the precision and efficiency of unmanned loading and unloading of the container truck.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" platform.
Fig. 7 is a schematic structural diagram of the truck box unloading device based on keyhole identification according to the present invention. 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 only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, the electronic device 600 is embodied in the form of a general purpose computing device. The components of the 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 the memory unit 620 and the processing unit 610), a display unit 640, etc.
Wherein the storage unit stores program code executable by the processing unit 610 to cause the processing unit 610 to perform steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of the present specification. For example, 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 memory units, such as a random access memory unit (RAM)6201 and/or a cache memory unit 6202, and may further include a read-only memory unit (ROM) 6203.
The memory 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 of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 600, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 600 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 650. Also, the electronic device 600 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via the bus 630. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms, to name a few.
The embodiment of the invention also provides a computer readable storage medium for storing a program, and the steps of the container truck unloading method based on the keyhole identification are 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 perform the steps according to various exemplary embodiments of the present invention described in the above-mentioned electronic prescription flow processing method section of this specification, when the program product is run on the terminal device.
As described above, the program of the computer-readable storage medium according to this embodiment can realize the cooperative loading and unloading operation between the unmanned container truck and the unmanned crane, and can satisfy the container truck alignment function well, thereby greatly improving the accuracy and efficiency of the unmanned loading and unloading of the container truck.
Fig. 8 is a schematic structural diagram of a computer-readable storage medium of the present invention. Referring to fig. 8, a program product 800 for implementing the above 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 in this regard and, in the present 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. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
A computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and 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 for aspects 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 and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, 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., through the internet using an internet service provider).
In conclusion, the container truck unloading method, the container truck unloading system, the container truck unloading equipment and the storage medium based on the lockhole identification can realize the matched loading and unloading operation of the unmanned container truck and the unmanned crane, well meet the function of aligning the container truck, and greatly improve the precision and the efficiency of unmanned loading and unloading of the container truck.
The foregoing is a more detailed description of the invention in connection with specific preferred embodiments and it is not intended that the invention be limited to these specific details. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A container truck unloading method based on keyhole identification is characterized by comprising the following steps:
s110, horizontally calibrating a container spreader with a camera assembly;
s120, shooting pictures of the lockholes through each camera, obtaining local picture areas occupied by the lockholes 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 each 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 driving direction of the container truck;
s130, rotating and moving the container spreader along the Y axis according to the alignment error information, 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 are overlapped in the Y axis direction, if so, executing the step S150, otherwise, returning to the step S120;
s150, sending the alignment error information to the container truck, moving the container through the forward and backward driving of the container truck, judging whether the projection of the lock head combination of the container spreader based on the ground is overlapped with the projection of the lock hole combination based on the ground in the X-axis direction, if so, executing the step S160, and if not, returning to the step S150; and
and S160, the container lifting appliance descends, and the lock head lifts the lock hole.
2. The lock hole identification based container unloading method according to claim 1, wherein in step S110, each lock head of the container spreader is provided with a corresponding camera, and the container spreader is calibrated such that all the cameras are located at the same horizontal height.
3. The lock hole identification based container truck-unloading method according to claim 1, wherein in the step S110, the container spreader is kept at a preset height from the ground;
the neural network is trained at the preset height and used for identifying the keyhole image based on the picture.
4. The lock hole identification based container unloading method according to claim 1, wherein the step S120 includes the steps of:
s121, shooting pictures of the lock holes to be hoisted below the lock heads corresponding to the cameras through the cameras;
s122, carrying out picture identification through a trained lockhole identification neural network to obtain a local picture area occupied by a corresponding lockhole 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 and a preset hoisting positioning point in the plane coordinate system on the X axis and the Y axis;
and S124, generating alignment error information according to the distance differences of all the cameras of the camera assembly.
5. The lock hole identification based container unloading method according to claim 1, wherein the step S130 includes the steps of:
s131, rotating the container spreader to enable 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;
s132, moving the container lifting appliance along the Y axis to enable two sides of the projection of the lock head combination based on the ground to be overlapped with the projection of the lock hole combination based on the ground in the Y axis direction.
6. The lock hole identification based container unloading method according to claim 1, wherein after step S130, step S150 further comprises the following steps:
s140, shooting pictures of the lock holes to be hoisted of the lock heads corresponding to the cameras through 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 center of each local picture area and the Y axis of a preset hoisting positioning point.
7. A lock hole identification based container unloading system, for implementing the lock hole identification based container unloading method of claim 1, comprising:
a horizontal calibration module for horizontally calibrating a spreader having a camera assembly;
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 each 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 driving direction of the truck container;
the first alignment module rotates and moves the container spreader along the Y axis according to the alignment error information, 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 are overlapped in the Y axis direction, executes the second alignment module if the projection is overlapped in the Y axis direction, and returns to the first alignment module if the projection is not overlapped in the Y axis direction;
the second alignment module is used for sending alignment error information to the container truck, judging whether the projection of the lock head combination of the container lifting appliance and the projection of the lock hole combination are overlapped in the X-axis direction or not by moving the container through the forward and backward running of the container truck, executing the lifting appliance lifting module if the projection is overlapped in the X-axis direction, and returning to the second alignment module if the projection is not overlapped in the X-axis direction; and
and the container lifting appliance descends, and the lock head lifts the lock hole.
8. The lock hole identification-based container truck-unloading method according to claim 1, further comprising a second detection module, wherein each camera is used for shooting a picture of a lock hole to be hoisted of a lock head corresponding to the second detection module, a local picture area occupied by the lock hole is obtained through a neural network, a planar coordinate system is established in each picture, and alignment error information is updated according to a distance difference between the center of the local picture area and a Y axis of a preset hoisting positioning point.
9. The utility model provides a case equipment is unloaded to collection card based on lockhole discernment which characterized in that includes:
a processor;
a memory having stored therein executable instructions of the processor;
wherein the processor is configured to perform the steps of the lockhole identification based hopper method of any one of claims 1 to 7 via execution of executable instructions.
10. A computer-readable storage medium storing a program, wherein the program is executed to implement the steps of the lockhole identification based container unloading method of any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115180512A (en) * | 2022-09-09 | 2022-10-14 | 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 |
| CN115849189A (en) * | 2022-11-16 | 2023-03-28 | 上海西井信息科技有限公司 | Point cloud-based secondary anchoring method, system, equipment and storage medium for lifting appliance |
| CN115849195A (en) * | 2022-11-16 | 2023-03-28 | 上海西井信息科技有限公司 | Self-adaptive alignment calibration method, system, equipment and storage medium for transportation equipment |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102452611A (en) * | 2010-10-21 | 2012-05-16 | 上海振华重工(集团)股份有限公司 | Detection method and detection device for space attitude of suspender of container crane |
| CN103818828A (en) * | 2014-03-05 | 2014-05-28 | 上海振华重工电气有限公司 | Container crane sling aligning guide system |
| CN204384730U (en) * | 2014-12-31 | 2015-06-10 | 曹敏 | Truck contraposition designating system under container wharf RTG, RMG |
| CN106809730A (en) * | 2017-01-18 | 2017-06-09 | 北京理工大学 | The container automatic butt tackling system and hoisting method of a kind of view-based access control model |
| CN107067439A (en) * | 2017-04-26 | 2017-08-18 | 北京航天自动控制研究所 | A kind of container truck positioning detected based on headstock and bootstrap technique |
| WO2018120591A1 (en) * | 2016-12-26 | 2018-07-05 | 深圳市招科智控科技有限公司 | System for remotely controlling automatic positioning of rtg crane |
| CN108491851A (en) * | 2018-01-29 | 2018-09-04 | 江苏大学 | A kind of container lockhole based on machine vision is quick to be identified and suspender method for correcting error |
| CN109384150A (en) * | 2017-08-03 | 2019-02-26 | 南通通镭软件有限公司 | The container tapered end framing of automated handling slings method with anti- |
| CN109455622A (en) * | 2017-12-15 | 2019-03-12 | 天津埃特维科技有限公司 | The visual identifying system of container spreader and the hanging box method of container |
| CN111302223A (en) * | 2020-02-26 | 2020-06-19 | 西南交通大学 | Method, device and system for aligning container by using lifting appliance |
-
2021
- 2021-05-11 CN CN202110511235.7A patent/CN113213340B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102452611A (en) * | 2010-10-21 | 2012-05-16 | 上海振华重工(集团)股份有限公司 | Detection method and detection device for space attitude of suspender of container crane |
| CN103818828A (en) * | 2014-03-05 | 2014-05-28 | 上海振华重工电气有限公司 | Container crane sling aligning guide system |
| CN204384730U (en) * | 2014-12-31 | 2015-06-10 | 曹敏 | Truck contraposition designating system under container wharf RTG, RMG |
| WO2018120591A1 (en) * | 2016-12-26 | 2018-07-05 | 深圳市招科智控科技有限公司 | System for remotely controlling automatic positioning of rtg crane |
| CN106809730A (en) * | 2017-01-18 | 2017-06-09 | 北京理工大学 | The container automatic butt tackling system and hoisting method of a kind of view-based access control model |
| CN107067439A (en) * | 2017-04-26 | 2017-08-18 | 北京航天自动控制研究所 | A kind of container truck positioning detected based on headstock and bootstrap technique |
| CN109384150A (en) * | 2017-08-03 | 2019-02-26 | 南通通镭软件有限公司 | The container tapered end framing of automated handling slings method with anti- |
| CN109455622A (en) * | 2017-12-15 | 2019-03-12 | 天津埃特维科技有限公司 | The visual identifying system of container spreader and the hanging box method of container |
| CN108491851A (en) * | 2018-01-29 | 2018-09-04 | 江苏大学 | A kind of container lockhole based on machine vision is quick to be identified and suspender method for correcting error |
| CN111302223A (en) * | 2020-02-26 | 2020-06-19 | 西南交通大学 | Method, device and system for aligning container by using lifting appliance |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115180512A (en) * | 2022-09-09 | 2022-10-14 | 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 |
| 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 |
| CN115849189A (en) * | 2022-11-16 | 2023-03-28 | 上海西井信息科技有限公司 | Point cloud-based secondary anchoring method, system, equipment and storage medium for lifting appliance |
| CN115849195A (en) * | 2022-11-16 | 2023-03-28 | 上海西井信息科技有限公司 | Self-adaptive alignment calibration method, system, equipment and storage medium for transportation equipment |
| 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 |
| 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 |
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