CN113822396B - Bridge crane real-time positioning method, device and system - Google Patents
Bridge crane real-time positioning method, device and system Download PDFInfo
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Abstract
The application provides a bridge crane real-time positioning method, device and system. The method comprises the following steps: the server can acquire a first image through a camera installed on the bridge crane supporting frame. The first image may include a position mark on the marking rod. The server may have a preset model stored therein. The preset model may identify position information in which the position mark is in the image, i.e., image position information, from the first image. The server may crop the position-marker image from the first image. The server may identify the tag information in the location tag by using the preset model. And the server determines the target position information of the hanging bridge according to the image position information, the mark information and the preset parameters. The method provides a novel bridge crane real-time positioning method, and effectively improves stability and accuracy of bridge crane positioning.
Description
Technical Field
The present application relates to the field of computers, and in particular, to a method, apparatus, and system for positioning a bridge crane in real time.
Background
The bridge crane of a port is a large-scale device applied to loading and unloading of containers at the port. The bridge crane is usually pre-provided with fixed rails. The bridge crane can be moved back and forth within the track to effect transport of containers between the truck and the ship.
In the process of carrying out automatic operation of ports, it is an important ring to accurately acquire the real-time position of the bridge crane. In the prior art, the problem of signal interference exists due to the metal materials used for the bridge crane equipment. Therefore, even if a high-precision integrated navigation apparatus is installed in the bridge crane, a problem may occur in that accurate positioning cannot be stably provided.
Therefore, how to accurately and stably obtain the positioning of the bridge crane is a problem to be solved.
Disclosure of Invention
The application provides a real-time positioning method, device and system for a bridge crane, which are used for solving the problem of how to accurately acquire the positioning of the bridge crane.
In a first aspect, the present application provides a real-time positioning method for a bridge crane, including:
acquiring a first image comprising a position mark, wherein the position mark is arranged on a mark rod positioned at one side of the bridge crane;
determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model;
and determining the target position information of the hanging bridge according to the image position information, the marking information and the preset parameters.
Optionally, the preset model includes a first preset module and a second preset module;
the determining, according to the first image and a preset model, image position information of the position mark in the first image and mark information of the position mark includes:
preprocessing the first image according to the first image and the preprocessing step;
inputting the preprocessed first image into the first preset module to obtain image position information of the position mark in the first image;
cutting to obtain a position mark image according to the first image and the image position information;
and obtaining the marking information of the position mark by the second preset module of the position mark image.
Optionally, the preset parameters include an image width of the first image, a length of a marking rod of the marking rod shot by the first image, and a blind area distance;
the determining the target position information of the bridge crane according to the position information, the marking information and the preset parameters comprises the following steps:
determining a deviation distance according to the image position information, the image width and the marking rod length;
and determining the target position information of the bridge crane according to the marking information, the blind area distance and the deviation distance.
Optionally, the position mark is any one of a number or a two-dimensional code.
Optionally, the method further comprises:
acquiring a plurality of first images comprising the position marks;
marking the image position information of the position mark in the first image, and correspondingly marking the mark information of the position mark in the first image;
and training to obtain a preset model by using the marked first image.
In a second aspect, the present application provides a real-time positioning device for a bridge crane, comprising:
the acquisition module is used for acquiring a first image comprising a position mark, wherein the position mark is arranged on a mark rod positioned at one side of the bridge crane;
the processing module is used for determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model; and determining the target position information of the hanging bridge according to the image position information, the marking information and the preset parameters.
Optionally, the preset model includes a first preset module and a second preset module;
the processing module comprises:
preprocessing the first image according to the first image and the preprocessing step;
inputting the preprocessed first image into the first preset module to obtain image position information of the position mark in the first image;
cutting to obtain a position mark image according to the first image and the image position information;
and obtaining the marking information of the position mark by the second preset module of the position mark image.
Optionally, the preset parameters include an image width of the first image, a length of a marking rod of the marking rod shot by the first image, and a blind area distance;
the processing module is specifically configured to:
determining a deviation distance according to the image position information, the image width and the marking rod length;
and determining the target position information of the bridge crane according to the marking information, the blind area distance and the deviation distance.
Optionally, the position mark is any one of a number or a two-dimensional code.
Optionally, the apparatus further comprises:
the model training module is used for acquiring a plurality of first images comprising the position marks; marking the image position information of the position mark in the first image, and correspondingly marking the mark information of the position mark in the first image; and training to obtain a preset model by using the marked first image.
In a third aspect, the present application provides a server comprising: a memory and a processor;
the memory is used for storing program instructions; the processor is configured to invoke the program instructions in the memory to perform the bridge crane real time positioning method of the first aspect and any of the possible designs of the first aspect.
In a fourth aspect, the present application provides a real-time positioning system for a bridge crane, comprising: bridge crane, camera and server in any of the possible designs of the third aspect and the third aspect;
the camera is installed on the bridge crane supporting frame, and the servers are respectively in communication connection with the camera.
In a fifth aspect, the present application provides a readable storage medium having a computer program stored therein, which when executed by at least one processor of a server, performs the bridge crane real time positioning method of the first aspect and any one of the possible designs of the first aspect.
In a sixth aspect, the present application provides a computer program product comprising a computer program which, when executed by at least one processor of a server, performs the method of real-time positioning of a bridge in any of the first aspect and the possible designs of the first aspect.
According to the bridge crane real-time positioning method, a first image is obtained through a camera arranged on a bridge crane supporting frame, and the first image can comprise a position mark on a marking rod; identifying image position information of the position mark in the first image through a preset model; clipping the first image to obtain the position mark image; by using the preset model, the marker information in the position marker is identified. The server determines the means of the target position information of the hanging bridge according to the image position information, the mark information and the preset parameters, and achieves the effect of improving the accuracy of calculating the position of the hanging bridge.
Drawings
For a clearer description of the present application or of the prior art, the drawings that are used in the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are some embodiments of the present application, and that other drawings may be obtained from these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic view of a real-time positioning scenario of a bridge crane according to an embodiment of the present application;
FIG. 2 is a flow chart of a real-time positioning method for a bridge crane according to an embodiment of the present application;
fig. 3 is a view field schematic diagram of a camera according to an embodiment of the present disclosure;
FIG. 4 is a flow chart of a real-time positioning method for a bridge crane according to an embodiment of the present application;
FIG. 5 is a flow chart of a real-time positioning method for a bridge crane according to an embodiment of the present application;
FIG. 6 is a schematic structural diagram of a real-time positioning device for a bridge crane according to an embodiment of the present disclosure;
fig. 7 is a schematic hardware structure of a server according to an embodiment of the present application;
fig. 8 is a schematic structural diagram of a real-time positioning system for a bridge crane according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the present application will be clearly and completely described below with reference to the drawings in the present application, and it is apparent that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims of this application and in the above-described figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged where appropriate. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope herein.
The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
Furthermore, as used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context indicates otherwise.
It will be further understood that the terms "comprises," "comprising," "includes," and/or "including" specify the presence of stated features, steps, operations, elements, components, items, categories, and/or groups, but do not preclude the presence, presence or addition of one or more other features, steps, operations, elements, components, items, categories, and/or groups.
The terms "or" and/or "as used herein are to be construed as inclusive, or meaning any one or any combination. Thus, "A, B or C" or "A, B and/or C" means "any of the following: a, A is as follows; b, a step of preparing a composite material; c, performing operation; a and B; a and C; b and C; A. b and C). An exception to this definition will occur only when a combination of elements, functions, steps or operations are in some way inherently mutually exclusive.
The bridge crane of a port is a large-scale device applied to loading and unloading of containers at the port. The bridge crane is usually pre-provided with fixed rails. The bridge crane of the port can move irregularly according to berthing ship leaning conditions and operation requirements. When carrying out the automated operation in harbour, unmanned truck needs to acquire the real-time position of bridge crane accurately to stop in suitable position, improve the efficiency of getting on and off goods. In the prior art, the navigation device can realize the positioning of the bridge crane. However, since the metal material of the bridge crane apparatus interferes with the signal, there is a problem in that stable and accurate position information cannot be acquired even if a high-precision integrated navigation apparatus is mounted on the bridge crane. In addition, the prior art may also assist in positioning by means of mileage information that is moved on rails by means of a bridge crane. However, due to defects and errors of mileage equipment of the bridge crane, the mileage data is not stable enough and the accuracy is poor. At present, the original track of the bridge crane is replaced by the magnetic nail track, so that the problems of unstable mileage data and poor accuracy can be solved. However, the original track is replaced by the magnetic nail track, the existing track of the bridge crane is required to be modified, the consumed manpower and material resources are huge, and the normal operation of the bridge crane can be influenced.
Aiming at the problems, the application provides a real-time positioning method for a bridge crane. The real-time positioning of the bridge crane is realized based on visual detection. The supporting frame of the bridge crane can be provided with a camera. Meanwhile, one side of the bridge crane may be provided with a marking rod. The marking rod has mapped thereon position marks and/or intermittent scale readings. The marker post can be photographed within the effective field of view of the camera. The server may obtain a first picture taken by the camera including the position mark on the marking rod. The service area may identify a location marker in the first picture. The server can determine the position of the bridge crane according to the identification result.
The technical scheme of the present application is described in detail below with specific examples. The following embodiments may be combined with each other, and some embodiments may not be repeated for the same or similar concepts or processes.
Fig. 1 shows a schematic view of a scenario of real-time positioning of a bridge crane according to an embodiment of the present application. As shown, a bridge crane may be included in the scene. The bridge crane can move back and forth on the bridge crane track. The support frame of the bridge crane can be provided with a camera. The mounting height of the camera can be determined according to the marking rod. The marker post may be captured within the effective field of view of the camera. Cameras are arranged in the forward and backward moving direction of the bridge crane. The camera can also be used for obtaining pictures of the bridge crane track. The server can determine whether the bridge crane track is unobstructed according to the picture of the bridge crane track. The marking rod can be sprayed with a position mark, and the position mark can be information such as a number and a two-dimensional code. The position mark is used for marking distance information on the marking rod.
In the application, the server is taken as an execution main body, and the bridge crane real-time positioning method in the following embodiment is executed. Specifically, the server may be a background device disposed at the cloud end, or the server may also be an edge device installed at the data end. The execution body may be a hardware device of a server, or a software application implementing the embodiments described below in the server, or a computer-readable storage medium on which a software application implementing the embodiments described below is installed, or code of a software application implementing the embodiments described below.
Fig. 2 shows a flowchart of a real-time positioning method for a bridge crane according to an embodiment of the present application. On the basis of the embodiment shown in fig. 1, as shown in fig. 2, with the server as the execution body, the method of this embodiment may include the following steps:
s101, acquiring a first image comprising a position mark, wherein the position mark is arranged on a marking rod positioned on one side of the bridge crane.
In this embodiment, the server may acquire the first image through a camera mounted on the bridge crane support frame. The first image may include a position mark on the marking rod. When a plurality of cameras are installed on the bridge crane, the server may designate one of the cameras to acquire the first image.
In one example, the location marker is any one of a number or a two-dimensional code. The position marker is used to uniquely identify the distance on the marker post. The marking rod is a marking object parallel to the bridge crane track. The length of the marking rod can be greater than or equal to the moving range of the bridge crane. The position mark on the marking rod can be set according to the moving distance of the bridge crane.
S102, determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model.
In this embodiment, the server may store a preset model. The preset model is obtained by training based on a convolutional neural network model. The preset model may include a first preset module and a second preset module. The first preset module is used for acquiring the position mark through computer vision target detection. The second preset module is used for realizing the identification of the mark information of the position mark through identification methods such as character identification, two-dimensional code identification and the like.
The first preset module in the preset model may identify position information in which the position mark is in the image, i.e., image position information, from the first image. The image location information may include coordinates of the location marker in a coordinate system in which the image is located. For example, with the upper left corner of the image as the origin of coordinates, the image position information may include coordinate points (x 1, y 1). Where x1 represents the distance from the origin of the upper left corner of the position mark on the horizontal axis, and y1 represents the distance from the origin of the upper left corner of the position mark on the vertical axis. The image position information may further include (x 2, y 2). Where x2 represents the distance from the origin on the horizontal axis of the lower right corner of the position mark, and y2 represents the distance from the origin on the vertical axis of the lower right corner of the position mark. Alternatively, (w, h) may be further included in the image position information. Where w represents the width of the position mark and h represents the height of the position mark.
When the position mark is a mark symbol such as a number, a letter, a Chinese character and the like, the server determines the image position information of the position mark and then cuts out the position mark image from the first image. The server may identify the tag information in the location tag by using a second preset module in the preset model. The mark information is the content of digital information, letter information, chinese character information, etc. The second preset module may be an optical character recognition technology (Optical character recognition, OCR) module.
When the position mark is a two-dimensional code, after the server determines the image position information of the position mark, a position mark image can be obtained by cutting from the first image. The position mark image includes a two-dimensional code. The server may invoke a two-dimensional code identification service to identify the two-dimensional code. The two-dimensional code may include tag information therein. The tag information may be distance information.
When the position mark is other marks, the server can identify the marks through the preset model. The server can determine the position information corresponding to the identification by looking up the record table
S103, determining target position information of the hanging bridge according to the image position information, the mark information and the preset parameters.
In this embodiment, after the server acquires the position mark in the first image, a certain distance still exists between the position mark and the bridge crane. As shown in fig. 3, a certain distance exists between the camera view and the bridge crane, and the distance is a blind area distance. The camera cannot shoot in the distance. In addition, a certain distance exists between the position mark and the boundary of the blind area in the view field of the camera. Therefore, after the server acquires the marking information, the position of the bridge crane cannot be directly determined according to the marking information.
In one example, the preset parameters may include an image width of the first image, a marker bar length of the marker bar captured by the first image, and a blind area distance. The image width of the first image is the pixel point of the first image on the horizontal axis. The length of the marking rod shot by the first image is the visual field width of the camera. The width of the field of view is a fixed length after the camera is fixed on the support frame of the bridge crane. Wherein the blind zone distance may be as shown in fig. 3.
In an example, the server determines the target position of the bridge according to the marking information, and if the marking information is digital information, the method may include the following steps:
and 1, determining the deviation distance according to the image position information, the image width and the length of the marking rod.
In this step, it is assumed that the distance corresponding to any one of the scale readings n on the marking rod is X n The X is n Is constant. The length of the offset distance b will vary as the position mark changes in the field of view. For example, when the position mark is at the leftmost side of the camera field of view as shown in fig. 3, the offset distance is 0. The offset distance gradually increases as the position marker moves to the right within the camera field of view. The actual value of the offset distance b can be estimated from the pixel distance on the image. Assuming that the actual width of the scale reading on the marking rod is w, its corresponding pixel length on the image is w p . Assume that the scale reads to the field of view boundary (left edge as shown in FIG. 3) Has a pixel length b p The estimated offset distance b is calculated as:
and step 2, determining the target position information of the bridge crane according to the marking information, the blind area distance and the deviation distance.
In this step, the view angle of the camera is fixed while the camera is fixed to the support frame of the bridge crane. In this case, the blind area distance L is constant. Assuming that the mark information of the position mark at this time indicates that the reading is m, the distance of the corresponding position mark is X m . Then for any scale reading n, its position can be expressed as:
X n ＝X m -m+n
at X n In the known case, the bridge is moved to a certain position C i When the scale is at the time, if the scale reading is n i The calculation formula of the blind area distance L is:
L＝C i -X m -m+n i -b i
wherein b i Is the offset distance at that location. After the positions of the bridge crane are acquired at k different positions, the average value of the k blind area distances L can be determined as the final blind area distance. The calculation formula of the blind area distance L can be:
the calculation formula for determining the target position information C of the bridge crane by the server according to the marking information, the blind area distance and the deviation distance can be as follows:
C＝X n +L+b
according to the bridge crane real-time positioning method, the server can acquire the first image through the camera installed on the bridge crane supporting frame. The first image may include a position mark on the marking rod. The server may have a preset model stored therein. The preset model may identify position information in which the position mark is in the image, i.e., image position information, from the first image. The server may crop the position-marker image from the first image. The server may identify the tag information in the location tag by using the preset model. And the server determines the target position information of the hanging bridge according to the image position information, the mark information and the preset parameters. In the method, the position mark in the first image is identified, so that the calculation of the bridge crane position is realized, and the accuracy of the calculation of the bridge crane position is improved.
Fig. 4 shows a flowchart of a real-time positioning method for a bridge crane according to an embodiment of the present application. Based on the embodiments of fig. 2 and 3, the present embodiment is also capable of communicating with a truck, so that the truck is parked to a correct position according to the target position information, to improve loading and unloading efficiency. As shown in fig. 4, with the server as the execution body, the method of this embodiment may include the following steps:
s201, acquiring a first image comprising a position mark, wherein the position mark is arranged on a marking rod positioned on one side of the bridge crane.
S202, determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model.
S203, determining target position information of the hanging bridge according to the image position information, the mark information and the preset parameters.
Steps S201 to S203 are similar to steps S101 to S103 in the embodiment of fig. 2, and are not repeated here.
S204, broadcasting target position information so that the truck can be correctly parked according to the target position information and waiting for loading/unloading goods.
In this embodiment, the server may also broadcast the target location information to the truck in an automated job state after determining the target location information. When the truck in automatic operation needs to travel to the position below the bridge crane for loading and unloading, the truck can plan the optimal travel route according to the target position information broadcast by the server. So that the truck can be parked in the correct position quickly and accurately.
According to the bridge crane real-time positioning method, the server can acquire the first image through the camera installed on the bridge crane supporting frame. The first image may include a position mark on the marking rod. The server may have a preset model stored therein. The preset model may identify position information in which the position mark is in the image, i.e., image position information, from the first image. The server may crop the position-marker image from the first image. The server may identify the tag information in the location tag by using the preset model. And the server determines the target position information of the hanging bridge according to the image position information, the mark information and the preset parameters. The server may also broadcast the target location information to trucks in an automated job state after determining the target location information. In the method, the target position information is broadcast to the truck in an automatic operation state, so that the truck can be correctly parked according to the target position information and can wait for loading/unloading cargoes, and the cargo loading/unloading efficiency is improved.
Fig. 5 shows a flowchart of a real-time positioning method for a bridge crane according to an embodiment of the present application. Based on the embodiments shown in fig. 2 to 4, the present embodiment can also train a preset module for obtaining the predicted position marks by obtaining a large number of first images. As shown in fig. 5, with the server as the execution body, the method of the present embodiment may include the following steps:
s301, acquiring a plurality of first images comprising position marks.
In this embodiment, the server may acquire a plurality of first images captured by the camera. The different first images may include position markers located at different positions. Different position markers may also be included in the different first images.
S302, marking the image position information of the position mark in the first image, and correspondingly marking the mark information of the position mark in the first image.
In the present embodiment, it is necessary to add marks of image position information and mark information for each first image. The mark can be image position information and mark information which are obtained by the server through recognition from the first image according to a preset model. Alternatively, the mark may be mark information manually input by the user for each first image.
S303, training to obtain a preset model by using the marked first image.
In this embodiment, after the server acquires the marked plurality of first images, the first images and the marks of the first images may be input into the model together. The server can obtain a preset model through the training of the model. The preset model may be used to accurately identify image position information of the position marker and marker information of the position marker in the first image.
In one example, the server may input the first image and the marked image location information into a preset model. The server can obtain a first preset module of the preset model through training. The first preset module is used for accurately identifying the image position information of the position mark in the first image. The server may crop the first image according to the image position information to obtain a position mark image. The position mark image and the mark information of the mark are input into a preset model. The server may obtain the second preset module by training the preset model. The second preset module is used for accurately identifying the mark information of the position mark in the position mark image.
According to the bridge crane real-time positioning method, the server can acquire a plurality of first images shot by the camera. The image position information of the position mark in the first image is marked in the first image, and the mark information of the position mark in the first image is correspondingly marked. And training to obtain a preset model by using the marked first image. In the method, a preset model is obtained through training the marked first image, so that prediction of image position information and mark information of the position mark in the first image is realized.
Fig. 6 is a schematic structural diagram of a real-time bridge crane positioning apparatus according to an embodiment of the present application, as shown in fig. 6, a real-time bridge crane positioning apparatus 10 according to the present embodiment is used for implementing operations corresponding to a server in any of the above method embodiments, where the real-time bridge crane positioning apparatus 10 according to the present embodiment includes:
the acquisition module 11 is used for acquiring a first image comprising position marks, and the position marks are arranged on a marking rod positioned on one side of the bridge crane.
The processing module 12 is configured to determine image position information of the position mark in the first image and mark information of the position mark according to the first image and the preset model. And determining the target position information of the hanging bridge according to the image position information, the mark information and the preset parameters.
In one example, the preset parameters include an image width of the first image, a marker bar length of the marker bar captured by the first image, and a blind area distance.
The processing module 12 is specifically configured to:
the offset distance is determined based on the image position information, the image width, and the marker post length.
And determining the target position information of the bridge crane according to the marking information, the blind area distance and the deviation distance.
In one example, the location marker is any one of a number or a two-dimensional code.
In one example, the bridge crane real-time positioning apparatus 10 further comprises:
the model training module is used for acquiring a plurality of first images comprising position marks. The image position information of the position mark in the first image is marked in the first image, and the mark information of the position mark in the first image is correspondingly marked. And training to obtain a preset model by using the marked first image.
The bridge crane real-time positioning device 10 provided in the embodiment of the present application may execute the above method embodiment, and the specific implementation principle and technical effects thereof may be referred to the above method embodiment, which is not described herein again.
Fig. 7 shows a schematic hardware structure of a server according to an embodiment of the present application. As shown in fig. 7, the server 20, configured to implement operations corresponding to the server in any of the above method embodiments, the server 20 of this embodiment may include: a memory 21, a processor 22 and a communication interface 24.
A memory 21 for storing a computer program. The Memory 21 may include a high-speed random access Memory (Random Access Memory, RAM), and may further include a Non-Volatile Memory (NVM), such as at least one magnetic disk Memory, and may also be a U-disk, a removable hard disk, a read-only Memory, a magnetic disk, or an optical disk.
A processor 22 for executing a computer program stored in the memory to implement the bridge crane real time positioning method in the above embodiment. Reference may be made in particular to the relevant description of the embodiments of the method described above. The processor 22 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the present invention may be embodied directly in a hardware processor for execution, or in a combination of hardware and software modules in a processor for execution.
Alternatively, the memory 21 may be separate or integrated with the processor 22.
When memory 21 is a separate device from processor 22, server 20 may also include a bus 23. The bus 23 is used to connect the memory 21 and the processor 22. The bus 23 may be an industry standard architecture (Industry Standard Architecture, ISA) bus, an external device interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, the buses in the drawings of the present application are not limited to only one bus or one type of bus.
The communication interface 24 may be connected to the processor 21 via a bus 23. The processor 22 may control the communication interface 24 to take a first picture taken by the camera. The processor 22 may also control the communication interface 24 to broadcast the target location information to terminal devices such as trucks that need to obtain the target location information.
The server provided in this embodiment may be used to execute the foregoing bridge crane real-time positioning method, and its implementation manner and technical effects are similar, and this embodiment is not repeated here.
Fig. 8 shows a schematic structural diagram of a real-time positioning system for a bridge crane according to an embodiment of the present application. As shown in fig. 8, the bridge crane real time positioning system 30 may include: bridge 32, camera 33 and server 34.
Wherein the camera 33 is mounted on a support frame of the bridge crane 32. The camera 33 may be mounted in particular at a distance of 4 meters from the ground of the support frame of the bridge 32. The server may be communicatively coupled to the camera and obtain the first image from the camera.
The server may also be connected to a terminal device such as a truck equipped with an autopilot system, which needs to acquire target position information. The server may acquire the target location information according to an acquisition request of the terminal device. The server may also broadcast the target location information according to a preset frequency terminal device. After the truck receives the target position information, the optimal driving route planning is realized, the rapid and effective parking is realized, and the cargo loading/unloading efficiency is improved. The truck is a truck that can carry containers.
The bridge crane real-time positioning system 30 provided in this embodiment may be used to execute the above-mentioned bridge crane real-time positioning method, and its implementation manner and technical effects are similar, and the details of this embodiment are not repeated here.
The present application also provides a computer-readable storage medium having a computer program stored therein, which when executed by a processor is adapted to carry out the methods provided by the various embodiments described above.
The computer readable storage medium may be a computer storage medium or a communication medium. Communication media includes any medium that facilitates transfer of a computer program from one place to another. Computer storage media can be any available media that can be accessed by a general purpose or special purpose computer. For example, a computer-readable storage medium is coupled to the processor such that the processor can read information from, and write information to, the computer-readable storage medium. In the alternative, the computer-readable storage medium may be integral to the processor. The processor and the computer readable storage medium may reside in an application specific integrated circuit (Application Specific Integrated Circuits, ASIC). In addition, the ASIC may reside in a user device. The processor and the computer-readable storage medium may also reside as discrete components in a communication device.
In particular, the computer readable storage medium may be implemented by any type or combination of volatile or non-volatile Memory devices, such as Static Random-Access Memory (SRAM), electrically erasable programmable Read-Only Memory (EEPROM), erasable programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), programmable Read-Only Memory (Programmable Read-Only Memory, PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic or optical disk. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.
The present application also provides a computer program product comprising a computer program stored in a computer readable storage medium. The computer program may be read from a computer-readable storage medium by at least one processor of the apparatus, and executed by the at least one processor, causes the apparatus to implement the methods provided by the various embodiments described above.
The embodiments also provide a chip including a memory for storing a computer program and a processor for calling and running the computer program from the memory, so that a device on which the chip is mounted performs the method in the above various possible embodiments.
In the several embodiments provided in this application, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of modules is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple modules may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or modules, which may be in electrical, mechanical, or other forms.
Wherein the individual modules may be physically separated, e.g. mounted in different locations of one device, or mounted on different devices, or distributed over a plurality of network elements, or distributed over a plurality of processors. The modules may also be integrated together, e.g. mounted in the same device, or integrated in a set of codes. The modules may exist in hardware, or may also exist in software, or may also be implemented in software plus hardware. The purpose of the embodiment scheme can be achieved by selecting part or all of the modules according to actual needs.
When the individual modules are implemented as software functional modules, the integrated modules may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or processor to perform some steps of the methods of the various embodiments of the present application.
It should be understood that, although the steps in the flowcharts in the above embodiments are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the figures may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily occurring in sequence, but may be performed alternately or alternately with other steps or at least a portion of the other steps or stages.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and are not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments may be modified or some or all of the technical features may be replaced with equivalents. Such modifications and substitutions do not depart from the spirit of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.
Claims (8)
1. A method for positioning a bridge crane in real time, the method comprising:
acquiring a first image comprising a position mark, wherein the position mark is arranged on a mark rod positioned at one side of the bridge crane, and the mark rod is parallel to a bridge crane track;
determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model;
determining target position information of the bridge crane according to the image position information, the marking information and preset parameters;
the preset parameters comprise the image width of the first image, the length of the marking rod shot by the first image and the blind area distance, wherein the blind area distance is the distance between the view field of the camera and the bridge crane;
the determining the target position information of the bridge crane according to the image position information, the marking information and the preset parameters comprises the following steps:
determining a deviation distance according to the image position information, the image width and the length of the marking rod, wherein the deviation distance is the distance between the leftmost side of the camera view and the position mark;
and determining the target position information of the bridge crane according to the mark information, the dead zone distance and the sum of the deviation distance.
2. The method of claim 1, wherein the pre-set model comprises a first pre-set module and a second pre-set module;
the determining, according to the first image and a preset model, image position information of the position mark in the first image and mark information of the position mark includes:
preprocessing the first image according to the first image and the preprocessing step;
inputting the preprocessed first image into the first preset module to obtain image position information of the position mark in the first image;
cutting to obtain a position mark image according to the first image and the image position information;
and inputting the position mark image into the second preset module to obtain mark information of the position mark.
3. The method of any one of claims 1-2, wherein the position marker is used to uniquely identify the distance of the marker post, the position marker being any one of a number, letter, or two-dimensional code.
4. The method according to any one of claims 1-2, further comprising:
acquiring a plurality of first images comprising the position marks;
marking the image position information of the position mark in the first image, and correspondingly marking the mark information of the position mark in the first image;
and training to obtain a preset model by using the marked first image.
5. A real-time positioning device for a bridge crane, the device comprising:
the acquisition module is used for acquiring a first image comprising a position mark, wherein the position mark is arranged on a mark rod positioned at one side of the bridge crane, and the mark rod is parallel to the bridge crane track;
the control module is used for determining image position information of the position mark in the first image and mark information of the position mark according to the first image and a preset model; determining target position information of the bridge crane according to the image position information, the marking information and preset parameters;
the preset parameters comprise the image width of the first image, the length of the marking rod shot by the first image and the blind area distance, wherein the blind area distance is the distance between the view field of the camera and the bridge crane;
the control module is specifically configured to determine a deviation distance according to the image position information, the image width and the length of the marking rod, where the deviation distance is a distance between the leftmost side of the camera view and the position mark;
and determining the target position information of the bridge crane according to the mark information, the dead zone distance and the sum of the deviation distance.
6. A server, the server comprising: a memory, a processor;
the memory is used for storing a computer program; the processor is configured to implement the bridge crane real-time positioning method according to the computer program stored in the memory.
7. A bridge crane real-time positioning system, the system comprising: bridge crane, camera and server according to claim 6; the camera is installed on the bridge crane supporting frame, and the servers are respectively in communication connection with the camera.
8. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program for implementing the bridge crane real time positioning method according to any of claims 1-4 when executed by a processor.
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