CN112633157B - Real-time detection method and system for safety of AGV working area - Google Patents
Real-time detection method and system for safety of AGV working area Download PDFInfo
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- 238000004519 manufacturing process Methods 0.000 claims abstract description 11
- 238000012544 monitoring process Methods 0.000 claims description 17
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Abstract
The invention discloses a real-time detection method for the safety of an AGV working area, which comprises the following steps: manufacturing an AGV working area diagram according to the AGV working area; marking the positions of an AGV working area and a goods placing area in an AGV working area diagram according to the area coordinates respectively; the AGV working area map marked with the position is added to a video stream of the AGV working area for display; processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video; and judging whether a person enters an AGV working area or not and whether the goods placement position is wrong or not according to the AGV working area diagram of the area pixel coordinates and the marking position. The invention considers the influence of the stored objects in the area on the area safety, has better visual effect and improves the safety of the AGV working area.
Description
Technical Field
The invention relates to the technical field of video monitoring, in particular to a real-time detection method and system for the safety of an AGV working area.
Background
With the continuous development of intelligent monitoring technology and the increasing maturity of image processing technology, the method of manually performing regional monitoring can not meet the actual needs. At present, the intelligent monitoring system mainly based on artificial intelligence, video analysis and other technologies makes up the problem of the deficiency of the artificial method to a certain extent. The intelligent monitoring system has the advantages that monitoring personnel can quickly make decisions by acquiring actual conditions of the scene through videos transmitted back by the monitoring system without on-site patrol, so that the intelligent monitoring system has wide development space and huge potential market. The existing area detection method mainly adopts the technologies of guard area intrusion detection, regional people stream statistics and regional crowd density detection, wherein the guard area intrusion detection is used for identifying targets which intrude into a guard area, the regional people stream statistics is used for counting the in-out people stream of a certain area in a certain period of time, and the regional crowd density detection is used for counting the targets in a certain area. Generally, the current area detection technology is to mark an area needing early warning by combining a visual analysis algorithm with a camera, and when people in the area are detected, an early warning function is generated. Aiming at an AGV working area, the current area detection technology does not consider the influence of objects in the area on the area safety, the function is single, and the visual effect is poor.
Disclosure of Invention
Aiming at the defects of the prior art, the invention aims to provide a real-time detection method and a real-time detection system for the safety of an AGV working area, so as to solve the problem that the influence of objects in the area on the safety of the area is not considered in the prior art.
In order to solve the technical problems, the invention adopts the following technical scheme:
a real-time detection method for the safety of an AGV working area comprises the following steps:
manufacturing an AGV working area diagram according to the AGV working area;
Marking the positions of an AGV working area and a goods placing area in an AGV working area diagram according to the area coordinates respectively;
the AGV working area map marked with the position is added to a video stream of the AGV working area for display;
processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video;
And judging whether a person enters an AGV working area or not and whether the goods placement position is wrong or not according to the AGV working area diagram of the area pixel coordinates and the marking position.
Further, the neural network model is built based on a deep learning framework tensorflow.
Further, the neural network model is obtained as follows:
acquiring a video stream for monitoring an AGV working area;
capturing a picture from a video stream and marking AGVs, cargoes and people in the picture to obtain a training set;
And training the neural network model through the training set to obtain the neural network model capable of identifying the AGVs, cargoes and people in the AGV working area.
Further, the video stream is acquired by a monitoring camera; the monitoring camera is selected according to the area and the length-width ratio of the AGV working area; the monitoring camera is arranged right above the AGV working area.
Further, the video stream is obtained from the camera in real time and continuously through a communication protocol.
Further, the method for judging whether the person enters the AGV working area and whether the goods placement position is wrong comprises the following steps:
If the area determined by the area pixel coordinates of the person intersects with the AGV working area in the AGV working area diagram, the person is judged to enter the AGV working area, otherwise, the person is judged not to enter the AGV working area; if the goods placement area in the AGV working area diagram cannot completely contain the goods, the goods placement position error can be judged.
A real-time detection system for AGV work area safety, the system comprising:
and (3) manufacturing a module: the AGV working area map is used for manufacturing an AGV working area map according to the AGV working area;
and a marking module: the position of an AGV working area and the position of a goods placing area in the AGV working area diagram are marked according to the area coordinates respectively;
And (3) an additional module: the AGV working area map used for determining the position is added to a video stream of the AGV working area for display;
The acquisition module is used for: the method comprises the steps of processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video;
And a judging module: and the AGV working area diagram is used for judging whether a person enters an AGV working area or not and whether the goods placing position is wrong or not according to the area pixel coordinates and the marking position.
A real-time detection system for AGV work area safety, the system comprising a processor and a storage medium;
The storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method described above.
A computer readable storage medium having stored thereon a computer program which when executed by a processor realizes the steps of the method described above.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the video stream of the AGV working area is processed in real time through the neural network model, the area pixel coordinates of the AGV, the goods and the person in the video are obtained, the area pixel coordinates of the AGV, the goods and the person are compared with the AGV working area diagram, whether the person enters the AGV working area or not and whether the goods placement position is wrong or not is judged, the state of the object in the current area can be obtained and analyzed in real time, the influence of the stored object in the area on the area safety is considered, the visual effect is good, and the safety of the AGV working area is improved.
Drawings
FIG. 1 is a simplified AGV work area diagram;
FIG. 2 is a flow chart of the proposed method of the present invention;
FIG. 3 is a schematic illustration of a person entering an AGV work area;
FIG. 4 is a diagram illustrating a cargo placement error.
Detailed Description
The present invention will be further described with reference to the accompanying drawings, and the following examples are only for more clearly illustrating the technical solution of the present invention, and are not to be construed as limiting the scope of the present invention.
A real-time detection method for the safety of an AGV working area comprises the following steps:
Manufacturing an AGV working area diagram according to the AGV working area; marking the positions of an AGV working area and a goods placing area in an AGV working area diagram according to the area coordinates respectively; the AGV working area map marked with the position is added to a video stream of the AGV working area for display; processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video; and judging whether a person enters an AGV working area or not and whether the goods placement position is wrong or not according to the AGV working area diagram of the area pixel coordinates and the marking position.
As shown in fig. 2, a real-time detection method for the safety of an AGV working area specifically includes the following steps:
Step S1: the area and the aspect ratio of the AGV working area to be monitored are used for selecting a camera meeting the monitoring requirement, then the camera is installed right above the AGV working area, the video stream of the AGV working area in the camera is continuously acquired in real time by using a communication protocol for 24 hours, and an area scene video image is acquired.
Step S2: and capturing a certain number of pictures of the AGV working areas from the video stream of the AGV working areas, and marking the AGVs, the cargoes and the people in the pictures by using marking tools to obtain a training set.
Step S3: s3.1, constructing a deep neural network model by using a deep learning framework tensorflow in deep learning, and training the neural network model by using the training set in the step 2 to obtain the neural network model capable of identifying AGVs, cargoes and people in an AGV working area.
Step S4: s4.1, a simple AGV working area diagram is manufactured according to the AGV working area monitored by the camera, as shown in FIG. 1, detailed area coordinates (Xmin, ymin, xmax and Ymax) of the AGV working area and the goods placing area are obtained by using a pixel coordinate system of the diagram, wherein a rectangular area is determined by the coordinates (Xmin, ymin, xmax and Ymax); and S4.2, the image is added to a video stream in the camera for display, so that the visual effect is improved.
Step S5: the method comprises the steps that a trained neural network model in the step 3 is utilized to process video streams in a camera in real time, AGVs, cargos and people in the video are identified, regional pixel coordinates (Xmin, ymin, xmax and Ymax) of the AGVs, the cargos and the people are respectively obtained, states of the AGVs, the cargos and the people, such as the position of the AGVs, whether each cargo placement position is idle, the cargo placement state and the like, are obtained continuously in real time, and then alarm processing is carried out on the conditions that the cargo placement position is wrong or is not fully placed in the placement position and the personnel enter the AGVs to influence the safety of the working area according to a simple AGV working area diagram; if the area determined by the area pixel coordinates (PersonXmin, personYmin, personXmax, personYmax) of the person and the area determined by the area coordinates (WorkXmin, workYmin, workXmax, workYmax) of the AGV working area meet (PersonXmin > = WorkXmax or PersonYmin > = WorkYmax or PersonXmax < = WorkXmin or PersonYmax < = WorkYmin), the person does not enter the AGV working area, otherwise, the AGV working area and the area where the person is located intersect, which indicates that the person enters the AGV working area, and an area alarm is performed. As shown in fig. 3. Judging according to the region coordinates, if the cargo is to be correctly placed in the region, the cargo cannot be completely contained, for example: if the goods to be placed area is 3 (Load 3Xmin, load3Ymin, load3Xmax, load3 Ymax) and the goods area coordinates (CargoXmin, cargoYmin, cargoXmax, cargoYmax) cannot be satisfied simultaneously (Load 3Xmin < = CargoXmin, load3Ymin < = CargoYmin, load3Xmax > = CargoXmax, load3Ymax > = CargoYmax), the goods placement position error can be determined, and an alarm response is made. As shown in fig. 4.
A real-time detection system for AGV work area safety, the system comprising:
and (3) manufacturing a module: the AGV working area map is used for manufacturing an AGV working area map according to the AGV working area;
and a marking module: the position of an AGV working area and the position of a goods placing area in the AGV working area diagram are marked according to the area coordinates respectively;
And (3) an additional module: the AGV working area map used for determining the position is added to a video stream of the AGV working area for display;
The acquisition module is used for: the method comprises the steps of processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video;
And a judging module: and the AGV working area diagram is used for judging whether a person enters an AGV working area or not and whether the goods placing position is wrong or not according to the area pixel coordinates and the marking position.
A real-time detection system for AGV work area safety, the system comprising a processor and a storage medium;
The storage medium is used for storing instructions;
the processor is configured to operate according to the instructions to perform the steps of the method described above.
A computer readable storage medium having stored thereon a computer program which when executed by a processor realizes the steps of the method described above.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (8)
1. The real-time detection method for the safety of the AGV working area is characterized by comprising the following steps of:
manufacturing an AGV working area diagram according to the AGV working area;
Acquiring detailed area coordinates of an AGV working area and a goods placement area by using a pixel coordinate system of a picture in an AGV working area diagram; marking the positions of the AGV working area and the goods placing area in the AGV working area diagram according to detailed area coordinates of the AGV working area and the goods placing area;
the AGV working area map marked with the position is added to a video stream of the AGV working area for display;
processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video;
Judging whether the person enters an AGV working area or not and whether the goods placement position is wrong or not according to the AGV working area diagram of the goods, the regional pixel coordinates of the person and the marking position;
the method for judging whether the person enters the AGV working area and whether the goods placement position is wrong comprises the following steps:
If the area determined by the area pixel coordinates of the person intersects with the AGV working area in the AGV working area diagram, the person is judged to enter the AGV working area, otherwise, the person is judged not to enter the AGV working area; if the goods placement area in the AGV working area diagram cannot completely contain the goods, the goods placement position error can be judged.
2. The method of claim 1 wherein the neural network model is constructed based on a deep learning framework tensorflow.
3. The method for detecting the safety of an AGV working area in real time according to claim 1, wherein the neural network model is obtained as follows:
acquiring a video stream for monitoring an AGV working area;
capturing a picture from a video stream and marking AGVs, cargoes and people in the picture to obtain a training set;
And training the neural network model through the training set to obtain the neural network model capable of identifying the AGVs, cargoes and people in the AGV working area.
4. The method for detecting the safety of an AGV working area according to claim 3 wherein said video stream is acquired by a monitoring camera; the monitoring camera is selected according to the area and the length-width ratio of the AGV working area; the monitoring camera is arranged right above the AGV working area.
5. The method of claim 3 wherein said video stream is obtained from a camera in real time and uninterrupted by a communication protocol.
6. A real-time detection system for the safety of an AGV work area, the system comprising:
and (3) manufacturing a module: the AGV working area map is used for manufacturing an AGV working area map according to the AGV working area;
and a marking module: the method comprises the steps that a pixel coordinate system of a picture in an AGV working area diagram is used for obtaining detailed area coordinates of an AGV working area and a goods placing area; marking the positions of the AGV working area and the goods placing area in the AGV working area diagram according to detailed area coordinates of the AGV working area and the goods placing area;
And (3) an additional module: the AGV working area map used for determining the position is added to a video stream of the AGV working area for display;
The acquisition module is used for: the method comprises the steps of processing a video stream of an AGV working area through a neural network model, and acquiring area pixel coordinates of the AGV, cargoes and people in the video;
And a judging module: the AGV working area map is used for judging whether the person enters an AGV working area or not and whether the goods placement position is wrong or not according to the area pixel coordinates of the goods and the person and the AGV working area map of the marking position;
the method for judging whether the person enters the AGV working area and whether the goods placement position is wrong comprises the following steps:
If the area determined by the area pixel coordinates of the person intersects with the AGV working area in the AGV working area diagram, the person is judged to enter the AGV working area, otherwise, the person is judged not to enter the AGV working area; if the goods placement area in the AGV working area diagram cannot completely contain the goods, the goods placement position error can be judged.
7. A real-time detection system for the safety of an AGV working area, which is characterized by comprising a processor and a storage medium;
The storage medium is used for storing instructions;
The processor being operative according to the instructions to perform the steps of the method according to any one of claims 1-5.
8. Computer readable storage medium, on which a computer program is stored, characterized in that the program, when being executed by a processor, implements the steps of the method according to any of claims 1-5.
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| CN113343962B (en) * | 2021-08-09 | 2021-10-29 | 山东华力机电有限公司 | Visual perception-based multi-AGV trolley working area maximization implementation method |
| CN115171423A (en) * | 2022-06-24 | 2022-10-11 | 上海智能网联汽车技术中心有限公司 | Parking lot system supporting unmanned area linkage and vehicle scheduling method |
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