Automatic stacking system and method for warehouse goods

Abstract

The invention relates to the technical field of logistics storage automation, and provides a warehouse goods automatic stacking system comprising a data acquisition module used for acquiring task instructions and goods state information; the algorithm optimization module is used for matching the task instruction with the cargo state information to obtain cargo stacking sequence information; the central control scheduling module is used for scheduling the AGV, the stacking robot and the conveying line based on the cargo stacking sequence information; the stacking control module is used for controlling movement and reloading of a stacking robot clamp; the invention further provides an automatic stacking method for the warehouse goods based on the automatic stacking system for the warehouse goods. Different types of goods are identified through the visual module, the stacking robot and various transportation devices are coordinated through the central control dispatching module, rapid sorting and stacking of the different types of goods are achieved, unmanned warehouse goods sorting and stacking can be achieved, and the labor intensity of workers is reduced. The labor cost is reduced, and the possibility that workers are injured due to contact with heavy objects is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics warehousing automation, and in particular to an automatic warehouse cargo stacking system and method. Background Art

[0002] With the rapid development of modern industry stimulated by the commodity economy and the popularization of digitalization, the intelligent upgrade of traditional large warehouses is particularly important. Most manufacturing companies have different storage needs, requiring various transport vehicles and corresponding storage space to classify, transport and store different types of pallets. The existing intelligent warehousing system is not mature enough in terms of the intelligence of scheduling and data processing, and lacks the ability to respond to environmental changes in real time.

[0003] Moreover, unmanned logistics is an inevitable trend, which can not only save more labor costs, but also prevent employees from touching heavy objects, reduce the occurrence of accidents, and protect the health of employees. There is an urgent need and extremely high economic potential for a warehouse to achieve automated unmanned upgrades.

[0004] The existing AVG warehouse conveyor system is too specialized, requiring a lot of manual design for routes and deployment, and is too costly. The products transported and stacked are relatively single, and it cannot handle a large number of different goods at the same time. Therefore, there is an urgent need for a warehouse automated stacking system that can simultaneously identify and sort and stack different types of goods and is easy to deploy. Summary of the invention

[0005] The present invention provides a warehouse cargo automatic stacking system and method, the main purpose of which is to visually identify different categories of cargo, and coordinate stacking robots and various transport devices through a central control scheduling module to achieve rapid sorting and stacking of different categories of cargo.

[0006] The automatic warehouse cargo stacking system is characterized by comprising: a data acquisition module, an algorithm optimization module, a central control scheduling module, a stacking control module and a visualization module;

[0007] The data collection module is used to collect task instructions and cargo status information;

[0008] The algorithm optimization module is used to match the task instruction with the cargo status information to obtain cargo stacking sequence information;

[0009] The central control scheduling module schedules the speed of AGVs transporting goods, stacking robots moving, and conveyor lines transporting goods based on the goods stacking order information;

[0010] The stacking control module is used to control the movement and replacement of the stacking robot fixture;

[0011] A visualization module, used to display the completion status of the collection task instructions and the cargo status information in real time;

[0012] The data collection module includes a visual recognition device, through which the cargo status information at a fixed position is collected in real time.

[0013] The algorithm optimization module includes a recognition optimization model and a decision optimization model; the recognition optimization module uses a pyramid algorithm to perform image optimization processing on the cargo status information, and the decision optimization model uses a simulated annealing algorithm to achieve an optimal solution for the stacking sequence.

[0014] Preferably, there are at least two visual recognition devices, one of which is aimed at the bottom plate to obtain the status information of the goods on the bottom plate, and the other visual recognition device is aimed at the raw material goods to obtain the status information of the raw material goods.

[0015] Preferably, the method for identifying cargo status information using the visual recognition model comprises the following steps:

[0016] S1, a visual recognition device photographs a fixed position at a preset time interval to obtain an image photo at the fixed position;

[0017] S2, uploading each of the image photos to the server in chronological order;

[0018] S3, performing object recognition on each of the image photos, and matching each recognized object with the cargo information stored in the server;

[0019] S4, using a pyramid algorithm, superimposing each of the image photos in chronological order to construct three-dimensional cargo status information at the fixed position.

[0020] Preferably, in step S3, an edge detection algorithm is used to identify objects in the image photograph, and the outline size of each discrete individual in the image photograph is measured.

[0021] Preferably, there are at least two stacking robots, including a general stacking robot and a special stacking robot. The general stacking robot can identify and sort all goods, and the special stacking robot can only identify and sort one type of goods.

[0022] Preferably, the data acquisition module also includes collecting site path information, and the site path information is collected by a visual acquisition device or a radar acquisition device located on the AGV vehicle.

[0023] Preferably, it also includes an automatic obstacle avoidance module, which calculates the running path of the AGV vehicle. Based on the site path information, the automatic obstacle avoidance application includes dynamic replanning, ant colony algorithm or genetic algorithm to calculate the running path.

[0024] Preferably, the data acquisition module also includes a height measuring device, which includes at least two positioning devices, and the positioning device includes a visual recognition device or a radar. The cargo height information is measured and collected by identifying the same cargo by at least two of the positioning devices.

[0025] Preferably, the formula of the pyramid algorithm includes:

[0026] Collect cargo status information in chronological order, with the first one being the next sampling information ; The latter is the upsampling information ;

[0027] (x,y)= (2x,2y);

[0028] = −upsample( +1), where k is the cargo status information of layer k.

[0029] Based on the above system, the present invention also provides a method for automatically stacking goods in a warehouse, comprising:

[0030] S11, the data acquisition module acquires task instructions;

[0031] S12, the central control scheduling module schedules the AGV to transport the goods to the designated location;

[0032] S13, the stacking robot collects cargo status information through a visual recognition device, and uploads the cargo status information to a server carrying the algorithm optimization module;

[0033] S14, the algorithm optimization module calculates the cargo stacking sequence information;

[0034] S15, based on the cargo stacking sequence information and cargo status information, the central control scheduling module controls the stacking robot to adjust the clamp and move the cargo to the conveyor belt;

[0035] S16, the central control scheduling module controls the conveyor belt to transport the goods to another stacking robot;

[0036] S17, the central control scheduling module controls the stacking robot to place the goods from the conveyor belt to the designated location, thereby realizing automatic stacking of the goods in the warehouse.

[0037] The present invention proposes an automatic warehouse cargo stacking system and method, which can realize fast sorting and stacking of different categories of cargo by visually identifying different categories of cargo and coordinating stacking robots and various transport devices through a central control scheduling module. The AVG trolley has an automatic obstacle avoidance module that can calculate a suitable running path in real time. The deployment is simple and can realize unmanned sorting and stacking of cargo in the warehouse, thereby reducing labor costs and the possibility of employees being injured due to contact with heavy objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a structural schematic diagram of the automatic warehouse cargo stacking system of the present invention;

[0039] Figure 2 This is a flow chart of a method for identifying cargo status information using a visual recognition model of the present invention;

[0040] Figure 3 This is a flow chart of the automatic stacking method of warehouse goods of the present invention;

[0041] Figure 4 A schematic diagram of one embodiment of the automatic warehouse cargo stacking system of the present invention;

[0042] Figure 5 It is a schematic diagram of another embodiment of the automatic warehouse cargo stacking system of the present invention.

[0043] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0045] like Figure 1 As shown, a warehouse cargo automatic stacking system includes: a data acquisition module, an algorithm optimization module, a central control scheduling module, a stacking control module and a visualization module;

[0046] Data collection module, used to collect task instructions and cargo status information;

[0047] Algorithm optimization module, used to match task instructions with cargo status information to obtain cargo stacking sequence information;

[0048] The central control scheduling module schedules the speed of AGVs transporting goods, stacking robots moving, and conveyor lines transporting goods based on the goods stacking order information;

[0049] The stacking control module is used to control the movement and replacement of the stacking robot fixture;

[0050] Visualization module, used to display the completion status of collection task instructions and cargo status information in real time;

[0051] The data collection module includes a visual recognition device, which collects the status information of the goods at a fixed position in real time.

[0052] The algorithm optimization module includes a recognition optimization model and a decision optimization model; the recognition optimization module uses a pyramid algorithm to perform image optimization processing on cargo status information, and the decision optimization model uses a simulated annealing algorithm to achieve the optimal solution for the stacking order.

[0053] Furthermore, there are at least two visual recognition devices, one of which is aimed at the bottom plate to obtain the status information of the goods on the bottom plate, and the other visual recognition device is aimed at the raw material goods to obtain the status information of the raw material goods.

[0054] Furthermore, if Figure 2 As shown, the method for recognizing cargo status information by a visual recognition model includes the following steps:

[0055] S1, the visual recognition device photographs a fixed position at a preset time interval to obtain an image photo at the fixed position;

[0056] S2, upload each image photo to the server in chronological order;

[0057] S3, performing object recognition on each image photo, and matching each recognized object with the cargo information stored in the server;

[0058] S4, using a pyramid algorithm, superimposes each image photo in chronological order to construct three-dimensional cargo status information at a fixed position.

[0059] Furthermore, in step S3, an edge detection algorithm is used to identify objects in the image photograph, and the outline size of each discrete individual in the image photograph is measured.

[0060] Furthermore, the formula of the pyramid algorithm includes:

[0061] Collect cargo status information in chronological order, with the first one being the next sampling information ; The latter is the upsampling information ;

[0062] (x,y)= (2x,2y);

[0063] = −upsample( +1), where k is the cargo status information of layer k.

[0064] In a certain embodiment, the image photos will be preprocessed first. The purpose is that during the image acquisition, digitization and transmission process, due to the influence of environmental conditions (such as light intensity, light uniformity, shooting angle), equipment performance and random interference, the original image obtained by the camera may have problems such as image blur, poor contrast, mixed noise, etc. In order to improve the effect of feature extraction, matching and recognition, the contrast between the recognition target and the image background is first enhanced by grayscale transformation, and then the interference points are removed by the filtering algorithm. Finally, the edge detection algorithm is used to extract the geometric edges of the target object, so that the geometric edges and contour sizes of the object are compared with the sizes of the standard library of goods, and the type of goods can be identified more accurately.

[0065] Furthermore, there are at least two stacking robots, including a general stacking robot and a special stacking robot. The general stacking robot can identify and sort all goods, while the special stacking robot can only identify and sort one type of goods.

[0066] Furthermore, the data collection module also includes collecting site path information, and the site path information is collected by a visual collection device or a radar collection device located on the AGV vehicle.

[0067] Furthermore, it also includes an automatic obstacle avoidance module, which calculates the running path of the AGV car. Based on the site path information, the automatic obstacle avoidance application includes dynamic replanning, ant colony algorithm or genetic algorithm to calculate the running path.

[0068] Furthermore, the data acquisition module also includes a height measuring device, which includes at least two positioning devices, and the positioning device includes a visual recognition device or a radar. The same cargo is recognized by at least two positioning devices to measure and collect cargo height information.

[0069] Further, if Figure 3 As shown, based on the above-mentioned automatic stacking of warehouse goods, a method for automatic stacking of warehouse goods includes the following steps:

[0070] S11, the data acquisition module collects task instructions;

[0071] S12, the central control scheduling module dispatches the AGV to transport the goods to the designated location;

[0072] S13, the stacking robot collects cargo status information through a visual recognition device, and uploads the cargo status information to a server carrying an algorithm optimization module;

[0073] S14, the algorithm optimization module calculates the cargo stacking sequence information;

[0074] S15, based on the cargo stacking sequence information and cargo status information, the central control scheduling module controls the stacking robot to adjust the fixture and move the cargo to the conveyor belt;

[0075] S16, the central control scheduling module controls the conveyor belt to transport the goods to another stacking robot;

[0076] S17, the central control scheduling module controls the stacking robot to place the goods from the conveyor belt to the designated location, realizing automatic stacking of warehouse goods.

[0077] like Figure 4 As shown, it is one of the embodiments of the present invention. The goods are relatively simple, and the goods moved by the AGV car are only one or two kinds. The working arm of the stacking robot has a certain circumferential range, and only one stacking robot is needed to complete the sorting.

[0078] like Figure 5 As shown, it is another embodiment of the present invention. The cargo is relatively complex and there are multiple stacking robots. After the first general-purpose stacking robot recognizes that the cargo has been transported to the conveyor belt, the central control module controls the conveyor belt to transport each cargo forward, allowing the specific robot that only stacks a single cargo to pick up and stack the accurate cargo, thereby realizing the rapid sorting of complex cargo. In other embodiments, the variety of cargo may be more complex, or in order to increase the stacking speed, more corresponding specific stacking robots can be deployed. The entire warehouse cargo sorting and stacking system is simple to deploy, highly modular, and has low subsequent expansion costs.

[0079] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, device, article or method including the element.

[0080] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An automatic warehouse cargo stacking system, characterized in that: include: Data acquisition module, algorithm optimization module, central control scheduling module, stacking control module and visualization module; The data collection module is used to collect task instructions and cargo status information; The algorithm optimization module is used to match the task instruction with the cargo status information to obtain cargo stacking sequence information; The central control scheduling module schedules the speed of AGVs transporting goods, stacking robots moving, and conveyor lines transporting goods based on the goods stacking order information; The stacking control module is used to control the movement and replacement of the stacking robot fixture; A visualization module, used to display the completion status of the collection task instructions and the cargo status information in real time; The data collection module includes a visual recognition device, through which the cargo status information at a fixed position is collected in real time. The algorithm optimization module includes a recognition optimization model and a decision optimization model; the recognition optimization module uses a pyramid algorithm to perform image optimization processing on the cargo status information, and the decision optimization model uses a simulated annealing algorithm to achieve an optimal solution for the stacking sequence.

2. The automatic warehouse cargo stacking system according to claim 1, characterized in that: There are at least two visual recognition devices, one of which is aimed at the bottom plate to obtain the status information of the goods on the bottom plate, and the other visual recognition device is aimed at the raw material goods to obtain the status information of the raw material goods.

3. The automatic warehouse cargo stacking system according to claim 1, characterized in that: The method for identifying cargo status information using the visual recognition model comprises the following steps: S1, a visual recognition device photographs a fixed position at a preset time interval to obtain an image photo at the fixed position; S2, uploading each of the image photos to the server in chronological order; S3, performing object recognition on each of the image photos, and matching each recognized object with the cargo information stored in the server; S4, using a pyramid algorithm, superimposing each of the image photos in chronological order to construct three-dimensional cargo status information at the fixed position.

4. The automatic warehouse cargo stacking system according to claim 3, characterized in that: In step S3, an edge detection algorithm is used to identify objects in the image photograph, and the outline size of each discrete individual in the image photograph is measured.

5. The automatic warehouse cargo stacking system according to claim 1, characterized in that: There are at least two stacking robots, including a general stacking robot and a special stacking robot. The general stacking robot can identify and sort all goods, and the special stacking robot can only identify and sort one type of goods.

6. The automatic warehouse cargo stacking system according to claim 1, characterized in that: The data acquisition module also includes collecting site path information, and the site path information is collected by a visual acquisition device or a radar acquisition device located on the AGV vehicle.

7. The automatic warehouse cargo stacking system according to claim 6, characterized in that: It also includes an automatic obstacle avoidance module, which calculates the running path of the AGV vehicle. Based on the site path information, the automatic obstacle avoidance application includes dynamic replanning, ant colony algorithm or genetic algorithm to calculate the running path.

8. The automatic warehouse cargo stacking system according to claim 1, characterized in that: The data acquisition module also includes a height measuring device, which includes at least two positioning devices, and the positioning device includes a visual recognition device or a radar. The cargo height information is measured and collected by identifying the same cargo by at least two positioning devices.

9. The automatic warehouse cargo stacking system according to claim 1 or 3, characterized in that: The formula of the pyramid algorithm includes: Collect cargo status information in chronological order, with the first one being the next sampling information ; The latter is the upsampling information ; <h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> (x,y)=<h2 style=";text-align:left;direction:ltr"> <h2 style=";text-align:left;direction:ltr"> (2x,2y); = −upsample( +1), where k is the cargo status information of layer k.

10. A method for automatically stacking goods in a warehouse, used to implement the steps of constructing an automatic warehouse stacking system as described in claims 1-9, characterized in that: include S11, the data acquisition module acquires task instructions; S12, the central control scheduling module schedules the AGV to transport the goods to the designated location; S13, the stacking robot collects cargo status information through a visual recognition device, and uploads the cargo status information to a server carrying the algorithm optimization module; S14, the algorithm optimization module calculates the cargo stacking sequence information; S15, based on the cargo stacking sequence information and cargo status information, the central control scheduling module controls the stacking robot to adjust the clamp and move the cargo to the conveyor belt; S16, the central control scheduling module controls the conveyor belt to transport the goods to another stacking robot; S17, the central control scheduling module controls the stacking robot to place the goods from the conveyor belt to the designated location, thereby realizing automatic stacking of the goods in the warehouse.

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