Product calculation device using automatic barcode scanning

Abstract

To provide an item calculator with automatic barcode scanning that quickly and accurately scans barcodes to calculate items that customers intend to purchase unattended.SOLUTION: An item calculator using automatic bar code scanning according to the present invention includes: a photographing unit that takes a picture of an item to generate an item image; a processor that recognizes, based on the item image, a barcode position of a barcode provided on one side of the item and contains price information of the item; and a robot arm unit that grasps the item so that the barcode is scanned and moves the item to a barcode scanning device.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a product calculation device using automatic barcode scanning, and more particularly to a product calculation device using automatic barcode scanning that senses the barcode position of a product, grasps the product using a robot arm unit, and moves the product to a barcode scanning device, thereby enabling product calculation through automatic barcode scanning. [Background technology]

[0002] Generally, a robot is a machine that automatically performs or operates a given task using its own capabilities, and the application fields of robots are generally classified into various fields such as industrial, medical, space, undersea, etc. In recent years, there has been an increase in communication robots that can communicate and interact with humans through voice, gestures, etc.

[0003] In addition, attempts are being made to reduce manpower and increase accuracy by automating the entire logistics process, including product production, shipping, transportation, loading and unloading, packaging, storage, and calculation. Automating logistics has the effect of reducing costs due to the reduction in manpower and preventing safety accidents, shortening the time required for logistics, and enabling systematic management.

[0004] In particular, when calculating the cost of merchandise at a sales floor, a sales clerk must scan the barcode of each item using a barcode scanning device to calculate the cost of the merchandise. This increases the time required to calculate the merchandise, which increases unnecessary waiting time for malicious customers, thereby increasing congestion at the sales floor. In addition, hiring staff to calculate the merchandise also increases the operational and management costs of the sales floor.

[0005] For this reason, there is currently a demand for technology that allows unattended calculations to be performed quickly and accurately for products that customers wish to calculate. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Korean Patent Publication No. 10-2018-0109107 Summary of the Invention [Problem to be solved by the invention]

[0007] An object of the present invention is to provide a product calculation device using automatic barcode scanning, which performs unmanned, rapid and accurate barcode scanning of products that customers are about to purchase and calculates the product.

[0008] The objects of the present invention are not limited to the objects mentioned above, and other objects and advantages of the present invention not mentioned above can be understood from the following description and can be more clearly understood from the embodiments of the present invention. In addition, it can be easily understood that the objects and advantages of the present invention can be realized by the means and combinations thereof set forth in the claims. [Means for solving the problem]

[0009] The product calculation device using automatic barcode scanning according to the present invention may include a photographing unit that photographs a product to generate a product image, a processor that is provided on one side of the product based on the product image and recognizes the position of a barcode that includes price information of the product, and a robot arm that grasps the product so that the barcode can be scanned and moves the product to a barcode scanning device.

[0010] Preferably, the processor can set the sensed barcode position based on the product image as a barcode area, and set a first gripping area based on the product image in which the product can be gripped by the robot arm unit so that the product can be moved to the barcode scanning device.

[0011] Preferably, the processor can set the barcode area and the first holding area so that the barcode area and the first holding area do not overlap.

[0012] Preferably, the robot arm unit can grasp a portion of the product corresponding to the first grasping area and move the product to the barcode scanning device.

[0013] Preferably, when the barcode position is not sensed, the processor can set a second gripping area that can be gripped by the robot arm unit based on the product image to change the product's position so that the barcode is exposed to the outside.

[0014] Preferably, the robot arm unit can grip a portion of the product corresponding to the second gripping area to change the arrangement of the product.

[0015] Preferably, the robot arm unit can move the product so that a portion of the product corresponding to a barcode region of the barcode position faces the barcode scanning device.

[0016] Preferably, the processor can calculate a fee for scanning the barcode of the product and performing calculation on the product based on one or more pieces of product calculation difficulty information corresponding to the product. [Effects of the Invention]

[0017] The product calculation device using automatic barcode scanning according to the present invention can reduce the labor and labor costs required by performing the product calculation process, which requires a lot of labor and labor costs, through a robot utilizing artificial intelligence. [Brief explanation of the drawings]

[0018] [Figure 1]1 is a diagram illustrating a product calculation device using automatic barcode scanning according to one embodiment of the present invention, a barcode scanning device, products, and a calculation table C. FIG. [Figure 2] 1 is a block diagram illustrating the configuration of a commodity calculation device using automatic barcode scanning according to an embodiment of the present invention. [Figure 3] 10A and 10B are diagrams illustrating a process in which a commodity counting device using automatic barcode scanning according to an embodiment of the present invention sets a barcode area and a first gripping area. [Figure 4] 10A and 10B are diagrams illustrating a process in which a commodity counting device using automatic barcode scanning according to an embodiment of the present invention grasps a commodity for barcode scanning. [Figure 5] 10A and 10B are diagrams illustrating a process in which a commodity counting device using automatic barcode scanning according to an embodiment of the present invention moves a grasped commodity to a barcode scanning device for barcode scanning. [Figure 6] 10A and 10B are diagrams illustrating a process in which a commodity counting device using automatic barcode scanning according to another embodiment of the present invention sets a second gripping area. [Figure 7] 10A and 10B are diagrams illustrating a process in which a commodity calculation device using automatic barcode scanning according to another embodiment of the present invention moves and rotates a commodity so that the barcode is exposed to the outside. DETAILED DESCRIPTION OF THE INVENTION

[0019] Various embodiments of the present invention will be described below with reference to the accompanying drawings. However, it should be understood that this is not intended to limit the present invention to the specific embodiments, but rather includes various modifications, equivalents, and / or alternatives of the embodiments of the present invention. In connection with the description of the drawings, similar reference numerals may be used to refer to similar components.

[0020] In this document, the terms "have," "can have," "include," or "can include" refer to the presence of a given feature (e.g., a value, function, operation, or component such as a part) and do not exclude the presence of additional features.

[0021] In this document, phrases such as "A or B," "at least one of A and / or B," or "one or more of A and / or B" may include all possible combinations of the items listed together. For example, "A or B," "at least one of A and B," or "at least one of A or B" may refer to any of the following: (1) including at least one A, (2) including at least one B, or (3) including at least one A and at least one B.

[0022] Terms such as "first," "second," "first," or "second" used herein may modify various components without regard to order and / or importance, and are used merely to distinguish one component from another, not to limit the components. For example, a first user device and a second user device may refer to different user devices without regard to order or importance. For example, a first component may be referred to as a second component, and similarly, a second component may be referred to as a first component, without departing from the scope of the rights described herein.

[0023] When a component (e.g., a first component) is referred to as being "operatively or communicatively coupled with" or "connected to" another component (e.g., a second component), it should be understood that the component may be directly coupled to the other component or may be coupled through another component (e.g., a third component). In contrast, when a component (e.g., a first component) is referred to as being "directly coupled" or "directly connected to" another component (e.g., a second component), it should be understood that there is no other component (e.g., a third component) between the component and the other component.

[0024] As used herein, the phrase "configured to" may be modified, depending on the context, to refer to, for example, "suitable for," "having the capacity to," "designed to," "adapted to," "made to," or "capable of." The term "configured to" does not necessarily refer only to hardware that is "specifically designed to." Instead, in some contexts, the phrase "device configured to" may mean that the device, together with other devices or components, is "capable of." For example, the phrase "a controller configured to perform A, B, and C" may refer to a dedicated processor for performing those operations (e.g., an embedded processor) or a general-purpose processor (e.g., a CPU or application processor) that can perform those operations by executing one or more software programs stored in memory.

[0025] In particular, in this specification, a "device" may include one or more of a Central Processing Unit (CPU), an Application Processor (AP), and a Communication Processor (CP).

[0026] In this specification, the term "device" refers to any type of hardware device that includes at least one processor, and may also encompass software components that operate on the hardware device, depending on the embodiment. For example, the term "device" may be understood to include, but is not limited to, mechanically driven devices, smartphones, tablet PCs, desktop computers, notebook computers, and user clients and applications that run on each device.

[0027] The terms used in this document are merely used to describe particular embodiments and are not intended to limit the scope of other embodiments. A singular term may include a plural term unless the context clearly dictates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person of ordinary skill in the art described in this document. Terms used in this document that are defined in a general dictionary may be interpreted as meanings that are identical to or similar to the meanings in the context of the relevant art, and should not be interpreted in an idealized or overly formal sense unless explicitly defined in this document. In some cases, even terms defined in this document should not be interpreted to exclude embodiments of this document.

[0028] FIG. 1 is a diagram showing a product calculation device using automatic barcode scanning according to one embodiment of the present invention, a barcode scanning device, products, and a calculation table C, and FIG. 2 is a block diagram showing the configuration of a product calculation device using automatic barcode scanning according to one embodiment of the present invention.

[0029] Referring to FIGS. 1 and 2, a product calculation device 100 using automatic barcode scanning according to an embodiment of the present invention is located on one side of a counter C in a sales area. When a customer places a product to be calculated on the counter C, the customer can move and rotate the product so that the barcode on one side of the product can be scanned by the barcode scanning device 200.

[0030] Here, the barcode scanning device 200 is located above or on the other side of the counter C and can scan the barcode of the product to obtain the price information of the product.

[0031] For this purpose, the barcode scanning device 200 may use one or more of a visible light barcode scanning method that receives input of visible light reflected from the barcode to scan the barcode, and a red light barcode scanning method that receives input of red light reflected from the barcode to scan the barcode, but it should be noted that the scanning method is not limited as long as it obtains product price information from the barcode.

[0032] Meanwhile, the barcode may be printed on one side of the product or printed on a plastic tag attached to one side of the product, and the price information of the product may be encoded and displayed. In this case, the barcode may be formed in any one of the following formats: Code 11, Code 39, Code 93, Code 128, UPC, EAN8, EAN13, PDF417, and Data Matrix, but it should be noted that the format is not limited as long as it contains the price information of the product.

[0033] A commodity calculation device 100 using automatic barcode scanning according to an embodiment of the present invention can grasp the other side of the commodity so that the barcode on one side of the commodity is exposed to the outside as much as possible while moving and rotating the commodity so that the barcode on one side of the commodity can be scanned by the barcode scanning device 200.

[0034] To this end, the commodity counting device 100 using automatic barcode scanning according to an embodiment of the present invention may include a photographing unit 110, a processor 120, and a robot arm unit .

[0035] The photographing unit 110 can take a photograph of a product placed on the counter C by a customer for calculation and generate a product image. To this end, the photographing unit 110 can include a camera module that generates an image. The photographing unit 110 can also include a vision sensing camera module that performs vision sensing on the product.

[0036] FIG. 3 is a diagram illustrating a process in which a commodity counting device using automatic barcode scanning according to an embodiment of the present invention sets a barcode area and a first gripping area.

[0037] Referring further to FIG. 3, the processor 120 can recognize the barcode position of barcode B, which is provided on one side of the product and contains price information of the product, based on the product image.

[0038] In this case, the processor 120 can recognize the barcode position using an artificial intelligence model. Specifically, the processor 120 trains the artificial intelligence model using various product images captured in the past and barcode positions recognized from the product images as learning data, inputs the product images of the products currently placed on the calculation table C as input data to the artificial intelligence model, and outputs the barcode position as output data.

[0039] Here, the trained artificial neural network can be referred to as an artificial intelligence model, which is used to infer a result value for new input data rather than the training data, and the inferred value can be used as a basis for making a decision to take some action.

[0040] Here, artificial intelligence refers to the field that studies artificial intelligence or the methodology to create it, while machine learning refers to the field that defines the various problems that are dealt with in the field of artificial intelligence and studies the methodology to solve them. Machine learning can also be defined as an algorithm that improves its performance for a certain task through continuous experience with that task.

[0041] An artificial neural network (ANN) is a model used in machine learning, and can refer to any model with problem-solving capabilities that is composed of artificial neurons (nodes) that form a network through synaptic connections. An artificial neural network can be defined by the connection patterns between neurons in different layers, a learning process that updates model parameters, and an activation function that generates output values.

[0042] An artificial neural network can include an input layer, an output layer, and optionally one or more hidden layers. Each layer includes one or more neurons, and an artificial neural network can include synapses connecting the neurons. In an artificial neural network, each neuron can output a function value of an activation function in response to input signals, weights, and biases received via synapses.

[0043] Model parameters are parameters that are determined through learning, such as synaptic weights and neuron biases, while hyperparameters are parameters that must be set before learning in a machine learning algorithm, such as the learning rate, number of iterations, mini-batch size, and initialization function.

[0044] The goal of training an artificial neural network can be seen as determining model parameters that minimize a loss function, which can be used as an index for determining optimal model parameters during the training process of an artificial neural network.

[0045] Depending on the learning method, machine learning can be classified into supervised learning, unsupervised learning, and reinforcement learning.

[0046] Supervised learning refers to a method of training an artificial neural network when labels for training data are given, where a label can refer to the correct answer (or result value) that the artificial neural network must infer when training data is input to the artificial neural network. Unsupervised learning can refer to a method of training an artificial neural network when labels for training data are not given. Reinforcement learning can refer to a learning method in which an agent defined in an environment is trained to select an action or sequence of actions that maximizes cumulative compensation in each state.

[0047] Machine learning realized by a deep neural network (DNN), which is an artificial neural network that includes multiple hidden layers, is also called deep learning, and deep learning is a part of machine learning. In this specification, machine learning is used to mean deep learning.

[0048] On the other hand, the barcode position may be a three-dimensional area in a three-dimensional coordinate space in which the calculation table C is defined as the XY plane and the height from the calculation table C is defined as the Z axis.

[0049] Thereafter, the processor 120 can set the barcode position sensed based on the product image as the barcode area BA. That is, the processor 120 can set the three-dimensional area recognized as the barcode position as the barcode area BA. The processor 120 can set the barcode area BA as the area that is closest to the barcode recognition device 200 compared to other areas of the product and that is covered by the robot arm unit 130 and is not blocked from the outside.

[0050] That is, the barcode area BA may be the area where the barcode B of the product is located, the area that will be closest to the barcode recognition device 200 later, and the area that will not be grasped by the robot arm unit 130.

[0051] Meanwhile, the processor 120 may set a first gripping area GA1 in which the product can be gripped by the robot arm unit 130 so that the product can be moved to the barcode scanning device 200 based on the product image.

[0052] For this purpose, the processor 120 can recognize the shape of the product based on the product image, and set the area of ​​the product that can be structurally grasped by the robot arm unit 130 as the graspable area.

[0053] Thereafter, the processor 120 can remove the above-mentioned barcode area BA from the graspable area and set it as the first graspable area GA1.

[0054] That is, the processor 120 can set the area of ​​the product that can be grasped by the robot arm unit 130 as the graspable area, taking into account the structure of the robot arm unit 130 and the shape of the product, and then set the first graspable area GA1 by removing the barcode area BA from the graspable area for barcode scanning.

[0055] In other words, the processor 120 sets the barcode area BA and the first holding area GA1 so that the barcode area BA and the first holding area GA1 do not overlap with each other, As a result, when the robot arm unit 130 grasps a portion of a product corresponding to the first grasping area GA1, it can move and rotate the product by grasping it without obstructing the barcode B, and have the barcode B scanned by the barcode scanning device 200.

[0056] FIG. 4 is a diagram illustrating a process in which a commodity calculation device using automatic barcode scanning according to one embodiment of the present invention grasps a commodity for barcode scanning, and FIG. 5 is a diagram illustrating a process in which a commodity calculation device using automatic barcode scanning according to one embodiment of the present invention moves a grasped commodity for barcode scanning to a barcode scanning device.

[0057] 4 and 5, the robot arm unit 130 can grasp the product so that the barcode B of the product can be scanned, and move the product to the barcode scanning device 200.

[0058] Specifically, the robot arm unit 130 may include a robot arm 131 whose operation is controlled based on a control signal received from the processor 120, one end of which is fixed to the support unit 140, and a gripper unit 132 connected to the other end of the robot arm 131.

[0059] In this case, the support unit 140 has a lower end fixed to the ground adjacent to the calculation platform C and an upper end connected to one end of the robot arm 131, thereby supporting the moving robot arm 131.

[0060] The gripping portion 132 may also be formed in a clamp shape and configured to apply pressure to both sides of the product to grip the product.

[0061] Such a robot arm unit 130 can control the operation of the robot arm 131 and the gripper unit 132 in response to control signals from the processor 120 .

[0062] Specifically, the robot arm unit 130 can grasp a portion of the product corresponding to the first grasping area GA1 via the robot arm 131 and the grasping unit 132, and move the product to the barcode scanning device 200.

[0063] The robot arm unit 130 can then move and rotate the item so that the barcode in the barcode area BA faces the barcode scanning device 200 .

[0064] As a result, the robot arm unit 130 can grasp the product without blocking the barcode and scan the barcode, without the need for a staff member to directly move the product's barcode to the barcode scanning device 200 and scan the barcode, as long as the customer places the product on the counter C, thereby completing the product calculation quickly and without labor.

[0065] To this end, the robot arm unit 130 may be configured to realize mechanical movement. Specifically, the robot arm unit 130 may include one or more joints, links, gears, etc. that can perform various tasks. The robot arm unit 130 may include a plurality of joints, a plurality of links connected to each other by the plurality of joints, and a drive motor that rotates the plurality of joints. In this case, the processor 120 controls the operation of the drive motor to control the robot arm unit 130, and thus the robot arm unit 130 can control the robot arm 131 and the gripper 132.

[0066] Meanwhile, the commodity calculation device 100 using automatic barcode scanning according to an embodiment of the present invention may further include a communication unit 150 for transmitting and receiving data, information, and signals, and a storage unit 160 for storing data, information, and signals, in order to perform the above-mentioned functions.

[0067] Meanwhile, the processor 120 may perform the operations of each of the above-mentioned components and may include one or more cores (not shown) and a graphics processing unit (not shown) and / or connecting paths (e.g., buses) for transmitting and receiving signals to and from other components.

[0068] The processor 120 may be configured to perform the operations of each of the components described above by executing one or more instructions stored in the storage unit 160 .

[0069] The storage unit 160 may store a program (one or more instructions) for processing and controlling the processor 120. The program stored in the storage unit 160 may be divided into a plurality of modules according to their functions.

[0070] FIG. 6 is a diagram illustrating a process in which a commodity counting device using automatic barcode scanning according to another embodiment of the present invention sets a second gripping area, and FIG. 7 is a diagram illustrating a process in which a commodity counting device using automatic barcode scanning according to another embodiment of the present invention moves and rotates a commodity so that the barcode is exposed to the outside.

[0071] Referring to Figures 6 and 7, if the barcode position is not sensed from the product placed on the counter C, the processor 120 can set a second gripping area GA2 that can be gripped by the robot arm unit 130 based on the product image to change the product placement state so that the barcode is exposed to the outside.

[0072] When a customer places a product on counter C, if barcode B is in contact with the top surface of counter C and is not exposed to the outside, as shown in Figure 6, the position of the product's barcode will not be sensed.

[0073] At this time, the processor 120 can recognize the shape of the product based on the product image of the product that is positioned so that the barcode position cannot be sensed, and set the area of ​​the product that can be structurally grasped by the robot arm unit 130 as the second grasping area GA2.

[0074] Thereafter, the robot arm unit 130 can grasp a portion of the product corresponding to the second grasping area GA2 and change the position of the product so that the barcode is exposed to the outside.

[0075] Once the barcode position of the product is positioned so as to be sensed through the above-mentioned process, the processor 120 can again set the above-mentioned first gripping area GA1, and control the robot arm unit 130 so that the part of the product corresponding to the first gripping area GA1 is gripped by the robot arm unit 130 and the product moves to the barcode scanning device 200.

[0076] Meanwhile, the processor 120 of the product calculation device 100 using automatic barcode scanning according to another embodiment of the present invention may calculate a fee for calculating the product by scanning the barcode of the product based on product calculation difficulty information corresponding to the product.

[0077] First, the processor 120 can calculate the product calculation difficulty level information based on the calculation time required to set the first gripping area GA1 for the product image of the product placed on the calculation table C.

[0078] Specifically, when processor 120 sets the first grasping area GA1 for a product that is difficult to grasp, such as when the product has a shape that makes it difficult to grasp or the size of the barcode is large compared to the size of the product, the calculation time required to set the first grasping area GA1 may increase.

[0079] As a result, the processor 120 can calculate the product calculation difficulty level information by increasing the product calculation difficulty level indicated by the product calculation difficulty level information as the calculation time required to set the first gripping area GA1 increases.

[0080] Finally, the processor 120 can calculate a commission for the product by increasing the higher the product calculation difficulty indicated by the product calculation difficulty information.

[0081] Here, the fee may refer to the cost of the product calculation device 100 using automatic barcode scanning according to the present invention scanning the barcode of the product on behalf of the staff and calculating the product price.

[0082] On the other hand, the above-mentioned fee can be charged to the store manager who operates the store, rather than to the customers of the store.

[0083] Meanwhile, the commodity counting device 100 using automatic barcode scanning according to another embodiment of the present invention may further include a scanning unit for the robot arm unit 130 to scan the barcode B of the commodity.

[0084] Specifically, a scanning unit for scanning a barcode B provided on one side of a product, similar to the barcode scanning device 200, may be disposed on one side of the gripping unit 132 included in the robot arm unit 130.

[0085] The processor 120 can grasp and move the product using the gripping unit 132 of the robot arm unit 130, without scanning the barcode B, but can control the operation of the robot arm unit 130 to bring the scanning unit close to the part of the product that corresponds to the barcode area BA and scan the product's barcode B.

[0086] As a result, the product calculation device 100 using automatic barcode scanning according to another embodiment of the present invention can reduce the time required to grasp the product and move it to the barcode scanning device 200, and can quickly calculate the product by directly scanning the barcode B from the product placed on the counter C.

[0087] The present invention has been described above with a focus on preferred embodiments. Those skilled in the art will understand that the present invention can be realized in modified forms without departing from the essential characteristics of the present invention. Therefore, the disclosed embodiments should be considered from an illustrative rather than a restrictive perspective. The scope of the present invention is defined by the claims, not the foregoing description, and all variations within the scope of the claims should be construed as being within the scope of the present invention.

[0088] Although the present invention has been described above using limited embodiments and drawings, it goes without saying that the present invention is not limited thereto, and that various modifications and variations can be made by a person having ordinary knowledge in the technical field to which the present invention pertains within the technical spirit of the present invention and the equivalent scope of the claims described below. [Explanation of symbols]

[0089] 100 Product calculation device using automatic barcode scanning 110 Filming Department 120 processors 130 Robot arm 200 Barcode Scanner

Claims

1. a photography unit that photographs the product and generates a product image; a processor for recognizing a barcode position of a barcode including price information of the product, the barcode being provided on one side of the product based on the product image; a robotic arm unit that grasps the product so that the barcode can be scanned and moves the product to a barcode scanning device; Including, The processor: A product calculation device using automatic barcode scanning, characterized in that it calculates a fee for calculating the product by scanning the barcode of the product based on one or more pieces of product calculation difficulty information corresponding to the product.

2. The processor:

2. The commodity calculation device using automatic barcode scanning according to claim 1, wherein the barcode position sensed based on the commodity image is set as a barcode area, and a first gripping area that can be gripped by the robot arm unit so that the commodity can be moved to the barcode scanning device is set based on the commodity image.

3. The processor: setting the barcode area and the first gripping area so that the barcode area and the first gripping area do not overlap; The robot arm unit 3. The product calculation device using automatic barcode scanning according to claim 2, wherein the product is moved to the barcode scanning device by gripping a portion of the product corresponding to the first gripping area.

4. The robot arm unit 4. The product calculation device using automatic barcode scanning according to claim 3, wherein the product is moved so that a portion of the product corresponding to the barcode area of ​​the barcode position faces the barcode scanning device.

Images