Product return system, product return method, and product return program

Abstract

The process of returning products to their designated locations within the store will be automated. [Solution] A product return system comprising a robot that can move within a store and an information processing device, wherein the robot comprises a placement means on which products can be placed and a shooting means for photographing products placed on the placement means, and the information processing device is capable of communicating with the robot and comprises a recognition means for recognizing products from images captured by the shooting means, a identification means for comparing the product information recognized by the recognition means with product shelf arrangement data within the store to identify the location of the product shelf to which the product will be returned, and a return control means for controlling the robot to return the product to the product shelf based on the location of the product shelf identified by the identification means.

Description

Technical Field

[0001] The present disclosure relates to a product return system, a product return method, and a product return program.

Background Art

[0002] Generally, in a store where products are displayed, a user (customer) carries a plurality of products that the user wants to purchase, and settles payment for the plurality of products collectively at a POS register or the like.

[0003] Here, product display in a store is often performed according to the type of product and the like. For example, in a store, a snack area is provided in a predetermined section, and predetermined snack products are displayed on a predetermined display shelf in the snack area.

Prior Art Literature

Patent Literature

[0004]

Patent Literature 1

Summary of the Invention

Problem to be Solved by the Invention

[0005] However, even when a customer picks up a product and carries it around the store, the customer may decide not to purchase the product before payment. In this case, some customers return the product to the position where it was originally displayed, while some customers do not return it to the original display position. Therefore, in a store, a product may be placed at an unintended position.

[0006] If a customer does not return the picked-up product to the original position, a store clerk needs to organize the product manually. This requires time and labor, and is inefficient particularly in a large-scale store.

[0007] Patent Document 1 describes a method in which a mobile terminal recognizes product identification information of a product and transmits it to a higher-level device, and the higher-level device transmits detailed information of the recognized product to the mobile terminal.

[0008] The product return system described in this disclosure aims to automate the process of returning products to designated locations within stores, as specified for each product. [Means for solving the problem]

[0009] The product return system according to this disclosure is a product return system comprising a robot that can move within a store and an information processing device, wherein the robot comprises a placement means on which products can be placed and a shooting means for photographing products placed on the placement means, and the information processing device is capable of communicating with the robot and comprises a recognition means for recognizing products from images taken by the shooting means, a identification means for comparing the product information recognized by the recognition means with product shelf placement data within the store and identifying the location of the product shelf to which the product will be returned, and a return control means for controlling the robot based on the location of the product shelf identified by the identification means and returning the product to the product shelf.

[0010] The product return method described herein involves placing a product on a robot that travels through a store, and when photographic data of the placed product is transmitted to an information processing device, the information processing device then... The system recognizes products from captured images, compares the information of the recognized products with product shelf placement data within the store, identifies the location of the product shelf to which the product should be returned, and controls the robot to return the product to the product shelf based on the location of the product shelf identified by the identification means.

[0011] The product return program relating to this disclosure is a product return program that is executed by an information processing device when a product is placed on a robot traveling in a store and photographic data of the placed product is transmitted to the information processing device, wherein the information processing device recognizes the product from the captured image, compares the information of the recognized product with product shelf placement data in the store, identifies the location of the product shelf to which the product will be returned, and transmits a control signal to the robot to return the product to the product shelf based on the location of the product shelf identified by the identification means. [Effects of the Invention]

[0012] This allows for the automation of the process of returning products to their designated locations within the store. [Brief explanation of the drawing]

[0013] [Figure 1] This block diagram shows an example of the configuration of the product return system related to this disclosure. [Figure 2] This flowchart illustrates an example of how the product return system described in this disclosure works. [Figure 3] This block diagram shows an example of the configuration of the product return system related to this disclosure. [Figure 4] This flowchart illustrates an example of how the product return system described in this disclosure works. [Figure 5] This block diagram shows an example of the configuration of the product return system related to this disclosure. [Figure 6] This flowchart illustrates an example of how the product return system described in this disclosure works. [Figure 7] This block diagram shows an example of the configuration of the product return system related to this disclosure. [Figure 8] This flowchart illustrates an example of how the product return system described in this disclosure works. [Figure 9] This block diagram shows an example of the configuration of the product return system related to this disclosure. [Figure 10]It is a flow diagram showing an example of the operation of the product return system according to the present disclosure. DETAILED DESCRIPTION OF EMBODIMENTS

[0014] Embodiment 1. Hereinafter, a configuration example of the product return system 1 will be described with reference to FIG. 1. The product return system 1 includes a robot 10 and an information processing device 20 capable of communicating with the robot 10.

[0015] The robot 10 includes a placing means 11 and an imaging means 12.

[0016] The placing means 11 is a means capable of placing a product thereon, and is, for example, a placing table. For example, the robot 10 has a gripping means such as a robot hand, and can grip a target product and place the product on the placing means 11.

[0017] The imaging means 12 is a means for capturing an image of the product placed on the placing means 11, and is, for example, a camera. The robot 10 can transmit image data captured by the imaging means 12 to the information processing device 20.

[0018] Here, the robot 10 is an autonomous robot that self-propels within a store. The robot 10 includes a gripping means for gripping a product, a traveling means for self-propulsion, and the like. The operation of the robot 10 is controlled to return the product to a predetermined product shelf in response to an operation control signal from the information processing device 20.

[0019] As an example, the robot 10 includes a control means, which can perform control for causing a driving means to operate to travel, control for gripping a product by the gripping means, control for the operation of the imaging means 12, and control for transmission and reception of information with the information processing device 20. Further, for example, the control means can execute programs corresponding to respective controls to perform these controls.

[0020] The information processing device 20 comprises a recognition means 21, a specification means 22, and a return control means 23. The information processing device 20 can communicate wirelessly with the robot 10.

[0021] The recognition means 21 recognizes the captured product based on the image of the product received from the robot 10.

[0022] The identification means 22 compares the product information recognized by the recognition means 21 with the product shelf placement data within the store to identify the location of the product shelf to which the product will be returned.

[0023] Here, for example, the information processing device 20 has a database that stores product information and product placement data for each product within the store. Here, we assume that the identification means 22 has the database. In the information processing device 20, the identification means 22 identifies the product recognized by the recognition means 21 by comparing it with the database, and by comparing it with the product shelf placement data within the store for that product, the location of the product shelf to which the product should be returned within the store can be determined.

[0024] The return control means 23 controls the robot 10 to return the product to the product shelf based on the location of the product shelf identified by the identification means 22.

[0025] As a specific example, the return control means 23 transmits a control signal to the robot 10 so that the robot 10 operates based on the location of the product shelf identified by the identification means 22. Based on the received control signal, the robot 10 performs operation control, travels to the location of the product shelf identified by the identification means 22, and can then grasp the product with the gripping means and return the product to the identified product shelf.

[0026] This allows the product return system 1 to efficiently return products picked up by customers in the store to their original locations.

[0027] Here, referring to Figure 2, we will explain an example of the operation flow of the product return system 1.

[0028] Robot 10 patrols the store (Step S1).

[0029] The customer places the item they wish to return on the placement means 11 of the robot 10 (step S2).

[0030] The robot 10 photographs the product placed on the placement means 11 using the photography means 12 (step S3).

[0031] The robot 10 transmits the image data acquired by the camera to the information processing device 20 (step S4).

[0032] The information processing device 20 recognizes the product corresponding to the captured image data using the recognition means 21 (step S5).

[0033] The identification means 22 compares the product information of the product recognized by the recognition means 21 with the product shelf placement data to identify the product shelf location to which the product should be returned (step S6).

[0034] The return control means 23 transmits a control signal to the robot 10 to operate based on the identified product shelf location (step S7).

[0035] The robot 10 moves according to the control signal received from the information processing device 20 to the specified return destination on the product shelf (step S8).

[0036] Robot 10 returns the product to the appropriate shelf (step S9).

[0037] Afterward, returning to step S1, robot 10 resumes patrolling the store.

[0038] This automates the product return process, reducing the workload and saving time for store staff. Furthermore, it eliminates the need for customers to return items to their proper locations, which is expected to improve customer satisfaction.

[0039] Furthermore, product organization becomes more efficient, making it easier to maintain the store's aesthetic appeal. In addition, inventory management becomes easier, reducing the risk of lost or misplaced products.

[0040] Embodiment 2. Next, the product return system 2 will be described with reference to Figure 3. Note that components that perform the same function as those in the product return system 1 shown in Embodiment 1 are denoted by the same reference numerals, and their descriptions are omitted.

[0041] Furthermore, the product return system 2 described below operates as a category-based product management system using a robot with multiple placement means.

[0042] In other words, the robot 30 comprises two mounting platforms 31a and 31b, and a shooting means 12.

[0043] The information processing device 40 comprises a recognition means 21, a identification means 42, and a return control means 43. The information processing device 40 can communicate wirelessly with the robot 30.

[0044] The first display stand 31a is for fresh food. The second display stand 31b is for food other than processed food.

[0045] For example, it is preferable for a customer to place items to be returned on the first loading platform 31a if they are perishable food items, and on the second loading platform 31b if they are not perishable food items. However, in this case, the customer will place items on loading platforms 31a and 31b regardless of whether they are perishable food items or not.

[0046] The identification means 42 of the information processing device 40 performs the same function as the identification means 22 shown in Embodiment 1, and can also determine whether or not the product is a fresh food product when identifying the product information recognized by the recognition means 21.

[0047] As a specific example, the information processing device 40 stores information about a product in a database that stores information about that product, and maintains the category information of that product in association with the product.

[0048] Here, the identification means 42 is assumed to have a database in which product information, in-store shelf placement data, and product category information are associated with each other. In other words, the identification means 42 identifies the in-store shelf placement data and product category information for a product recognized by the recognition means 21 by referring to the database.

[0049] Here, we will explain product categories as being either fresh food or non-fresh food, but this is not the only way to define them.

[0050] The return control means 43 has the functions of the return control means 23 shown in Embodiment 1, and controls the robot 30 to sort products onto the loading tables 31a and 31b according to the product category, whether they are fresh food or not, and controls the robot 30 to return products to the shelves in the appropriate order according to the product category.

[0051] Refer to Figure 4 to see an example of the operation flow of the product return system 2.

[0052] Robot 30 patrols the store (step S11).

[0053] The customer places the item they wish to return on either the first loading platform 31a or the second loading platform 31b of the robot 30 (step S12).

[0054] The robot 30 photographs the products placed on the mounting tables 31a and 31b using the photography means 12 (step S13).

[0055] The robot 30 transmits the image data acquired by the camera to the information processing device 40 (step S14).

[0056] The information processing device 40 recognizes the product corresponding to the captured image data using the recognition means 21 (step S15).

[0057] The identification means 42 compares the product information of the product recognized by the recognition means 21 with the product shelf placement data to determine the product category. In other words, the identification means 42 determines whether or not the product to be returned is a fresh food product. The identification means 42 also determines the location of the product shelf to which the product should be returned (step S16).

[0058] The return control means 43 sends a signal to sort the product into the appropriate storage means according to the category of the identified product, and also sends a control signal to the robot 30 to operate based on the identified product shelf location (step S17).

[0059] The robot 30 sorts the products onto the appropriate placement tables according to the identified category (step S18). For example, the robot 30 grasps the products with its gripping means and sorts them.

[0060] The robot 30 efficiently returns the products classified by category (step S19). In other words, the return control means 43 calculates the optimal return route for each product category, thereby achieving efficient return work.

[0061] As described above, the robot 30 can sort fresh food items onto the first loading platform 31a and non-fresh food items onto the second loading platform 31b, and return each product category via the most optimal return route.

[0062] Therefore, when the identification means 42 of the information processing device 40 determines whether or not the goods placed by the customer on the first display stand 31a or the second display stand 31b are fresh food products, the robot 30 can sort them according to the determination result so that fresh food products are placed on the first display stand 31a and non-fresh food products are placed on the second display stand 31b.

[0063] For example, when fresh food is placed on the first display stand 31a, the robot 30 can immediately move to the shelf and return the product to the shelf.

[0064] On the other hand, if products other than fresh food are placed on the second display stand 31b, the robot 30 may not immediately return the products to the shelves, but may temporarily suspend the action of returning them to the shelves. The robot 30 can patrol the store while keeping products other than fresh food placed on the second display stand 31b without returning them to the shelves until it is no longer possible to place other products on the second display stand 31b.

[0065] Alternatively, when fresh food is placed on the first display stand 31a and non-fresh food products are placed on the second display stand 31b, that is, when fresh food and non-fresh food products are placed on the display stands 31a and 31b, the robot 30 may prioritize returning the fresh food to a product shelf equipped with refrigeration equipment or the like.

[0066] In other words, if the identification means 42 determines that the product contains fresh food, the return control means 43 controls the robot 30 to move to the product shelf and return the product to the shelf. On the other hand, if the identification means 42 determines that the product does not contain fresh food, the return control means 43 can further control the robot 30 to accept the return of the product.

[0067] Furthermore, when customers place products on the robot 30, it is desirable that fresh food products be placed on the first placement platform 31a and non-fresh food products be placed on the second placement platform 31b. This reduces the chance of misjudging whether a photographed product is fresh food or not, and also reduces the number of times the robot 30 uses its gripping means to sort products between the first placement platform 31a and the second placement platform 31b.

[0068] Embodiment 3. Next, with reference to Figure 5, the product return system 3 for determining whether the returned products are damaged or soiled will be described. Note that components that perform the same function as those in the product return system 1 shown in Embodiment 1 are denoted by the same reference numerals, and their descriptions are omitted.

[0069] The robot 50 includes a mounting means 11 and a shooting means 52 capable of taking high-resolution images.

[0070] The information processing device 60 comprises a recognition means 61, a specification means 22, and a return control means 63. The information processing device 60 can communicate wirelessly with the robot 50.

[0071] The shooting device 52 can photograph products in high resolution.

[0072] The recognition means 61 has the same function as the recognition means 21 shown in Embodiment 1, and also determines the condition of the product, such as damage or dirt, from the high-resolution image acquired by the imaging means 52.

[0073] Here, by implementing an image recognition algorithm using machine learning in the recognition means 61, damage or stains on the product can be detected with high accuracy.

[0074] The return control means 63 has the same function as the return control means 23 shown in Embodiment 1, and determines whether the item can be returned based on its condition. If the return control means 63 determines that the item cannot be returned, it transmits a control signal to the robot 50 to transport the item to a separately provided dedicated location.

[0075] Refer to Figure 6 to see an example of the operation flow of the product return system 3.

[0076] Robot 50 patrols the store (Step S21).

[0077] The customer places the item they wish to return on the robot 50's placement means 11 (step S22).

[0078] The robot 50 takes high-resolution photographs of the product placed on the placement means 11 using the photography means 52 (step S23).

[0079] The robot 50 transmits the image data acquired by the camera to the information processing device 60 (step S24).

[0080] The information processing device 60 recognizes the product covered by the captured image data using the recognition means 61 (step S25). At this time, the recognition means 61 analyzes the image and determines the condition of the product, such as damage or dirt.

[0081] The return control means 63 determines whether the item can be returned based on its condition, and if it is determined that the item cannot be returned, it transmits a control signal to the robot 50 to transport it to a separate designated location (step S26).

[0082] Furthermore, if the return control means 63 determines that the item can be returned, the identification means 42 can identify the corresponding shelf location for the item, as in Embodiment 1, and the return control means 63 can transmit a control signal to the robot 50 to instruct it to return the item to the shelf.

[0083] This allows robot 50 to transport products appropriately according to their condition. In other words, robot 50 will transport products that are deemed unreturnable due to damage or soiling to another location without returning them to the shelves, while products that are deemed returnable will be returned to the shelves.

[0084] Therefore, the product return system 3 can prevent the return of inappropriate products and maintain product quality by automatically determining the condition of the products.

[0085] Embodiment 4. Next, with reference to Figure 7, the product return system 4, which is equipped with multiple robots, will be described. Note that components that perform the same function as those in the product return system 1 shown in Embodiment 1 are denoted by the same reference numerals, and their descriptions are omitted.

[0086] Robot 70 includes a mounting means 11 and a shooting means 12. Two or more robots are used here, and they will be described as robot (first robot) 70a and robot (second robot) 70b, respectively.

[0087] The information processing device 80 includes a recognition means 21, a identification means 22, and a return control means 83. The information processing device 80 can communicate wirelessly with robots 70a and 70b.

[0088] Robots 70a and 70b will travel within designated areas of the store. Here, robots 70a and 70b will travel within different areas that they are responsible for.

[0089] The return control means 83 has the same functions as the return control means 23 shown in Embodiment 1, targeting multiple robots 70a and 70b, and also controls the transfer of goods between robots 70a and 70b. For example, when a customer places a product on robot 70a, and the area where the product shelf is located is an area handled by robot 70b rather than an area handled by robot 70a, the return control means 83 transmits a control signal to robots 70a and 70b to operate them to transfer the product from robot 70a to robot 70b.

[0090] In other words, the return control means 83 is equipped with an advanced optimization algorithm that can formulate the most efficient return plan based on the location information and product information of each robot 70a, 70b.

[0091] Refer to Figure 8 to see an example of the operation flow of the product return system 4.

[0092] Multiple robots 70a and 70b patrol their respective assigned areas within the store (step S31).

[0093] The customer places the item they wish to return on the placement means 11 of the robot 70a (step S32).

[0094] The robot 70a photographs the product placed on the placement means 11 using the photography means 12 (step S33).

[0095] The robot 70a transmits the image data acquired by the imaging process to the information processing device 80 (step S34).

[0096] The information processing device 80 recognizes the product corresponding to the captured image data using the recognition means 21 (step S35).

[0097] The identification means 22 compares the product information of the product recognized by the recognition means 21 with the product shelf placement data to identify the product shelf location to which the product should be returned (step S36).

[0098] The return control means 83, based on the identified product shelf location, sends a control signal to robot 70a to perform a return operation if the product shelf is within robot 70a's area of ​​responsibility. On the other hand, if the product shelf is within robot 70b's area of ​​responsibility and not robot 70a's area where the product is currently held, the return control means 83 sends control signals to robots 70a and 70b respectively to transfer the product from robot 70a to robot 70b, and also sends a control signal to robot 70b to return the product to the product shelf (step S37).

[0099] Therefore, the return control means 83 can control the robot 70a and robot 70b to cooperate in returning the product.

[0100] As a result, the product return system 4, through its product transfer function between robots, can transfer the return of a product from a customer to another robot responsible for the area where the product's return shelf is located, even if the robot receives a product from a customer outside its assigned area.

[0101] Embodiment 5. Next, with reference to Figure 9, a product return system 5 for preventing customers from mistakenly returning products will be described. Note that components that perform the same function as those in the product return system 1 shown in Embodiment 1 are denoted by the same reference numerals, and their descriptions are omitted.

[0102] The product return system 5 comprises a robot 90, an information processing device 100, and an in-store device 110.

[0103] The in-store device 110 includes an in-store photography means 111 and an in-store notification means 112.

[0104] The in-store photography means 111 is a camera installed inside the store. Typically, the in-store photography means 111 is a camera fixed in a predetermined position inside the store, and there may be multiple such cameras. Images captured by the in-store photography means 111 are transmitted to the information processing device 100 in real time.

[0105] The in-store notification means 112 is a notification means installed within the store. This in-store notification means 112 is a means of giving instructions to customers by means of voice, flashing lights, etc., but is not limited to these methods.

[0106] The robot 90 comprises a mounting means 11, a first imaging means 92a, a second imaging means 92b, and a notification means 93.

[0107] The information processing device 100 includes a first recognition means 101a, a second recognition means 101b, a first identification means 102a, a second identification means 102b, and a return control means 103. The information processing device 100 can communicate wirelessly with the robot 90 and the in-store equipment 110.

[0108] The first imaging means 92a is the same as the imaging means 12 shown in Embodiment 1, and photographs the product placed on the placement means 11. The robot 90 can transmit the image data captured by the first imaging means 92a to the information processing device 100.

[0109] The second imaging means 92b is a camera that captures images of the store interior while the robot 90 is moving around. The images captured by the second imaging means 92b are transmitted to the information processing device 100 in real time.

[0110] Notification means 93 is a notification means provided on the robot 90. Notification means 93 is a means of giving instructions to the customer by voice, flashing lights, etc., but is not limited to these methods.

[0111] The first recognition means 101a has the same function as the recognition means 21 shown in Embodiment 1.

[0112] The second recognition means 101b detects the customer's product return behavior using image recognition technology, based on images received from the second imaging means 92b of the robot 90 and the in-store imaging means 111 of the in-store device 110.

[0113] The first identification means 102a has the same function as the identification means 22 shown in Embodiment 1.

[0114] The second identification means 102b compares the returned product recognized by the second recognition means 101b with the information of the return location to determine if it is a erroneous return. Here, the second identification means 102b is equipped with advanced image recognition AI for product recognition and human behavior analysis, and can immediately detect erroneous returns.

[0115] The return control means 103 performs the same functions as the return control means 23 shown in Embodiment 1, and when it determines that an incorrect return has occurred, it controls at least one of the robot 90 and the in-store device 110 to notify the customer.

[0116] Specifically, if the return control means 103 detects an incorrect return, it can control the lights and sound devices provided as the in-store notification means 112 to issue a warning.

[0117] Furthermore, if the return control means 103 detects an incorrect return, it can send a control signal to the robot 90, causing it to move to the customer who made the incorrect return. For example, if multiple robots 90 are being used in the store, the return control means 103 can move the nearest robot 90 to the customer.

[0118] Furthermore, the return control means 103 can control the robot 90 so that it uses the robot 90's notification means 93 to guide the customer on how to return the item using speech synthesis and speech playback functions, or to provide visual guidance by displaying a predetermined information on an LED display provided on the exterior of the robot 90.

[0119] Refer to Figure 10 to see an example of the operation flow of the product return system 5.

[0120] The store interior is constantly monitored by the store camera 111 of the store device 110 and the second camera 92b of the robot 90 (step S41). Image data acquired through this monitoring is transmitted to the information processing device 100 in real time.

[0121] The second recognition means 101b recognizes the customer's return action (step S42).

[0122] The second identification means 102b compares the returned product with the information of the return location to determine if it was a erroneous return (step S43).

[0123] If the return control means 103 detects an incorrect return, the in-store notification means 112 of the in-store device 110 will alert the customer by illuminating a light or making an audible sound, and the robot 90 will approach the customer who made the incorrect return and guide them on the appropriate return method (step S44). Either or both of these notifications may be made.

[0124] Furthermore, when robot 90 approaches a customer to guide them on how to return the item, robot 90 may prompt the customer to return the item to robot 90.

[0125] As a result, the product return system 5 can prevent misplacement of products, improve the efficiency of product management in stores, and encourage customers to return items appropriately.

[0126] Furthermore, the product return system 5 can analyze the data obtained during this process to identify products and locations that are prone to incorrect returns, and this information can be used to improve store layouts.

[0127] Other embodiments. The product return system 1 shown in Embodiment 1 can be applied to the automation of book returns in libraries. Here, it is assumed that each book has a barcode on which information is recorded. For example, the product return system 1 operates as follows.

[0128] Robot 10 is equipped with a barcode reader to read the barcode attached to the book, instead of the photographing means 12. Robot 10 reads the barcode of the book placed on the placement means 11 and transmits it to the information processing device 100.

[0129] Next, in the information processing device 20, the recognition means 21 recognizes the book based on the barcode reading information received from the robot 10.

[0130] The identification means 22 can refer to a library database that associates detailed information about a book with information about the bookshelf where the book should be stored. Here, the identification means 22 identifies the book information recognized by the recognition means 21 and the location of the bookshelf based on the barcode reading information.

[0131] The return control means 23 calculates an efficient return route using an algorithm optimized for book returns, based on the location of the books on the shelves to be returned and the layout information of the library's bookshelves, and sends a control signal to the robot 10 to operate. The robot 10 then operates according to the received control signal, enabling efficient book returns.

[0132] From the above, in the product return systems 1 to 5 disclosed in embodiments 1 to 5 and other embodiments, a robot having a mounting means, a shooting means, etc., and an information processing device can operate in cooperation with each other.

[0133] Product return systems 1-5 can automate processes through the collaboration of robots and information processing devices. This means that the processes of product recognition, location identification, and return, which were previously performed manually by humans, can be carried out without human intervention, significantly improving efficiency.

[0134] Furthermore, product return systems 1-5 utilize image recognition technology to analyze captured product images in real time and accurately identify products, thereby improving the accuracy and efficiency of the return process.

[0135] Furthermore, product return systems 1-5 maximize the efficiency of the return process by dynamically calculating the optimal return route, taking into account the location information of the product shelves and the current position of the robot.

[0136] Furthermore, as shown in the product return system 4 of Embodiment 4, multiple robots can share information and work together to achieve efficient return operations even in large-scale environments.

[0137] Although the present disclosure has been described above with reference to embodiments, the present disclosure is not limited to the embodiments described above. Various modifications to the structure and details of the present disclosure can be made as can be understood by those skilled in the art within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0138] For example, in the product return system 2 shown in Embodiment 2, it was described that the customer places the product on the first placement platform 31a or the second placement platform 31b, but the system is not limited to this. For example, a separate placement platform can be provided for the customer to place the product on the robot 30, in addition to the first placement platform 31a and the second placement platform 31b.

[0139] Furthermore, for example, the product return system 4 of Embodiment 4 can utilize three or more robots. In this case, when the robots return the products, to ensure that each robot does not stray from its assigned area, the first robot may pass the product to the second robot, the second robot may pass the product to the third robot, and the third robot may return the product to the shelf.

[0140] Each drawing is merely illustrative to illustrate one or more embodiments. Each drawing may be associated with one or more other embodiments rather than with only one specific embodiment. As those skilled in the art will understand, various features or steps described with reference to any one drawing can be combined with features or steps shown in one or more other drawings, for example, to create embodiments not explicitly shown or described. Not all features or steps shown in any one drawing to illustrate an exemplary embodiment are necessarily required, and some features or steps may be omitted. The order of steps shown in any of the drawings may be changed as appropriate.

[0141] Embodiments of the present disclosure may be implemented in hardware or in dedicated circuitry, software, logic, or any combination thereof. Some embodiments may be implemented in hardware, while others may be implemented in firmware or software that can be executed by a controller, microprocessor, or other computing device.

[0142] This disclosure also provides at least one computer program product tangibly stored on a non-temporary computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions contained in a program module, and is executed on a device on a target real or virtual processor to perform the processes or methods of this disclosure. The program module includes routines, programs, libraries, objects, classes, components, data structures, etc., that perform a specific task or implement a specific abstract data type. The functionality of the program module may be combined or divided among the program module as desired in various embodiments. The machine-executable instructions of the program module can be executed on a local or distributed device. On a distributed device, the program module can reside on both local and remote storage media.

[0143] Program code for performing the methods of this disclosure may be written in any combination of one or more programming languages. These program codes are provided to a processor or controller of a general-purpose computer, a dedicated computer, or other programmable data processing device. When the program code is executed by the processor or controller, the functions / operations in the flowchart and / or block diagrams it implements are performed. The program code may run entirely on a machine, partially on a machine, partially as a standalone software package, partially on a machine, partially on a remote machine, or entirely on a remote machine or server.

[0144] Programs can be stored and supplied to a computer using various types of non-temporary computer-readable media. Non-temporary computer-readable media include various types of tangible recording media. Examples of non-temporary computer-readable media include magnetic recording media, magneto-optical recording media, optical disc media, and semiconductor memory. Magnetic recording media include, for example, flexible disks, magnetic tapes, and hard disk drives. Magneto-optical recording media include, for example, magneto-optical disks. Optical disc media include, for example, Blu-ray discs, CD (Compact Disc)-ROM (Read Only Memory), CD-R (Recordable), and CD-RW (ReWritable). Semiconductor memory includes, for example, solid-state drives, mask ROMs, PROMs (Programmable ROMs), EPROMs (Erasable PROMs), flash ROMs, and RAMs (random access memory). Programs may also be supplied to a computer using various types of temporary computer-readable media. Examples of temporary computer-readable media include electrical signals, optical signals, and electromagnetic waves. Temporary computer-readable media can supply programs to a computer via wired communication channels such as electric wires and optical fibers, or via wireless communication channels.

[0145] Some or all of the above embodiments may also be described as follows, but are not limited to the following: (Note 1) A product return system comprising a robot that can move around inside the store and an information processing device, The aforementioned robot, A mounting means on which products can be placed, A photographing means for photographing the product placed on the aforementioned placement means, Equipped with, The information processing device is capable of communicating with the robot, A recognition means for recognizing a product from an image captured by the aforementioned photographic means, A recognition means compares the product information recognized by the recognition means with product shelf placement data within the store to identify the location of the product shelf to which the product should be returned, A return control means controls the robot based on the location of the product shelf identified by the specified means and returns the product to the product shelf, Equipped with, Product return system. (Note 2) The mounting means has a plurality of mounting platforms, The aforementioned identification means classifies the products by category, Products categorized according to their classification are placed on each of the aforementioned multiple display stands. Product return system as described in Appendix 1. (Note 3) The aforementioned identification means has the function of determining whether or not the category of the product is fresh food. The return control means, if it determines that the identification means includes fresh food, controls the robot to move to the position of the product shelf, and if it determines that the identification means does not include fresh food, it further controls the robot to accept the return of the product. Product return system as described in Appendix 2. (Note 4) The aforementioned specifying means is, The system includes a database that records information about the aforementioned product, data on the placement of products on store shelves, and information about the category of the aforementioned product, in association with each other. For the product recognized by the recognition means, the store's shelf placement data and the product's category are identified by referring to the database. Product return system as described in Appendix 3. (Note 5) The recognition means determines the condition of the product from the image captured by the imaging means, The return control means determines whether the product can be returned based on the condition of the product determined by the recognition means. Product return system as described in Appendix 4. (Note 6) The robots mentioned above are a first robot and a second robot. The conversion control means is, The first robot and the second robot cooperate to control the return of the product. Product return system as described in Appendix 5. (Note 7) The return control means is The system controls the transfer of the product from the first robot to the second robot, and also controls the second robot to return the product to the product shelf. Product return system as described in Appendix 6. (Note 8) The return control means is When a product is placed in front of the first robot, and the product shelf for the product is outside the area of ​​responsibility of the first robot, the first robot and the second robot are instructed to transfer the product to the second robot, whose area of ​​responsibility includes the product shelf for the product. The product return system described in Appendix 6 or Appendix 7. (Note 9) When a product is placed on a robot that travels through a store, and the image data of the placed product is transmitted to an information processing device, The aforementioned information processing device The product is recognized from the captured image. The information of the recognized product is compared with the product shelf placement data within the store to identify the location of the product shelf to which the product should be returned. Based on the location of the identified product shelf, the robot is controlled to return the product to the product shelf. How to return a product. (Note 10) A product return program is executed by an information processing device when a product is placed on a robot that travels through a store, and photographic data of the placed product is transmitted to the information processing device, The aforementioned information processing device The product is recognized from the captured image. The information of the recognized product is compared with the product shelf placement data within the store to identify the location of the product shelf to which the product should be returned. Based on the location of the identified product shelf, a control signal is transmitted to the robot to cause it to return the product to the product shelf. Product return program.

[0146] Some or all of the elements described in Appendices 2 to 8, which are dependent on the product return system described in Appendice 1, may also be dependent on the product return method shown in Appendice 9 and the product return program shown in Appendice 10, in the same manner as those described in Appendices 2 to 8. Some or all of the elements described in any appendice may be applied to various hardware, software, recording means, systems, and methods for recording software. [Explanation of Symbols]

[0147] 1-5 Product Return System 10 Robots 11 Mounting means 12. Method of filming 20 Information Processing Devices 21 Recognition means 22 Specific means 23. Return control means 30 robots 31a First mounting platform 31b Second mounting platform 40 Information Processing Devices 42 Specific means 43 Return control means 50 robots 52. Methods of Photography 60 Information Processing Devices 61 Recognition means 63 Return control means 70 Robots 70a First robot 70b The second robot 80 Information Processing Device 83 Return control means 90 robots 92a First photographic means 92b Second photographic method 93. Notification methods 100 Information Processing Devices 101a First recognition means 101b Second recognition means 102a First identifying means 102b Second specific means 103 Return control means 110 In-store equipment 111 In-store photography methods 112 In-store notification methods

Claims

1. A product return system comprising a robot that can move around inside the store and an information processing device, The aforementioned robot, A mounting means on which products can be placed, A photographing means for photographing the product placed on the aforementioned placement means, Equipped with, The information processing device is capable of communicating with the robot, A recognition means for recognizing a product from an image captured by the aforementioned photographic means, A recognition means compares the product information recognized by the recognition means with product shelf placement data within the store to identify the location of the product shelf to which the product should be returned, A return control means controls the robot based on the location of the product shelf identified by the specified means and returns the product to the product shelf, Equipped with, Product return system.

2. The mounting means has a plurality of mounting platforms, The aforementioned identification means classifies the products by category, Products categorized according to their classification are placed on each of the aforementioned multiple display stands. The product return system according to claim 1.

3. The aforementioned identification means has the function of determining whether or not the category of the product is fresh food. The return control means, if it determines that the identification means includes fresh food, controls the robot to move to the position of the product shelf, and if it determines that the identification means does not include fresh food, it further controls the robot to accept the return of the product. The product return system according to claim 2.

4. The aforementioned specifying means is, The system includes a database that records information about the aforementioned product, data on the placement of products on store shelves, and information about the category of the aforementioned product, in association with each other. For the product recognized by the recognition means, the store's shelf placement data and the product's category are identified by referring to the database. The product return system according to claim 3.

5. The recognition means determines the condition of the product from the image captured by the imaging means, The return control means determines whether the product can be returned based on the condition of the product determined by the recognition means. The product return system according to claim 4.

6. The robots are a first robot and a second robot. The conversion control means is, The first robot and the second robot cooperate to control the return of the product. The product return system according to claim 5.

7. The return control means is The system controls the transfer of the product from the first robot to the second robot, and also controls the second robot to return the product to the product shelf. The product return system according to claim 6.

8. The return control means is When a product is placed in front of the first robot, and the product shelf for the product is outside the area of ​​responsibility of the first robot, the first robot and the second robot are instructed to transfer the product to a second robot whose area of ​​responsibility includes the product shelf for the product. The product return system according to claim 6 or claim 7.

9. When a product is placed on a robot that travels through a store, and the image data of the placed product is transmitted to an information processing device, The aforementioned information processing device The product is recognized from the captured image. The information of the recognized product is compared with the product shelf placement data within the store to identify the location of the product shelf to which the product should be returned. Based on the location of the identified product shelf, the robot is controlled to return the product to the product shelf. How to return a product.

10. A product return program is executed by an information processing device when a product is placed on a robot that travels through a store, and photographic data of the placed product is transmitted to the information processing device, The aforementioned information processing device The product is recognized from the captured image. The information of the recognized product is compared with the product shelf placement data within the store to identify the location of the product shelf to which the product should be returned. Based on the location of the identified product shelf, a control signal is transmitted to the robot to cause it to return the product to the product shelf. Product return program.

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