Method for picking goods by using intelligent wearable device and intelligent wearable device

Abstract

The invention relates to a method for picking goods by using intelligent wearable equipment and the intelligent wearable equipment, and relates to the technical field of warehouse picking management, and the method comprises the following steps: generating an order query request according to a picking instruction of picking goods from a target warehouse initiated by a target deliveryman, and sending the order query request to a server according to the order query request; obtaining order picking order information associated with a currently logged-in delivery end account, determining order picking prompt information of to-be-sorted goods according to an order picking order and a goods storage record of a target warehouse, obtaining an image of a target order picking stage collected by an intelligent wearable device when a target deliveryman arrives at a goods location where the target to-be-sorted goods are located, and sending the image to the target deliveryman; and on the basis of comparison between an identification result obtained by identifying the image in the target goods picking stage and target goods to be sorted in the goods picking order information, a goods picking result of the target deliveryman for the target goods to be sorted is determined, and an order corresponding to the target goods to be sorted is updated according to the goods picking result. By adopting the method, the order picking efficiency of the deliveryman can be improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of warehouse picking management, and in particular to a picking method using a smart wearable device and the smart wearable device. Background Art

[0002] Warehouse picking management, due to the large number of goods in the warehouse and their scattered distribution, still cannot meet the needs of efficient and fast picking if relying on the memory of warehouse workers or simple marking guidance. In addition, in some scenarios, unmanned warehouse business with unmanned retail model is rapidly emerging, and by having delivery personnel pick the goods themselves, it can help merchants effectively save labor costs. However, due to the large number of goods in the warehouse and the lack of professional sorting experience of the personnel, the proficiency of self-service picking is insufficient, the efficiency of manual picking is limited, and there are also risks such as wrong picking and missing picking. Therefore, improving the efficiency and accuracy of goods picking by target delivery personnel or target users in the warehouse is a key challenge in warehouse picking operations. Summary of the Invention

[0003] The purpose of the present disclosure is to provide a method for picking goods using a smart wearable device and a smart wearable device.

[0004] According to a first aspect of an embodiment of the present disclosure, a method for picking goods using a smart wearable device is provided, comprising: When it is determined that the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse, an order query request is generated, where the order query request indicates the delivery end account currently logged in corresponding to the smart wearable device; According to the order query request, the picking order information associated with the currently logged-in delivery-end account is obtained, and according to the picking order and the goods storage record of the target warehouse, the picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery-end account of the smart wearable device output by the smart wearable device is determined; When it is determined that the target picking stage has been entered, an image of the target picking stage captured by the smart wearable device is obtained, wherein when the target delivery person arrives at the storage location where the target goods to be sorted are located, it is determined that the target picking stage corresponding to the target goods to be sorted has been entered, the target goods to be sorted are goods in the picking order associated with the delivery end account currently logged in by the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The image of the target picking stage is recognized, and the recognition result of the image of the target picking stage is compared with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted, and the order corresponding to the target goods to be sorted is updated according to the picking result.

[0005] Optionally, the identifying the image of the target picking stage and comparing the identification result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted include: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined based on the cargo status feature identification result that the target delivery person has taken the cargo from the cargo location where the target cargo to be sorted is located, and the taken cargo matches the target cargo to be sorted in terms of category and quantity, a picking result is generated indicating that the target delivery person has completed picking the target cargo to be sorted.

[0006] Optionally, the identifying the image of the target picking stage and comparing the identification result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted include: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined according to the cargo status feature recognition result that the target cargo to be sorted does not exist in the cargo location where the target cargo to be sorted is located, a picking result indicating that the target cargo to be sorted is out of stock is generated.

[0007] Optionally, updating the order corresponding to the target goods to be sorted according to the picking result includes: In a case where the picking result indicates that the target goods to be sorted are out of stock, the target goods to be sorted are cancelled from one or more orders including the picking order of the target delivery person, the buyer order of the user who purchased the target goods to be sorted, and the seller order of the merchant corresponding to the target warehouse.

[0008] Optionally, the method further includes: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined, based on the cargo status feature identification result, that other cargoes other than the target cargo to be sorted are present in the cargo location where the target cargo to be sorted is located, based on the identified categories and quantities of the other cargoes, the record associated with the cargo location where the target cargo to be sorted is located in the cargo storage record of the target warehouse is updated.

[0009] Optionally, the method further includes: Acquire images captured by the smart wearable device of the target delivery person in the process of heading to the cargo location where the target goods to be sorted are located; Performing cargo location environment feature recognition on images of the target delivery person in the process of going to the cargo location where the target goods to be sorted are located, and obtaining a cargo location environment feature recognition result; When it is determined based on the result of the cargo location environment feature recognition that the image of the target delivery person in the process of heading to the cargo location where the target goods to be sorted are located is consistent with the cargo location environment where the target goods to be sorted are located, it is determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located.

[0010] Optionally, the picking prompt information of the goods to be sorted includes at least one of the identification of the goods to be sorted, the picking progress of the goods to be sorted, the identification of the cargo location where the goods to be sorted are located, and the cargo location layout diagram corresponding to the target warehouse, and the cargo location where the goods to be sorted are located is highlighted in the cargo location layout diagram.

[0011] According to a second aspect of an embodiment of the present disclosure, there is provided a smart wearable device, including: a generating module configured to, upon determining that a target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from a target warehouse, generate an order query request to determine a picking order corresponding to a delivery end account currently logged in to the smart wearable device; a determination module configured to obtain, based on the order query request, picking order information associated with the currently logged-in delivery-end account, and determine, based on the picking order, picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery-end account of the smart wearable device, output by the smart wearable device; an acquisition module configured to, upon determining that a target picking stage has been entered, acquire an image of the target picking stage captured by the smart wearable device, wherein, upon determining that the target delivery person arrives at the storage location where the target goods to be sorted are located, enter the target picking stage corresponding to the target goods to be sorted, the target goods to be sorted being goods in a picking order associated with the delivery-end account currently logged into the smart wearable device, and the target goods to be sorted being goods to be sorted by the target delivery person in the target warehouse; The first updating module is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information, so as to determine the picking result of the target delivery person for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

[0012] According to a third aspect of an embodiment of the present disclosure, there is provided a smart wearable device, including: An acquisition component is configured to acquire picking order information, where the picking order information corresponds to a picking order corresponding to a delivery end account associated with the smart wearable device; a determining component configured to obtain, based on the picking order information, the picking order information associated with the currently logged-in delivery end account, and determine, based on the picking order information, picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery end account of the smart wearable device, output by the smart wearable device; Output component, outputs picking prompt information of the goods to be sorted corresponding to the picking order; an image acquisition component configured to acquire images of a target picking stage, wherein the images include images of target goods to be sorted, wherein the target goods to be sorted are goods in a picking order associated with the delivery end account currently logged into the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The first updating component is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information, determine the picking result for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

[0013] Optionally, the output component includes an optical component, which is configured to transmit the picking prompt information image to the eyes or in front of the eyes of the target delivery person wearing the smart wearable device through light projection or light reflection, so that the target user can see the picking prompt information while observing the real picking environment in the warehouse.

[0014] Optionally, the output component is further configured to output prompt information or correction information associated with the picking result in a manner that can be visually observed by a target user wearing the smart wearable device.

[0015] Optionally, the output component further includes a voice output component configured to output voice prompt information or voice correction information associated with the picking result.

[0016] Through the above technical solution, the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse and generates an order query request. Afterwards, the picking order information associated with the currently logged-in delivery end account can be obtained according to the order query request, and the picking prompt information of the goods to be sorted output by the smart wearable device can be determined according to the picking order and the goods storage record of the target warehouse, so as to assist the target delivery person in picking goods in the target warehouse. In addition, when the target delivery person arrives at the cargo location where the target goods to be sorted are located, the image of the target picking stage captured by the smart wearable device can be obtained to further identify the image of the target picking stage, and the target goods to be sorted in the picking order information can be compared based on the recognition result to determine the picking result of the target delivery person for the target goods to be sorted, and the order corresponding to the target goods to be sorted can be updated according to the picking result. It can be seen that the above method can assist the target delivery personnel in the picking process in the target warehouse and reduce the difficulty of the target delivery personnel in picking in the unmanned warehouse. In addition, it can also replace manual management of the target delivery personnel in the unmanned warehouse to improve the picking completion and efficiency.

[0017] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 is a schematic diagram showing the architecture of an unmanned warehouse picking system according to an exemplary embodiment; Figure 2 is a flowchart of a method for picking goods using a smart wearable device according to an exemplary embodiment; Figure 3 is a block diagram showing a method of using a smart wearable device according to an exemplary embodiment; Figure 4 is a block diagram of a smart wearable device according to an exemplary embodiment; Figure 5 is a block diagram of a server according to an exemplary embodiment; Figure 6 This is a flowchart showing a normal process in a picking scenario using a warehouse picking method using a smart wearable device according to an exemplary embodiment; Figure 7 is a schematic diagram showing a system architecture diagram and related data flows according to an exemplary embodiment; Figure 8 The present invention is a schematic diagram showing a process of interaction between a smart glasses device worn by a user and a server according to an exemplary embodiment. DETAILED DESCRIPTION

[0019] The following describes the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure and are not intended to limit the present disclosure.

[0020] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0021] Figure 1 FIG. 1 shows a schematic structural diagram of an unmanned warehouse picking system according to an embodiment of the present disclosure. Figure 1 As shown, the unmanned warehouse picking system includes a delivery person 101, a smart wearable device 102, a warehouse 103 (which can be an unmanned warehouse store or a manned warehouse), and a server 104. The smart wearable device 102 can be a smart head-mounted device, such as AR smart glasses or a smart helmet. The server 104 can be a collection of servers with multiple functions, either a single server or a server cluster. For example, the server 104 can include an order management server, a delivery management server, a picking management server, and a warehouse management server. Delivery person 101 can wear the smart wearable device 102 to pick items in the unmanned warehouse 103. Through the collaboration between the server 104 and the smart wearable device 102, the delivery person 101 can be managed and assisted in the picking process in the unmanned warehouse 103.

[0022] In some implementations, the smart wearable device 102 can communicate with the server 104, using an AI Agent development model with intelligent AI capabilities. Through AIGC's multimodal recognition and interaction capabilities, it can intelligently identify goods, shelves, and process requirements, and accurately complete operations such as goods warehousing, shelving, and location picking in real time. Its overall architecture is divided into four layers: 1. Interaction layer: Provides the user's voice and video stream input data to the Agent, and is also responsible for sending the Agent's input to the user.

[0023] 2. Agent layer: mainly includes three agents, namely ChatAgent, PickerAgent and ErrorAgent.

[0024] 3. AI service layer: provides basic large-model capability packaging, tool packaging, memory storage, and multimodal data perception.

[0025] 4. Infrastructure layer: including large model development framework, large model interface and database.

[0026] In some embodiments, the smart wearable device 102 may include an output component, which includes an optical component, and the optical component is configured to transmit the picking prompt information image to the eyes or in front of the eyes of the target delivery person wearing the smart wearable device through light projection or light reflection, so that the target user can see the picking prompt information while observing the real picking environment in the warehouse.

[0027] Figure 2 This is a flowchart of a method for picking goods using a smart wearable device according to an exemplary embodiment. The method can be applied to the smart wearable device alone, to the server alone, or to the smart wearable device in part and the server in part. Figure 2 As shown, the method for picking goods using a smart wearable device may include the following steps: S210, when it is determined that the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse, an order query request is generated, and the order query request indicates the currently logged-in delivery end account of the corresponding smart wearable device.

[0028] Here, the target delivery person can be any delivery person wearing a smart wearable device to pick up goods from the target warehouse. The target warehouse can be an unmanned warehouse where the target delivery person sorts goods.

[0029] In some embodiments, the target delivery person may initiate a picking instruction to pick up items from the target warehouse in a variety of ways. Optionally, the target delivery person may initiate a picking instruction to pick up items from the target warehouse by voice or key command. For example, the target delivery person may initiate a picking instruction to pick up items from the target warehouse by saying "XXX, I'm going to start picking up items" or by pressing a preset picking button on a smart wearable device.

[0030] In some embodiments, the target warehouse is selected by the target delivery person on the smart wearable device. In other embodiments, the target warehouse may be the warehouse where the target delivery person is located as located by the smart wearable device.

[0031] In the embodiment of the present disclosure, the delivery-end account of the target delivery person can be logged into the smart wearable device. Therefore, when the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse, an order query request indicating the currently logged-in delivery-end account of the corresponding smart wearable device can be generated. That is, the picking order associated with the currently logged-in delivery-end account of the smart wearable device can be queried.

[0032] S220, according to the order query request, obtain the picking order information associated with the currently logged-in delivery end account, and according to the picking order and the cargo storage record of the target warehouse, determine the picking prompt information of the target delivery person of the delivery end account corresponding to the smart wearable device output by the smart wearable device for the cargo to be sorted in the target warehouse.

[0033] In the disclosed embodiment, the picking order information associated with the currently logged-in delivery-end account can be obtained based on the generated order query request. In addition, the cargo storage record of the target warehouse can also be obtained. Furthermore, based on the picking order and the cargo storage record of the target warehouse, the picking prompt information of the cargo to be sorted in the target warehouse by the target delivery person corresponding to the delivery-end account of the smart wearable device output by the smart wearable device can be further determined.

[0034] In some embodiments, there are multiple ways to output picking prompt information via a smart wearable device. Optionally, the smart wearable device may have a display screen, so that the picking prompt information can be output in a visual manner via the display screen of the smart wearable device. For example, when the smart wearable device is an AR pair of glasses, the picking prompt information can be displayed via the AR pair of glasses. Optionally, the smart wearable device may have a voice output device, so that the picking prompt information can be output in the form of voice via the voice output device of the smart wearable device.

[0035] In some embodiments, the picking prompt information of the goods to be sorted includes at least one of the identification of the goods to be sorted, the picking progress of the goods to be sorted, the identification of the cargo location where the goods to be sorted are located, and the cargo location layout diagram corresponding to the target warehouse. The cargo location where the goods to be sorted are located is highlighted in the cargo location layout diagram.

[0036] For example, the identification of the goods to be sorted is such as "product name: paper towel", the picking progress of the goods to be sorted is such as "quantity: 0 / 1", and the identification of the cargo location where the goods to be sorted are located is such as "shelf number: 103".

[0037] In some embodiments, the cargo location layout diagram corresponding to the target warehouse can be a planar layout diagram or a three-dimensional layout diagram. By highlighting the cargo location where the goods to be sorted are located in the cargo location layout diagram, it is easier for the target delivery person to quickly locate the approximate location of the goods to be sorted, further improving the target delivery person's picking efficiency.

[0038] In the disclosed embodiment, by displaying at least one of the above-mentioned picking prompt information, the target delivery person can understand the picking status in the target warehouse, thereby improving the picking efficiency of the target delivery person.

[0039] S230, when it is determined that the target picking stage has been entered, an image of the target picking stage captured by the smart wearable device is obtained, wherein, when the target delivery person arrives at the storage location where the target goods to be sorted are located, it is determined that the target picking stage corresponding to the target goods to be sorted has been entered, and the target goods to be sorted are the goods in the picking order associated with the delivery end account currently logged in to the smart wearable device, and the target goods to be sorted are the goods to be sorted by the target delivery person in the target warehouse.

[0040] In the embodiment of the present disclosure, the target delivery person can pick goods in the target warehouse according to the picking prompt information. For example, the target delivery person can go to the cargo location where the target goods to be sorted are located in order to pick goods. Here, the target goods to be sorted can be any goods to be sorted in the target warehouse that is associated with the delivery-end account currently logged in by the smart wearable device by the target delivery person, or it can be a pre-designated target delivery person in the target warehouse that is associated with the delivery-end account currently logged in by the smart wearable device. When the target delivery person arrives at the cargo location where the target goods to be sorted are located, it can be determined that the target picking stage corresponding to the target goods to be sorted has entered. In this case, the image of the target picking stage captured by the smart wearable device is obtained until the picking result of the target delivery person for the target goods to be sorted is determined, or the record associated with the cargo location where the target goods to be sorted are located in the goods storage record of the target warehouse is updated.

[0041] That is, in the embodiment of the present disclosure, when it is determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located, the image acquisition device of the smart wearable device is used to capture images, and the picking process of the target delivery person is further analyzed based on the images captured by the smart wearable device, and the picking process is managed.

[0042] In the disclosed embodiment, there are multiple ways to determine whether the target delivery person has arrived at the location where the target goods to be sorted are located. Optionally, the target delivery person can determine whether the target delivery person has arrived at the location where the target goods to be sorted are located by using a voice command or by recognizing an image captured by a smart wearable device.

[0043] For example, by saying "I have arrived at XX cargo location" by voice, or by recognizing images collected by a smart wearable device, when the recognition result includes the cargo location corresponding to the target goods to be sorted, it can be determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located.

[0044] S240, identifying the image of the target picking stage, comparing the identification result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted, and updating the order corresponding to the target goods to be sorted according to the picking result.

[0045] In an embodiment of the present disclosure, after obtaining an image of the target picking stage, the image of the target picking stage can be identified, and the identification result of the image of the target picking stage can be compared with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted, and the picking order can be further updated based on the picking result.

[0046] According to the above method, the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse and generates an order query request. After that, the picking order information associated with the currently logged-in delivery end account can be obtained according to the order query request. According to the picking order and the goods storage record of the target warehouse, the picking prompt information of the goods to be sorted output by the smart wearable device is determined to assist the target delivery person in picking goods in the target warehouse. In addition, when the target delivery person arrives at the storage location where the target goods to be sorted are located, the image of the target picking stage captured by the smart wearable device can be obtained to further identify the image of the target picking stage. Based on the recognition result and the target goods to be sorted in the picking order information, the picking result of the target delivery person for the target goods to be sorted is determined, and the order corresponding to the target goods to be sorted is updated according to the picking result. It can be seen that the above method can assist the target delivery person in the picking process in the target warehouse, reduce the difficulty of the target delivery person in picking in the unmanned warehouse, and replace manual management of the picking process of the target delivery person in the unmanned warehouse, thereby improving the picking completion and picking efficiency.

[0047] It should be noted that the data used in the method for picking goods using a smart wearable device according to the present disclosure can be obtained by the smart wearable device or server directly or indirectly. Direct acquisition includes but is not limited to data collection or calculation by the smart wearable device itself, and indirect acquisition includes but is not limited to data transmission between other devices.

[0048] In some embodiments, recognizing an image of the target picking stage and comparing the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted may include the following steps: Perform cargo status feature recognition on the target picking stage image to obtain cargo status feature recognition results; When it is determined based on the results of cargo status feature recognition that the target delivery person has taken the cargo from the cargo location where the target cargo to be sorted is located, and the cargo taken away matches the target cargo to be sorted in terms of category and quantity, a picking result is generated to indicate that the target delivery person has completed picking the target cargo to be sorted.

[0049] In the disclosed embodiment, the cargo status feature recognition result may indicate whether cargo exists, and, if so, the cargo category and corresponding quantity. Furthermore, based on the cargo status feature recognition result, it can be determined whether cargo has been removed, and whether the removed cargo matches the target cargo to be sorted in terms of category and quantity. If the removed cargo matches the target cargo to be sorted in terms of both category and quantity, it indicates that the target delivery person has correctly removed the target cargo to be sorted, and a picking result can be generated indicating that the target delivery person has completed picking the target cargo to be sorted.

[0050] In some embodiments, a pre-trained cargo state feature recognition model may be used to perform cargo state feature recognition on images of the target picking stage to obtain cargo state feature recognition results.

[0051] In some embodiments, recognizing an image of the target picking stage and comparing the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted may include the following steps: Perform cargo status feature recognition on the target picking stage image to obtain cargo status feature recognition results; When it is determined according to the cargo status feature recognition result that the target cargo to be sorted does not exist in the cargo location where the target cargo to be sorted is located, a picking result indicating that the target cargo to be sorted is out of stock is generated.

[0052] In the embodiment of the present disclosure, if it is determined based on the cargo status feature recognition result that the target cargo to be sorted does not exist in the cargo location where the target cargo to be sorted is located, it means that the target cargo to be sorted is out of stock, and then a picking result indicating that the target cargo to be sorted is out of stock can be generated.

[0053] In some embodiments, updating the order corresponding to the target goods to be sorted according to the picking result may include the following steps: If the picking result indicates that the target goods to be sorted are out of stock, the target goods to be sorted are cancelled from one or more orders including the picking order of the target delivery person, the buyer order of the user who purchased the target goods to be sorted, and the seller order of the merchant corresponding to the target warehouse.

[0054] In an embodiment of the present disclosure, if the picking result is a picking result indicating that the target goods to be sorted are out of stock, the target goods to be sorted can be cancelled from one or more orders of the picking order of the target delivery person, the buyer order of the user who purchased the target goods to be sorted, and the seller order of the merchant corresponding to the target warehouse.

[0055] For example, the target goods to be sorted can be canceled from one or more orders of the target deliveryman's picking order, and the target deliveryman can be prompted through the smart wearable device that the target goods to be sorted have been canceled and no longer need to be delivered, and the target deliveryman or target user does not need to be responsible.

[0056] In some implementations, the method for picking goods using a smart wearable device in the embodiments of the present disclosure may further include the following steps: Perform cargo status feature recognition on the target picking stage image to obtain cargo status feature recognition results; When it is determined based on the cargo status feature identification result that there are other cargoes in the cargo location where the target cargo to be sorted is located, based on the identified categories and quantities of the other cargoes, the records associated with the cargo location where the target cargo to be sorted is located in the cargo storage records of the target warehouse are updated.

[0057] In the embodiment of the present disclosure, after obtaining the image of the target picking stage captured by the smart wearable device, the image of the target picking stage can be used to identify the status characteristics of the goods to obtain a cargo status characteristic recognition result. If it is determined according to the cargo status characteristic recognition result that there are other goods besides the target goods to be sorted in the cargo location where the target goods to be sorted are located, it means that the goods are placed incorrectly. In this case, the record associated with the cargo location where the target goods to be sorted are located in the cargo storage record of the target warehouse can be updated based on the category and quantity of the other goods identified.

[0058] For example, assuming that it is determined based on the cargo status feature identification results that the cargo location where the target cargo to be sorted is located (for example, the third cargo location in the first row of the first shelf) currently contains item A, and the quantity is 5, then the record associated with the third cargo location in the first row of the first shelf in the cargo storage record of the target warehouse can be updated to item A, and the quantity is 5.

[0059] By adopting the above method, when it is determined based on the results of cargo status feature identification that there are other cargoes in the cargo storage location where the target cargo to be sorted is located, the records associated with the cargo storage location where the target cargo to be sorted is located in the cargo storage records of the target warehouse are directly updated based on the categories and quantities of the other cargoes identified. This eliminates the need to notify the warehouse manager to exchange the cargo locations, thereby improving the management efficiency of the cargo in the target warehouse.

[0060] It can be seen that in the aforementioned embodiment, images of the target delivery person after he arrives at the storage location where the target goods to be sorted are located can be collected to perform goods status feature recognition, so as to prompt or update whether the target delivery person has completed picking the target goods to be sorted, whether the target goods to be sorted are out of stock, and whether there are any goods placed incorrectly in the storage location of the target goods to be sorted based on the goods status feature recognition results, so as to further improve the picking efficiency of the target delivery person in the target warehouse and the management efficiency of the goods in the target warehouse.

[0061] In some implementations, the method for picking goods using a smart wearable device in the embodiments of the present disclosure may further include the following steps: Obtain images captured by the smart wearable device of the target delivery person on their way to the location where the target goods to be sorted are located; Performing location environment feature recognition on the image of the target delivery person going to the location where the target goods to be sorted are located, and obtaining the location environment feature recognition result; When it is determined based on the result of the cargo location environment feature recognition that the image of the target delivery person going to the cargo location where the target goods to be sorted are located has an environment that is consistent with the cargo location where the target goods to be sorted are located, it is determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located.

[0062] In the embodiment of the present disclosure, after the picking prompt information of the target goods to be sorted is output through the smart wearable device, the target delivery person can go to the cargo location where the target goods to be sorted are located according to the picking prompt information to pick the target goods to be sorted. In the process of the target delivery person going to the cargo location where the target goods to be sorted are located, the image acquisition device of the smart wearable device can be used to capture images of the process, and further perform cargo location environment feature recognition based on the images captured by the smart wearable device to obtain cargo location environment feature recognition results.

[0063] In the disclosed embodiments, the cargo location environment feature recognition result may include a cargo location environment image or a cargo location identification. Furthermore, if the cargo location environment feature recognition result includes a cargo location environment image, a determination may be made as to whether the cargo location environment image in the cargo location environment feature recognition result matches the cargo location environment image of the target cargo to be sorted. If so, it is determined that the target delivery person has arrived at the cargo location where the target cargo to be sorted is located, and the smart wearable device may be used to notify the target delivery person of their arrival at the cargo location where the target cargo to be sorted is located.

[0064] If the location identification result includes a location identifier, it can be determined whether the location identifier in the location identification result matches the identifier of the location where the target goods to be sorted are located. If so, it is determined that the target delivery person has arrived at the location where the target goods to be sorted are located, and the smart wearable device can then be used to notify the target delivery person of their arrival at the location where the target goods to be sorted are located.

[0065] That is to say, in the embodiment of the present disclosure, images of the target delivery person in the process of heading to the cargo location where the target goods to be sorted are located can be collected to identify the cargo location environment characteristics, so as to prompt the target delivery person whether he has arrived at the cargo location where the target goods to be sorted are located based on the cargo location environment characteristic identification results, so as to further improve the efficiency of the target delivery person in picking goods in the target warehouse.

[0066] In some embodiments, a pre-trained cargo location environment feature recognition model can be used to perform cargo location environment feature recognition on images of a target delivery person heading to the cargo location where the target goods to be sorted are located to obtain a cargo location environment feature recognition result.

[0067] In some embodiments, the smart wearable device can output the picking order information through voice playback.

[0068] In some embodiments, the smart wearable device can output the picking order information in a visual manner, for example, it can output the picking order information through augmented reality projection, wherein the augmented reality projection allows the delivery person to view the picking order information while observing the real scene of the glasses.

[0069] Augmented reality projection refers to a display method in which virtual information or images are superimposed on the user's real-time field of view. Alternatively, a special optical component, such as a waveguide, can be used to guide the generated image to the user's eyes to achieve augmented reality projection. Alternatively, the generated image can be transmitted through a medium to the front of the glasses through light transmission to achieve augmented reality projection. Alternatively, translucent lenses can be used to allow light from the generated image to enter the eyes together with external light to achieve augmented reality projection.

[0070] The following is an example of a picking scenario using the above-mentioned warehouse picking method using smart wearable devices: Normal process: The target delivery person or target user (i.e., delivery person) arrives at the warehouse and puts on smart glasses. The target delivery person or target user's client account, logged in through the smart glasses, obtains the current target delivery person or target user's information. The agent (intelligent agent) pulls the current target delivery person or target user's pending pickup orders and displays the order information (i.e., picking order information). Starting with the first item, the target delivery person or target user is guided to pick the item: voice prompts and simple icons are used to guide the target delivery person or target user to a specific shelf location for picking. During the picking process, the target delivery person or target user is automatically captured to identify the item and location number, and to verify the correct quantity. If there is any abnormality, a voice prompt will be given to inform the target delivery person or target user if they have picked the wrong item.

[0071] Abnormal process: If the target delivery person or target user encounters insufficient quantity during picking, the agent will identify this scenario through specific complaints from the target delivery person or target user or images of empty shelves. This will trigger a workflow to cancel the order, inform the target delivery person or target user that the order cannot be completed and needs to be canceled, notify the user, and initiate an order verification task.

[0072] In the above-mentioned warehouse picking method using smart wearable devices, by combining AI technology with wearable devices, the ability of "smart devices as warehouse management" can be realized, greatly reducing the operation and maintenance costs of manual warehouse management.

[0073] In addition, smart glasses can also monitor the picking operation process in real time, promptly remind errors, and ensure accurate operations.

[0074] In some embodiments, when the picking order information includes multiple items, a picking route and a picking sequence may be designed based on the locations of the multiple items.

[0075] In the above-mentioned warehouse picking method using smart wearable devices, the AI ​​Agent guides the target delivery person or target user to find the location of the goods and automatically records the picked goods, thereby improving picking efficiency.

[0076] The following is an example of a replenishment scenario using the above-mentioned warehouse picking method using smart wearable devices: Normal process: Operations personnel use voice commands to initiate the replenishment process. Smart glasses control the replenishment process, prompting personnel to pick up the items, identify them, and then indicate the correct location to replenish them. As the operator places the items in the correct location, they automatically detect whether they are in the correct location. If not, a voice prompt is given. The replenishment process repeats until all items have been replenished, at which point a notification is displayed indicating the replenishment is complete. For example, smart glasses will identify the item name and quantity to be replenished, automatically record the replenishment list, and then indicate completion.

[0077] Abnormal process: During the replenishment process, the system monitors the operations of the maintenance personnel, identifies situations where goods are placed in the wrong location, and provides prompts and corrections. Here, correction means that the maintenance personnel can also be informed of the correct location.

[0078] In the above-mentioned warehouse replenishment method using smart wearable devices, by combining AI technology with wearable devices, the ability of "smart devices as warehouse managers" can be realized, greatly reducing the operation and maintenance costs of manual warehouse management. In addition, AI agents can guide warehouse managers to replenish stocks, improving picking efficiency. In addition, smart glasses can also monitor the replenishment operation process in real time, promptly remind of errors, and ensure accurate operations.

[0079] In the disclosed embodiment, through the multimodal recognition and interaction capabilities of AIGC, goods, shelves, and process requirements can be intelligently identified, and operations such as goods warehousing and shelving, and location picking can be completed in real time and accurately, achieving a set of AR+AI intelligent hardware equipment to realize low-cost unmanned warehouse operation and management.

[0080] Figure 3 FIG. 1 is a block diagram showing a method of using a smart wearable device according to an exemplary embodiment. Figure 3 As shown, an embodiment of the present disclosure provides a smart wearable device, and the smart wearable device 300 includes: The generating module 310 is configured to generate an order query request to determine the picking order corresponding to the delivery end account currently logged in to the smart wearable device when it is determined that the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse; The determination module 320 is configured to obtain, based on the order query request, the picking order information associated with the currently logged-in delivery end account, and determine, based on the picking order, the picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery end account of the smart wearable device, output by the smart wearable device; The acquisition module 330 is configured to, when it is determined that the target picking stage has been entered, acquire an image of the target picking stage captured by the smart wearable device, wherein, when the target delivery person arrives at the storage location where the target goods to be sorted are located, it is determined that the target picking stage corresponding to the target goods to be sorted has been entered, and the target goods to be sorted are goods in the picking order associated with the delivery end account currently logged in by the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The first updating module 340 is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

[0081] Optionally, the determination module is further configured to receive picking order information returned by the delivery service system server.

[0082] Optionally, the smart wearable device 300 further includes a communication module configured to send an order query request to the receiving and delivery service system server, and receive picking order information returned by the delivery service system server.

[0083] Optionally, the first update module 340 is further configured to perform cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; when it is determined according to the cargo status feature recognition result that the target delivery person has taken the goods from the storage location where the target goods to be sorted are located, and the taken goods match the target goods to be sorted in terms of category and quantity, a picking result is generated indicating that the target delivery person has completed picking the target goods to be sorted.

[0084] Optionally, the first updating module 340 is further configured to perform cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; when it is determined according to the cargo status feature recognition result that the target cargo to be sorted does not exist in the storage location where the target cargo to be sorted is located, a picking result indicating that the target cargo to be sorted is out of stock is generated.

[0085] Optionally, the first update module 340 is further configured to cancel the target goods to be sorted from one or more orders of the picking order of the target delivery person, the buyer order of the user who purchased the target goods to be sorted, and the seller order of the merchant corresponding to the target warehouse when the picking result is a picking result indicating that the target goods to be sorted are out of stock.

[0086] Optionally, the smart wearable device 300 also includes a second updating module, which is configured to perform cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; when it is determined according to the cargo status feature recognition result that there are other cargoes in addition to the target cargo to be sorted in the cargo location where the target cargo to be sorted is located, based on the identified category and quantity of the other cargoes, the record associated with the cargo location where the target cargo to be sorted is located in the cargo storage record of the target warehouse is updated.

[0087] Optionally, the smart wearable device 300 also includes a processing module configured to obtain images captured by the smart wearable device of the target delivery person in the process of going to the cargo location where the target goods to be sorted are located; perform cargo location environment feature recognition on the images of the target delivery person in the process of going to the cargo location where the target goods to be sorted are located to obtain cargo location environment feature recognition results; when it is determined according to the cargo location environment feature recognition results that the images of the target delivery person in the process of going to the cargo location where the target goods to be sorted are located are consistent with the cargo location environment where the target goods to be sorted are located, it is determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located.

[0088] Optionally, the picking prompt information of the goods to be sorted includes at least one of the identification of the goods to be sorted, the picking progress of the goods to be sorted, the identification of the cargo location where the goods to be sorted are located, and the cargo location layout diagram corresponding to the target warehouse, and the cargo location where the goods to be sorted are located is highlighted in the cargo location layout diagram.

[0089] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0090] In another exemplary embodiment, a smart wearable device is provided, including: An acquisition component is configured to acquire picking order information, where the picking order information corresponds to a picking order corresponding to a delivery end account associated with the smart wearable device; a determining component configured to obtain, based on the picking order information, the picking order information associated with the currently logged-in delivery end account, and determine, based on the picking order information, picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery end account of the smart wearable device, output by the smart wearable device; Output component, outputs picking prompt information of the goods to be sorted corresponding to the picking order; an image acquisition component configured to acquire images of a target picking stage, wherein the images include images of target goods to be sorted, wherein the target goods to be sorted are goods in a picking order associated with the delivery end account currently logged into the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The first updating component is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information, determine the picking result for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

[0091] Optionally, the output component includes an optical component, which is configured to transmit the picking prompt information image to the eyes or in front of the eyes of the target delivery person wearing the smart wearable device through light projection or light reflection, so that the target user can see the picking prompt information while observing the real picking environment in the warehouse.

[0092] Optionally, the output component is further configured to output prompt information or correction information associated with the picking result in a manner that can be visually observed by a target user wearing the smart wearable device.

[0093] Optionally, the output component further includes a voice output component configured to output voice prompt information or voice correction information associated with the picking result.

[0094] Figure 4 FIG. 4 is a block diagram of a smart wearable device 400 according to an exemplary embodiment. Figure 4 As shown, the smart wearable device 400 may include: a processor 401 , a memory 402 . The smart wearable device 400 may also include one or more of a multimedia component 403 , an input / output (I / O) interface 404 , and a communication component 405 .

[0095] The processor 401 is used to control the overall operation of the smart wearable device 400 to complete all or part of the steps in the above-mentioned method for picking goods using a smart wearable device. The memory 402 is used to store various types of data to support the operation of the smart wearable device 400. This data may include, for example, instructions for any application or method operating on the smart wearable device 400, as well as application-related data, such as graphical symbols, model data of information collection devices, etc. The memory 402 can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The multimedia component 403 may include a screen and an audio component. The audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 402 or sent through the communication component 405. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 404 provides an interface between the processor 401 and other interface modules, and the above-mentioned other interface modules may be, for example, buttons. These buttons may be virtual buttons or physical buttons. The communication component 405 is used for wired or wireless communication between the smart wearable device 400 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 405 may include: a Wi-Fi module, a Bluetooth module, an NFC module, etc.

[0096] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When executed by a processor, the program instructions implement the steps of the above-described method for picking goods using a smart wearable device. For example, the computer-readable storage medium may be the aforementioned memory 402 including the program instructions. The program instructions may be executed by the processor 401 of the smart wearable device 400 to implement the above-described method for picking goods using a smart wearable device.

[0097] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the method for picking using a smart wearable device in the above embodiment when executed by the programmable device.

[0098] Figure 5 FIG. 5 is a block diagram of a server 500 according to an exemplary embodiment. Figure 5 The server 500 includes one or more processors 522 and a memory 532 for storing a computer program executable by the processor 522. The computer program stored in the memory 532 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 522 may be configured to execute the computer program to perform the above-described method for picking goods using a smart wearable device.

[0099] In addition, the server 500 may further include a power supply component 526 and a communication component 550. The power supply component 526 may be configured to perform power management of the server 500, and the communication component 550 may be configured to implement communication, such as wired or wireless communication, of the server 500. In addition, the server 500 may further include an input / output (I / O) interface 555. The server 500 may operate based on an operating system stored in the memory 532.

[0100] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When executed by a processor, the program instructions implement the steps of the above-described method for picking goods using a smart wearable device. For example, the computer-readable storage medium may be the aforementioned memory 532 including the program instructions. The program instructions may be executed by the processor 522 of the server 500 to implement the above-described method for picking goods using a smart wearable device.

[0101] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable device, and the computer program has a code portion for executing the method for picking using a smart wearable device in the above embodiment when executed by the programmable device.

[0102] Next, combined with Figure 6 The normal process in the picking scenario using the above-mentioned warehouse picking method using smart wearable devices is exemplified. This process is implemented by the interaction between the delivery person and the device. The device includes chatAgent (dialogue agent), pickService (picking service), context (context service), guidAgent (guidance agent) and pickAgent (picking agent). The various units included in the device can be provided by at least one of the smart wearable device or the server. Figure 6 As shown: The delivery person starts a voice dialogue: Help me start picking the goods.

[0103] The dialogue agent generates a dialogue: recognizes the "pick" instruction, queries the picking service for the current status, and creates a picking list for the picking service.

[0104] The picking service returns the complete picking list information to the dialog agent.

[0105] The conversational agent arranges the picking sequence and uses voice playback on the smart wearable device to output the conversation: picking has begun. It also uses augmented reality projection to display the picking list and the first item to be picked. Furthermore, the conversational agent sends a request to the guidance agent to begin guidance to shelf X, location X.

[0106] The dialogue agent receives the successful acceptance information sent by the guidance agent, and outputs the dialogue in the form of voice playback on the smart wearable device: start shelf guidance.

[0107] The guidance agent determines in real time whether the delivery person has arrived. If not, it sends guidance information to the dialogue agent: Dialogue: In which direction should you move? Data display: Picture of the target location.

[0108] The dialogue agent outputs the dialogue through voice playback on the smart wearable device: "Please move in which direction?" and outputs data display through augmented reality projection: a picture of the target location.

[0109] If the guiding agent determines that the delivery person has arrived at the location, it sends a message to the dialogue agent that the delivery person has arrived at the location.

[0110] The dialogue agent records its arrival to the context service and outputs the dialogue through voice playback on the smart wearable device: "You have arrived at the designated location, please start picking." It also outputs data display through augmented reality projection: details of the items to be picked, and sends a message to the picking agent to start picking.

[0111] The picking agent determines the picking results in real time and sends a picking prompt "Dialogue: XXX" to the dialogue agent based on the picking results.

[0112] The dialogue agent outputs the dialogue through voice playback on the smart wearable device: XXX.

[0113] If the picking agent determines that the picking is successful based on the picking results, it sends a message of successful picking to the dialogue agent.

[0114] The dialogue agent updates the picking list information and outputs the dialogue through voice playback on the smart wearable device: The picking of XX has been completed, please proceed to the next one according to the prompts, and outputs the data display through augmented reality projection: Picking list details (item to be picked - 1).

[0115] It can be seen that through the above Figure 6 This example shows the normal process of a delivery person arriving at the warehouse and picking the first item to be picked. During this process, the delivery person and the smart wearable device can engage in one or more rounds of question-and-answer sessions. Furthermore, the smart wearable device can generate targeted responses to the delivery person's voice data based on the collected multimodal data.

[0116] By adopting the warehouse picking method using smart wearable devices according to the embodiment of the present disclosure, through the multimodal recognition and interaction capabilities of AIGC, goods, shelves, and process requirements can be intelligently identified, and operations such as goods picking and location guidance can be completed in real time and accurately, achieving low-cost unmanned warehouse operation and management with a set of AR+AI smart hardware equipment.

[0117] Next, combine Figure 7 A system architecture diagram and related data flows of an embodiment of the present disclosure are described. Figure 7 As shown: AR smart glasses can send image streams and chat content to the AUK IoT Platform, and the AUK IoT Platform can send instructions to start video streaming, chat replies, and order information display to the AR smart glasses.

[0118] There are uplink and downlink information links between the AUK IoT platform and the AR smart glasses service, and the AR smart glasses service is deployed with an AI agent.

[0119] The AR smart glasses service can send images to the database for storage and retrieve picking lists and order information from the database.

[0120] In some implementations, the AI ​​agents deployed by the AR smart glasses service may include a conversation agent, an order management agent, a shelf guidance agent, a picking agent, and an exception handling agent. The conversation agent is used to identify the user's intention. If a custom action is matched, it will be processed by the corresponding agent. The custom action list is as follows: a. Get the current list of pending orders; b. Get the details of a pending order; c. Start picking for an order; d. Problems encountered in picking goods.

[0121] Order Management Agent: Input: Several fixed instructions: 1. Query the current person's pending orders, 2. Query the details of a certain order; 3. Process abnormal orders.

[0122] Output: corresponding data content.

[0123] Shelf Guidance Agent: Memory: Shelf layout in the warehouse (picture or description); Input: target shelf number + location number + picture from the current viewing angle; Output: Whether the target position is reached.

[0124] Picking Agent: Input: the ID of the item to be picked, its feature description, shelf location, context, and n screenshots of the user's current field of view. Output: Whether the picked items are correct. Whether the picking is completed.

[0125] Exception handling agent: Input: out-of-stock information of the picked goods; Output: Cancel or modify the order, inform the user, and notify the merchant to restock.

[0126] Next, combine Figure 8 The process of interaction between a user-worn smart glasses device and a server in an embodiment of the present disclosure is described. Figure 8 As shown: On the one hand, the smart glasses device can record the user's voice through the microphone, then send the recorded voice to the voice recognition module for processing, and then obtain voice text data based on the processed text information. On the other hand, the smart glasses device can record the current scene through the camera, then send the recorded video stream to the image recognition module for processing, and then obtain scene image data based on the processed image data. Subsequently, the smart glasses device can send the voice text data and scene image data to the server based on the network communication protocol for processing by the server.

[0127] After processing, the server can send the analyzed voice content in text format and the reply order information in text format to the smart glasses device based on the network communication protocol. On the one hand, the smart glasses device can process the voice content in text format through the text-to-speech module to obtain voice data corresponding to the voice content, and play the voice data corresponding to the voice content through the speaker. On the other hand, the smart glasses device can process the order information in text format through the text display module to obtain image data corresponding to the order information, and display the image data corresponding to the order information through the display screen.

[0128] In some embodiments, the smart wearable device includes hardware and software components. The hardware includes a microphone, camera, display, speaker, and battery module; the software includes a voice SDK, a user-friendly glasses interaction UI, multimodal voice recognition, speech synthesis, image recognition, etc., a sensory data collection and processing module, a behavior module, a warehouse management database (recording product / location information), and a memory module (large model).

[0129] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the scope of protection of the present disclosure.

[0130] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0131] In addition, the various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for picking goods using a smart wearable device, characterized in that: The method comprises: When it is determined that the target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from the target warehouse, an order query request is generated, where the order query request indicates the delivery end account currently logged in corresponding to the smart wearable device; According to the order query request, the picking order information associated with the currently logged-in delivery-end account is obtained, and according to the picking order and the goods storage record of the target warehouse, the picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery-end account of the smart wearable device output by the smart wearable device is determined; When it is determined that the target picking stage has been entered, an image of the target picking stage captured by the smart wearable device is obtained, wherein when the target delivery person arrives at the storage location where the target goods to be sorted are located, it is determined that the target picking stage corresponding to the target goods to be sorted has been entered, the target goods to be sorted are goods in the picking order associated with the delivery end account currently logged in by the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The image of the target picking stage is recognized, and the recognition result of the image of the target picking stage is compared with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted, and the order corresponding to the target goods to be sorted is updated according to the picking result.

2. The method according to claim 1, characterized in that The identifying of the target picking stage image and comparing the identification result of the target picking stage image with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted include: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined based on the cargo status feature identification result that the target delivery person has taken the cargo from the cargo location where the target cargo to be sorted is located, and the taken cargo matches the target cargo to be sorted in terms of category and quantity, a picking result is generated indicating that the target delivery person has completed picking the target cargo to be sorted.

3. The method according to claim 1, characterized in that The identifying of the target picking stage image and comparing the identification result of the target picking stage image with the target goods to be sorted in the picking order information to determine the picking result of the target delivery person for the target goods to be sorted include: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined according to the cargo status feature recognition result that the target cargo to be sorted does not exist in the cargo location where the target cargo to be sorted is located, a picking result indicating that the target cargo to be sorted is out of stock is generated.

4. The method according to claim 3, characterized in that The updating of the order corresponding to the target goods to be sorted according to the picking result includes: In a case where the picking result indicates that the target goods to be sorted are out of stock, the target goods to be sorted are cancelled from one or more orders including the picking order of the target delivery person, the buyer order of the user who purchased the target goods to be sorted, and the seller order of the merchant corresponding to the target warehouse.

5. The method according to claim 1, wherein The method further comprises: Performing cargo status feature recognition on the image of the target picking stage to obtain a cargo status feature recognition result; When it is determined, based on the cargo status feature identification result, that other cargoes other than the target cargo to be sorted are present in the cargo location where the target cargo to be sorted is located, based on the identified categories and quantities of the other cargoes, the record associated with the cargo location where the target cargo to be sorted is located in the cargo storage record of the target warehouse is updated.

6. The method according to claim 1, characterized in that The method further comprises: Acquire images captured by the smart wearable device of the target delivery person in the process of heading to the cargo location where the target goods to be sorted are located; Performing cargo location environment feature recognition on images of the target delivery person in the process of going to the cargo location where the target goods to be sorted are located, and obtaining a cargo location environment feature recognition result; When it is determined based on the result of the cargo location environment feature recognition that the image of the target delivery person in the process of heading to the cargo location where the target goods to be sorted are located is consistent with the cargo location environment where the target goods to be sorted are located, it is determined that the target delivery person has arrived at the cargo location where the target goods to be sorted are located.

7. The method according to claim 1, characterized in that The picking prompt information of the goods to be sorted includes at least one of the identification of the goods to be sorted, the picking progress of the goods to be sorted, the identification of the cargo location where the goods to be sorted are located, and the cargo location layout diagram corresponding to the target warehouse, and the cargo location where the goods to be sorted are located is highlighted in the cargo location layout diagram.

8. A smart wearable device, characterized in that: include: a generating module configured to, upon determining that a target delivery person wearing the smart wearable device initiates a picking instruction to pick goods from a target warehouse, generate an order query request to determine a picking order corresponding to a delivery end account currently logged in to the smart wearable device; a determination module configured to obtain, based on the order query request, picking order information associated with the currently logged-in delivery-end account, and determine, based on the picking order, picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery-end account of the smart wearable device, output by the smart wearable device; an acquisition module configured to, upon determining that a target picking stage has been entered, acquire an image of the target picking stage captured by the smart wearable device, wherein, upon determining that the target delivery person arrives at the storage location where the target goods to be sorted are located, enter the target picking stage corresponding to the target goods to be sorted, the target goods to be sorted being goods in a picking order associated with the delivery-end account currently logged into the smart wearable device, and the target goods to be sorted being goods to be sorted by the target delivery person in the target warehouse; The first updating module is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information, so as to determine the picking result of the target delivery person for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

9. A smart wearable device, characterized in that: include: An acquisition component is configured to acquire picking order information, where the picking order information corresponds to a picking order corresponding to a delivery end account associated with the smart wearable device; a determining component configured to obtain, based on the picking order information, the picking order information associated with the currently logged-in delivery end account, and determine, based on the picking order information, picking prompt information of the goods to be sorted in the target warehouse by the target delivery person corresponding to the delivery end account of the smart wearable device, output by the smart wearable device; Output component, outputs picking prompt information of the goods to be sorted corresponding to the picking order; an image acquisition component configured to acquire images of a target picking stage, wherein the images include images of target goods to be sorted, wherein the target goods to be sorted are goods in a picking order associated with the delivery end account currently logged into the smart wearable device, and the target goods to be sorted are goods to be sorted by the target delivery person in the target warehouse; The first updating component is configured to recognize the image of the target picking stage, compare the recognition result of the image of the target picking stage with the target goods to be sorted in the picking order information, determine the picking result for the target goods to be sorted, and update the order corresponding to the target goods to be sorted according to the picking result.

10. The smart wearable device according to claim 9, characterized in that: The output component includes an optical component, which is configured to transmit the picking prompt information image to the eyes or in front of the eyes of the target delivery person wearing the smart wearable device through light projection or light reflection, so that the target user can see the picking prompt information while observing the real picking environment in the warehouse.

11. The smart wearable device according to claim 9, characterized in that: The output component is further configured to output prompt information or correction information associated with the picking result in a manner that can be visually observed by a target user wearing the smart wearable device.

12. The smart wearable device according to claim 9, characterized in that: The output component further includes a voice output component configured to output voice prompt information or voice correction information associated with the picking result.

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