An article commodity mobile unmanned delivery and self-service settlement system

Abstract

The application discloses a kind of article commodity mobile unmanned transport and self-service settlement system, it is related to article commodity mobile intelligent selling and distribution technical field, including: intelligent mobile cabinet car, self-service settlement terminal and background manager;The intelligent mobile cabinet car includes commodity management module, image acquisition module, automatic driving module and data processing module;The self-service settlement terminal bar includes code scanner, touch screen display, payment terminal;Merchant can set the various parameters of system by background management module, these parameters can be flexibly modified according to market changes, business strategy adjustment and the like;The application reduces labor cost, and self-service settlement system can quickly and accurately complete commodity settlement, avoids the possible human error and change time in traditional cash register mode, improves settlement efficiency, reduces the time of customer queuing and waiting, so as to can improve the customer flow and sales of shop.

Description

Technical Field

[0001] This invention relates to the field of logistics and distribution technology, and in particular to a mobile unmanned sales and self-service checkout system for goods. Background Technology

[0002] The rapid development of mobile internet has enabled device mobility and real-time communication. Through 4G / 5G networks, mobile unmanned vending machines can maintain a stable connection with backend servers, enabling real-time data transmission and updates. Mobile retail vehicles can send their location and inventory information to the server at any time, while simultaneously receiving instructions from the server regarding price adjustments and restocking notifications.

[0003] Traditional retail models have many limitations in terms of operating hours, labor costs, and shopping experience. For example, traditional stores need to employ a large number of cashiers, sales assistants, and other staff, and with the continuous rise in labor costs, this expense places a significant burden on retailers. Moreover, the limited operating hours of traditional retail stores cannot meet the growing demand from consumers for shopping outside of business hours.

[0004] There is an urgent need for a technology to automate the transportation of goods and commodities in order to reduce labor costs and achieve digital logistics information transmission. Summary of the Invention

[0005] This application provides a mobile unmanned sales and self-service checkout system for goods. This solves the problem in related technologies of reducing labor costs and achieving digital logistics information transmission while transporting and storing goods.

[0006] According to one aspect of the embodiments of this application, a mobile unmanned sales and self-service checkout system for goods is provided, including: an intelligent mobile vending vehicle, a self-service checkout terminal, and a back-end manager; The intelligent mobile container vehicle includes a commodity management module, an image acquisition module, and an automatic driving module; The product management module categorizes and places products in different areas according to their type. Each area is equipped with an independent access control system. The product management module includes a temperature control system to keep products warm and fresh. The product management module includes a weight sensor to detect when products are picked up and put back, and uploads the data to the backend manager. The product management module also includes a retrieving device for customers to retrieve products that are further away. The image acquisition module includes multiple camera modules, which are used to collect road conditions when the intelligent mobile container truck is moving and to monitor and identify customers' shopping behavior. Through computer recognition algorithms, the system can identify the goods picked up by customers, accurately determine the type and quantity of products based on weight sensors, and upload the data to the background manager. The calculation formula for computer recognition is as follows: , in, For each element of the output feature map; The elements are in the convolution kernel; For elements in the input feature map; Image features are extracted through multiple convolutional and pooling layers for subsequent classification and recognition. In the classification stage, classification probabilities are calculated using the softmax function. Let the output of the neural network be... j represents the number of categories and the probability of category k. The category to which a product belongs is determined by comparing the probability magnitudes.

[0007] The automatic driving module determines traffic conditions, road information, and the priority of delivery tasks through the positioning unit, driving unit, and route navigation unit, automatically plans the optimal delivery route, and uploads the delivery route and road condition data to the background manager in real time. The self-service checkout terminal includes a touch screen display, which provides an interface for customers to select payment methods, view product information, and view shopping lists. The self-service checkout terminal also includes a self-service checkout system, which receives product information from hardware devices, calculates the total price of the products, and completes the payment operation. During the payment process, the self-service checkout system needs to ensure the security and accuracy of the payment.

[0008] The platform manager is used to collect and save data information uploaded by each module and set various parameters of the module. These parameters can be flexibly modified according to market changes and business strategy adjustments.

[0009] The mobile unmanned sales and self-service settlement system for goods includes an automatic vending module in the intelligent mobile vending vehicle. After customers complete identity verification and select an area through the intelligent mobile vending vehicle APP or mini-program on their mobile terminals, the back-end manager controls the access control system to open the storage compartment in that area. After the customer selects the goods, the storage compartment is closed automatically, or the storage compartment is closed automatically after a period of time. When the storage compartment is closed, the self-service settlement terminal automatically settles the amount and deducts the transportation fee on the identity verification platform based on the collected data, and sends the settlement data to the back-end manager and the customer's mobile terminal at the same time.

[0010] The mobile unmanned sales and self-service checkout system for goods includes a touch screen display for the self-service checkout terminal, which also includes a voice interaction interface and a human service interface. The voice interaction module is used to enable human-computer communication through voice interaction during use. If the intelligent mobile container vehicle device or system malfunctions and the system cannot resolve the issue, customers can contact staff through the human service interface.

[0011] The image acquisition module includes an image enhancement unit, which changes the contrast and brightness of the image by transforming the grayscale value of each pixel in the image. The linear grayscale transformation formula is as follows: To indicate, among which These are the pixel values ​​of the original image; These are the transformed pixel values; a and b are constants; when When the image contrast increases, when... When the contrast decreases. When, the image brightens; when At that time, the image darkens.

[0012] The positioning unit in the mobile unmanned sales and self-service checkout system for goods is used to determine the location information of the intelligent mobile container vehicle and upload the location information to the back-end management module in real time.

[0013] The mobile unmanned sales and self-service checkout system for goods includes a driving unit comprising a battery and a battery management system. The battery provides power to the intelligent mobile container vehicle. The battery management system monitors and collects information about the battery through sensors, estimates its operating status, and implements control algorithms. Based on the calculation results, it controls the balancing system and the charging and discharging circuit.

[0014] The mobile unmanned sales and self-service checkout system for goods includes a back-end manager that sends the location information of customers and the intelligent mobile container truck to the path navigation unit. The path navigation unit first processes the map data, and after constructing a road network model, it uses a path planning algorithm to calculate the optimal path. The back-end manager obtains weather data as a driving standard for the intelligent mobile container truck. The path navigation unit also includes an automatic obstacle avoidance system and a traffic sign recognition system. The automatic collision avoidance system continuously scans the environment around the intelligent mobile container truck using lidar, collecting information about roads and pedestrians, assessing potential collision risks, and comprehensively considering factors such as the relative speed and distance between the container and surrounding objects, as well as the trajectory of the objects. Once a collision risk is determined, the automatic collision avoidance system will formulate an avoidance strategy based on the degree of risk and the surrounding environment. If the distance is sufficient, it may choose to brake to avoid the collision; if braking cannot avoid the collision, it will combine steering to avoid the collision and upload the driving trajectory of the avoidance process to the background manager. The aforementioned unmanned mobile sales and self-service checkout system for goods and commodities uses weather data as a driving standard for the intelligent mobile container vehicle's driving data in the background manager. The traffic sign recognition system is trained on a large number of traffic sign images and identifies the traffic sign images through the image acquisition module, accurately implementing the movement information represented by the traffic sign images.

[0015] The mobile unmanned sales and self-service checkout system for goods includes a path navigation unit that further comprises a voice prompt system and a visual guidance system. The voice prompt system provides navigation prompts to users via voice, while the visual guidance system displays navigation information on the screen of the intelligent mobile container vehicle in the form of maps, arrows, and lane lines.

[0016] The aforementioned mobile unmanned sales and self-service settlement system allows the platform to collect a certain percentage of commission after a transaction is completed. Alternatively, the platform can cooperate with merchants to conduct sales, and merchants can purchase or lease intelligent mobile vending vehicles for automated transportation and supply to disperse customers.

[0017] The mobile unmanned vending and self-service checkout system for goods includes a backend manager comprising a data entry system and a learning system. The data entry system supports data import and export functions for data exchange with other systems. Data import allows reading data from external files and storing it in the database; data export allows exporting data from the database to external files for further analysis and processing. The learning system continuously collects sales data generated by the intelligent mobile vending vehicle, including the sales quantity, sales time, and sales location. Through sensors and database recording, it understands the specific circumstances of each customer purchase, analyzes customer behavior patterns in the unmanned vending environment, such as shopping paths, dwell time, and product selection preferences, to better understand their shopping habits. It also collects operational status data of the intelligent mobile vending vehicle, shelf inventory, and equipment malfunction information, monitors changes in the quantity of goods on the shelves in real time, and issues replenishment reminders when inventory falls below a certain level.

[0018] Furthermore, in the mobile unmanned sales and self-service checkout system for goods, the goods management module stores the categories of goods as follows: daily necessities, food ingredients, food seasonings, alcoholic beverages, cosmetics, general merchandise, hardware, and fruits.

[0019] Furthermore, in the mobile unmanned sales and self-service checkout system for the goods, the positioning module adopts the Beidou positioning module of China's independently developed satellite navigation system, which can simultaneously track multiple frequency points of Beidou B1I / B2I / B3I / B1C / B2a / B2b.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) Since the unmanned vending system eliminates the steps of queuing and checkout, consumers can quickly complete their shopping. Through automatic identification technology and self-service settlement system, consumers can quickly complete payment after selecting goods, which greatly saves time. (2) Mobile unmanned vending systems minimize reliance on manual labor. They eliminate the need to hire large numbers of cashiers, sales assistants, etc., thereby reducing labor costs. (3) Mobile unmanned vending equipment occupies a relatively small area and can be flexibly placed in different locations. Unlike traditional stores, it does not require renting a large commercial space, which effectively reduces rental costs.

[0021] The technical solution of this application will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0022] The accompanying drawings, which form part of this specification, illustrate embodiments of this application and, together with the description, serve to explain the principles of this application.

[0023] This application can be more clearly understood with reference to the accompanying drawings and the following detailed description, wherein: Figure 1 This is a structural block diagram of a mobile unmanned sales and self-service checkout system for goods proposed in this application; Figure 2 This is a structural block diagram of the intelligent mobile container truck proposed in this application; Figure 3 This is a structural block diagram of the background manager proposed in this application. Detailed Implementation

[0024] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present application.

[0025] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0026] The following description of at least one exemplary embodiment is merely illustrative and is not intended to limit the scope of this application or its application or use.

[0027] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0028] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0029] Furthermore, the technical solutions of the various embodiments of this application can be combined with each other, but only if they are based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be considered that such combination of technical solutions does not exist and is not within the scope of protection claimed by this application.

[0030] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of this application are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0031] The following is combined with Figures 1-3This application describes an unmanned mobile sales and self-checkout system for goods according to exemplary embodiments of the present application. It should be noted that the following application scenarios are shown only to facilitate understanding of the spirit and principles of the present application, and the embodiments of the present application are not limited in any way. Rather, the embodiments of the present application can be applied to any applicable scenario.

[0032] This embodiment provides a mobile unmanned sales and self-service checkout system for goods, including: an intelligent mobile vending vehicle, a self-service checkout terminal, and a back-end manager; The intelligent mobile container vehicle includes a commodity management module, an image acquisition module, and an autonomous driving module; The product management module categorizes and places products in different areas based on their type. Each area is equipped with an independent access control system. The product management module includes weight sensors to detect when products are picked up and put back, and uploads the data to the backend manager. The image acquisition module includes multiple camera modules, which are used to collect road conditions when the intelligent mobile container truck is moving and to monitor and identify customers' shopping behavior. Through computer recognition algorithms, the system can identify the goods picked up by customers, accurately determine the type and quantity of products based on weight sensors, and upload the data to the backend manager. The calculation formula for computer recognition is as follows:

[0033] in, For each element of the output feature map; The elements are in the convolution kernel; For elements in the input feature map; Image features are extracted through multiple convolutional and pooling layers for subsequent classification and recognition. In the classification stage, classification probabilities are calculated using the softmax function. Let the output of the neural network be... j represents the number of categories and the probability of category k. The category to which a product belongs is determined by comparing the probability magnitudes.

[0034] The autonomous driving module determines traffic conditions, road information, and the priority of delivery tasks through the positioning unit, drive unit, and route navigation unit, automatically plans the optimal delivery route, and uploads the delivery route and road condition data to the background manager in real time. The self-checkout terminal includes a touch screen, which provides an interface for customers to choose payment methods, view product information, and view shopping lists. The self-checkout terminal also includes a self-checkout system, which receives product information from the hardware device, calculates the total price of the goods, and completes the payment. During the payment process, the self-checkout system needs to ensure the security and accuracy of the payment.

[0035] The background manager is used to collect and save data uploaded by each module and set various parameters of the modules. These parameters can be flexibly modified according to market changes and business strategy adjustments.

[0036] Specifically, customers can register and log in using mobile terminal verification codes, account passwords, and third-party accounts, so that the system can record customers' personal information and shopping history. After logging in, customers can view and modify their personal information so that merchants can accurately contact them when needed. For member customers, the system can record member points, registration and consumption records, and provide corresponding discounts and services based on member level and consumption.

[0037] As can be seen from the above, unmanned vending and self-service checkout systems require stable and fast network communication support to ensure that product information and transaction data can be transmitted and processed in a timely manner. A combination of wired and wireless networks is adopted. Wired networks are used in fixed locations such as shopping malls and supermarkets to ensure the stability of data transmission, while wireless networks are used in mobile unmanned vending vehicles, temporary stalls, and other locations to ensure the flexibility and mobility of the system.

[0038] Understandably, because unmanned vending systems eliminate queuing and checkout processes, consumers can quickly complete their shopping. Through automatic identification technology and self-service checkout systems, consumers can quickly pay after selecting their goods, significantly saving time. Mobile unmanned vending systems also minimize reliance on human labor. They eliminate the need to hire a large number of cashiers and sales assistants, thus reducing labor costs. Furthermore, mobile unmanned vending equipment has a relatively small footprint and can be flexibly placed in different locations, eliminating the need to rent large commercial spaces like traditional stores, effectively reducing rental costs.

[0039] Specifically, the mobile unmanned sales and self-service checkout system for goods includes an automatic vending module in the smart mobile vending vehicle. After customers complete identity verification and select an area through the smart mobile vending vehicle's APP or mini-program on their mobile phones, the back-end manager controls the door control system to open the storage compartment in that area. After the customer selects the goods, they can manually close the storage compartment or the storage compartment can automatically close after a period of time. Once the storage compartment is closed, the self-service checkout terminal automatically calculates the amount and deducts the transportation fee on the identity verification platform based on the collected data, and simultaneously sends the settlement data to the back-end manager and the customer's mobile phone terminal.

[0040] Specifically, for customers, the vending machine system is not restricted by the traditional store's business hours. Whether it is late at night or early in the morning, as long as consumers have a need, they can purchase goods at the designated location.

[0041] Understandably, automated vending systems do not require a large number of cashiers, sales assistants, and other staff like traditional stores. A smart mobile vending vehicle only needs regular restocking and maintenance personnel, which greatly reduces labor costs.

[0042] Specifically, the mobile unmanned sales and self-service checkout system for goods includes a touch screen display for the self-service checkout terminal, which also includes a voice interaction interface and a human service interface. The voice interaction module is used to enable human-computer communication through voice interaction during use. If the intelligent mobile container vehicle device or system malfunctions and cannot be resolved by the system, customers can contact staff through the human service interface.

[0043] Specifically, self-checkout terminals can record detailed transaction data, including the types of goods purchased, the time, and the amount. By analyzing this data, merchants can gain a deeper understanding of consumer purchasing behavior and preferences, providing a basis for product display, procurement, and promotional strategies. Based on the collected data, merchants can conduct targeted marketing campaigns.

[0044] Specifically, in the mobile unmanned sales and self-service checkout system for goods, the image acquisition module includes an image enhancement unit. This unit alters the contrast and brightness of the image by transforming the grayscale value of each pixel. The linear grayscale transformation formula is as follows: To indicate, among which These are the pixel values ​​of the original image; These are the transformed pixel values; a and b are constants; when When the image contrast increases, when... When the contrast decreases. When, the image brightens; when At this time, the image becomes darker. Understandably, image enhancement units can improve image quality under low light conditions. In nighttime monitoring scenarios, dim lighting may cause the monitoring image to be blurry. Image enhancement units can use low-light enhancement technology to utilize the weak light information in the image to enhance the brightness and clarity of the entire image, enabling monitoring personnel to better detect potential security risks.

[0045] Specifically, the mobile unmanned sales and self-service checkout system for goods includes a positioning unit used to determine the location information of the intelligent mobile vending vehicle and upload the location information to the backend manager in real time.

[0046] Specifically, the mobile unmanned sales and self-service checkout system for goods includes a driving unit consisting of a battery and a battery management system. The battery provides power to the intelligent mobile container vehicle, and the battery management system monitors and collects information about the battery through sensors, estimates the operating status and uses control algorithms. Based on the calculation results, it controls the equalization system and the charging and discharging circuit.

[0047] Specifically, in the mobile unmanned sales and self-service checkout system for goods, the back-end manager sends the location information of customers and intelligent mobile container vehicles to the path navigation unit. The path navigation unit first processes the map data, and after building a road network model, it uses a path planning algorithm to calculate the optimal path. The path navigation unit also includes an automatic obstacle avoidance system and a traffic sign recognition system.

[0048] Specifically, the automatic collision avoidance system continuously scans the environment around the intelligent mobile container truck using LiDAR, collecting information about roads and pedestrians to assess potential collision risks. It comprehensively considers factors such as the relative speed and distance between the container and surrounding objects, as well as the trajectory of the objects. Once a collision risk is determined, the automatic collision avoidance system will formulate an avoidance strategy based on the degree of risk and the surrounding environment. If the distance is sufficient, it may choose to brake to avoid the collision; if braking cannot avoid the collision, it will combine steering to avoid the collision and upload the driving trajectory of the avoidance process to the background manager.

[0049] Specifically, the traffic sign recognition system trains on a large number of traffic sign images and identifies the traffic sign images through the image acquisition module, accurately implementing the movement information represented by the traffic sign images.

[0050] Specifically, the mobile unmanned sales and self-service checkout system for goods includes a navigation unit that also includes a voice prompt system and a visual guidance system. The voice prompt system provides navigation prompts to users through voice, while the visual guidance system displays navigation information on the screen of the intelligent mobile container vehicle in the form of maps, arrows, and lane lines.

[0051] Understandably, based on the user-defined starting point and destination, the path navigation unit will use a path planning algorithm to calculate the optimal path. The algorithm is Algorithm A. Dijkstra's algorithm can find the shortest path from the starting point to the destination, but its computational complexity is high. Algorithm A, on the other hand, adds heuristic information to Dijkstra's algorithm, which can find a better path more efficiently.

[0052] Furthermore, during route planning, the navigation unit also considers various factors, such as traffic conditions, road type, and toll information. In urban traffic navigation, if the user chooses to avoid congested sections, the navigation unit will prioritize planning routes with less traffic based on real-time traffic information; if the user wants to take highways to save time, the navigation unit will include as many highway sections as possible when planning the route.

[0053] Furthermore, in the mobile unmanned sales and self-service checkout system for goods, the background manager obtains weather data to serve as the driving standard for the intelligent mobile container vehicle.

[0054] Specifically, the mobile unmanned vending and self-checkout system for goods includes a backend manager comprising a data entry system and a learning system. The data entry system supports data import and export functions for data exchange with other systems. Data import allows reading data from external files and storing it in the database; data export allows exporting data from the database to external files for further analysis and processing. The learning system continuously collects sales data generated by the intelligent mobile vending vehicles, including information on the quantity of goods sold, sales time, and sales location. Through sensors and database records, it understands the specific circumstances of each customer purchase, analyzes customer behavior patterns in the unmanned vending environment, such as shopping paths, dwell time, and product selection preferences, to better understand their shopping habits. It also collects operational status data of the intelligent mobile vending vehicles, shelf inventory, equipment malfunction information, and monitors changes in the quantity of goods on the shelves in real time, issuing replenishment reminders when inventory falls below a certain level.

[0055] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the following claims.

[0056] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A mobile unmanned sales and self-service checkout system for goods, characterized in that, include: Intelligent mobile container truck, self-service checkout terminal and back-end manager; The intelligent mobile container vehicle includes a commodity management module, an image acquisition module, and an automatic driving module; The product management module categorizes and places products in different areas according to their type. Each area is equipped with an independent access control system. The product management module includes a temperature control system to keep products warm and fresh. The product management module includes a weight sensor to detect when products are picked up and put back, and uploads the data to the backend manager. The product management module also includes a retrieving device for customers to retrieve products that are further away. The image acquisition module includes multiple camera modules, which are used to collect road conditions when the intelligent mobile container truck is moving and to monitor and identify customers' shopping behavior. Through computer recognition algorithms, the system can identify the goods picked up by customers, accurately determine the type and quantity of products based on weight sensors, and upload the data to the background manager. The calculation formula for computer recognition is as follows: ， in, For each element of the output feature map; The elements are in the convolution kernel; For elements in the input feature map; Image features are extracted through multiple convolutional and pooling layers for subsequent classification and recognition. In the classification stage, classification probabilities are calculated using the softmax function. Let the output of the neural network be... , j represents the number of categories, and the probability of category k. The category to which a product belongs is determined by comparing the probability magnitudes; The automatic driving module determines traffic conditions, road information, and the priority of delivery tasks through the positioning unit, driving unit, and route navigation unit, automatically plans the optimal delivery route, and uploads the delivery route and road condition data to the background manager in real time. The self-service checkout terminal includes a touch screen display, which provides an interface for customers to select payment methods, view product information, and view shopping lists. The self-service checkout terminal also includes a self-service checkout system, which receives product information from hardware devices, calculates the total price of the products, and completes the payment operation. During the payment process, the self-service checkout system needs to ensure the security and accuracy of the payment. The platform manager is used to collect and save data information uploaded by each module and set various parameters of the module. These parameters can be flexibly modified according to market changes and business strategy adjustments.

2. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, The intelligent mobile vending vehicle also includes an automatic vending module. After customers complete identity verification and select an area through the intelligent mobile vending vehicle APP or mini-program on their mobile terminals, the back-end manager controls the gate control system to open the storage compartment in that area. After the customer selects the goods, the storage compartment is closed automatically, or the storage compartment is closed automatically after a period of time. When the storage compartment is closed, the self-service checkout terminal automatically calculates the amount and deducts the transportation fee on the identity verification platform based on the collected data, and sends the settlement data to the back-end manager and the customer's mobile terminal at the same time.

3. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, The touch screen of the self-service checkout terminal also includes a voice interaction interface and a human service interface. The voice interaction module is used to realize human-computer communication through voice interaction during use. If the intelligent mobile container vehicle device or system has a problem that the system cannot solve, the customer can contact the staff through the human service interface.

4. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, The image acquisition module includes an image enhancement unit, which changes the contrast and brightness of the image by transforming the grayscale value of each pixel in the image. The linear grayscale transformation formula is as follows: To indicate, among which These are the pixel values ​​of the original image; These are the transformed pixel values; a and b are constants; when When the image contrast increases, when... When the contrast decreases. When, the image brightens; when At that time, the image darkens.

5. The mobile unmanned sales and self-service checkout system for goods according to claim 1, characterized in that, The positioning unit is used to determine the location information of the intelligent mobile container vehicle and upload the location information to the background management module in real time.

6. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, The drive unit includes a battery and a battery management system. The battery provides power to the intelligent mobile container vehicle. The battery management system monitors and collects information about the battery through sensors, estimates the operating status and uses control algorithms, and controls the equalization system and charging / discharging circuit based on the calculation results.

7. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, The back-end manager sends the location information of the customer and the intelligent mobile container truck to the route navigation unit. The route navigation unit first processes the map data, and after constructing a road network model, it uses a route planning algorithm to calculate the optimal route. The back-end manager obtains weather data as the driving standard for the intelligent mobile container truck. The route navigation unit also includes an automatic obstacle avoidance system and a traffic sign recognition system. The automatic collision avoidance system continuously scans the environment around the intelligent mobile container truck using lidar, collecting information about roads and pedestrians, assessing potential collision risks, and comprehensively considering factors such as the relative speed and distance between the container and surrounding objects, as well as the trajectory of the objects. Once a collision risk is determined, the automatic collision avoidance system will formulate an avoidance strategy based on the degree of risk and the surrounding environment. If the distance is sufficient, it may choose to brake to avoid the collision; if braking cannot avoid the collision, it will combine steering to avoid the collision and upload the driving trajectory of the avoidance process to the background manager. The aforementioned unmanned mobile sales and self-service checkout system for goods and commodities uses weather data as a driving standard for the intelligent mobile container vehicle's driving data in the background manager. The traffic sign recognition system is trained on a large number of traffic sign images and identifies the traffic sign images through the image acquisition module, accurately implementing the movement information represented by the traffic sign images.

8. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 7, characterized in that, The route navigation unit also includes a voice prompt system and a visual guidance system. The voice prompt system provides navigation prompts to users through voice, while the visual guidance system displays navigation information in the form of maps, arrows, and lane lines on the screen of the intelligent mobile container vehicle.

9. The mobile unmanned sales and self-service checkout system for goods and commodities according to claim 1, characterized in that, After a transaction is completed, the platform will collect a certain percentage of commission. Alternatively, the platform can cooperate with merchants to conduct sales. Merchants can purchase or lease smart mobile delivery vehicles for automated transportation and supply to customers.

10. The mobile unmanned sales and self-service checkout system for goods according to claim 1, characterized in that, The background manager includes a data entry system and a learning system. The data entry system supports data import and export functions to facilitate data exchange with other systems. Data import can read data from external files and store it in the database. Data export allows data from the database to be exported as external files for further analysis and processing. The learning system continuously collects sales data generated by the intelligent mobile vending vehicle, including information on the quantity of goods sold, sales time, and sales location. Through sensors and database records, it understands the specific circumstances of each customer purchase, analyzes customer behavior patterns in the unmanned vending environment, such as shopping paths, dwell time, and product selection preferences, to better understand their shopping habits. It also collects operational status data of the intelligent mobile vending vehicle, shelf inventory, and equipment malfunction information, monitors changes in the quantity of goods on the shelves in real time, and issues replenishment reminders when inventory falls below a certain level.

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