Loading trolley management method, device and equipment and readable storage medium

Abstract

The invention discloses a carrying trolley management method, device and equipment and a readable storage medium, and the method comprises the steps: distributing carrying trolleys for a user based on the current states and use positions of all carrying trolleys and the maximum waiting time acceptable by the user when a carrying trolley use request sent by the user through an intelligent terminal is received, the use request comprises a use position and the maximum waiting time which can be accepted by the user; and the distributed loading trolley moves along with the intelligent terminal of the user based on the real-time position of the loading trolley and the real-time position of the intelligent terminal. According to the application, after the loading trolley use request sent by the user is received, the loading trolley is allocated to the user by comprehensively considering the current states and the use positions of all the loading trolleys and the maximum waiting time acceptable by the user, and then the allocated loading trolley follows the user through the following intelligent terminal; automatic and intelligent management of the whole process is realized, and the use efficiency and experience of the user are greatly improved.

Description

Technical Field

[0001] This application relates to the field of intelligent cargo cart technology, and in particular to a cargo cart management method, device, equipment and readable storage medium. Background Technology

[0002] In today's fast-paced life, people's demand for convenient and efficient services is growing. Whether in industrial parks or supermarkets, there are challenges in improving the delivery of goods and the shopping experience. In industrial parks, staff often need to move large quantities of goods, from office supplies to raw materials. Traditional manual handling is not only physically demanding but also easily limited by time and manpower, resulting in low efficiency. In supermarkets, customers push heavy shopping carts, weaving between shelves, and movement becomes difficult when their carts are full.

[0003] In summary, the current use of cargo carts in industrial parks and supermarkets suffers from problems such as lack of intelligence, low efficiency, and poor user experience. Summary of the Invention

[0004] This application provides a method, apparatus, device, and readable storage medium for managing cargo carts, aiming to solve the technical problems of unintelligent, inefficient, and unpleasant user experience in the current use of cargo carts in parks and supermarkets.

[0005] In a first aspect, embodiments of this application provide a method for managing a cargo cart, the method comprising: When a user sends a request to use a cargo cart via a smart terminal, a cargo cart is assigned to the user based on the current status of all cargo carts, their usage locations, and the maximum waiting time that the user can accept. The usage request includes the usage location and the maximum waiting time that the user can accept. The assigned cargo cart moves according to the user's smart terminal, based on its own real-time location and the real-time location of the smart terminal.

[0006] Optionally, the process of allocating a cargo vehicle to a user based on the current status, usage location, and maximum acceptable waiting time of all cargo vehicles includes: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the user's maximum acceptable waiting time, and assign it to the user.

[0007] Optionally, before allocating a cargo cart to the user based on the current status, usage location, and maximum acceptable waiting time of all cargo carts upon receiving a user's request to use the cargo cart via a smart terminal, the following steps are included: Before business hours begin, a cargo cart is allocated to each service point according to the total number of cargo carts and a preset ratio for each service point. The preset ratio for each service point is determined based on the proportion of the number of historical usage requests for each service point during business hours to the total number of historical usage requests for all service points.

[0008] Optionally, the cargo cart management method further includes: Within the preset time frame before the end of business hours, for each cargo vehicle that is not at a service point and is in an idle state and is waiting to be dispatched, if the nearest service point is not full, the cargo vehicle will be dispatched to the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is less than the distance from the waiting service point to another service point, then the nearest service point will be used to send the nearest service point for charging and battery swapping, and the waiting service point will be used to send the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is not less than the distance from the waiting-to-be-dispatched service point to another service point, then the waiting-to-be-dispatched service point will be dispatched to another service point for charging and battery swapping.

[0009] Optionally, the assigned cargo vehicle moves according to the user's smart terminal based on its own real-time location and the real-time location of the smart terminal, including: The assigned cargo trolley is controlled using a two-wheel linear two-degree-of-freedom steering model based on its own real-time location and the real-time location of the smart terminal, so that the cargo trolley can move following the user's smart terminal. The two-wheel linear two-degree-of-freedom steering model is as follows: ; Where v and w are the velocities of the cargo trolley on the x-axis and y-axis, respectively, θ is the heading angle of the cargo trolley, φ is the turning angle of the cargo trolley, and d is the distance from the center of the cargo trolley's axle to the center of the axle of the front or rear wheel of the cargo trolley.

[0010] Optionally, the allocated cargo vehicle, based on its own real-time location and the real-time location of the intelligent terminal, uses a two-wheel linear two-degree-of-freedom steering model to control the cargo vehicle, including: The assigned cargo vehicle calculates the target heading angle based on its own real-time location and the real-time location of the smart terminal; The actual heading angle of the cargo trolley was measured. The deviation between the actual heading angle and the target heading angle is used as input, and the steering angle is output through the fuzzy adaptive control system to control the cargo trolley to execute the output steering angle. The fuzzy adaptive control system uses a two-wheel linear two-degree-of-freedom steering model as the controlled object.

[0011] Secondly, embodiments of this application provide a cargo cart management device, the cargo cart management device comprising: The allocation module is used to allocate a cargo vehicle to the user when it receives a cargo vehicle usage request sent by the user through a smart terminal, based on the current status of all cargo vehicles, their usage location, and the maximum waiting time that the user can accept. The usage request includes the usage location and the maximum waiting time that the user can accept. The follow module is used to assign a cargo cart to follow the user's smart terminal based on its own real-time location and the real-time location of the smart terminal.

[0012] Optionally, the allocation module is used for: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the user's maximum acceptable waiting time, and assign it to the user.

[0013] Thirdly, embodiments of this application provide a cargo cart management device, which includes a processor, a memory, and a cargo cart management program stored in the memory and executable by the processor. When the cargo cart management program is executed by the processor, it implements the steps of the cargo cart management method described above.

[0014] Fourthly, embodiments of this application provide a readable storage medium storing a cargo cart management program, wherein when the cargo cart management program is executed by a processor, it implements the steps of the cargo cart management method as described above.

[0015] The beneficial effects of the technical solutions provided in this application include: In this embodiment, when a user sends a request to use a cargo cart via a smart terminal, a cargo cart is allocated to the user based on the current status and location of all cargo carts and the maximum acceptable waiting time. The request includes the location and the maximum acceptable waiting time. The allocated cargo cart moves with the user's smart terminal based on its own real-time location and the real-time location of the smart terminal. Through this embodiment, a scheduling platform connects all smart terminals and cargo carts. First, the user sends a cargo cart use request to the scheduling platform via a wearable or handheld smart terminal. After receiving the request, the scheduling platform comprehensively considers the current status, location, and maximum acceptable waiting time of all cargo carts to allocate a cargo cart to the user. The allocated cargo cart then follows the user by following the smart terminal. This achieves fully automated and intelligent management of cargo carts within parks and supermarkets, from request to allocation to following, greatly improving user efficiency and experience. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating an embodiment of the cargo cart management method of this application; Figure 2 This is a schematic diagram of the application architecture of an embodiment of the cargo cart management method of this application; Figure 3 This is a schematic diagram of the kinematic model of an embodiment of the cargo cart management method of this application; Figure 4 This is a schematic diagram of the functional modules of an embodiment of the cargo cart management device of this application; Figure 5 This is a schematic diagram of the hardware structure of the cargo cart management device involved in the embodiments of this application. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present application.

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0019] In a first aspect, embodiments of this application provide a method for managing cargo carts.

[0020] In one embodiment, reference is made to Figure 1 , Figure 1 This is a flowchart illustrating an embodiment of the cargo cart management method of this application, as shown below. Figure 1 As shown, the management method for cargo carts includes: Step S10: When a user sends a request to use a cargo vehicle via a smart terminal, a cargo vehicle is assigned to the user based on the current status of all cargo vehicles, their usage locations, and the maximum acceptable waiting time for the user. The usage request includes the usage location and the maximum acceptable waiting time for the user.

[0021] In this embodiment, it is mainly applied to parks and supermarkets, referring to... Figure 2 , Figure 2 This is a schematic diagram of the application architecture of an embodiment of the cargo cart management method of this application, as shown below. Figure 2 As shown, the dispatch platform connects all smart terminals and cargo carts. Users request to use a cargo cart through their smart terminals. The dispatch platform collects real-time status information of all cargo carts within the area, including the current status (idle, occupied, or damaged), estimated idle time T(x), and estimated location after idleness for each cart. The dispatch platform receives cargo cart usage requests sent by users through their smart terminals. These requests include the usage location (which can be located in real-time via the smart terminal's positioning function) and the maximum acceptable waiting time for the user. The dispatch platform comprehensively considers the current status of all cargo carts, their usage locations, and the maximum acceptable waiting time for the user to intelligently allocate cargo carts to the user, achieving optimal allocation. It can handle the idle and busy states of cargo carts, improve system availability during peak periods, and significantly enhance the user experience.

[0022] In step S20, the assigned cargo vehicle moves according to its own real-time location and the real-time location of the smart terminal, following the user's smart terminal.

[0023] In this embodiment, the assigned cargo trolley acquires and calculates the target heading angle based on its own real-time location and the real-time location of the user's smart terminal. Then, the actual heading angle of the cargo trolley is acquired through a heading angle sensor, and the deviation between the actual heading angle and the target heading angle is calculated. Using this deviation as input, a fuzzy adaptive control system outputs a steering angle to control the cargo trolley to perform steering, achieving automatic following of the user. Through precise heading control and adaptive adjustment, the cargo trolley achieves stable following of the user. The user can wear a wearable or handheld smart terminal. Both the smart terminal and the cargo trolley have real-time positioning (such as GPS) capabilities. The real-time location of the smart terminal can be sent to the cargo trolley through a scheduling platform, or the cargo trolley and the smart terminal can communicate directly to obtain each other's real-time locations. The real-time location of the smart terminal represents the user's real-time location. The cargo trolley follows the movement of the smart terminal to achieve following of the user, ensuring that the target user is not lost.

[0024] In this embodiment, it is mainly applied to parks and supermarkets. The dispatch platform connects all smart terminals and delivery vehicles. Users apply to the dispatch platform for delivery vehicles through their smart terminals. The dispatch platform collects real-time status information of all delivery vehicles in the area. It receives delivery vehicle usage requests sent by users through their smart terminals and intelligently allocates delivery vehicles to users by comprehensively considering the current status of all delivery vehicles, their usage locations, and the maximum acceptable waiting time for the user. This achieves optimal allocation of delivery vehicles, handling idle and busy states, improving system availability during peak periods, and significantly enhancing the user experience. Through precise heading control and adaptive adjustment, the delivery vehicles stably follow users. The delivery vehicles follow the movement of the smart terminals to ensure that target users are not lost.

[0025] Furthermore, in one embodiment, allocating a cargo vehicle to the user based on the current status, usage location, and maximum acceptable waiting time of all cargo vehicles includes: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the user's maximum acceptable waiting time, and assign it to the user.

[0026] In this embodiment, the scheduling platform collects the real-time status information of all the load-carrying trolleys in the area in real time to form the total set of load-carrying trolley information Veh(t). For each load-carrying trolley, the system records its current status α(x), the estimated idle time T(x), the set of distances β(x) from the position after idling to each service point, and the set of times γ(x). Among them, α(x) = {1, 2, 3} respectively represent the idle, damaged, and occupied statuses of the load-carrying trolley. Multiple service points can be set in the park and the supermarket, and different numbers of idle load-carrying trolleys are parked at each service point. During allocation, the system first determines whether there are idle load-carrying trolleys (α(x) = 1) among all the service points. If there are, the system selects the idle load-carrying trolley in the service point closest to the user's requested usage location. If not, the system filters out the load-carrying trolleys with T(x) < Tp (the maximum waiting duration acceptable to the user), then calculates the distances from the positions of these load-carrying trolleys after idling to the user's usage location, and selects the load-carrying trolley with the shortest distance for allocation. It is easy to understand that if there are no load-carrying trolleys with the current status of idle among all the service points, and there are no load-carrying trolleys with T(x) < Tp (the maximum waiting duration acceptable to the user), it is informed that there are no available load-carrying trolleys for the user, and allocation will be carried out after there are load-carrying trolleys meeting the conditions, and an allocation notice is sent to the user's intelligent terminal.

[0027] Through comprehensive consideration of the status and position of the load-carrying trolley, the intelligent allocation of the load-carrying trolley is achieved, improving the utilization rate of the load-carrying trolley and the user satisfaction. By introducing the judgment condition of T(x) < Tp, the problem of shortage of load-carrying trolleys during peak periods is effectively solved, controlling the user's waiting time within an acceptable range, and significantly improving the user experience.

[0028] Further, in one embodiment, before step S10, it includes: Before the business starts, load-carrying trolleys are allocated to each service point according to the total number of load-carrying trolleys and the preset ratio of each service point, and the preset ratio of each service point is determined based on the proportion of the historical usage requests of each service point during business hours in the total number of historical usage requests of all service points.

[0029] In this embodiment, a preset ratio of delivery carts to be allocated to each service point is calculated based on historical data. Through a data-driven approach, the system anticipates the usage demand at each service point and pre-allocates a reasonable number of delivery carts to each point before business hours begin. For example, if historical data shows that service point A accounts for 30% of the total requests during business hours, service point B for 50%, and service point C for 20%, then the system will allocate 30% of the delivery carts to service point A, 50% to service point B, and 20% to service point C. By analyzing historical data and anticipating the usage demand at each service point in advance, the system can rationally allocate delivery carts, avoiding situations of insufficient or excessive delivery carts at service points during peak business hours. This significantly reduces user waiting time and improves overall service efficiency.

[0030] Furthermore, in one embodiment, the cargo cart management method further includes: Within the preset time frame before the end of business hours, for each cargo vehicle that is not at a service point and is in an idle state and is waiting to be dispatched, if the nearest service point is not full, the cargo vehicle will be dispatched to the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is less than the distance from the waiting service point to another service point, then the nearest service point will be used to send the nearest service point for charging and battery swapping, and the waiting service point will be used to send the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is not less than the distance from the waiting-to-be-dispatched service point to another service point, then the waiting-to-be-dispatched service point will be dispatched to another service point for charging and battery swapping.

[0031] In this embodiment, within a preset time frame before the end of business hours (e.g., the last 30 minutes before closing time), the system schedules charging and battery swapping for trolleys that are not at service points and are idle. The system calculates the distance from each trolley to various service points and prioritizes scheduling them to the nearest service point that is not yet full. If the nearest service point is full, the system compares the distances of trolleys at a service point to other service points with the distances of the trolleys to be scheduled, and selects the optimal scheduling scheme. For example, if the distance from a trolley at service point A to point B is 500 meters, and the distance from the trolley to point B is 600 meters, then the trolley at service point A is scheduled to go to service point B, and the trolley to be scheduled goes to service point A. Through this intelligent charging and battery swapping scheduling strategy, the capacity of each service point can be maximized, saving trolley travel distances while avoiding service point overload or idleness, ensuring that the number of trolleys at each service point is reasonable and their batteries are sufficient before the next business day, thus improving the overall operational efficiency of the system.

[0032] Further, in one embodiment, step S20 includes: The assigned cargo trolley is controlled using a two-wheel linear two-degree-of-freedom steering model based on its own real-time location and the real-time location of the smart terminal, so that the cargo trolley can move following the user's smart terminal. The two-wheel linear two-degree-of-freedom steering model is as follows: ; Where v and w are the velocities of the cargo trolley on the x-axis and y-axis, respectively, θ is the heading angle of the cargo trolley, φ is the turning angle of the cargo trolley, and d is the distance from the center of the cargo trolley's axle to the center of the axle of the front or rear wheel of the cargo trolley.

[0033] In this embodiment, refer to Figure 3 , Figure 3 This is a schematic diagram of the kinematic model of an embodiment of the cargo cart management method of this application, as shown below. Figure 3 As shown, the system accurately describes the kinematic characteristics of the cargo vehicle using a two-wheel linear two-degree-of-freedom steering model. This model can accurately describe the motion characteristics of the cargo vehicle at different steering angles, providing a precise mathematical basis for subsequent following control. Furthermore, a steering angle constraint condition |φ|≤φ can be added based on the mechanical characteristics of the cargo vehicle's steering structure. max <π / 3, ensuring the physical feasibility of steering. The system calculates the target heading angle based on the current position of the cargo vehicle and the position of the user's smart terminal, then calculates the required steering angle through a model, and controls the cargo vehicle to perform the steering.

[0034] Furthermore, in one embodiment, the allocated cargo vehicle, based on its own real-time location and the real-time location of the smart terminal, uses a two-wheel linear two-degree-of-freedom steering model to control the cargo vehicle, including: The assigned cargo vehicle calculates the target heading angle based on its own real-time location and the real-time location of the smart terminal; The actual heading angle of the cargo trolley was measured. The deviation between the actual heading angle and the target heading angle is used as input, and the steering angle is output through the fuzzy adaptive control system to control the cargo trolley to execute the output steering angle. The fuzzy adaptive control system uses a two-wheel linear two-degree-of-freedom steering model as the controlled object.

[0035] In this embodiment, we continue to refer to... Figure 3The system first calculates the target heading angle, which is the angle between the user's smart terminal position and the current position of the cargo vehicle. Then, it measures the actual heading angle of the cargo vehicle using a heading angle sensor. The deviation between the actual and target heading angles is used as input, and the fuzzy adaptive control system outputs the corresponding steering angle based on this deviation. The fuzzy adaptive control system uses a two-wheeled linear two-degree-of-freedom steering model as the controlled object. It also includes a fuzzy controller and an adaptive law. The fuzzy controller outputs a control quantity based on the deviation, and the adaptive law dynamically adjusts the parameters of the fuzzy controller based on system operation, enabling the system to adapt to environmental changes. By adaptively adjusting the control parameters, the system can automatically optimize the control strategy according to environmental changes and usage conditions, improving the system's robustness and adaptability. Through the fuzzy adaptive control system, precise tracking of the target heading angle can be achieved, solving the problems of target loss and inaccurate tracking. This significantly improves the stability and accuracy of the cargo vehicle's following, maintaining stable following performance even in complex environments, greatly enhancing the user experience.

[0036] Secondly, embodiments of this application also provide a cargo cart management device.

[0037] In one embodiment, reference is made to Figure 4 , Figure 4 This is a functional module diagram of an embodiment of the cargo cart management device of this application, as shown below. Figure 4 As shown, the cargo cart management device includes: The allocation module 10 is used to allocate a cargo vehicle to the user when it receives a cargo vehicle usage request sent by the user through a smart terminal, based on the current status of all cargo vehicles, their usage locations, and the maximum waiting time that the user can accept. The usage request includes the usage location and the maximum waiting time that the user can accept. The follow module 20 is used to assign a cargo cart to follow the user's smart terminal based on its own real-time location and the real-time location of the smart terminal.

[0038] Furthermore, in one embodiment, the allocation module 10 is used for: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the user's maximum acceptable waiting time, and assign it to the user.

[0039] Furthermore, in one embodiment, the cargo cart management device further includes a pre-opening allocation module, used for: Before business hours begin, a cargo cart is allocated to each service point according to the total number of cargo carts and a preset ratio for each service point. The preset ratio for each service point is determined based on the proportion of the number of historical usage requests for each service point during business hours to the total number of historical usage requests for all service points.

[0040] Furthermore, in one embodiment, the cargo vehicle management device further includes a charging and battery swapping scheduling module, used for: Within the preset time frame before the end of business hours, for each cargo vehicle that is not at a service point and is in an idle state and is waiting to be dispatched, if the nearest service point is not full, the cargo vehicle will be dispatched to the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is less than the distance from the waiting service point to another service point, then the nearest service point will be used to send the nearest service point for charging and battery swapping, and the waiting service point will be used to send the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is not less than the distance from the waiting-to-be-dispatched service point to another service point, then the waiting-to-be-dispatched service point will be dispatched to another service point for charging and battery swapping.

[0041] Furthermore, in one embodiment, the follower module 20 is used for: The assigned cargo trolley is controlled using a two-wheel linear two-degree-of-freedom steering model based on its own real-time location and the real-time location of the smart terminal, so that the cargo trolley can move following the user's smart terminal. The two-wheel linear two-degree-of-freedom steering model is as follows: ; Where v and w are the velocities of the cargo trolley on the x-axis and y-axis, respectively, θ is the heading angle of the cargo trolley, φ is the turning angle of the cargo trolley, and d is the distance from the center of the cargo trolley's axle to the center of the axle of the front or rear wheel of the cargo trolley.

[0042] Furthermore, in one embodiment, the allocated cargo vehicle, based on its own real-time location and the real-time location of the smart terminal, uses a two-wheel linear two-degree-of-freedom steering model to control the cargo vehicle for: The assigned cargo vehicle calculates the target heading angle based on its own real-time location and the real-time location of the smart terminal; The actual heading angle of the cargo trolley was measured. The deviation between the actual heading angle and the target heading angle is used as input, and the steering angle is output through the fuzzy adaptive control system to control the cargo trolley to execute the output steering angle. The fuzzy adaptive control system uses a two-wheel linear two-degree-of-freedom steering model as the controlled object.

[0043] The functions of each module in the above-mentioned cargo cart management device correspond to the steps in the above-mentioned cargo cart management method embodiment, and their functions and implementation processes will not be described in detail here.

[0044] Thirdly, embodiments of this application provide a cargo cart management device.

[0045] Reference Figure 5 , Figure 5 This is a schematic diagram of the hardware structure of the cargo cart management device involved in the embodiments of this application. In the embodiments of this application, the cargo cart management device may include a processor, a memory, a communication interface, and a communication bus.

[0046] The communication bus can be of any type and is used to interconnect the processor, memory, and communication interface.

[0047] The communication interface includes input / output (I / O) interfaces, physical interfaces, and logical interfaces used for interconnecting devices within the cargo cart management device, as well as interfaces used for interconnecting the cargo cart management device with other devices (such as other computing devices or user equipment). Physical interfaces can be Ethernet interfaces, fiber optic interfaces, ATM interfaces, etc.; user equipment can be displays, keyboards, etc.

[0048] Memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0049] The processor can be a general-purpose processor, which can call the cargo cart management program stored in the memory and execute the cargo cart management method provided in the embodiments of this application. For example, the general-purpose processor can be a central processing unit (CPU). The method executed when the cargo cart management program is called can be referred to in the various embodiments of the cargo cart management method of this application, and will not be repeated here.

[0050] Those skilled in the art will understand that Figure 5 The hardware structure shown does not constitute a limitation of this application and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0051] Fourthly, embodiments of this application also provide a readable storage medium.

[0052] The present application has a readable storage medium storing a cargo cart management program, wherein when the cargo cart management program is executed by a processor, it implements the steps of the cargo cart management method described above.

[0053] The method implemented when the cargo cart management program is executed can be referred to in various embodiments of the cargo cart management method of this application, and will not be repeated here.

[0054] It should be noted that the sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0055] The terms "comprising" and "having," and any variations thereof, in the specification, claims, and accompanying drawings of this application are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such process, method, product, or apparatus. The terms "first," "second," and "third," etc., are used to distinguish different objects, etc., and do not indicate a sequence, nor do they limit "first," "second," and "third" to different types.

[0056] In the description of the embodiments of this application, terms such as "exemplary," "for example," or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "exemplary," "for example," or "for instance" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary," "for example," or "for instance" is intended to present the relevant concepts in a concrete manner.

[0057] In the description of the embodiments of this application, unless otherwise stated, " / " means "or". For example, A / B can mean A or B. The "and / or" in the text is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist simultaneously, and B exists alone. In addition, in the description of the embodiments of this application, "multiple" means two or more.

[0058] In some processes described in the embodiments of this application, multiple operations or steps are included in a specific order. However, it should be understood that these operations or steps may not be executed in the order they appear in the embodiments of this application, or they may be executed in parallel. The sequence number of the operation is only used to distinguish different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed sequentially or in parallel, and these operations or steps may be combined.

[0059] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device to execute the methods described in the various embodiments of this application.

[0060] The above are merely preferred embodiments of this application and do not limit the patent scope of this application. Any equivalent structural or procedural transformations made using the content of this application's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of this application.

Claims

1. A method for managing a cargo cart, characterized in that, The method for managing the cargo cart includes: When a user sends a request to use a cargo cart via a smart terminal, a cargo cart is assigned to the user based on the current status of all cargo carts, their usage locations, and the maximum waiting time that the user can accept. The usage request includes the usage location and the maximum waiting time that the user can accept. The assigned cargo cart moves according to its own real-time location and the real-time location of the smart terminal, following the user's smart terminal.

2. The cargo cart management method as described in claim 1, characterized in that, The process of allocating a cargo vehicle to a user based on the current status of all cargo vehicles, their usage location, and the maximum acceptable waiting time for the user includes: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the maximum acceptable waiting time for the user.

3. The cargo cart management method as described in claim 2, characterized in that, Before allocating a cargo cart to the user upon receiving a request from the user via a smart terminal, based on the current status and location of all cargo carts and the maximum acceptable waiting time for the user, the following steps are included: Before business hours begin, a cargo cart is allocated to each service point according to the total number of cargo carts and a preset ratio for each service point. The preset ratio for each service point is determined based on the proportion of the number of historical usage requests for each service point during business hours to the total number of historical usage requests for all service points.

4. The cargo cart management method as described in claim 1, characterized in that, The cargo cart management method also includes: Within the preset time frame before the end of business hours, for each cargo vehicle that is not at a service point and is idle and awaiting dispatch, if the nearest service point is not full, the cargo vehicle awaiting dispatch will be dispatched to the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is less than the distance from the waiting service point to another service point, then the nearest service point will be used to send the nearest service point for charging and battery swapping, and the waiting service point will be used to send the nearest service point for charging and battery swapping. If the nearest service point is full, and the distance from the nearest service point to another service point is not less than the distance from the waiting-to-be-dispatched service point to another service point, then the waiting-to-be-dispatched service point will be dispatched to another service point for charging and battery swapping.

5. The cargo cart management method as described in claim 1, characterized in that, The assigned cargo vehicle moves according to the user's smart terminal based on its own real-time location and the real-time location of the smart terminal, including: The assigned cargo trolley is controlled using a two-wheeled linear two-degree-of-freedom steering model based on its own real-time location and the real-time location of the smart terminal, allowing the cargo trolley to move following the user's smart terminal. The two-wheeled linear two-degree-of-freedom steering model is as follows: ； Where v and w are the velocities of the cargo trolley on the x-axis and y-axis, respectively, θ is the heading angle of the cargo trolley, φ is the turning angle of the cargo trolley, and d is the distance from the center of the cargo trolley's axle to the center of the axle of the front or rear wheel of the cargo trolley.

6. The cargo cart management method as described in claim 5, characterized in that, The assigned cargo vehicle, based on its own real-time location and the real-time location of the smart terminal, is controlled using a two-wheel linear two-degree-of-freedom steering model, including: The assigned cargo vehicle calculates the target heading angle based on its own real-time location and the real-time location of the smart terminal; The actual heading angle of the cargo trolley was measured. The deviation between the actual heading angle and the target heading angle is used as input, and the steering angle is output through the fuzzy adaptive control system to control the cargo trolley to execute the output steering angle. The fuzzy adaptive control system uses a two-wheel linear two-degree-of-freedom steering model as the controlled object.

7. A cargo cart management device, characterized in that, The cargo cart management device includes: The allocation module is used to allocate a cargo vehicle to the user when it receives a cargo vehicle usage request sent by the user through a smart terminal, based on the current status of all cargo vehicles, their usage location, and the maximum waiting time that the user can accept. The usage request includes the usage location and the maximum waiting time that the user can accept. The follow module is used to assign a cargo cart to follow the user's smart terminal based on its own real-time location and the real-time location of the smart terminal.

8. The cargo cart management device as described in claim 7, characterized in that, The allocation module is used for: Obtain the current state of all cargo carts, the time required for them to transition from a non-idle state to an idle state, and their location after transitioning from a non-idle state to an idle state; If there are idle carts among all service points, the cart in the service point that is currently idle and closest to the usage location will be the cart assigned to the user. If there are no idle carts at any of the service points, then select the cart whose location is closest to the user's desired location after transitioning from a non-idle state to an idle state, from among all carts whose transition time from a non-idle state to an idle state is less than the maximum acceptable waiting time for the user.

9. A cargo cart management device, characterized in that, The cargo vehicle management device includes a processor, a memory, and a cargo vehicle management program stored in the memory and executable by the processor, wherein when the cargo vehicle management program is executed by the processor, it implements the steps of the cargo vehicle management method as described in any one of claims 1 to 6.

10. A readable storage medium, characterized in that, The readable storage medium stores a cargo cart management program, wherein when the cargo cart management program is executed by a processor, it implements the steps of the cargo cart management method as described in any one of claims 1 to 6.

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