A cargo compartment allocation method and device based on a transfer robot

Abstract

The application relates to the technical field of robots, and provides a cargo hold distribution method and device based on a transfer robot. The method comprises the following steps: determining a distribution task according to loading information of a target cargo hold; determining state information of each candidate robot; determining a matching score of each candidate robot performing the distribution task according to the distribution task and the state information; and determining a target robot in each candidate robot according to the matching score, so that the target robot performs the distribution task. According to the application, the target cargo hold and the state information of the robot are matched and scored, and then the target robot transporting the target cargo hold is determined, so that the stability and efficiency in the transportation process are improved.

Description

Technical Field

[0001] This application relates to the field of robotics technology, and in particular to a cargo hold allocation method and apparatus based on a docking robot. Background Technology

[0002] Robots have broad application prospects in the transportation of goods. They can be used in scenarios such as express delivery, freight, and e-commerce warehousing, and can also enter the manufacturing process to provide logistics solutions for factories. Robots can automatically complete tasks such as loading, unloading, handling, sorting, and delivery of goods, greatly reducing the intensity of manual labor and improving work efficiency. In addition, robots can optimize logistics operation processes through intelligent algorithms and data analysis, helping companies reduce costs and improve service quality.

[0003] If the robot chassis lacks sufficient energy to support the weight of the cargo hold, the robot will operate slowly and take longer to complete its tasks. This not only reduces work efficiency but also increases battery consumption and shortens battery life. Insufficient chassis energy can also lead to stability issues during transport. Therefore, because the robot's energy and the cargo hold's weight differ, improper pairing can result in instability and inefficiency during transport. Summary of the Invention

[0004] In view of this, the present application provides a cargo hold allocation method and apparatus based on a shuttle robot to solve the problems of instability and low efficiency of robots in the transportation process in the prior art.

[0005] A first aspect of this application provides a cargo hold allocation method based on a shuttle robot, comprising:

[0006] The delivery task is determined based on the loading information of the target cargo hold;

[0007] Determine the status information of each candidate robot;

[0008] Based on the delivery task and status information, determine the matching score for each candidate robot to perform the delivery task;

[0009] Based on the matching score, the target robot is selected from the candidate robots so that the target robot can perform the delivery task.

[0010] A second aspect of this application provides a cargo hold distribution device based on a shuttle robot, comprising:

[0011] The delivery task determination module is configured to determine the delivery task based on the loading information of the target cargo hold;

[0012] The status information determination module is configured to determine the status information of each candidate robot;

[0013] The matching score determination module is configured to determine the matching score for each candidate robot to perform the delivery task based on the delivery task and status information.

[0014] The execution module is configured to determine the target robot from among the candidate robots based on the matching score, so that the target robot can perform the delivery task.

[0015] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described method.

[0016] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described method.

[0017] The beneficial effects of this application's embodiments compared to existing technologies are as follows: Delivery tasks are determined based on the loading information of the target cargo hold; the status information of each candidate robot is determined; a matching score is determined for each candidate robot to perform the delivery task based on the delivery task and status information; and a target robot is selected from among the candidate robots based on the matching score, so that the target robot can perform the delivery task. This application performs pairing and scoring based on the loading information of the target cargo hold and the robot's status information, thereby determining the target robot for transporting the target cargo hold, thus improving the stability and efficiency of the transportation process. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram illustrating an application scenario of this application embodiment;

[0020] Figure 2 This is a schematic flowchart of a cargo hold allocation method based on a shuttle robot provided in an embodiment of this application;

[0021] Figure 3 This is a schematic diagram of a cargo hold distribution device based on a shuttle robot provided in an embodiment of this application;

[0022] Figure 4This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0023] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0024] The following describes in detail, with reference to the accompanying drawings, a cargo compartment allocation method and apparatus based on a shuttle robot according to embodiments of this application.

[0025] Figure 1 This is a schematic diagram illustrating an application scenario according to an embodiment of this application. The application scenario may include a server 101 and a connecting robot 102.

[0026] Server 101 is the allocation system that issues delivery tasks to shuttle robots 102. It generates delivery tasks based on the loading information of the target cargo hold and matches them with the status information of shuttle robots 102. All matching information is processed to determine the shuttle robot 102 to perform the delivery task, and then the delivery task for the target cargo hold is issued to the shuttle robot 102 so that it can execute the delivery task. Shuttle robots 102 can accept delivery tasks issued by server 101 and execute the delivery tasks according to their requirements. The number of shuttle robots 102 is usually multiple (…). Figure 1 Only one is shown in the image; the others are similar.

[0027] It should be noted that the specific type, quantity, and combination of the server 101 and the connecting robot 102 can be adjusted according to the actual needs of the application scenario, and this application embodiment does not limit this.

[0028] Figure 2 This is a schematic flowchart of a cargo compartment allocation method based on a shuttle robot provided in an embodiment of this application. Figure 2 The cargo hold allocation method based on shuttle robots is applied to the allocation system. For example... Figure 2 As shown, the cargo hold allocation method based on the shuttle robot includes:

[0029] S201, determine the delivery task based on the loading information of the target cargo hold.

[0030] S202, determine the status information of each candidate robot.

[0031] S203, based on the delivery task and the status information, determine the matching score for each candidate robot to perform the delivery task.

[0032] S204, Based on the matching score, determine the target robot among the candidate robots so that the target robot can perform the delivery task.

[0033] Specifically, determining the delivery task based on the loading information of the target cargo hold refers to determining the specific content and objectives of the delivery task based on the characteristics and requirements of the goods to be transported in the cargo hold. The loading information includes a detailed description of the goods to be transported in the target cargo hold. This may include the type, quantity, weight, and special requirements of the goods. The loading information may also include the destination or recipient information of the goods to determine which location or target location the goods need to be delivered to.

[0034] Based on the loading information of the target cargo hold, the delivery task needs to be planned and defined. The starting location of the goods must be determined, i.e., the outdoor vehicle, storage area, or other location where the goods are located. The weight and other special requirements of the goods need to be considered to plan a suitable route for transportation. This may involve avoiding obstacles and choosing appropriate paths to minimize time and resource consumption. The time requirements of the delivery task also need to be determined, including the start time and delivery deadline. This helps ensure that the goods can be delivered to the target location on time. Based on the scale and requirements of the delivery task, the required resources need to be determined, such as the number of robots or other auxiliary equipment needed. Once the delivery task is determined, the task information needs to be communicated to the robots. Simultaneously, the task information may also need to be transmitted to the robot's control system or scheduling system so that the robot can perform the delivery operation according to the task requirements.

[0035] Determining the status information of each candidate robot is crucial in a cargo compartment allocation method based on shuttle robots. By obtaining the status information of the candidate robots, their current availability and operational status can be understood. For example, a robot's operational status can include whether it is performing other tasks, whether it needs charging or maintenance, etc. This ensures that only robots that are in a usable state and can immediately begin delivery tasks are selected.

[0036] Robot location information is crucial for cargo hold allocation and task execution. By obtaining the robot's current location, the robot closest to the target cargo hold and location can be identified, improving delivery efficiency and reducing transit time. Understanding the robot's battery level is also essential for effective cargo hold allocation and task execution. Robots consume energy to perform delivery tasks, so their battery status must be considered to ensure they have sufficient power to complete the mission. Furthermore, based on the robot's battery information, the energy consumption required for task execution can be estimated, and energy consumption factors can be taken into account to optimize cargo hold allocation.

[0037] Based on the robot's status information, the time required for the robot to complete the delivery task can be predicted. This helps in planning task scheduling and delivery routes to minimize overall delivery time. In summary, determining the status information of each candidate robot provides key data and metrics for optimizing cargo hold allocation and task execution. By comprehensively considering factors such as robot availability, location, battery power, and task prediction, the most suitable robot can be selected to perform the delivery task, improving efficiency, accuracy, and reliability.

[0038] Furthermore, determining the matching score for each candidate robot to perform the delivery task based on the delivery task and status information is to evaluate the degree of matching between the robot and the delivery task, so as to select the most suitable robot to perform the task. Based on the requirements of the delivery task and the robot's status information, the energy consumption required for each candidate robot to perform the delivery task is calculated. By estimating the energy consumption, the power consumption required by the robot to perform the task can be assessed.

[0039] Based on the timeliness requirements of the delivery task and the robot's status information, the time required for each candidate robot to complete the delivery task is predicted. This includes considering factors such as the robot's current position, speed, and workload. Time estimation allows for an assessment of whether the robot can complete the task within the specified timeframe. Taking into account the robot's status information, such as battery level, location, and operational status, the resource utilization during delivery task execution is evaluated. This may include considering the robot's current battery status and the energy consumption required for the task, the matching degree between the robot's location and the delivery route, and the compatibility of the robot's operational status with the task requirements.

[0040] Based on the above considerations, a matching score can be calculated using the delivery task and the robot's status information. The matching score is a quantitative evaluation metric that reflects the degree of matching between the robot and the delivery task. A higher matching score indicates that the robot is more suitable for performing the task, while a lower matching score indicates a lower degree of matching.

[0041] The target robot is determined from among the candidate robots based on the matching score in order to select the most suitable robot to perform the delivery task. The candidate robots are sorted or ranked according to their calculated matching scores. The robots are sorted from highest to lowest matching score to more easily determine the most suitable robot for the delivery task. Based on the sorted matching scores, the robot with the highest matching score is selected as the target robot. The highest-scoring robot represents the robot that best matches the requirements of the delivery task and the robot's state information, possessing the highest execution capability and adaptability.

[0042] In some cases, a threshold can be set for the matching score to filter out robots that meet the requirements. Only robots whose matching score exceeds or equals the set threshold are considered suitable target robots. This further ensures that the selected robots have high adaptability and performance.

[0043] By determining the target robot based on matching scores, it is ensured that delivery tasks are assigned to the most suitable robot to maximize delivery efficiency, accuracy, and reliability. This process comprehensively considers the requirements of the delivery task and the status information of each candidate robot to select the best robot to perform the task, thereby optimizing the performance of the entire delivery system.

[0044] According to the technical solution provided in this application, a delivery task is determined based on the loading information of the target cargo hold; the status information of each candidate robot is determined; based on the delivery task and status information, a matching score is determined for each candidate robot to perform the delivery task; and based on the matching score, a target robot is determined among the candidate robots so that the target robot can perform the delivery task. This application embodiment performs pairing and scoring based on the loading information of the target cargo hold and the status information of the robots, thereby determining the target robot for transporting the target cargo hold, thus improving the stability and efficiency of the transportation process.

[0045] In some embodiments, determining a delivery task based on the loading information of the target cargo hold includes: determining the loading information of the target cargo hold; the loading information includes the delivery time, cargo weight, cargo location, and target location of the target cargo hold; determining a delivery route based on the cargo location, target location, and a pre-established environmental map; determining the load energy consumption required to transport the target cargo hold from its location to its target location based on the delivery route, delivery time, and cargo weight; and determining the delivery task based on the delivery route, delivery time, and load energy consumption.

[0046] Specifically, determining delivery tasks based on the target cargo hold's loading information is crucial for ensuring the efficiency and accuracy of the delivery process. First, it's necessary to determine the target cargo hold's loading information, including delivery time, cargo hold weight, cargo hold location, and target location. This information forms the basis for determining delivery tasks, as it determines the urgency of the task, the required transport capacity, and the origin and destination locations of the goods.

[0047] Based on the cargo hold location, target location, and a pre-established environmental map, determine the optimal delivery route. This may involve considering factors such as obstacles, traffic conditions, and road networks on the map to determine the best path to transport the target cargo hold. Optimized delivery routes can reduce time and energy consumption and improve overall efficiency.

[0048] Based on the determined delivery route, delivery time, and cargo weight, calculate the load energy consumption required to transport the target cargo from its current location to its destination. This involves considering the robot's travel distance along the route, the impact of load on energy consumption, and the time constraints of the delivery task. By calculating load energy consumption, the required resources and the robot's ability to perform the task can be assessed.

[0049] Furthermore, by combining delivery routes, delivery timelines, and payload energy consumption, specific delivery tasks are determined. This includes determining when and where the robot needs to pick up the target cargo hold, along which route, and when and where to deliver the cargo hold to the target location. The goal of determining the delivery tasks is to ensure that the cargo hold arrives at the target location on time, meets delivery timeline requirements, and guarantees the rational use of resources and energy.

[0050] In some embodiments, the method further includes: predicting the delivery time required for the shuttle robot to complete the delivery task based on the current location, current working status, cargo hold location, and target location of the shuttle robot; determining the delivery energy consumption required for the shuttle robot to complete the delivery task based on the current location, current working status, cargo hold location, and load energy consumption of the shuttle robot; and determining the shuttle robot as a candidate robot when the delivery time is less than the delivery timeliness and the current battery power of the shuttle robot is greater than the delivery energy consumption.

[0051] Specifically, after determining the delivery task, further evaluation is needed based on the current status information of the shuttle robot to determine the candidate robot. Delivery time can be predicted based on factors such as the shuttle robot's current location, current working status, cargo hold location, and target location. This involves estimating the time required for the shuttle robot to complete the delivery task based on information such as its moving speed, route distance, and traffic conditions. By predicting delivery time, tasks and resources can be better allocated to meet delivery timeliness requirements.

[0052] Based on factors such as the current location, operational status, cargo hold location, and load energy consumption of the shuttle robot, the delivery energy consumption required to complete the delivery task can be determined. This includes the energy consumption of the shuttle robot during the delivery process, such as battery energy and fuel consumption. By calculating the delivery energy consumption, the energy status of the shuttle robot can be assessed, ensuring that the shuttle robot has sufficient energy to complete the delivery task.

[0053] Furthermore, when the delivery time is less than the delivery efficiency, and the current battery level of the shuttle robot is greater than the delivery energy consumption, the shuttle robot can be identified as a candidate robot. This means that the robot has sufficient time and energy to perform the delivery task and meet the requirements for task completion. Through this judgment, suitable robots can be selected for delivery tasks, improving the reliability and efficiency of the task.

[0054] In summary, based on information such as the current location, current working status, cargo compartment location, and target location of the shuttle robot, delivery time and energy consumption can be predicted, thereby selecting suitable candidate robots. This allows for better matching of robots with delivery tasks, improving delivery accuracy and efficiency, and ensuring that the robot has sufficient power and time to complete the task.

[0055] In some embodiments, the status information includes power information, robot position, and working status; determining the matching score for each candidate robot to perform the delivery task based on the delivery task and status information includes: determining the delivery energy consumption required for the candidate robot to complete the delivery task based on the robot position, working status, cargo compartment position, and load energy consumption; determining a first reference score corresponding to the delivery energy consumption; determining the remaining power of the candidate robot after completing the delivery task based on the power information and delivery energy consumption; determining a second reference score corresponding to the remaining power; and determining a matching score based on the first reference score and the second reference score.

[0056] Specifically, when determining the matching score for each candidate robot to perform the delivery task, the robot's status information needs to be considered, including battery level, robot position, and operating status. Based on factors such as robot position, operating status, cargo compartment position, and load energy consumption, the delivery energy consumption required for the candidate robot to complete the delivery task can be determined. This involves the amount of energy consumed by the robot when performing the task, such as movement energy consumption and power consumption during operation. By calculating the delivery energy consumption, the energy expenditure of the robot performing the task can be evaluated.

[0057] Based on delivery energy consumption, a corresponding first reference score can be determined. This reference score is used to measure the energy expenditure required for the candidate robot to perform the delivery task. Generally, robots with lower energy consumption will receive a higher first reference score, indicating that they are more efficient in energy use.

[0058] Furthermore, based on the robot's battery information and delivery energy consumption, the remaining battery power of the candidate robot after completing the delivery task can be determined. This involves assessing the balance between the robot's energy consumption and power supply during task execution. By calculating the remaining battery power, the robot's battery status after the task is completed can be understood.

[0059] Based on the remaining battery power, a corresponding second reference score can be determined. This reference score is used to measure the remaining battery power of the candidate robot after it performs the delivery task. Generally, robots with higher remaining battery power will receive a higher second reference score, indicating that they have more sufficient power reserves after completing the task.

[0060] A matching score is determined based on a first reference score and a second reference score. This score is used to compare the suitability between different candidate robots. A higher matching score means that the robot meets the requirements of the delivery task in terms of energy consumption and battery life, and is therefore more suitable for performing the task. By comprehensively considering the robot's status information and the requirements of the delivery task, determining the matching score helps to select the most suitable candidate robot to perform the delivery task. This improves the efficiency and reliability of delivery and ensures that the robot can complete the task with sufficient battery power.

[0061] In some embodiments, when the number of target cargo holds is one, determining the target robot among the candidate robots based on the matching score includes: sorting the matching scores; and determining the target robot from the candidate robots based on the score sort.

[0062] Specifically, when there is only one target cargo hold, the target robot is determined based on the matching score. The matching scores of each candidate robot are sorted to compare their suitability. This allows the robots to be ranked according to their matching scores, from the most suitable robot to the least suitable robot.

[0063] Based on the ranked matching scores, the robot with the highest score is selected as the target robot. This means that this robot best meets the requirements and conditions of the delivery task among all the candidate robots. By selecting the robot with the highest matching score, the efficiency and success rate of the delivery task can be improved.

[0064] By sorting candidate robots according to their matching scores, the most suitable robot can be prioritized for delivery tasks. The highest-ranked robot typically exhibits better adaptability and matching accuracy, making it the first choice for delivery. This method ensures that when there is only one target cargo hold, the most suitable robot is selected to perform the task. Ranking by matching scores allows for quick and reliable identification of the target robot, thereby improving delivery efficiency and accuracy.

[0065] In some embodiments, when the number of target cargo compartments is greater than one, determining the target robot among the candidate robots based on the matching score includes: determining the matching score between each target cargo compartment and each candidate robot; determining the priority of each target cargo compartment; and determining the target robot corresponding to each target cargo compartment based on the matching score and priority.

[0066] Specifically, when there is more than one target cargo hold, the target robot needs to be determined from among the candidate robots based on the matching score. This ensures optimal task allocation among multiple target cargo holds and multiple candidate robots. By selecting the target robot based on the matching score, it ensures that each cargo hold is assigned to the most suitable robot, thereby maximizing overall delivery efficiency.

[0067] For each combination of target cargo hold and candidate robot, a matching score is calculated. This matching score can be based on various factors, such as the distance between the robot and the cargo hold, the robot's adaptability, the cargo hold's priority, and so on. By calculating the matching score for each combination, the degree of matching between the target cargo hold and the candidate robot is obtained. The matching score reflects the degree of matching between the candidate robot and the target cargo hold. By using the matching score, the robot that best matches the target cargo hold can be selected. This ensures that the robot has the ability to adapt to the requirements of the target cargo hold, thereby improving the accuracy and reliability of task completion.

[0068] Furthermore, before identifying the target robot, the priority of each target cargo compartment needs to be determined. Different cargo compartments may have different levels of urgency or importance. By combining matching scores and priorities, delivery tasks for high-priority cargo compartments can be prioritized to ensure that important or urgent goods can be delivered in a timely manner.

[0069] The target robot for each target cargo hold is determined by combining its priority with its matching score against candidate robots. This decision is made by comparing the matching scores of various combinations with the cargo hold priorities. Typically, combinations with higher priorities and higher matching scores are selected first.

[0070] By considering matching scores and priorities, it can be ensured that when there are more than one target cargo hold, the most suitable robot is selected to perform the delivery task for each cargo hold. The purpose of determining the target robot from among the candidate robots based on matching scores is to achieve optimal task allocation, improve delivery efficiency, ensure matching accuracy and adaptability, and consider factors such as priority and resource balance. This maximizes the satisfaction of the needs of multiple target cargo holds and optimizes the delivery process.

[0071] In some embodiments, determining the priority of each target cargo hold includes: determining the corresponding quantity between each target cargo hold and each candidate machine; and determining the priority of each target cargo hold based on the corresponding quantity.

[0072] Specifically, the purpose of prioritizing each target cargo hold is to rationally allocate robot resources based on the urgency, importance, or other priority criteria of the task. By prioritizing resources for the target cargo holds with a larger number of corresponding targets, more robots can be deployed to important or urgent delivery tasks, improving delivery efficiency and meeting task requirements.

[0073] Based on the delivery task requirements and the capabilities of the candidate robots, the matching relationship between each target cargo hold and each candidate robot is evaluated. This can be achieved by calculating a matching score for each target cargo hold and each candidate robot. For each target cargo hold, the number of candidate robots associated with it is recorded.

[0074] By analyzing the corresponding quantities of target cargo compartments and candidate robots, the priority of each target cargo compartment is determined. Generally, target cargo compartments with fewer corresponding quantities are considered higher priority because these cargo compartments require specific types of robots or robots with specific capabilities to complete the delivery task. Since the number of such robots may be limited, or only a few robots may possess the required capabilities, target cargo compartments with fewer corresponding quantities are considered higher priority. Conversely, target cargo compartments with more corresponding quantities may be considered lower priority.

[0075] Priority determination can be adjusted based on specific business rules and needs. In certain special cases, in addition to the corresponding quantity, other factors such as the urgency, value, or other priority criteria of the goods can be considered to adjust the priority ranking of target cargo holds. Therefore, priority determination can be flexibly adjusted according to specific circumstances to meet the needs of a particular delivery system.

[0076] All of the above-mentioned optional technical solutions can be combined in any way to form the optional embodiments of this application, and will not be described in detail here.

[0077] The following are embodiments of the apparatus described in this application, which can be used to execute the embodiments of the method described in this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the method described in this application.

[0078] Figure 3 This is a schematic diagram of a cargo hold distribution device based on a shuttle robot, provided in an embodiment of this application. Figure 3 As shown, the cargo compartment distribution device based on the shuttle robot includes:

[0079] The delivery task determination module 301 is configured to determine the delivery task based on the loading information of the target cargo hold;

[0080] The status information determination module 302 is configured to determine the status information of each candidate robot;

[0081] The matching score determination module 303 is configured to determine the matching score for each candidate robot to perform the delivery task based on the delivery task and status information.

[0082] The execution module 304 is configured to determine the target robot among the candidate robots based on the matching score, so that the target robot can perform the delivery task.

[0083] In some embodiments, Figure 3 The delivery task determination module 301 determines the loading information of the target cargo hold; the loading information includes the delivery time, cargo hold weight, cargo hold location and target location of the target cargo hold; the delivery route is determined based on the cargo hold location, target location and pre-established environmental map; the load energy consumption required to transport the target cargo hold from the cargo hold location to the target location is determined based on the delivery route, delivery time and cargo hold weight; the delivery task is determined based on the delivery route, delivery time and load energy consumption.

[0084] In some embodiments, Figure 3 The matching score determination module 303 determines the delivery energy consumption required for the candidate robot to complete the delivery task based on the robot's position, working status, cargo compartment position, and load energy consumption; determines the first reference score corresponding to the delivery energy consumption; determines the remaining power of the candidate robot after completing the delivery task based on the power information and delivery energy consumption; determines the second reference score corresponding to the remaining power; and determines the matching score based on the first reference score and the second reference score.

[0085] In some embodiments, Figure 3 The execution module 304 sorts the matching scores; based on the score sorting, it determines the target robot from the candidate robots.

[0086] In some embodiments, Figure 3 The execution module 304 determines the matching score between each target cargo compartment and each candidate robot; determines the priority of each target cargo compartment; and determines the target robot corresponding to each target cargo compartment based on the matching score and priority.

[0087] In some embodiments, Figure 3 The execution module 304 determines the corresponding quantity between each target cargo hold and each candidate machine; and determines the priority of each target cargo hold based on the corresponding quantity.

[0088] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0089] Figure 4 This is a schematic diagram of the electronic device 4 provided in an embodiment of this application. Figure 4 As shown, the electronic device 4 of this embodiment includes: a processor 401, a memory 402, and a computer program 403 stored in the memory 402 and executable on the processor 401. When the processor 401 executes the computer program 403, it implements the steps in the various method embodiments described above. Alternatively, when the processor 401 executes the computer program 403, it implements the functions of each module / unit in the various device embodiments described above.

[0090] Electronic device 4 can be a desktop computer, laptop, handheld computer, cloud server, or other electronic device. Electronic device 4 may include, but is not limited to, processor 401 and memory 402. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 4 and does not constitute a limitation on electronic device 4. It may include more or fewer components than shown, or different components.

[0091] The processor 401 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0092] The memory 402 can be an internal storage unit of the electronic device 4, such as a hard disk or RAM of the electronic device 4. The memory 402 can also be an external storage device of the electronic device 4, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc., equipped on the electronic device 4. The memory 402 can also include both internal and external storage units of the electronic device 4. The memory 402 is used to store computer programs and other programs and data required by the electronic device.

[0093] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0094] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program may include computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium may include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium may be appropriately added to or subtracted according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0095] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A cargo hold allocation method based on a shuttle robot, characterized in that, The method is applied to an allocation system, and the method includes: The delivery task is determined based on the loading information of the target cargo hold; Determine the status information of each candidate robot; Based on the delivery task and the status information, determine the matching score for each candidate robot to perform the delivery task; Based on the matching score, a target robot is determined from the candidate robots so that the target robot can perform the delivery task. The process of determining the delivery task based on the loading information of the target cargo hold includes: Determine the loading information of the target cargo hold; the loading information includes the delivery time, cargo hold weight, cargo hold location, and target location of the target cargo hold; The delivery route is determined based on the cargo hold location, the target location, and the pre-established environmental map; Based on the delivery route, the delivery time, and the cargo hold weight, determine the load energy consumption required to transport the target cargo hold from the cargo hold location to the target location; The delivery task is determined based on the delivery route, the delivery time, and the load energy consumption; Also includes: Based on the current location of the shuttle robot, its current working status, the location of the cargo hold, and the target location, the delivery time required for the shuttle robot to complete the delivery task is predicted. Based on the current location of the shuttle robot, the current working status, the cargo hold location, and the load energy consumption, determine the delivery energy consumption required for the shuttle robot to complete the delivery task; When the delivery time is less than the delivery efficiency and the current battery level of the shuttle robot is greater than the delivery energy consumption, the shuttle robot is determined to be the candidate robot. The status information includes battery level, robot location, and operating status; determining the matching score for each candidate robot to perform the delivery task based on the delivery task and the status information includes: Based on the robot's position, its working status, the cargo hold's position, and the load energy consumption, the delivery energy consumption required for the candidate robot to complete the delivery task is determined. Determine the first reference score corresponding to the delivery energy consumption; The remaining battery power of the candidate robot after completing the delivery task is determined based on the battery information and the delivery energy consumption. Determine the second reference score corresponding to the remaining battery power; The matching score is determined based on the first reference score and the second reference score; When the number of target cargo holds is one; determining the target robot from the candidate robots based on the matching score includes: Sort the matching scores; The target robot is determined from the candidate robots based on the scores. When the number of target cargo holds is greater than one; determining the target robot from the candidate robots based on the matching score includes: Determine the matching score between each target cargo hold and each candidate robot; Determine the priority of each target cargo hold; Based on the matching score and the priority, the target robot corresponding to each target cargo compartment is determined.

2. The method according to claim 1, characterized in that, The process of determining the priority of each target cargo hold includes: Determine the corresponding quantity between each target cargo hold and each candidate machine; The priority of each target cargo hold is determined based on the corresponding quantity.

3. A cargo compartment distribution device based on a shuttle robot, characterized in that, The apparatus employs the method according to any one of claims 1-2, and the apparatus comprises: The delivery task determination module is configured to determine the delivery task based on the loading information of the target cargo hold; The status information determination module is configured to determine the status information of each candidate robot; The matching score determination module is configured to determine the matching score of each candidate robot for performing the delivery task based on the delivery task and the status information; An execution module is configured to determine a target robot among the candidate robots based on the matching score, so that the target robot performs the delivery task.

4. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 2.

5. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 2.

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