Automated delivery methods and devices for robots

Abstract

This application discloses an automated delivery method and apparatus for robots. The method includes: acquiring the start and end points of a delivery task to plan a target path; controlling the robot to start moving and calculating a target communication base station and a target computing power base station based on the robot's position and the target path; requesting a corresponding intelligent model through the target communication base station based on the functional requirements of the delivery task; the intelligent model acquiring and analyzing the robot's environmental and state information through the target computing power base station and the target communication base station to obtain analysis results; and controlling the robot to travel to the destination based on the analysis results of the artificial intelligence model. This application's technical solution enables robots to complete long-distance delivery along relatively complex paths.

Description

Technical Field

[0001] This application belongs to the field of data communication, and specifically relates to an automated delivery method and apparatus for robots. Background Technology

[0002] With the development and progress of the times, the automated delivery function of robots is becoming increasingly sophisticated, enabling automated delivery and transportation. However, during delivery, automated robots face limitations due to their limited computing power and relatively limited network interface options. This can lead to their inability to handle complex situations encountered along the way. Furthermore, the limited network interface options can result in insufficient computing power or poor signal strength, preventing the robot from successfully completing its delivery tasks.

[0003] Therefore, how to enable robots to complete long-distance delivery along complex routes is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] The purpose of this application is to enable robots to complete long-distance deliveries along relatively complex routes.

[0005] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0006] According to one aspect of the embodiments of this application, an automated delivery method using a robot is provided, the method comprising:

[0007] Obtain the origin and destination of the delivery task to plan the target route;

[0008] Control the robot to start moving, and determine the target communication base station and target computing power base station based on the robot's position and the target path;

[0009] Based on the functional requirements of the delivery task, request the corresponding intelligent model through the target communication base station;

[0010] The intelligent model obtains and analyzes the robot's environmental and status information through the target computing base station and the target communication base station to obtain analysis results;

[0011] Based on the analysis results of the intelligent model, the robot is controlled to travel until the destination.

[0012] According to one aspect of the embodiments of this application, determining a target communication base station and a target computing power base station based on the robot's position and the target path includes:

[0013] Based on the robot's location and the target path, determine the target communication base station for the section of road the robot will travel, and reserve communication resources accordingly.

[0014] Based on the predicted communication delay between the target communication base station and the robot, the target computing base station corresponding to the target communication base station is determined, and computing resources are reserved.

[0015] According to one aspect of the embodiments of this application, determining the target communication base station for the section of road the robot will travel on, based on the robot's position and the target path, includes:

[0016] When the robot senses that the signal of the target communication base station it is currently using reaches a set threshold, the robot's first position is obtained.

[0017] In the target path, determine the position at a first set distance from the first position as the second position;

[0018] Centered on the second location, a communication base station within a second predetermined distance range is selected as the initial communication base station;

[0019] The initial communication base station with the largest communication resources among the initial communication base stations is selected as the target communication base station.

[0020] According to one aspect of the embodiments of this application, determining the target computing power base station corresponding to the target communication base station based on the predicted communication delay between the target communication base station and the robot includes:

[0021] Based on the parameter information of the computing base station and the difficulty of the delivery task, the computing latency of the computing base station is calculated and used as the first latency.

[0022] Based on the distance between each target communication base station and the target planned path, the communication delay between the target communication base station and the robot is predicted as a second delay;

[0023] The difference between the standard delay and the first and second delays is taken as the third delay. The computing power base station whose communication delay with the target communication base station is less than the third delay is taken as the target computing power base station corresponding to the target communication base station.

[0024] According to one aspect of the embodiments of this application, the method further includes:

[0025] During the robot's movement, the signals of the current target communication base station and the next target communication base station are monitored as a first signal and a second signal, respectively, and the robot communicates via the current target communication base station.

[0026] When the ratio of the first signal to the second signal is less than a set ratio threshold, the next target communication base station is used as the current target communication base station to ensure smooth communication for the robot.

[0027] According to one aspect of the embodiments of this application, requesting a corresponding intelligent model through the target communication base station based on the functional requirements information of the delivery task includes:

[0028] Based on the functional requirements of the delivery task, determine the delivery functions required to complete the delivery task;

[0029] Based on the external functions in the delivery function, a smart model with corresponding external functions is requested through the target communication base station and transmitted to the target computing power base station;

[0030] Based on the built-in functions in the delivery function, when a smart model is requested for the first time through the target communication base station, a smart model with the corresponding built-in functions is transmitted to the robot.

[0031] According to one aspect of the embodiments of this application, the intelligent model acquires and analyzes the environmental information and state information of the robot through the target computing power base station and the target communication base station, and obtains analysis results, including:

[0032] The robot's state information and environmental information are acquired, and the built-in function is used to perform built-in analysis on the state information and environmental information to obtain the built-in analysis results.

[0033] The status information, environmental information, and built-in analysis results are sent to the target computing power base station via the target communication base station.

[0034] The intelligent model in the target computing base station analyzes the driving status information and environmental information to obtain external analysis results;

[0035] If the external analysis result and the internal analysis result are the same, then the internal analysis result shall be used as the analysis result;

[0036] If the external analysis result and the internal analysis result are different, the external analysis result shall be used as the analysis result, and the parameters of the intelligent model set on the target computing power node shall be sent to the robot to update the parameters of the robot's internal intelligent model.

[0037] According to one aspect of the embodiments of this application, the method further includes:

[0038] If the signal of the target communication base station is unstable, the bandwidth allocation of the target communication base station to the delivery task will be increased and / or the corresponding communication task will be moved forward in the task queue.

[0039] According to one aspect of the embodiments of this application, the communication base station includes: a 3GPP base station and a non-3GPP base station.

[0040] According to one aspect of the embodiments of this application, this application provides an automated delivery device for a robot, comprising:

[0041] The business management module is used to determine the target route of the delivery task based on the start and end points of the delivery task, and to determine the target communication base station and the target computing power base station.

[0042] The model management module provides intelligent models for various delivery functions and can install these intelligent models on target computing base stations and robots via target communication base stations.

[0043] The resource scheduling module, located within the target computing base station, is used to calculate the external analysis results based on the robot's state information and environmental information, and to compare the built-in analysis results with the external analysis results; it is also used to balance the communication resources of the target communication base station when the network of the target communication base station is not smooth, so as to ensure that the first delay and the third delay do not increase.

[0044] The data management module receives and sends data between the robot and the target computing base station, and stores the data.

[0045] In the technical solution provided in this application embodiment, the starting point and ending point of the delivery task are first obtained to plan the target path; the robot is controlled to start moving, and the target communication base station and target computing power base station are calculated based on the robot's position and the target path; according to the functional requirements information of the delivery task, the corresponding intelligent model is requested through the target communication base station; the intelligent model obtains and analyzes the robot's environmental and status information through the target computing power base station and the target communication base station to obtain the analysis results; based on the analysis results of the artificial intelligence model, the robot is controlled to travel until the destination. In this application, determining multiple target communication base stations through the target path enables the robot to maintain smooth communication and gives the robot the ability to travel long distances. By peripheralizing the target computing power base station, the computing power that the robot can use is greatly increased, enabling it to cope with various complex road conditions.

[0046] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.

[0047] It should be understood that the above general description and the following detailed description are exemplary and illustrative only, and should not be construed as invalidating this application. Attached Figure Description

[0048] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0049] Figure 1 A flowchart of an automated delivery method using a robot according to an embodiment of this application is shown.

[0050] Figure 2 A flowchart illustrating the determination of a target communication base station and a target computing base station based on the robot's position and target path according to an embodiment of this application is shown.

[0051] Figure 3 A flowchart illustrating a method for determining a target communication base station for a section of road the robot will travel, based on the robot's location and target path, according to one embodiment of this application, is shown.

[0052] Figure 4 A flowchart illustrating a method for determining a target computing base station corresponding to a target communication base station based on a predicted communication delay between the target communication base station and the robot, according to an embodiment of this application, is shown.

[0053] Figure 5 A flowchart illustrating a robot changing its currently used target communication base station according to an embodiment of this application is shown.

[0054] Figure 6 A flowchart illustrating a method for requesting a corresponding intelligent model via a target communication base station based on functional requirements information of a delivery task, according to one embodiment of this application, is shown.

[0055] Figure 7 The flowchart illustrates an embodiment of the present application showing how an intelligent model acquires and analyzes environmental and state information of a robot through a target computing base station and a target communication base station to obtain analysis results.

[0056] Figure 8 A computer system architecture block diagram for implementing an automated delivery method for robots according to an embodiment of this application is shown. Detailed Implementation

[0057] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.

[0058] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.

[0059] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0060] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0061] In this application embodiment, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0062] Please see Figure 1 , Figure 1 A flowchart of an automated delivery method using a robot according to an embodiment of this application is shown. This application provides the steps of an automated delivery method using a robot, including:

[0063] Step S110: Obtain the start and end points of the delivery task to plan the target route;

[0064] Step S120: Control the robot to start moving, and determine the target communication base station and target computing power base station based on the robot's position and target path;

[0065] Step S130: Based on the functional requirements of the delivery task, request the corresponding intelligent model through the target communication base station;

[0066] Step S140: The artificial intelligence model obtains and analyzes the robot's environmental and status information through the target computing base station and the target communication base station, and obtains the analysis results.

[0067] Step S150: Based on the analysis results of the artificial intelligence model, control the robot to travel to the destination.

[0068] The above five steps are described in detail below.

[0069] In step S110, the starting point and ending point of the delivery task are obtained, and the target route is planned.

[0070] In some embodiments, the shortest path between the origin and destination of the delivery task is used as the target path.

[0071] In some embodiments, each path between the origin and destination of the delivery task is obtained as a candidate path. If there is only one candidate path, then the candidate path is directly used as the target path.

[0072] If there are multiple alternative paths, predict the transit time of each alternative path and select the alternative path with the shortest transit time as the target path.

[0073] In step S120, the robot is controlled to start moving, and the target communication base station and target computing base station are determined according to the robot's position and target path.

[0074] In this embodiment, the target communication base station is gradually identified as the robot moves along the target path. This ensures that the robot receives continuous support from the target communication base station along the target path, maintaining a strong communication signal and guaranteeing that the robot can consistently upload its status and environmental information and receive timely feedback. Support is also readily available even in complex environments.

[0075] Then, based on the target communication base station, the corresponding target computing base station is determined. The target computing base station provides computing power support to the robot through the target communication base station, in conjunction with a good target communication signal. This allows the robot to receive instructions quickly throughout its journey along the target path, enabling it to cope with various complex environments.

[0076] Through multi-target communication base stations and "computing peripherals", the robot can fully cope with both long paths and target paths with complex environments.

[0077] In one embodiment of this application, the communication base station includes: a 3GPP base station and a non-3GPP base station. A base station refers to a base station using the 3GPP plan. A non-3GPP base station refers to a base station not using the 3GPP plan. The goal of 3GPP (3rd Generation Partnership Project) is to achieve a smooth transition from 2G networks to 3G networks, ensure backward compatibility of future technologies, and support easy network deployment and roaming and compatibility between systems. Its functions include: 3GPP primarily develops specifications for third-generation technologies based on the GSM core network and using UTRA (FDD for W-CDMA technology, TDD for TD-SCDMA technology) as the radio interface.

[0078] In this embodiment, both 3GPP and non-3GPP base stations can be used simultaneously, providing the robot with more communication access options and further ensuring the robot's communication reliability.

[0079] Please see Figure 2 , Figure 2 A flowchart illustrating the process of determining a target communication base station and a target computing base station based on the robot's position and target path according to an embodiment of this application is shown. This embodiment provides step S120 for determining the target communication base station and target computing base station based on the robot's position and target path, including...

[0080] Step S121: Based on the robot's location and target path, determine the target communication base station for the section of road the robot will travel, and reserve communication resources.

[0081] Step S122: Based on the predicted communication delay between the target communication base station and the robot, determine the target computing power base station corresponding to the target communication base station and reserve computing power resources.

[0082] The two steps described above are described in detail below.

[0083] In step S121, based on the robot's location and target path, the target communication base station for the section of road the robot will travel is determined, and communication resources are reserved.

[0084] In some embodiments, the target road segment is divided into several segments. For each segment, the nearest communication base station that can completely cover that segment is selected as the initial communication base station. The initial communication base station with the most communication resources is selected as the target communication base station. It should be noted that communication resources include the allocatable bandwidth of the communication base station (more allocatable bandwidth indicates more communication resources) and the number of tasks in the task queue (a smaller number of tasks in the task queue indicates more communication resources for the communication base station).

[0085] After identifying the target communication base stations, predict the time periods during which the robot will use each target communication base station, and reserve communication resources for the time periods during which the target communication base stations will be used, so as to avoid communication disruptions due to insufficient communication resources when using the target communication base stations.

[0086] Please see Figure 3 , Figure 3 A flowchart illustrating the process of determining a target communication base station for a route segment to be traveled by a robot based on the robot's position and target path, according to an embodiment of this application, is shown. This embodiment provides step S121, which involves determining the target communication base station for a route segment to be traveled by a robot based on the robot's position and target path, including:

[0087] Step S201: When the robot senses that the signal of the target communication base station being used has reached a set threshold, the robot's first position is obtained.

[0088] Step S202: Determine the second position as the position on the target path that is a first set distance away from the first position;

[0089] Step S203: Using the second location as the center, the communication base station within the second set distance range is taken as the initial communication base station;

[0090] Step S204: Select the initial communication base station with the largest communication resources from the initial communication base stations as the target communication base station.

[0091] The above four steps are described in detail below.

[0092] In step S201, when the robot starts moving, a target communication base station is first determined based on the starting location of the delivery task. Specifically, based on the starting location of the delivery task, several communication base stations that can cover the starting location of the delivery task are determined as initial communication base stations. Among the multiple initial communication base stations, the one with the most communication resources is selected as the target communication base station to be used.

[0093] Then, when the robot senses that the signal from the currently used target communication base station has reached a set threshold, it obtains its first position. That is, once the signal from the currently used target communication base station reaches the set threshold, it needs to begin preparing to determine the next target communication base station.

[0094] In some embodiments, a threshold is set as the peak range that the currently used target communication base station can reach for the robot. This allows the next target communication base station to be determined in advance when the robot's signal is strongest, and the target communication base station can be switched in a timely manner when the robot's signal is weak, without leaving a communication gap.

[0095] In step S202, the position at a first set distance from the first position in the target path is determined as the second position. It should be noted that the first set distance can be adjusted according to the user's needs.

[0096] In step S203, with the second location as the center, the communication base station within the second set distance range is taken as the initial communication base station;

[0097] It needs to be further clarified that, in some embodiments, the signal coverage of the initial communication base station should be able to cover the road segment between the first location and the second location.

[0098] In step S204, the initial communication base station with the largest communication resources is selected as the target communication base station from the initial communication base stations.

[0099] In some embodiments, the signal strength of the next target communication base station at the first location is less than the product of a set threshold and a set coefficient. The set coefficient is a decimal between 0 and 1. This is to avoid the next target communication base station being too close to the currently used target communication base station. If adjacent target communication base stations are too close, the number of target communication base stations required for the target path will increase significantly, resulting in excessive communication resource consumption and affecting other delivery tasks. Furthermore, it will cause the robot to frequently switch target communication base stations, affecting the robot's travel efficiency. Therefore, in this embodiment, the next target communication base station is determined in this way.

[0100] In some embodiments, the initial communication base station with the largest communication resources is selected as the target communication base station from the initial communication base stations, and the communication resources of the target communication base station must be greater than the communication resource threshold.

[0101] If no initial communication base station has communication resources exceeding the communication resource threshold, the first predetermined distance is reduced by a preset ratio, and a new initial communication base station is determined. This process continues until the next target communication base station is determined. It is important to note that once the next target communication base station is determined, the first predetermined distance is restored to its value before the first reduction, to facilitate the determination of the next target communication base station.

[0102] In this embodiment of the application, it can always be ensured that the signal coverage area between the target communication base stations can cover the robot, and that the communication resources of the target communication base stations are sufficient to complete the robot's communication.

[0103] In step S122, based on the predicted communication delay between the target communication base station and the robot, the target computing base station corresponding to the target communication base station is determined, and computing resources are reserved.

[0104] In some embodiments, after determining the target communication base station, taking one of the target communication base stations as an example, the target computing power base station corresponding to that target communication base station can be determined in the following way: First, obtain the location of the target communication base station. Based on the location of the target communication base station, predict the predicted communication delay between the target communication base station and the robot. Based on the predicted communication delay, determine the computing power base stations whose communication delay with the target base station is less than a set delay as initial computing power base stations. The predicted communication delay and the set delay are negatively correlated. Then, the top N initial computing power base stations with more computing power resources are selected as target computing power base stations. N is a positive integer.

[0105] Please see Figure 4 , Figure 4 A flowchart illustrating a method for determining a target computing base station corresponding to a target communication base station based on a predicted communication delay between the target communication base station and the robot, according to an embodiment of this application, is shown. This application embodiment provides step S122 for determining the target computing base station corresponding to a target communication base station based on a predicted communication delay between the target communication base station and the robot, including:

[0106] Step S301: Calculate the computing delay of the computing base station based on the parameter information of the computing base station and the difficulty of the delivery task, and use it as the first delay.

[0107] Step S302: Based on the distance between each target communication base station and the target planned path, predict the communication delay between the target communication base station and the robot as the second delay;

[0108] Step S303: The difference between the standard delay and the first delay and the second delay is taken as the third delay. The computing power base station whose communication delay with the target communication base station is less than the third delay is obtained and taken as the target computing power base station corresponding to the target communication base station.

[0109] The above three steps are described in detail below.

[0110] First, it's important to clarify that since the robot is constantly moving, it must be able to quickly upload its status and environmental information to the target computing base station, and the target computing base station must be able to quickly feed back the analysis results to the robot. To meet the robot's control requirements, the time taken for the above processes must be less than or equal to the standard latency.

[0111] Standard latency is mainly caused by three parts: first, the round-trip communication latency between the robot and the target communication base station; second, the computing power latency of the target computing base station in analyzing status and environmental information; and third, the round-trip communication latency between the target computing base station and the target communication base station.

[0112] Therefore, in order to meet the above criteria, the target computing power base station is determined in the following manner.

[0113] In step S301, the computational latency of the computing base station is calculated based on its parameter information and the difficulty of the delivery task, and is used as the first latency. It should be noted that the difficulty of the delivery task is determined by the difficulty of the target path and the number of required functions. The greater the difficulty of the delivery task, the greater the computation time required by the computing base station with the same computing power, i.e., the longer the computational latency.

[0114] In step S302, the communication delay between the target communication base station and the robot is predicted as a second delay based on the distance between each target communication base station and the target planned path. The communication delay between the target communication base station and the robot is calculated based on the distance from the target communication base station to the target path, and this second delay is also used.

[0115] In step S303, the difference between the standard delay and the first and second delays is taken as the third delay. That is, the standard delay is obtained by successively subtracting the first and second delays. The computing power base station whose communication delay with the target communication base station is less than the third delay is designated as the target computing power base station corresponding to the target communication base station. It should be noted that each target communication base station corresponds to at least one target computing power base station, and the target computing power base station interacts with the robot through its corresponding target communication base station.

[0116] In some implementations, each target communication base station corresponds to three target computing power base stations.

[0117] In some implementations, each target communication base station corresponds to a set number of target computing power base stations. Based on the computing power of each target computing power base station, a corresponding intelligent model is set up for each target computing power base station. For example, in descending order of computing power, each target communication base station corresponds to four target computing power base stations, namely A, B, C, and D. The delivery task corresponds to five intelligent models, namely 1, 2, 3, 4, and 5. Intelligent models 1 and 2 need to be set up on target computing power base station A. Intelligent model 3 needs to be set up on target computing power base station B, intelligent model 4 needs to be set up on target computing power base station C, and intelligent model 5 needs to be set up on target computing power base station D. This correspondence is applied to each target communication base station and its corresponding target computing power base station.

[0118] In this embodiment, by setting the intelligent model on different target computing power base stations, the pressure on each target computing power base station is reduced. This also shortens the computing power latency, resulting in a faster response speed for the target computing power base stations.

[0119] Please see Figure 5 , Figure 5 A flowchart illustrating a robot changing its currently used target communication base station according to an embodiment of this application is shown. This application embodiment provides steps for a flowchart of a robot changing its currently used target communication base station, including:

[0120] Step S401: During the robot's movement, the signals of the current target communication base station and the next target communication base station are monitored as the first signal and the second signal, respectively, and the robot communicates through the current target communication base station.

[0121] Step S402: When the ratio of the first signal and the second signal is detected to reach the set ratio threshold, the next target communication base station is used as the current communication base station to ensure smooth communication for the robot.

[0122] The two steps described above are described in detail below.

[0123] In step S401, during the robot's movement, the signals of the current target communication base station and the next target communication base station are monitored as the first signal and the second signal, respectively, and the robot communicates through the current target communication base station.

[0124] In step S402, when the ratio of the first signal to the second signal is detected to be less than a set ratio threshold, the next target communication base station is designated as the current target communication base station to ensure smooth communication for the robot. It is important to clarify that the ratio threshold is less than 1. That is, when the ratio of the first signal to the second signal is detected to be less than the set ratio threshold, the signal from the next target communication base station is better. To ensure the robot always has relatively smooth communication, when the next target communication base station can provide a better signal, it is directly designated as the current target communication base station, allowing the robot to communicate through the new current target communication base station.

[0125] In some embodiments, if the signal of the target communication base station is unstable, the bandwidth allocation of the target communication base station to the delivery task is increased and / or the corresponding communication task is moved up in the task queue.

[0126] In step S130, based on the functional requirements of the delivery task, the corresponding intelligent model is requested through the target communication base station. It's important to note that different delivery tasks have different functional requirements. For example, during holidays, a greeting function might be needed. In a delivery task in Chongqing, due to the city's many steps and slopes, the robot needs to be configured with corresponding recognition functions to specifically identify slopes and steps. Different movement methods are used for different terrains. For better "uphill" and "downhill" movement, corresponding "climbing control functions" and "downhill control functions" are configured. This may involve calculating parameters such as the robot's driving power and climbing speed based on the slope.

[0127] In some embodiments, the delivery function includes visual recognition, sensory recognition, and obstacle recognition.

[0128] In some embodiments, various intelligent models are stored in the model management module. It should be clarified that each intelligent model corresponds to at least one delivery function. The robot sends a request to the model management module via the target communication base station. The model management module matches the intelligent model with the corresponding function based on the request information and then sends the intelligent model to the target computing base station corresponding to the target communication base station via the target communication base station.

[0129] It should be clarified that, in some embodiments, the robot only needs to send a request message to the model management module once through the target communication base station. The model management module records the intelligent model required for the delivery task and detects updates to the target communication base station for the delivery task. Whenever a target communication base station is identified, the intelligent model required for the current delivery task is transmitted to the target computing power base station corresponding to the newly discovered target communication base station. The intelligent model is set up in the target computing power base station, using the computing power resources provided by the target computing power base station to analyze the status information and environmental information uploaded by the robot and provide feedback.

[0130] In other embodiments, all data is collected by the data management module during the robot's movement along the target path. Each time a new target communication base station is identified, the newly identified target communication base station obtains the intelligent model required for the current delivery task through the data management module and sends a request message to the model management module. The model management module determines the corresponding intelligent model and transmits the intelligent model to the target computing base station corresponding to the target communication base station that sent the request message.

[0131] Please see Figure 6 , Figure 6 A flowchart illustrating a method for requesting a corresponding intelligent model via a target communication base station based on functional requirement information of a delivery task, according to an embodiment of this application, is shown. This embodiment provides step S130 of requesting a corresponding intelligent model via a target communication base station based on functional requirement information of a delivery task, including:

[0132] Step S131: Determine the delivery functions required to complete the delivery task based on the functional requirements information of the delivery task;

[0133] Step S132: Based on the external functions in the delivery function, request a smart model with the corresponding external functions through the target communication base station and transmit it to the target computing base station;

[0134] Step S133: Based on the built-in functions in the delivery function, when the intelligent model is requested for the first time through the target communication base station, the intelligent model with the corresponding built-in functions is transmitted to the robot.

[0135] The above three steps are described in detail below.

[0136] In step S131, the delivery functions required for the delivery task are determined based on the functional requirements information of the delivery task. In some embodiments, the delivery functions are defined by the user. In some embodiments, the delivery functions are determined based on the attributes of the target path itself. For example, some paths must be equipped with corresponding delivery functions to complete the delivery. The delivery functions required to complete the delivery task are determined based on the delivery functions required by the target path and the delivery functions defined by the user or automatically determined by the delivery task itself.

[0137] In step S132, it needs to be clarified that the delivery functions required to complete the delivery task can be divided into external functions and internal functions. External functions refer to the functions provided by the intelligent model set on the target communication node, such as lane changing, route planning, obstacle sensing, obstacle recognition, etc. Internal functions refer to the functions provided by the intelligent model set inside the robot, such as self-balancing.

[0138] Based on the external functions in the delivery process, a smart model with the corresponding external function is requested from the target communication base station and transmitted to the target computing power base station. Since the external function requires the target computing power base station to function, the smart model must be acquired again each time a new target computing power base station is identified.

[0139] In step S133, based on the built-in functions of the delivery function, when the intelligent model is requested for the first time through the target communication base station, the intelligent model with the corresponding built-in function is transmitted to the robot. Since there is only one robot, the intelligent model corresponding to the built-in function only needs to be downloaded on the first request.

[0140] In step S140, the intelligent model acquires and analyzes the robot's environmental and state information through the target computing power base station and the target communication base station, obtaining analysis results. The robot is equipped with sensors that can detect its own state parameters, such as endurance, speed, direction, position, levelness, and weight. It can also acquire environmental information, such as weather, road friction coefficient, surrounding obstacles, surrounding vehicles, and pedestrians. The robot's state and environmental information are sent to the target computing power base station corresponding to the target communication base station. The intelligent model in the target computing power base station analyzes the received robot state and environmental information, obtaining analysis results, which are then used as control commands for the robot. These commands can include controlling the robot to accelerate, decelerate, change lanes, overtake, stop, and sound its horn.

[0141] Please see Figure 7 , Figure 7This document illustrates a flowchart illustrating how an intelligent model, according to an embodiment of this application, acquires and analyzes environmental and state information of a robot via a target computing power base station and a target communication base station to obtain analysis results. The embodiment of this application provides step S140, which involves an intelligent model acquiring and analyzing environmental and state information of a robot via a target computing power base station and a target communication base station to obtain analysis results, including:

[0142] Step S141: Obtain the robot's state information and environmental information, and use the built-in function to perform built-in analysis on the state information and environmental information to obtain the built-in analysis results;

[0143] Step S142: The status information, environmental information, and built-in analysis results are sent to the target computing power base station via the target communication base station;

[0144] Step S143: The intelligent model in the target computing base station analyzes the driving status information and environmental information to obtain external analysis results;

[0145] Step S144: If the external analysis result and the internal analysis result are the same, then the internal analysis result shall be used as the analysis result.

[0146] Step S145: If the external analysis result and the internal analysis result are different, the external analysis result shall be used as the analysis result, and the parameters of the intelligent model set on the target computing power node shall be sent to the robot to update the parameters of the robot's internal intelligent model.

[0147] The above five steps are described in detail below.

[0148] In step S141, the robot acquires its state information and environmental information, and uses built-in functions to perform built-in analysis on the state information and environmental information to obtain the built-in analysis results.

[0149] In step S142, the robot uploads its state information, environmental information, and built-in analysis results to the target computing power base station via the target communication base station.

[0150] In step S143, the target base station also performs external analysis based on the robot's state information and environmental information to obtain external analysis results. That is, the intelligent model set up inside the robot is partially the same as the intelligent model in the target computing base station, allowing for the same analysis of the robot's state information and environmental information, resulting in both built-in and external analysis results.

[0151] In step S144, if the external analysis result and the internal analysis result are the same, then the internal analysis result is taken as the analysis result. This is equivalent to the internal analysis result being verified, allowing the robot to run directly based on the internal analysis result.

[0152] In step S145, if the external analysis result differs from the internal analysis result, the external analysis result is used as the analysis result. Since the external analysis result is calculated using the intelligent model in the target computing node with more computing power, it is more reliable, so the external analysis result is used as the analysis result. This also indicates that the intelligent model inside the robot has a large error. Therefore, when transmitting the external analysis result, the parameters of the intelligent model set in the target computing node are simultaneously sent to the robot to update the parameters of the robot's internal intelligent model.

[0153] In this embodiment, the analysis results are verified to make them more accurate. Furthermore, when an error is detected in the intelligent model set within the robot, parameters are sent to the intelligent model to repair it. This ensures that the analysis results are always verified.

[0154] In step S150, the target computing base station transmits the analysis results to the robot through the target communication base station. The robot then runs according to the analysis results of the artificial intelligence model until it reaches the destination of the delivery task.

[0155] It should be clarified that, in some embodiments, the robot sends its status information and environmental information to the target computing base station corresponding to the target communication base station at set time intervals to obtain analysis results and then adjust the robot's driving state.

[0156] In other embodiments, the robot collects its environmental and driving information in real time, but only when the status and driving information fluctuate outside a set range, such as changes in environmental information (e.g., detecting a vehicle or obstacle ahead), or changes in status information (e.g., insufficient battery life or blurred camera), will the robot's status and environmental information be transmitted via the target communication base station to the target computing base station for analysis of the fluctuations. The robot then continues driving based on the analysis results.

[0157] In this embodiment, determining multiple target communication base stations via the target path enables the robot to maintain smooth communication and provides it with long-distance endurance. By externalizing the target computing base stations, the robot's available computing power is significantly increased, allowing it to handle various complex road conditions. This enables the robot to complete long-distance delivery tasks along relatively complex routes.

[0158] An automated delivery device for robots, characterized in that it comprises:

[0159] The business management module is configured to determine the target path of the delivery task based on the start and end points of the delivery task, and to determine the target communication base station and the target computing power base station.

[0160] The model management module is configured to provide intelligent models corresponding to various delivery functions, and can install the intelligent models on the target computing base station and robot through the target communication base station;

[0161] The resource scheduling module, located within the target computing base station, is used to calculate external analysis results based on the robot's state and environmental information, compare internal and external analysis results, and provide computing power for the intelligent model. It is also used to balance the communication resources of the target communication base station when the network of the target communication base station is not smooth, so as to ensure that the first and third delays do not increase.

[0162] The data management module receives and sends data between the robot and the target computing base station, and stores the data.

[0163] The application scenario description for the robot's automated delivery device includes, in some embodiments, the business management module acquiring the start and end points of the delivery task, as well as the delivery requirements; the business management module then determines the target path based on the start and end points of the delivery task and the delivery requirements.

[0164] When the robot performs a delivery task, the business management module determines the target communication base station and the target computing power base station based on the target path. The business management module then requests the corresponding intelligent model for the delivery function from the model management module based on the functional requirements of the delivery task. After each determination of the target computing power base station, the model management module sends the corresponding intelligent model for the delivery function to the target computing power base station. The robot then maintains interaction with the target computing power base station to enable it to complete the delivery task.

[0165] For each interaction between the robot and the target computing base station, the robot sends its status information, environmental information, and built-in analysis results to the data management module via the target communication network. The data management module then sends this data to the target computing base station. The target computing base station analyzes the robot's status and environmental information to obtain external analysis results. The resource scheduling module located in the target computing base station compares the external and built-in analysis results. If the external and built-in analysis results differ, the external analysis results and intelligent model parameters are sent to the data management module. The data management module then sends this data to the robot via the target communication base station. If the external and built-in analysis results are the same, the built-in analysis results are sent to the data management module. The data management module then sends this data to the robot via the target communication base station. The robot operates based on the data sent from the target communication base station.

[0166] In some embodiments, the data management module is responsible for storing and relaying data to prevent data loss, and can also be used to train other intelligent models.

[0167] In some embodiments, the resource scheduling module is further configured to balance the communication resources of the target communication base station when the target communication base station network is unreliable, so as to ensure that the first delay and the third delay do not increase. It also switches the target communication base station to provide communication resources to the robot according to the order of use.

[0168] Figure 8 A computer system architecture block diagram for implementing an automated delivery method for robots, according to an embodiment of this application, is shown.

[0169] It should be noted that, Figure 8 The computer system 800 shown is merely an example and should not be construed as to its functionality or scope of use in the embodiments of this application.

[0170] like Figure 8 As shown, the computer system 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 802 or programs loaded from storage section 808 into random access memory (RAM). The random access memory 803 also stores various programs and data required for system operation. The CPU 801, ROM 802, and RAM 803 are interconnected via a bus 804. An input / output interface 805 (I / O interface) is also connected to the bus 804.

[0171] The following components are connected to the input / output interface 805: an input section 806 including a keyboard, mouse, etc.; an output section 807 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 808 including a hard disk, etc.; and a communication section 809 including a network interface card such as a local area network card, modem, etc. The communication section 809 performs communication processing via a network such as the Internet. A drive 810 is also connected to the input / output interface 805 as needed. A removable medium 811, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 810 as needed so that computer programs read from it can be installed into the storage section 808 as needed.

[0172] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 809, and / or installed from removable medium 811. When the computer program is executed by central processing unit 801, it performs various functions defined in the system of this application.

[0173] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.

[0174] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0175] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0176] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0177] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0178] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is solely defined by the appended claims.

Claims

1. An automated delivery method using a robot, characterized in that, The method includes: Obtain the origin and destination of the delivery task to plan the target route; Control the robot to start moving, and determine the target communication base station and target computing power base station based on the robot's position and the target path; Based on the functional requirements of the delivery task, determine the delivery functions required to complete the delivery task; based on the external functions in the delivery functions, request an intelligent model with the corresponding external functions through the target communication base station and transmit it to the target computing base station; based on the built-in functions in the delivery functions, when requesting an intelligent model through the target communication base station for the first time, transmit the intelligent model with the corresponding built-in functions to the robot. The robot's state information and environmental information are acquired, and the built-in functions are used to perform built-in analysis on the state information and environmental information to obtain built-in analysis results; the state information, environmental information, and built-in analysis results are sent to the target computing power base station via the target communication base station; the intelligent model in the target computing power base station analyzes the state information and environmental information to obtain external analysis results; If the external analysis result and the internal analysis result are the same, then the internal analysis result shall be used as the analysis result; if the external analysis result and the internal analysis result are different, then the external analysis result shall be used as the analysis result. Based on the analysis results of the intelligent model, the robot is controlled to travel until the destination.

2. The method according to claim 1, characterized in that, Determining the target communication base station and the target computing base station based on the robot's position and the target path includes: Based on the robot's location and the target path, determine the target communication base station for the section of road the robot will travel, and reserve communication resources accordingly. Based on the predicted communication delay between the target communication base station and the robot, the target computing base station corresponding to the target communication base station is determined, and computing resources are reserved.

3. The method according to claim 2, characterized in that, Based on the robot's location and the target path, the target communication base station for the section of road the robot will travel is determined, including: When the robot senses that the signal of the target communication base station it is currently using reaches a set threshold, the robot's first position is obtained. In the target path, determine the position at a first set distance from the first position as the second position; Centered on the second location, a communication base station within a second predetermined distance range is selected as the initial communication base station; The initial communication base station with the largest communication resources among the initial communication base stations is selected as the target communication base station.

4. The method according to claim 3, characterized in that, Based on the predicted communication latency between the target communication base station and the robot, the target computing base station corresponding to the target communication base station is determined, including: Based on the parameter information of the computing base station and the difficulty of the delivery task, the computing latency of the computing base station is calculated and used as the first latency. Based on the distance between each target communication base station and the target planned path, the communication delay between the target communication base station and the robot is predicted as a second delay; The difference between the standard delay and the first and second delays is taken as the third delay. The computing power base station whose communication delay with the target communication base station is less than the third delay is taken as the target computing power base station corresponding to the target communication base station.

5. The method according to claim 1, characterized in that, The method further includes: During the robot's movement, the signals of the current target communication base station and the next target communication base station are monitored as a first signal and a second signal, respectively, and the robot communicates via the current target communication base station. When the ratio of the first signal to the second signal is less than a set ratio threshold, the next target communication base station is used as the current target communication base station to ensure smooth communication for the robot.

6. The method according to claim 1, characterized in that, The method further includes: If the signal of the target communication base station is unstable, the bandwidth allocation of the target communication base station to the delivery task will be increased and / or the corresponding communication task will be moved forward in the task queue.

7. The method according to claim 1, characterized in that, The communication base stations include: 3GPP base stations and non-3GPP base stations.

8. An automated delivery device for a robot, used to perform the method according to any one of claims 1 to 7, characterized in that, include: The business management module is used to determine the target route of the delivery task based on the start and end points of the delivery task, and to determine the target communication base station and the target computing power base station. The model management module provides intelligent models for various delivery functions and can install these intelligent models on target computing base stations and robots via target communication base stations. The resource scheduling module, located within the target computing power base station, is used to calculate external analysis results and compare internal analysis results with external analysis results based on the robot's state information and environmental information. The data management module is used to send and receive data between the robot and the target computing base station, and to store the data.

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