Robotic lawn mower system based on cloud-edge-terminal collaboration, and electric tool management system

Abstract

Disclosed in the present application are a robotic lawn mower system based on cloud-edge-terminal collaboration, and an electric tool management system. The robotic lawn mower system comprises: a terminal device, which comprises a robotic lawn mower and is configured to at least collect local data; an edge node, which is in communication connection with the terminal device and is configured to acquire the local data from the terminal device and to update a control program of the terminal device by using the local data; and a cloud platform, which is in communication connection with the edge node and is configured to acquire the control program from the edge node and to perform overall management on the control program.

Description

Lawn mowing robot system and power tool management system based on cloud-edge-end collaboration

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on July 24, 2023, with application number 202310906130.0. The entire contents of the above application are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of power tool technology, and in particular to a lawn mowing robot system and a power tool management system based on cloud-edge-end collaboration. Background Art

[0003] When power tools are used or operated autonomously, they generate large amounts of data. In some cases, this data forms the basis for generating power tool control commands, requiring collection for related computations. In other cases, this data can reflect user habits and preferences, or indicate potential optimization areas for power tools, requiring collection for analysis and processing. Whether using data for computational purposes or conducting analysis and processing, the requirements are increasingly large, complex, real-time, and highly accurate. Thanks to relevant technological developments, cross-cutting technology applications are becoming increasingly common in the power tool field, making the vision of the Internet of Everything a reality.

[0004] This section provides background information related to the present application which is not necessarily prior art.

[0005] Summary of the Invention

[0006] One object of the present application is to solve or at least alleviate part or all of the above problems. To this end, one object of the present application is to provide a lawn mowing robot system and a power tool management system based on cloud-edge-end collaboration.

[0007] In order to achieve the above objectives, this application adopts the following technical solutions:

[0008] A lawn mowing robot system based on cloud-edge-end collaboration includes: a terminal device, including a lawn mowing robot, the terminal device is configured to at least collect local data; an edge node, which is communicatively connected to the terminal device, the edge node is configured to obtain local data from the terminal device and use the local data to update the control program of the terminal device; a cloud platform, which is communicatively connected to the edge node, the cloud platform is configured to obtain the control program from the edge node and comprehensively manage the control program.

[0009] In some embodiments, the edge node transmits the control program to the corresponding terminal device; the terminal device generates a control instruction for the terminal device according to the control program and local data.

[0010] In some embodiments, the edge node generates a control instruction for the terminal device based on the control program and local data, and transmits the control instruction to the corresponding terminal device.

[0011] In some embodiments, the terminal device controls the driving motor and / or the traveling motor of the lawn mowing robot according to the control instruction.

[0012] In some embodiments, the edge node uses local data to optimize control parameters of the control program.

[0013] In some embodiments, the control program is a machine learning model, and the edge node uses local data to train the original machine learning model and / or retrain the trained machine learning model.

[0014] In some embodiments, edge nodes use local data to incrementally train machine learning models.

[0015] In some embodiments, the terminal device further includes a charging station and / or a positioning base station within the working area of ​​the lawn mowing robot.

[0016] In some embodiments, the terminal device further includes a monitoring device near the working area of ​​the lawn mowing robot.

[0017] In some embodiments, the local data includes environmental data around the lawn mower robot and / or working status data of the lawn mower robot collected by the terminal device; the working status data of the lawn mower robot includes power information and / or positioning information of the lawn mower robot.

[0018] In some embodiments, the edge node communicates with the terminal device using fifth-generation mobile communication technology or sixth-generation mobile communication technology.

[0019] In some embodiments, the edge nodes include region servers.

[0020] A lawn mowing robot comprises: a drive component comprising a blade and a drive motor for driving the blade; a walking component comprising walking wheels and a walking motor for driving the walking wheels; wherein the lawn mowing robot further comprises: a communication component communicatively connected to an edge node, the communication component being configured to transmit local data to the edge node so that the edge node uses the local data to update a control program, and to transmit the control program to a cloud platform so that the cloud platform can comprehensively manage the control program; a processor being electrically connected to the communication component, the processor being configured to control the actions of the lawn mowing robot according to control instructions, the control instructions being generated according to the control program and local data.

[0021] A lawn mowing robot system based on cloud-edge-end collaboration includes: a terminal device, including a lawn mowing robot, the terminal device is configured to at least collect local data; an edge node, which is communicatively connected to the terminal device, the edge node is configured to obtain local data from the terminal device, generate control instructions for the terminal device according to a first control program and local data, and transmit the control instructions to the terminal device; a cloud platform, which is communicatively connected to the edge node, and the cloud platform is configured to coordinate and manage the edge nodes.

[0022] In some embodiments, the edge node transmits local data to the cloud platform; the cloud platform uses the local data to update the first control program of the edge node, and transmits the updated first control program to the edge node.

[0023] In some embodiments, the edge node processes the local data before transmitting the local data to the cloud platform, and transmits the processed local data to the cloud platform.

[0024] In some embodiments, the edge node updates the first control program using local data and transmits the first control program to the cloud platform.

[0025] In some embodiments, the lawn mowing robot system includes a plurality of lawn mowing robots; the edge node schedules the plurality of lawn mowing robots according to the second control program and local data.

[0026] In some embodiments, the cloud platform uses local data to update the second control program of the edge node and transmits the updated second control program to the edge node.

[0027] In some embodiments, the edge node updates the second control program using local data and transmits the second control program to the cloud platform.

[0028] In some embodiments, the average communication delay between the edge node and the terminal device is less than or equal to 10 ms.

[0029] A lawn mowing robot comprises: a driving component comprising a blade and a driving motor for driving the blade; a walking component comprising walking wheels and a walking motor for driving the walking wheels; wherein the lawn mowing robot further comprises: a communication component communicatively connected to an edge node, the communication component being configured to transmit local data to the edge node so that the edge node generates control instructions based on a control program and local data, and the edge node is centrally managed by a cloud platform; the communication component is further configured to receive control instructions transmitted by the edge node; and a processor being electrically connected to the communication component, the processor being configured to control the actions of the lawn mowing robot based on the control instructions.

[0030] A lawn mowing robot system based on cloud-edge-end collaboration includes: a terminal device, including a lawn mowing robot, the terminal device is configured to collect at least local first data; an edge node, which is communicatively connected to the terminal device, the edge node is configured to obtain the first data from the terminal device and process the first data to generate second data; a cloud platform, which is communicatively connected to the edge node, and the cloud platform is configured to comprehensively manage the edge node.

[0031] In some embodiments, the edge node transmits the second data to the terminal device; the terminal device generates a control instruction according to the control program and the second data.

[0032] In some embodiments, the edge node transmits the second data to the cloud platform; the cloud platform generates a control instruction for the terminal device according to the control program and the second data.

[0033] In some embodiments, the edge node transmits the second data to the cloud platform; the cloud platform uses the second data to update the control program and comprehensively manages the control program.

[0034] In some embodiments, the cloud platform transmits the control program to the edge node; the edge node generates a control instruction for the terminal device based on the control program and the second data.

[0035] In some embodiments, the edge node performs data cleaning and / or data integration on the first data.

[0036] A lawn mowing robot comprises: a driving component including a blade and a driving motor for driving the blade; a walking component including walking wheels and a walking motor for driving the walking wheels; wherein the lawn mowing robot further comprises: a communication component communicatively connected to an edge node, the communication component being configured to transmit first data to the edge node so that the edge node processes the first data and generates second data, and the edge node is centrally managed by a cloud platform.

[0037] An electric tool management system based on cloud-edge-end collaboration includes: multiple terminal devices, including one or more of electric tools, battery packs, and power management devices, and the terminal devices are configured to collect at least first data; an edge node, which is communicatively connected to at least some of the multiple terminal devices and has a computing power of greater than or equal to 1 TFLOPS, and the edge node is configured to obtain first data from the terminal device and process the first data to generate second data; a cloud platform, which is communicatively connected to the edge node, and the cloud platform is configured to obtain second data from the edge node and comprehensively manage the second data.

[0038] In some embodiments, the first data includes real-time data and / or historical data of the terminal device.

[0039] In some embodiments, the cloud platform restarts, rolls back, and scales up or down based on the second data management edge node.

[0040] An electric tool management system based on cloud-edge-end collaboration includes: multiple terminal devices, including one or more of electric tools, battery packs, and power management devices, and the terminal devices are configured to at least collect local data; edge nodes, which are communicatively connected to at least some of the multiple terminal devices and the average communication delay between the edge nodes and the terminal devices is less than or equal to 10ms, and the edge nodes are configured to obtain local data from the terminal devices, generate control instructions for the terminal devices according to the control program and local data, and transmit the control instructions to the terminal devices; a cloud platform, which is communicatively connected to the edge nodes, and the cloud platform is configured to coordinate the management of the edge nodes.

[0041] In some embodiments, the edge node updates the control program based on local data and transmits the control program to the cloud platform.

[0042] In some embodiments, the local data includes sensor data and / or working status data of the terminal device.

[0043] In some embodiments, the working status data includes one or more of the terminal device's environmental information, power information, positioning information, user information, and operation information.

[0044] In some embodiments, some of the multiple terminal devices transmit the collected local data to other terminal devices, and the other terminal devices forward the local data to the edge node.

[0045] In some embodiments, the battery pack transmits local data to other terminal devices through the DT terminal.

[0046] In some embodiments, the terminal device transmits local data to other terminal devices via a Bluetooth Low Energy (BLE) unit and / or a Near Field Communication (NFC) unit.

[0047] In some embodiments, fifth-generation mobile communication technology is used for communication between the terminal device and the edge node, and / or between the edge node and the cloud platform.

[0048] In some embodiments, massive MIMO technology is used for communication between terminal devices and edge nodes, and / or between edge nodes and cloud platforms. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] FIG1 is a network architecture diagram of a lawn mowing robot system or electric tool management system based on cloud-edge-end collaboration, shown in one embodiment.

[0050] FIG2 is a diagram showing data interaction in a robotic lawn mower system when an edge node updates a control program, according to an embodiment.

[0051] FIG3 is a data interaction diagram of a robotic lawn mower system when an edge node updates a control program, shown in another embodiment.

[0052] FIG4 is a data interaction diagram of a lawn mowing robot system when an edge node updates a control program, shown in yet another embodiment.

[0053] FIG5 is a perspective view showing a partial structure of a lawn mowing robot according to an embodiment.

[0054] FIG6 is a schematic diagram of the electric control principle of the lawn mowing robot in FIG5 .

[0055] FIG7 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in one embodiment.

[0056] FIG8 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in another embodiment.

[0057] FIG9 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in yet another embodiment.

[0058] FIG10 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in yet another embodiment.

[0059] FIG11 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in yet another embodiment.

[0060] FIG12 is a data interaction diagram of a lawn mowing robot system in which an edge node generates a control instruction, shown in yet another embodiment.

[0061] FIG13 is a data interaction diagram in a robotic lawn mower system when an edge node processes and obtains second data, showing an embodiment.

[0062] FIG. 14 is a data interaction diagram in a robotic lawn mower system when an edge node processes and obtains second data, shown in another embodiment.

[0063] FIG15 is a data interaction diagram in a robotic lawn mower system when an edge node processes and obtains second data, showing another embodiment.

[0064] FIG16 is a data interaction diagram in a robotic lawn mower system when an edge node processes and obtains second data, shown in yet another embodiment.

[0065] FIG. 17 is a data interaction diagram in a robotic lawn mower system when an edge node processes and obtains second data, shown in yet another embodiment.

[0066] Figure 18 is a data interaction diagram in an electric tool management system based on cloud-edge-end collaboration shown in one embodiment.

[0067] Figure 19 is a data interaction diagram in an electric tool management system based on cloud-edge-end collaboration shown in another embodiment. DETAILED DESCRIPTION

[0068] Before any embodiments of the present application are explained in detail, it is to be understood that the application is not limited in its application to the details of construction and the arrangement of components set forth in the following description or illustrated in the foregoing drawings.

[0069] In this application, the terms "comprises," "includes," "has," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0070] In this application, the term "and / or" describes a relationship between related objects, indicating that three possible relationships exist. For example, "A and / or B" can represent: A exists alone, A and B exist simultaneously, or B exists alone. Additionally, the character " / " in this application generally indicates that the related objects are in an "and / or" relationship.

[0071] In this application, the terms "connect," "combine," "couple," and "install" may refer to direct connection, combination, coupling, or installation, or indirect connection, combination, coupling, or installation. For example, a direct connection refers to two parts or components being connected together without an intermediary, and an indirect connection refers to two parts or components being connected to at least one intermediary, with the two parts or components being connected via the intermediary. Furthermore, "connect" and "couple" are not limited to physical or mechanical connections or couplings and may include electrical connections or couplings.

[0072] In this application, it will be understood by those skilled in the art that relative terms (e.g., "about," "approximately," "substantially," etc.) used in conjunction with quantities or conditions include the values ​​and have the meaning indicated by the context. For example, the relative terms include at least the degree of error associated with the measurement of a specific value, the tolerance caused by manufacturing, assembly, use, etc. associated with a specific value. Such terms should also be considered to disclose a range defined by the absolute values ​​of the two endpoints. Relative terms may refer to plus or minus a certain percentage (e.g., 1%, 5%, 10% or more) of the indicated value. Numerical values ​​that do not use relative terms should also be disclosed as specific values ​​with tolerances. In addition, "substantially" may refer to plus or minus a certain degree (e.g., 1 degree, 5 degrees, 10 degrees or more) on the basis of the indicated angle when expressing a relative angular position relationship (e.g., substantially parallel, substantially perpendicular).

[0073] In this application, it will be understood by those skilled in the art that the function performed by an assembly can be performed by one assembly, multiple assemblies, one part, or multiple parts. Similarly, the function performed by a part can also be performed by one part, one assembly, or a combination of multiple parts.

[0074] In the present application, the terms "upper", "lower", "left", "right", "front", "back" and other directional words are described based on the orientation and positional relationship shown in the accompanying drawings, and should not be understood as limiting the embodiments of the present application. In addition, in the context, it is also necessary to understand that when it is mentioned that an element is connected to another element "upper" or "lower", it can not only be directly connected to the other element "upper" or "lower", but also be indirectly connected to the other element "upper" or "lower" through an intermediate element. It should also be understood that directional words such as upper side, lower side, left side, right side, front side, back side, etc. not only represent the positive orientation, but can also be understood as the lateral orientation. For example, below can include directly below, lower left, lower right, lower front and lower back, etc.

[0075] In this application, the terms "controller," "processor," "central processing unit," "CPU," and "MCU" are used interchangeably. Where a unit "controller," "processor," "central processing unit," "CPU," or "MCU" is used to perform a particular function, unless otherwise specified, the function may be performed by a single unit or multiple units.

[0076] In this application, the terms "device", "module" or "unit" can be implemented in the form of hardware or software to achieve specific functions.

[0077] In this application, the terms "calculate", "judge", "control", "determine", "identify", etc. refer to the operations and processes of a computer system or similar electronic computing device (e.g., controller, processor, etc.).

[0078] Various power tools and related equipment, such as charging stations and positioning base stations, generate and collect vast amounts of data during user use and autonomous operation. Analyzing and mining this data can improve power tools' efficiency, accuracy, safety, and user experience. Thanks to relevant technological developments, the power tool sector is experiencing a trend of cross-cutting technologies, with cloud-edge-end being a practical architecture for the IoT.

[0079] The technical solution proposed in this application is described in detail below with reference to the accompanying drawings and specific implementation methods.

[0080] Referring to Figure 1, we first explain the networking architecture involved in the proposed robot mower system and power tool management system based on cloud-edge-end collaboration. Unlike the traditional cloud-based architecture consisting of end-to-end and cloud-based components, the proposed robot mower system and power tool management system, comprising end-to-end, edge-to-end, and cloud-based components, will perform communication, command control, data processing, and other tasks in a cloud-edge-end collaborative manner, and can be applied to various working scenarios of various power tools.

[0081] The term "end" refers to a terminal device 10, which is at the bottom layer of the cloud-edge-end architecture and interacts with the edge. A network may include one or more terminal devices 10, and generally a large number of terminal devices 10. Terminal devices 10 include various types of power tools and other related devices that may interact with various types of power tools. Table 1 below shows the specific types of terminal devices 10 that may be involved in this application.

[0082] Table 1

[0083] It is understandable that the devices in Table 1 above are only used for illustration, and the classification of the devices in the table is not absolute. In addition, depending on the actual scenario requirements, the terminal device 10 may also include other types of devices outside of Table 1.

[0084] The edge is an edge node 20, which is located in the middle layer of the cloud-edge-end architecture. It interacts with the end-end downward and with the cloud upward. The edge node 20 performs local edge computing with smaller data scale and higher real-time performance. The network can include one or more edge nodes 20, and generally there can be a small number of edge nodes 20. The physical carrier of the edge node 20 includes a server or server cluster, such as a regional server, etc. In some cases, it can also be an intelligent gateway or a reuse of the local area network / wide area network center. In the cloud-edge-end architecture, the edge node 20 is responsible for several terminal devices 10 within its jurisdiction, that is, an edge node 20 can correspond to one or more terminal devices 10. These terminal devices 10 are within the jurisdiction of the edge node 20. They are usually terminal devices 10 that are closer to the edge node 20 in terms of geographical location or data link. The edge node 20 will provide storage, computing and communication resources to these corresponding terminal devices 10. As shown in FIG1 , edge node 21 may be responsible for terminal devices 11 , 12 , and 13 within its jurisdiction; edge node 22 may be responsible for terminal devices 14 and 15 within its jurisdiction; and edge node 23 may be responsible for terminal devices 16 , 17 , 18 , and 19 within its jurisdiction.

[0085] It is understandable that in some cases, the terminal devices 10 that the edge node 20 is responsible for can also be dynamically adjusted. For example, the cloud platform 30 can adjust the terminal devices 10 within the jurisdiction of the edge node 20 at regular intervals based on the needs of each terminal device 10 and the capabilities of each edge node 20.

[0086] The cloud platform 30 is at the top level in the cloud-edge architecture and interacts with the edge downward. The cloud platform 30 performs global management and calculations with large data scale and weak real-time performance. The network can include one or more cloud platforms 30, generally several cloud platforms 30. The following mainly describes the situation of one cloud platform 30. The cloud platform 30 can be a central cloud node in a traditional cloud architecture, and its physical carrier also includes a server or a server cluster. Under the cloud-edge architecture, the cloud platform 30 is responsible for several edge nodes 20, manages various resources of one or more edge nodes 20, or collects and analyzes various data of one or more edge nodes 20. As shown in Figure 1, edge nodes 21, 22, and 23 are all managed by the cloud platform 30.

[0087] Figures 1 and 2 illustrate a robotic lawnmower system based on cloud-edge-end collaboration as an embodiment of this application. The robotic lawnmower system includes a terminal device 10, an edge node 20, and a cloud platform 30. It should be understood that the number, type, and connection relationship of the terminal devices 10, edge nodes 20, and cloud platform 30 in Figure 1 are for illustrative purposes only and do not constitute a specific limitation.

[0088] In this embodiment, the terminal device 10 may include a lawn mowing robot, specifically, a plurality of lawn mowing robots located in different working areas and belonging to different users. In some embodiments, the terminal device 10 may also include a charging station and / or a positioning base station within the working area of ​​each lawn mowing robot. In other embodiments, the terminal device 10 also includes monitoring equipment near the working area of ​​each lawn mowing robot. In still other embodiments, the terminal device 10 also includes external sensors such as electromagnetic sensors within the working area of ​​each lawn mowing robot. In still other embodiments, the terminal device 10 also includes user devices such as personal computers, tablet computers, and smart phones of the users to whom each lawn mowing robot belongs.

[0089] The terminal device 10 can communicate with the edge node 20. Specifically, the terminal device 10 can establish a connection with the edge node 20 within its jurisdiction. In some cases, the terminal device 10 only establishes a connection with one edge node 20. In other cases, there are multiple edge nodes 20 within the same jurisdiction based on geographic location or data link division. The terminal device 10 can also select one of the edge nodes 20 to establish a connection based on relevant rules. For example, the terminal device 10 can select a corresponding edge node 20 to establish a connection based on the type of local data to be transmitted. For example, the edge node 20 connected to it when transmitting positioning information can be different from the edge node 20 connected to it when transmitting power information.

[0090] The communication connection between the terminal device 10 and the edge node 20 can be implemented based on a variety of communication technologies or a combination thereof, and the communication connection between the two complies with the protocol requirements of each communication technology. In some embodiments, the communication connection between the terminal device 10 and the edge node 20 can be implemented based on local area network or wide area network technology, and the terminal device 10 and the edge node 20 of its jurisdiction are in the same local area network or wide area network, or, the division of the jurisdiction to which the terminal device 10 belongs is based on the division of the local area network or wide area network, and the edge node 20 is the local area network / wide area network center. In other embodiments, the communication connection between the terminal device 10 and the edge node 20 can also be implemented based on massive MIMO technology (Massive Multiple Input Multiple Output) and / or the fifth generation mobile communication technology (5G). In some other embodiments, the average communication delay between the terminal device 10 and the edge node 20 is less than or equal to 10ms.

[0091] The terminal device 10 transmits the local data generated and / or collected by the terminal device 10 to the corresponding edge node 20. In some cases, the terminal device 10 proactively uploads local data to the edge node 20. In other cases, the terminal device 10 feeds back local data in response to a request from the edge node 20. In some embodiments, the local data of the terminal device 10 includes environmental data surrounding the lawn mower robot and / or operating status data of the lawn mower robot. The environmental data includes an image of the environment surrounding the lawn mower robot, and the operating status data includes one or more of the lawn mower robot's power information, positioning information, user information, and operating information.

[0092] The same terminal device 10 can transmit one or more types of local data to the edge node 20. Different terminal devices 10 can transmit the same or different types of local data to the edge node 20. For example, a lawn mower robot can collect and transmit local data including user information of the user, power information such as the current battery level or battery level changes over a period of time, positioning information such as the current location or movement trajectory over a period of time, and operation information such as the current operation completion level or operation history over a period of time.

[0093] For example, a charging station within the robot's work area can collect and transmit local data, including information such as the charging station's current charging status or its charging history over a certain period of time. For example, a positioning base station within the robot's work area can collect and transmit local data, including information such as the robot's current detected location or its location over a certain period of time. For example, a monitoring device near the robot's work area can collect and transmit local data, including environmental data such as the current environment image of the work area or environmental video over a certain period of time.

[0094] An edge node can be a server or server cluster. In some embodiments, edge node 20 can be a regional server. This region can be a physical region, i.e., a region consisting of multiple devices within a certain geographical area, or an artificially divided region, i.e., a region consisting of devices of several individual or enterprise users. In some embodiments, terminal device 10 and edge node 20 can be in the same local area network or wide area network, and edge node 20 can be a management device in the local area network or wide area network, such as a local area network or wide area network center, an intelligent gateway, etc.

[0095] The edge node can be communicatively connected to the terminal device 10, and can also be communicatively connected to the cloud platform 30 to be described later. Specifically, the edge node 20 can be communicatively connected to one or more terminal devices 10 within its jurisdiction, and can also be communicatively connected to the cloud platform 30 that manages the edge node 20. The communication connection between the edge node 20 and the terminal device 10, and the communication connection between the edge node 20 and the cloud platform 30 can be implemented based on a variety of communication technologies such as local area networks, wide area networks, 5G, massive MIMO, or a combination thereof. For details, please refer to the relevant description above and will not be repeated here.

[0096] The edge node uses the local data obtained from each terminal device 10 to update the control program of each terminal device 10. Specifically, the edge node 20 can store and update the control program of each terminal device 10 within its jurisdiction. In some cases, when the edge node 20 obtains the local data of any terminal device 10, it can use the local data of that terminal device 10 to update one or more control programs of that terminal device 10. In other cases, after obtaining the local data of multiple terminal devices 10, the terminal device 10 can also jointly update one or more control programs of these multiple terminal devices 10 based on the local data of multiple terminal devices 10. In addition, the edge node 20 can perform streaming updates to the control program when obtaining local data, or it can periodically update the control program using the local data of that period at regular intervals.

[0097] The control program is used to generate control instructions for controlling the actions of each terminal device 10. In some cases, one terminal device 10 may correspond to one control program, and the edge node 20 uses various local data of the terminal device 10 to update the control program. In other cases, one terminal device 10 may correspond to multiple control programs, and the edge node 20 uses different types of local data of the terminal device 10 to update different corresponding control programs. For example, the edge node 20 may use charging information to update the charging control program of the terminal device 10, and use positioning information to update the travel control program of the terminal device 10.

[0098] In some embodiments, the control program of each terminal device 10 can be a machine learning model. The edge node 20 will use the acquired local data as a training set to train the current machine learning model until its loss function converges, thereby obtaining an updated new machine learning model adapted to the current data environment. In some cases, the edge node 20 can use local data to train the original machine learning model. In other cases, the edge node 20 can also use local data to retrain a trained machine learning model or perform downstream task training on a pre-trained machine learning model.

[0099] There are multiple optional implementation algorithms for the machine learning models described here, as shown in Table 2 below. Machine learning models include but are not limited to general machine learning models such as support vector machines, decision trees, naive Bayes, random forests, and K-Means; neural network models such as convolutional neural networks, recurrent neural networks, and long short-term memory neural networks; and other deep learning models such as encoder-decoders and generator-discriminators.

[0100] Table 2

[0101] The machine learning models in Table 2 above are for illustration only. The classification of the models in the table is not absolute. In addition, depending on the actual scenario requirements, the machine learning models in this embodiment may also include other types of models outside of Table 2.

[0102] It is understood that the distinction between supervised and unsupervised models is made, and the process of training a machine learning model using local data should correspond to the model's implementation algorithm. In some embodiments, the edge node 20 uses the local data of the terminal device 10 to perform incremental training on the machine learning model of the terminal device 10, such as regularization-based incremental training and playback-based incremental training, to avoid forgetting old local data when training the machine learning model with new local data, thereby achieving a balance between model balance and model plasticity.

[0103] In other embodiments, the control program of each terminal device 10 may be a conventional control program, and the edge node 20 may use the acquired local data to optimize the control parameters in the control program. For example, the edge node 20 may use the acquired local data to optimize the threshold parameters used as decision criteria in the control program to improve the accuracy of the control program in the current data environment. It is understood that if a terminal device 10 has multiple control programs, some of these control programs may be machine learning models and some may be conventional control programs.

[0104] The edge node also transmits the updated control programs of each terminal device 10 to the cloud platform 30, so that the cloud platform 30 can coordinate and manage the control programs of the edge node 20 and each terminal device 10. In some cases, the edge node 20 proactively uploads the updated control program to the cloud platform 30 after the control program is updated. In other cases, the edge node 20 responds to a request from the cloud platform 30 and provides feedback on the current control program.

[0105] The cloud platform can be a server or server cluster. In some embodiments, the cloud platform 30 can be a central cloud node in a traditional cloud architecture. The cloud platform 30 can be connected to the edge node 20 in a communication manner. The communication connection between the cloud platform 30 and the edge node 20 can be implemented based on a variety of communication technologies and their combination. For details, please refer to the relevant description above and will not be repeated here.

[0106] The cloud platform manages the control programs obtained from each edge node 20. In some embodiments, the cloud platform 30 can back up the control programs on each edge node 20 and restore the control programs on the edge node 20 after the edge node 20 crashes and restarts. In other embodiments, the cloud platform 30 can record the history of the control programs stored and updated on each edge node 20 and backtrack the control programs on the edge node 20 when the current control program on the edge node 20 fails. In still other embodiments, the cloud platform 30 can record the history of the control programs on each edge node 20, score each control program in the history of the edge node 20 at regular intervals, and distribute the control program with the best score to the edge node 20 for adoption. In still other cases, when multiple edge nodes 20 share common control programs, when an edge node 20 updates and uploads a new control program, the cloud platform 30 can distribute the updated control program to several corresponding edge nodes 20 to conserve computing resources on the edge nodes 20.

[0107] In one embodiment, referring to FIG3 , the edge node 20 also transmits the control program to the terminal device 10. In some examples, multiple terminal devices 10 share a common control program, and the edge node 20 broadcasts the control program to these multiple terminal devices 10. In other examples, each terminal device 10 uses a different control program, and the edge node 20 transmits each control program separately to the corresponding terminal device 10. Furthermore, in some cases, the edge node 20 transmits the new control program to the corresponding terminal device 10 immediately after the control program is updated. In other cases, the edge node 20 periodically transmits the current control program to the terminal device 10, regardless of whether the control program is updated.

[0108] The terminal device 10 will generate control instructions for controlling the local machine's actions based on the control program and local data obtained from the edge node 20. Specifically, the terminal device 10 uses the local data as input parameters to the control program obtained from the edge node 20 and generates corresponding control instructions based on the output of the control program. In some embodiments, the terminal device 10 may be a lawn mower robot, which can control the drive motor or travel motor based on the generated control instructions to directly control the lawn mower robot's actions. In other embodiments, the terminal device 10 may be a charging station, a positioning base station, or a monitoring device, which can send charging, warning, and other related signals to the lawn mower robot based on the generated control instructions to indirectly control the lawn mower robot's actions.

[0109] In one embodiment, referring to FIG4 , the edge node 20 further generates control instructions based on the control program and local data, and transmits the control instructions to the corresponding terminal device 10. In some cases, the edge node 20 uses the local data of a terminal device 10 to update one or more control programs of the terminal device 10. Subsequently, the edge node 20 may also use the local data of the terminal device 10 and the one or more control programs to generate control instructions for the terminal device 10 and transmit the control instructions to the terminal device 10. For example, the edge node 21 may use the positioning information of the lawn mower robot 11 to update the travel control program of the lawn mower robot 11, and use the power information of the lawn mower robot 11 to update the charging control program of the lawn mower robot 11. Subsequently, based on the newly acquired positioning information of the lawn mower robot 11 and the updated travel control program, the edge node 20 generates new travel control instructions and transmits them to the lawn mower robot 11. Furthermore, based on the newly acquired power information of the lawn mower robot 11 and the updated charging control program, the edge node 20 generates new charging control instructions and transmits them to the lawn mower robot 11.

[0110] In other cases, the edge node 20 integrates the local data of multiple terminal devices 10 to jointly update one or more control programs corresponding to the multiple terminal devices 10. Subsequently, the edge node 21 may use the local data of the multiple terminal devices 10 and the one or more control programs to generate control instructions for the multiple terminal devices 10 and transmit the control instructions to the corresponding terminal devices 10. For example, the edge node 21 uses the power information of the lawn mower robot 11 and the charging history information of the charging pile 13 to update the charging control programs of the lawn mower robot 11 and the charging pile 13. Subsequently, based on the newly acquired charging information of the lawn mower robot 11 and the charging status information of the charging pile 13, as well as the charging control programs of the lawn mower robot 11 and the charging pile 13, it generates charging control instructions for the lawn mower robot 11 and the charging pile 13, respectively, and sends them to the lawn mower robot 11 and the charging pile 13.

[0111] 5 and 6 show a lawn mower robot 10 used in the above lawn mower robot system. The lawn mower robot 10 includes a driving component 110 , a walking component 120 , a communication component 130 , and a processor 140 .

[0112] The drive assembly 110 includes a blade 111 and a drive motor 112 that drives the blade 111. The motor shaft of the drive motor 112 rotates to transmit power directly or indirectly through a first transmission assembly to a first output shaft, thereby driving the blade 111 to mow the lawn. The travel assembly 120 includes a travel wheel 121 and a travel motor 122 that drives the travel wheel 121. The motor shaft of the travel motor 122 rotates to transmit power directly or indirectly through a second transmission assembly to a second output shaft, thereby driving the travel wheel 121 to travel along a target path. In some examples, the travel motor 122 is a hub motor, which integrates power, transmission, braking, and other related devices into the wheel hub.

[0113] The communication component 130 is communicatively connected to the edge node 20 and can be a communication circuit such as a transceiver chip that adapts to various communication technology requirements. It is configured to transmit local data to the edge node 20 so that the edge node 20 uses the local data to update the control program, and transmit the control program to the cloud platform 30 so that the cloud platform 30 can coordinate and manage the control program; the processor 140 is electrically connected to the communication component 130 and can be an MCU (Microcontroller Unit) or a CPU (Central Processing Unit). It is configured to control the actions of the lawn mower robot according to control instructions, and the control instructions are generated according to the control program and local data.

[0114] Figure 7 shows a data interaction diagram for a robotic lawnmower system based on cloud-edge-end collaboration, another embodiment of the present application. The robotic lawnmower system includes a terminal device 10, an edge node 20, and a cloud platform 30. The specific physical carriers of the terminal device 10, edge node 20, and cloud platform 30, as well as the specific communication connection methods between the three, can be found in the previous description and will not be repeated here.

[0115] In this embodiment, the terminal device 10 can transmit the local data generated and / or collected by the terminal device 10 to the corresponding edge node 20. The edge node 20 will generate control instructions for each terminal device 10 based on the local data obtained from each terminal device 10 and the first control program of each terminal device 10, and transmit the control instructions to the corresponding terminal device 10. The cloud platform 30 will coordinate and manage each edge node 20.

[0116] The first control program is a conventional control program or a machine learning model that uses the local data of the terminal device 10 as input and generates control instructions for controlling the terminal device 10 based on its output. In some cases, the same terminal device 10 may correspond to multiple first control programs, each of which may use different types of local data from the terminal device 10 as input and generate control instructions for different control purposes based on the program output. For example, to control the movement of the lawn mower robot 11, the edge node 21 is equipped with a first movement control program that combines local data such as the positioning information of the lawn mower robot 11 to generate movement control instructions for the lawn mower robot 11. For another example, to control the charging of the lawn mower robot 11, the edge node 21 is also equipped with a first charging control program that combines local data such as the battery level of the lawn mower robot 11 to generate charging control instructions for the lawn mower robot 11. In other cases, a single first control program may use local data from multiple terminal devices 10 as input and generate corresponding control instructions for multiple terminal devices 10. For example, the edge node 21 is provided with a first charging control program, which can generate charging control instructions for the lawn mower robot 11 and the charging pile 13 by combining local data such as the power level of the lawn mower robot 11 and the charging history of the charging pile 13.

[0117] The control instruction can directly or indirectly control the actions of terminal devices 10 such as lawn mower robots. In some embodiments, the control instruction can be transmitted to the lawn mower robot, and the control instruction can carry relevant parameters such as travel speed, travel direction, and travel trajectory, so that the lawn mower robot can travel on the target path at a target speed and in a target direction after receiving the control instruction. In other embodiments, the control instruction can warn of dangerous conditions such as being close to a boundary line or a cliff, so that the lawn mower robot can perform operations such as stopping, decelerating, and avoiding after receiving the control instruction. In some other embodiments, the control instruction can instruct the lawn mower robot to return to the charging station for charging. In some further embodiments, the control instruction can be transmitted to a tablet computer or a smart phone user device, and the control instruction can inform the user of various information conditions of each terminal device 10 in the working area where the lawn mower robot is located.

[0118] In one embodiment, referring to FIG8 , after acquiring the local data of each terminal device 10, the edge node 20 further updates the first control program of each terminal device 10 using the local data of each terminal device 10. The specific content of the edge node 20 updating the control program using the local data can be found in the relevant description above and will not be repeated here.

[0119] In one embodiment, referring to FIG9 , the edge node 20 may also transmit local data obtained from each terminal device 10 to the cloud platform 30. The cloud platform 30 may use the local data obtained from the edge node 20 to update the first control program and transmit the updated first control program to the corresponding edge node 20. An edge node 20 may correspond to one or more first control programs. In some examples, the multiple first control programs corresponding to an edge node 20 include first control programs corresponding to various data types. After obtaining local data, the cloud platform 30 may update the first control program corresponding to the data type based on the data type of the local data. For example, after obtaining charging information of a lawn mower robot and / or charging station, the cloud platform 30 may update the charging first control program. In other examples, the multiple first control programs corresponding to an edge node 20 include the first control program of each terminal device 10 within the jurisdiction of the edge node 20. After obtaining local data, the cloud platform 30 may update the first control program corresponding to the data type of the terminal device 10 based on the terminal device 10 to which the local data belongs and the data type of the local data. For example, after obtaining the charging information of the lawn mower robot 11, the cloud platform 30 may update the charging first control program of the lawn mower robot 11.

[0120] In some embodiments, referring to Figure 10, before transmitting the local data of each terminal device 10 to the cloud platform 30, the edge node 20 also processes the local data of each terminal device 10, and then transmits the processed local data to the cloud platform 30. The data processing includes but is not limited to data cleaning such as duplicate data processing, missing data processing, and abnormal data processing, as well as image preprocessing operations such as cropping, compression, grayscale, and geometric changes. The cloud platform 30 will subsequently use the processed local data to update each first control program.

[0121] In one embodiment, referring to FIG11 , a lawn mower robot system includes multiple terminal devices 10 that need to work collaboratively. Taking multiple lawn mower robots in the lawn mower robot system as an example, an edge node 20 also schedules the multiple lawn mower robots in the lawn mower robot system based on local data obtained from each terminal device 10 and a second control program of the edge node 20. In some examples, multiple lawn mower robots collaborate to perform SLAM (Simultaneous Localization and Mapping) tasks. The edge node 23 may be equipped with a second SLAM control program. Combined with local data such as the positioning information of lawn mower robots 18, 19, etc., the edge node 23 can mobilize lawn mower robots 18, 19, etc. to travel along their respective target paths at their respective target speeds and directions and move to their respective target points.

[0122] In some embodiments, referring to FIG12 , after obtaining the local data of each terminal device 10, the edge node 20 uses the local data of each terminal device 10 to update the second control program of the edge node 20. The specific content of the edge node 20 using the local data to update the control program can be referred to the relevant description above and will not be repeated here. In other embodiments, the edge node 20 can also transmit the local data obtained from each terminal device 10 to the cloud platform 30. The cloud platform 30 can use the local data obtained from the edge node 20 to update the second control program and transmit the updated second control program to the corresponding edge node 20. The specific content of the cloud platform 30 using the local data to update the control program can be referred to the relevant description above and will not be repeated here.

[0123] The cloud platform 30's coordinated management of each edge node 20 includes not only the previously described operations of backing up, recording, scoring, and collecting and distributing the first and second control programs on each edge node 20, but also monitoring and evaluating the storage, computing, and communication resources of each edge node 20. In some examples, the cloud platform 30 can scale each edge node 20 and allocate channel bandwidth to each edge node 20.

[0124] Correspondingly, the lawn mower robot 10 used in the above-mentioned lawn mower robot system includes a drive component 110, a travel component 120, a communication component 130, and a processor 140. The drive component 110 includes a blade 111 and a drive motor 112 that drives the blade 111; the travel component 120 includes a travel wheel 121 and a travel motor 122 that drives the travel wheel 121; the communication component 130 is communicatively connected to the edge node 20 and is configured to transmit local data to the edge node 20 so that the edge node 20 generates control instructions based on the control program and local data. The edge node 20 is centrally managed by the cloud platform 30; the communication component 130 is also configured to receive control instructions transmitted by the edge node 20; and the processor 140 is electrically connected to the communication component 130 and is configured to control the actions of the lawn mower robot according to the control instructions.

[0125] Figure 13 shows a data interaction diagram for a robotic lawnmower system based on cloud-edge-end collaboration, another embodiment of the present application. The robotic lawnmower system includes a terminal device 10, an edge node 20, and a cloud platform 30. The specific physical carriers of the terminal device 10, edge node 20, and cloud platform 30, as well as the specific communication connection methods between the three, can be found in the previous description and will not be repeated here.

[0126] In this embodiment, the terminal device 10 can transmit the first data generated and / or collected by the terminal device 10 to the corresponding edge node 20. The edge node 20 processes the first data obtained from each terminal device 10 and generates second data. The cloud platform 30 coordinates and manages each edge node 20.

[0127] Among them, the first data is equivalent to the local data described above, and may include environmental data such as environmental images, as well as working status data such as positioning information, power information, and user information. In some embodiments, the edge node 20 may perform various data processing operations such as data cleaning and heterogeneous data integration on the first data of each terminal device 10 to convert the multi-source heterogeneous, erroneous, and redundant first data into second data that is easier for computer operation and analysis. In some examples, the data cleaning of the first data by the edge node 20 includes but is not limited to deleting duplicate values, filling missing values, outlier processing, data smoothing, noise processing, normalization, standardization, data dimensionality reduction, etc. In other examples, when the first data is image data, it may also include cropping and compression, grayscale, geometric transformation, image enhancement, etc.

[0128] In one embodiment, referring to Figure 14, after obtaining the second data, the edge node 20 returns the second data to the terminal device 10. The terminal device 10 can generate a control instruction according to the control program and the second data to control the lawn mower robot in the lawn mower robot system based on the generated control instruction.

[0129] In one embodiment, referring to FIG15 , after processing the second data from the terminal device 10, the edge node 20 also transmits the second data to the cloud platform 30. The cloud platform 30 may generate a control instruction based on the second data and the control program of the edge node 20 or the terminal device 10. In some examples, the cloud platform 30 may return the generated control instruction to the edge node 20 so that the edge node 20 forwards the control instruction to the corresponding terminal device 10. The specific content of the cloud platform 30 generating the control instruction based on the control program and related data can be referred to the relevant description above and will not be repeated here.

[0130] In one embodiment, referring to FIG16 , after processing the second data from the terminal device 10, the edge node 20 also transmits the second data to the cloud platform 30. The cloud platform 30 can use the second data to update the control program of the edge node 20 or the terminal device 10 and comprehensively manage the respective control programs. The specific details of how the cloud platform 30 uses the relevant data to update the control program and comprehensively manage the control program can be found in the previous description and are not further elaborated here.

[0131] In one embodiment, referring to FIG17 , the cloud platform 30 also transmits the control program to the corresponding edge node 20. After processing the second data, the edge node 20 may generate a control instruction based on the second data and the control program and transmit the control instruction to the corresponding terminal device 10, so that the terminal device 10 controls the actions of the lawn mower robot based on the control instruction. The specific details of how the edge node 20 generates the control instruction based on the control program and related data can be found in the previous description and will not be repeated here.

[0132] The cloud platform 30's coordinated management of each edge node 20 includes not only the previously described operations of backing up, recording, collecting, and distributing the second data on each edge node 20, but also monitoring and evaluating the storage, computing, and communication resources of each edge node 20. In some examples, the cloud platform 30 can scale each edge node 20 and allocate channel bandwidth to each edge node 20.

[0133] In some embodiments, the cloud platform 30 may also manage the second data obtained by each edge node 20, and the management of the second data includes organization, analysis, and mining. For example, assuming that there is a top-level task in the lawn mower robot system that requires the coordinated work of multiple terminal devices 10, and multiple lawn mower robots 18, 19, etc. collaboratively perform a SLAM task, the edge node 23 may process the original first data from the lawn mower robots 18, 19, etc., obtain second data representing a local map of the surrounding area of ​​the lawn mower robots 18, 19, etc., and transmit the second data to the cloud platform 30. After obtaining the second data, the cloud platform 30 may organize and analyze the local map to generate a global map of the working area of ​​the lawn mower robots 18, 19, etc.

[0134] Correspondingly, the lawn mower robot 10 used in the above-mentioned lawn mower robot system includes a drive component 110, a travel component 120, a communication component 130, and a processor 140. The drive component 110 includes a blade 111 and a drive motor 112 that drives the blade 111; the travel component 120 includes a travel wheel 121 and a travel motor 122 that drives the travel wheel 121; and the communication component 130 is communicatively connected to the edge node 20 and is configured to transmit first data to the edge node 20 so that the edge node 20 processes the first data and generates second data. The edge node 20 is centrally managed by the cloud platform 30.

[0135] 18 shows a data interaction diagram of an electric tool management system as an embodiment of the present application. The electric tool management system includes a terminal device 10, an edge node 20 and a cloud platform 30.

[0136] In this embodiment, the terminal device 10 may include at least one or more of a power tool, a battery pack, and a power management device. Specifically, it may include multiple power tools of different types located in different areas and belonging to different users, as well as power management devices such as battery packs, chargers, and adapters for these multiple power tools. In some embodiments, the terminal device 10 may also include related equipment that assists the operation of the power tools, such as charging stations, positioning base stations, and monitoring equipment, as well as user devices such as tablet computers and smart computers.

[0137] The terminal device 10 can be communicatively connected with the edge node 20, and can transmit the generated and / or collected first data to the edge node 20. The specific content of the communication connection and data transmission between the terminal device 10 and the edge node 20 can refer to the relevant description above and will not be repeated here. Among them, the first data includes real-time data and / or historical data, which can include real-time data such as user operation data, sensor data, working status data, etc. generated in real time during the use or autonomous operation of power tools, power management equipment, charging piles, positioning base stations, monitoring equipment, etc. by users, and can also include historical data such as the usage history or working history of the above-mentioned devices. In some embodiments, the first data also includes real-time data and historical data generated and / or collected by the user on the user device to control power tools and other equipment. The specific data type of the first data can be referred to in Table 3 below.

[0138] Table 3

[0139] The edge node 20 can be connected to communicate with some terminal devices 10, process the first data obtained from the terminal device 10 to generate second data, and transmit the second data to the cloud platform 30. The edge node 20 processes the first data to obtain the second data, including data cleaning and data integration of the first data. For specific content, please refer to the relevant description above and will not be repeated here. Among them, the computing power of the edge node 20 is greater than or equal to 1000TFLOPS to ensure the processing capability of dealing with massive data. FLOPS (Floating-point Operations Per Second) is a unit of measurement for server computing power, which represents the number of floating-point operations performed by a computer in one second. The computing power of the edge node 20 is greater than or equal to 1TFLOPS (Tera Floating-point Operations Per Second), which means that the number of floating-point operations that the edge node 20 can perform in one second exceeds 10. 12 In some cases, TOPS (Tera Operations Per Second) is also used as the unit of server computing power. 1TOPS represents the number of times a computer processor executes 10 operations per second. 12In some embodiments, the computing power of the edge node 20 can be greater than or equal to 1GFLOPS (Giga Floating-point Operations Per Second), that is, the number of floating-point operations that can be performed in one second exceeds 10. 9 , or greater than or equal to 1PFLOPS (Peta Floating-point Operations Per Second), that is, the number of floating-point operations that can be performed in one second exceeds 10 15 .

[0140] The cloud platform 30 can be in communication with the edge nodes 20 and comprehensively manage the second data obtained from the edge nodes 20 and each edge node 20. The cloud platform 30 can back up the second data on each edge node 20, perform historical records, and other operations to manage each edge node 20 for operations such as restarting and rolling back. The cloud platform 30 can also organize, analyze, and mine the second data to integrate big data to obtain deeper information. In some examples, the cloud platform 30 can also perform operations such as scaling capacity and channel bandwidth allocation on each edge node 20 based on the needs of each terminal device 10 and the capabilities of each edge node 20. For details, please refer to the relevant description above and will not be repeated here.

[0141] In one embodiment, some of the terminal devices 10 are directly connected to the edge node 20 for communication, while other terminal devices 10 other than these directly connected terminal devices 10 are not directly connected to the edge node 20 for communication. The first data generated and / or collected by these non-directly connected terminal devices 10 are forwarded to the edge node 20 by the directly connected terminal devices 10.

[0142] In some embodiments, the directly connected terminal device 10 establishes a connection with the edge node 20 based on technologies such as a local area network, a wide area network, 5G, and massive MIMO. These devices are mostly geographically close to the non-directly connected terminal devices 10. The non-directly connected terminal device 10 can establish a connection with the directly connected terminal device 10 based on technologies such as Bluetooth Low Energy (BLE), Near Field Communication (NFC), and Wireless Fidelity (WiFi), thereby enabling the directly connected terminal device 10 to transfer first data generated and / or collected by the non-directly connected terminal device 10 to the edge node 20. In some examples, the directly connected terminal device 10 may be a user device such as a tablet computer or a smartphone, while the non-directly connected terminal device 10 may be various power tools, power management devices such as chargers, adapters, and battery packs, as well as charging stations, positioning base stations, and monitoring equipment. The first data of the non-directly connected terminal device 10 is first transmitted to the user device, and then transmitted from the user device to the edge node 20.

[0143] In other embodiments, the non-directly connected terminal device 10 includes a battery pack, which can transmit the first data of the battery pack to the terminal device 10 such as the power tool equipped with the battery pack through the DT terminal, so that the terminal device 10 such as the power tool equipped with the battery pack transmits the first data of the battery pack to the edge node 20.

[0144] 19 shows a data interaction diagram of an electric tool management system as another embodiment of the present application. The electric tool management system includes a terminal device 10, an edge node 20 and a cloud platform 30.

[0145] In this embodiment, the terminal device 10 may include at least one or more of a power tool, a battery pack, and a power management device. Specifically, it may include multiple power tools of different types located in different areas and belonging to different users, as well as power management devices such as battery packs, chargers, and adapters for these multiple power tools. In some embodiments, the terminal device 10 may also include related equipment that assists the operation of the power tools, such as charging stations, positioning base stations, and monitoring equipment, as well as user devices such as tablet computers and smart computers.

[0146] The terminal device 10 can communicate with the edge node 20 and transmit the generated and / or collected local data to the edge node 20. The specific details of the communication connection and data transmission between the terminal device 10 and the edge node 20 can be referred to the relevant description above and will not be repeated here. The local data described here is equivalent to the first data described above and can be referred to the relevant description above. The specific data types can be referred to Table 3 above.

[0147] The edge node 20 can be connected to some terminal devices 10 for communication, and generate control instructions for the terminal device 10 based on the local data obtained from the terminal device 10 and the control program of the terminal device 10, and transmit the control instructions to the terminal device 10. The specific content of the edge node 20 generating the control instructions based on the local data and the control program can be referred to the relevant description above and will not be repeated here. Among them, the average communication delay between the edge node 20 and the terminal device 10 is less than or equal to 10ms to ensure real-time control of the terminal device 10. The communication connection between the edge node 20 and the terminal device 10 can be implemented based on technologies such as 5G and massive MIMO. In some embodiments, the average communication delay between the edge node 20 and the terminal device 10 can be less than or equal to 5ms, or less than or equal to 3ms.

[0148] The cloud platform 30 can communicate with the edge nodes 20 and comprehensively manage each edge node 20. The cloud platform 30 can back up the control programs on each edge node 20, record historical records, and other operations to manage each edge node 20 for restart, rollback, and other operations. The cloud platform 30 can also distribute models to each edge node 20 based on the timeliness and / or score of each control program. In some examples, the cloud platform 30 can also perform operations such as scaling capacity and channel bandwidth allocation for each edge node 20 based on the needs of each terminal device 10 and the capabilities of each edge node 20. For details, please refer to the relevant description above and will not be repeated here.

[0149] Similar to the previous description, some of the terminal devices 10 can be directly connected to the edge node 20 for communication, while other terminal devices 10 other than these directly connected terminal devices 10 are not directly connected to the edge node 20 for communication. The local data generated and / or collected by the non-directly connected terminal devices 10 are transferred to the edge node 20 by the directly connected terminal devices 10. For the specific content, please refer to the relevant description in the previous text and will not be repeated here.

[0150] The electric tool management system based on cloud-edge-end collaboration described in Figures 18 and 19 can realize a fleet service in an IoT scenario. Multiple terminal devices 10 including various electric tools, power management devices, charging piles, positioning base stations, monitoring equipment and user devices can belong to different users, but constitute the same group fleet. The edge node 20 and the cloud platform 30 will collaborate to provide services to each terminal device 10 in the group. This will be explained in conjunction with specific scenarios below.

[0151] In one embodiment, the power tool management system provides a loss prevention service to the fleet. The data transmitted by the power tool to the edge node 20 may include the user information and current location information of the current user. The data transmitted by the positioning base station and monitoring equipment to the edge node 20 may also include the user information, number information, and location information of the power tools within the positioning / monitoring range. When the power tool needs to be found, the user device sends a request to the edge node 20. The cloud and edge collaborate to use this information to analyze and determine the current location of the power tool and who is currently using it.

[0152] In one embodiment, the power tool management system provides power management services to the fleet. The power tool can transmit data such as current power and historical power to the edge node 20. The battery pack, charger, and adapter can transmit data such as charging and discharging voltage, current, and power. The charging pile can also transmit data such as current charging status and charging history. In one example, the cloud-edge collaboration can monitor the battery health status of power tools, power management equipment, etc., to notify the user to replace or repair the battery in time when the battery health status is poor. In another example, the cloud-edge collaboration can monitor the power of power tools, power management equipment, etc., to notify the user to charge when the power is low, or arrange and notify the charging plan based on the task calendar. In another example, the cloud-edge collaboration can monitor the charging and discharging process of power tools and power management equipment to ensure charging safety.

[0153] In one embodiment, the power tool management system provides safety management services to the fleet. The power tools can transmit data such as device temperature, device noise, working time, etc. to the edge node 20. The battery pack, charger, and adapter can transmit charging and discharging voltage, current, power, and other data. The monitoring equipment can transmit environmental images, environmental videos and other data within the monitoring range. The cloud-edge-end collaboration can monitor the temperature, voltage, current, vibration, and noise of power tools, power management equipment, etc., to provide early warning notifications and / or shutdown controls in the event of overtemperature, overcurrent, or overload. It can also monitor and alarm fires and other problems through image and video data.

[0154] In one embodiment, the power tool management system provides task management services to the fleet. In one example, each terminal device 10 can transmit its operation history to the edge node 20, and cloud-edge-end collaboration can evaluate the efficiency and cost of the operation tasks. In another example, each terminal device 10 can transmit data such as tool model, location information, power level information, and user information to the edge node 20, and cloud-edge-end collaboration can schedule tasks.

[0155] The above shows and describes the basic principles, main features and advantages of this application. Those skilled in the art should understand that the above embodiments do not limit this application in any form, and any technical solutions obtained by equivalent replacement or equivalent transformation fall within the scope of protection of this application.

Claims

1. A lawn mowing robot system based on cloud-edge-end collaboration, wherein: The lawn mowing robot system comprises: A terminal device, including a lawn mowing robot, wherein the terminal device is configured to at least collect local data; an edge node, which is in communication connection with the terminal device, and is configured to obtain the local data from the terminal device and update the control program of the terminal device using the local data; A cloud platform is connected to the edge node for communication, and the cloud platform is configured to obtain the control program from the edge node and to manage the control program in an overall manner.

2. The lawn mowing robot system according to claim 1, wherein: The edge node transmits the control program to the corresponding terminal device; the terminal device generates a control instruction of the terminal device according to the control program and the local data.

3. The lawn mowing robot system according to claim 1, wherein: The edge node generates a control instruction for the terminal device according to the control program and the local data, and transmits the control instruction to the corresponding terminal device.

4. The lawn mowing robot system according to claim 2 or 3, wherein: The terminal device controls the driving motor and / or the walking motor of the lawn mowing robot according to the control instruction.

5. The lawn mowing robot system according to claim 1, wherein: The edge node optimizes control parameters of the control program using the local data.

6. The lawn mowing robot system according to claim 1, wherein: The control program is a machine learning model, and the edge node uses the local data to train the original machine learning model and / or retrain the trained machine learning model.

7. The lawn mowing robot system according to claim 5, wherein: The edge node uses the local data to incrementally train the machine learning model.

8. The lawn mowing robot system according to claim 1, wherein: The terminal device also includes a charging pile or a positioning base station in the working area of ​​the lawn mowing robot, or a monitoring device near the working area of ​​the lawn mowing robot.

9. The lawn mowing robot system according to claim 1, wherein: The local data includes environmental data around the lawn mower robot and / or working status data of the lawn mower robot collected by the terminal device; the working status data of the lawn mower robot includes one or more of the environmental information, power information, positioning information, user information, and operation information of the lawn mower robot.

10. The lawn mowing robot system according to claim 1, wherein: The edge node and the terminal device, and / or the edge node and the cloud platform communicate using the fifth generation mobile communication technology, the sixth generation mobile communication technology, or the massive MIMO technology.

11. The lawn mowing robot system according to claim 1, wherein: The edge nodes include regional servers.

12. A lawn mowing robot system based on cloud-edge-end collaboration, wherein: The lawn mowing robot system comprises: A terminal device, including a lawn mowing robot, wherein the terminal device is configured to at least collect local data; an edge node, which is in communication connection with the terminal device, and is configured to obtain the local data from the terminal device, generate a control instruction for the terminal device according to the first control program and the local data, and transmit the control instruction to the terminal device; A cloud platform is connected to the edge nodes for communication, and the cloud platform is configured to perform overall management of the edge nodes.

13. The lawn mowing robot system according to claim 12, wherein: The edge node transmits the local data to the cloud platform; the cloud platform uses the local data to update the first control program of the edge node, and transmits the updated first control program to the edge node.

14. The lawn mowing robot system according to claim 13, wherein: The edge node processes the local data before transmitting the local data to the cloud platform, and transmits the processed local data to the cloud platform.

15. The lawn mowing robot system according to claim 12, wherein: The edge node updates the first control program using the local data and transmits the first control program to the cloud platform.

16. The lawn mowing robot system according to claim 12, wherein: The lawn mowing robot system includes a plurality of lawn mowing robots; the edge node schedules the plurality of lawn mowing robots according to the second control program and the local data.

17. The lawn mowing robot system according to claim 16, wherein: The cloud platform updates the second control program of the edge node using the local data, and transmits the updated second control program to the edge node.

18. The lawn mowing robot system according to claim 16, wherein: The edge node updates the second control program using the local data and transmits the second control program to the cloud platform.

19. The lawn mowing robot system according to claim 12, wherein: The average communication delay between the edge node and the terminal device is less than or equal to 10ms.

20. A lawn mowing robot system based on cloud-edge-end collaboration, wherein: The lawn mowing robot system comprises: A terminal device, including a lawn mowing robot, wherein the terminal device is configured to collect at least local first data; an edge node, which is in communication connection with the terminal device, and is configured to obtain the first data from the terminal device and perform data processing on the first data to generate second data; A cloud platform is connected to the edge nodes for communication, and the cloud platform is configured to perform overall management of the edge nodes.

21. The lawn mowing robot system according to claim 20, wherein: The edge node transmits the second data to the terminal device; the terminal device generates a control instruction according to the control program and the second data.

22. The lawn mowing robot system according to claim 20, wherein: The edge node transmits the second data to the cloud platform; the cloud platform generates a control instruction for the terminal device according to the control program and the second data.

23. The lawn mowing robot system according to claim 20, wherein: The edge node transmits the second data to the cloud platform; the cloud platform uses the second data to update the control program and comprehensively manages the control program.

24. The lawn mowing robot system according to claim 23, wherein: The cloud platform transmits the control program to the edge node; the edge node generates a control instruction for the terminal device according to the control program and the second data.

25. The lawn mowing robot system according to claim 20, wherein: The edge node performs data cleaning and / or data integration on the first data.

26. An electric tool management system based on cloud-edge-end collaboration, wherein: The electric tool management system comprises: A plurality of terminal devices, including one or more of a power tool, a battery pack, and a power management device, wherein the terminal device is configured to collect at least first data; an edge node, which is communicatively connected to at least some of the multiple terminal devices and has a computing power greater than or equal to 1000 TFLOPS, and the edge node is configured to obtain the first data from the terminal device and perform data processing on the first data to generate second data; The cloud platform is connected to the edge node for communication, and the cloud platform is configured to obtain the second data from the edge node and to perform overall management on the second data.

27. The power tool management system according to claim 26, wherein: The first data includes real-time data and / or historical data of the terminal device.

28. The power tool management system according to claim 26, wherein: The cloud platform manages the edge node to restart, roll back, and expand or shrink capacity according to the second data.

29. An electric tool management system based on cloud-edge-end collaboration, wherein: The electric tool management system comprises: A plurality of terminal devices, including one or more of a power tool, a battery pack, and a power management device, wherein the terminal device is configured to at least collect local data; an edge node, which is communicatively connected to at least some of the multiple terminal devices and has an average communication delay between the edge node and the terminal device of less than or equal to 10 ms, wherein the edge node is configured to obtain the local data from the terminal device, generate a control instruction for the terminal device according to a control program and the local data, and transmit the control instruction to the terminal device; A cloud platform is connected to the edge nodes for communication, and the cloud platform is configured to perform overall management of the edge nodes.

30. The power tool management system according to claim 29, wherein: The edge node updates the control program according to the local data and transmits the control program to the cloud platform.

31. The power tool management system according to claim 29, wherein: The local data includes sensor data and / or working status data of the terminal device; the working status data includes one or more of the environmental information, power information, positioning information, user information, and operation information of the terminal device.

32. The power tool management system according to claim 29, wherein: Some of the multiple terminal devices transmit the collected local data to other terminal devices, and the other terminal devices transfer the local data to the edge node.

33. The power tool management system according to claim 32, wherein: The battery pack transmits the local data to other terminal devices via the DT terminal.

34. The power tool management system according to claim 32, wherein: The terminal device transmits the local data to other terminal devices via a Bluetooth low energy consumption BLE unit and / or a near field communication NFC unit.

35. The power tool management system according to claim 29, wherein: The terminal device and the edge node, and / or the edge node and the cloud platform communicate using the fifth generation mobile communication technology.

36. The power tool management system according to claim 29, wherein: The terminal device and the edge node, and / or the edge node and the cloud platform communicate using large-scale MIMO technology.

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