Data processing method and device for unmanned system modeling

Abstract

The invention discloses a data processing method and a data processing device for unmanned system modeling, which are applied to a collaborative unmanned system so as to realize collaborative management of unmanned equipment in the unmanned system. The method comprises the following steps: acquiring to-be-processed equipment data; abstracting the to-be-processed equipment data based on equipment features to obtain equipment feature data, the equipment feature data being feature data for representing an equipment entity of the unmanned equipment; abstraction processing based on capability characteristics is carried out on the to-be-processed equipment data, capability characteristic data is obtained, and the capability characteristic data is characteristic data used for representing a function module of the unmanned equipment; and performing model construction processing based on an unmanned system cooperation scene on the equipment feature data and the capability feature data to obtain an unmanned system information model, thereby realizing cooperative management of the unmanned equipment according to the unmanned system information model. According to the invention, abstract modeling processing is carried out on the unmanned equipment based on OpenHarmony, so that the technical effect of improving the collaborative operation capability of the unmanned system is realized.

Description

Technical Field

[0001] This application relates to the field of the Internet of Things, and more specifically, to a data processing method and apparatus for modeling unmanned systems. Background Technology

[0002] With the rapid development of information technology, collaborative unmanned systems are becoming a key force in both civilian and scientific research fields. Within unmanned systems, different types and models of unmanned equipment need to interconnect to achieve information sharing, task allocation, and collaborative execution, building a complex system for collaborative operations. However, the various types of equipment in unmanned systems mostly use proprietary protocols at the link layer and network layer, resulting in significant differences in interfaces and architectures, making it difficult to achieve interoperability between devices from different manufacturers and of different types.

[0003] Therefore, existing collaborative unmanned systems suffer from low collaborative efficiency due to difficulties in interconnection and interoperability. Summary of the Invention

[0004] The main objective of this application is to provide a data processing method and apparatus for modeling unmanned systems, in order to solve the problem of low collaborative efficiency caused by the difficulty in interconnection in existing collaborative unmanned systems, and to achieve the technical effect of improving the collaborative operation capability and intelligence level of unmanned systems.

[0005] To achieve the above objectives, a first aspect of this application proposes a data processing method for modeling unmanned systems, applied to collaborative unmanned systems, to realize collaborative management of unmanned equipment in the unmanned system, the method comprising: Acquire device data to be processed, wherein the device data to be processed is relevant data used to represent unmanned equipment; The device data to be processed is subjected to abstract processing based on device features to obtain device feature data, wherein the device feature data is feature data used to represent the device entity of the unmanned device; The data of the device to be processed is subjected to abstract processing based on capability characteristics to obtain capability characteristic data, wherein the capability characteristic data is characteristic data used to represent the functional modules of the unmanned device; The device feature data and the capability feature data are processed to build a model based on the unmanned system collaborative scenario, so as to obtain an unmanned system information model, and to realize the collaborative management of unmanned equipment according to the unmanned system information model.

[0006] In some optional embodiments of this application, the device data to be processed is subjected to abstract processing based on device characteristics to obtain device characteristic data, including: The data of the device to be processed is abstracted based on the first device features to obtain the first device feature data, wherein the first device feature data is feature data used to represent the basic information of the unmanned device; The data of the device to be processed is subjected to abstract processing based on the second device features to obtain the second device feature data, wherein the second device feature data is feature data used to represent the static attributes of the unmanned device; The data of the device to be processed is abstracted based on the third device features to obtain the third device feature data, wherein the third device feature data is feature data used to represent the dynamic changes of the unmanned device; The device feature data is obtained based on the first device feature data, the second device feature data, and the third device feature data.

[0007] In some optional embodiments of this application, the data of the device to be processed is subjected to abstract processing based on capability characteristics to obtain capability characteristic data, including: The data of the device to be processed is subjected to abstract processing based on the first capability feature to obtain the first capability feature data, wherein the first capability feature data is feature data used to represent the capability module identifier; The data of the device to be processed is subjected to abstract processing based on the second capability feature to obtain the second capability feature data, wherein the second capability feature data is feature data used to represent the support of the capability module; The device data to be processed is abstracted based on the third capability feature to obtain the third capability feature data, wherein the third capability feature data is feature data used to represent the interaction specification of the capability module. The device data to be processed is subjected to abstract processing based on the fourth capability feature to obtain the fourth capability feature data, wherein the fourth capability feature data is feature data used to represent the capability module interface; The capability feature data is obtained based on the first capability feature data, the second capability feature data, the third capability feature data, and the fourth capability feature data.

[0008] In some optional embodiments of this application, the device feature data and the capability feature data are processed by model building based on unmanned system collaborative scenarios to obtain an unmanned system information model, including: The device feature data is processed by constructing a device information model based on a structure to obtain a device information model, wherein the device information model is a model used to represent device information; The capability feature data is processed by constructing a device function model based on a capability bitmap to obtain a device capability model, wherein the device capability model is a model used to represent the functions of the device; The equipment information model and the equipment capability model are mapped based on equipment entities to obtain the unmanned information system model.

[0009] In some optional embodiments of this application, after processing the device feature data and the capability feature data into a model based on an unmanned system collaborative scenario to obtain an unmanned system information model, the method further includes: Obtain updated device data, wherein the updated device data is relevant data used to indicate the addition of unmanned equipment; The updated device information is subjected to abstract processing based on device characteristics and capability characteristics to obtain updated device characteristic data and updated capability characteristic data. The equipment information model of the unmanned system information model is updated based on the updated equipment feature data to obtain the updated equipment information model. The equipment capability model of the unmanned system information model is updated based on the updated capability feature data to obtain an updated equipment capability model. The updated equipment information model and the updated equipment capability model are subjected to an update mapping process based on equipment entities to obtain an updated unmanned system information model.

[0010] In some optional embodiments of this application, after processing the device feature data and the device capability feature data into a model based on an unmanned system collaborative scenario to obtain an unmanned system information model, the method further includes: Acquire task data to be processed, wherein the task data to be processed is data used to represent collaborative tasks of unmanned systems; The task data to be processed is parsed based on functional requirements to obtain functional requirement data, wherein the functional requirement data is data used to represent the functional requirements of the unmanned system required to perform the task to be processed. The functional requirement data is subjected to device matching processing based on function mapping to obtain process device data, wherein the process device data is data used to represent devices with required functions; The process equipment data is filtered based on equipment status to obtain execution equipment data, wherein the execution equipment data is equipment data used to represent the execution of the unmanned system collaborative task.

[0011] According to a second aspect of this application, a data processing device for modeling unmanned systems is proposed, applied to collaborative unmanned systems to achieve collaborative management of unmanned equipment in the unmanned system, including: The data acquisition module is used to acquire data from the device to be processed, wherein the data from the device to be processed is relevant data representing the unmanned device; The device abstraction module is used to perform abstraction processing on the device data to be processed based on device features to obtain device feature data, wherein the device feature data is feature data used to represent the device entity of the unmanned device; The capability abstraction module is used to perform capability feature-based abstraction processing on the data of the device to be processed to obtain capability feature data, wherein the capability feature data is feature data used to represent the functional modules of the unmanned device. The model building module is used to process the equipment feature data and the capability feature data based on the unmanned system collaborative scenario to obtain the unmanned system information model, so as to realize the collaborative management of unmanned equipment according to the unmanned system information model.

[0012] In some optional embodiments of this application, the device abstraction module includes: The first device abstraction module is used to perform abstraction processing on the device data to be processed based on the first device features to obtain the first device feature data, wherein the first device feature data is feature data used to represent the basic information of the unmanned device. The second device abstraction module is used to perform abstraction processing on the device data to be processed based on the second device features to obtain the second device feature data, wherein the second device feature data is feature data used to represent the static attributes of the unmanned device. The third device abstraction module is used to perform abstraction processing on the device data to be processed based on the third device features to obtain the third device feature data, wherein the third device feature data is feature data used to represent the dynamic changes of unmanned equipment. The device feature data is obtained based on the first device feature data, the second device feature data, and the third device feature data.

[0013] According to a third aspect of this application, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing the computer to perform the above-described data processing method for unmanned system modeling.

[0014] According to a fourth aspect of this application, an electronic device is proposed, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to cause the at least one processor to perform the aforementioned data processing method for unmanned system modeling.

[0015] The technical solutions provided by the embodiments of this application may include the following beneficial effects: In this application, data on devices to be processed is acquired, wherein the data on devices to be processed is relevant data representing unmanned devices; the data on devices to be processed is subjected to abstraction processing based on device characteristics to obtain device feature data, wherein the device feature data is feature data representing the device entity of the unmanned device; the data on devices to be processed is subjected to abstraction processing based on capability characteristics to obtain capability feature data, wherein the capability feature data is feature data representing the functional modules of the unmanned device; the device feature data and the capability feature data are subjected to model construction processing based on unmanned system collaborative scenarios to obtain an unmanned system information model, so as to realize the collaborative management of unmanned devices according to the unmanned system information model. By abstracting and modeling unmanned devices based on OpenHarmony, the problem of low collaborative efficiency caused by the difficulty of interconnection in existing collaborative unmanned systems is solved, and the technical effect of improving the collaborative operation capability and intelligence level of unmanned systems is achieved. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings: Figure 1 A flowchart of a data processing method for modeling unmanned systems provided in this application; Figure 2 A flowchart of a data processing method for modeling unmanned systems provided in this application; Figure 3 A flowchart of a data processing method for modeling unmanned systems provided in this application; Figure 4 A flowchart of a data processing method for modeling unmanned systems provided in this application; Figure 5 A schematic diagram of a data processing device for modeling unmanned systems provided in this application. Detailed Implementation

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

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0020] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0021] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linked," and "socketing" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0022] OpenAtom OpenHarmony (hereinafter referred to as "OpenHarmony") is an open-source distributed operating system that supports cross-device collaboration across all scenarios. OpenHarmony's distributed soft bus technology provides the basic communication capabilities for device interconnection, enabling rapid device discovery, connection, networking, and data transmission within the system. This application proposes a data processing method for unmanned system modeling based on the OpenHarmony platform to address the problem of low collaborative efficiency in existing unmanned systems technologies.

[0023] In some optional embodiments of this application, a data processing method for modeling unmanned systems is proposed, applied to collaborative unmanned systems, to achieve collaborative management of unmanned equipment within the unmanned system. Figure 1 A flowchart of a data processing method for unmanned system modeling provided in this application is shown below. Figure 1 As shown, the method includes the following steps: S101: Obtain data from the device to be processed; The data to be processed is the data used to represent unmanned equipment. The data to be processed includes equipment entity information and equipment capability information. Equipment entity information includes basic information, static attributes, status information and other information associated with the equipment entity. Equipment capability information includes information on the functional modules in the equipment that can complete the specified tasks.

[0024] S102: Perform abstract processing based on device characteristics on the data of the device to be processed to obtain device characteristic data; Equipment feature data refers to the feature data used to represent the equipment entity of unmanned equipment; In some optional embodiments of this application, a data processing method for modeling unmanned systems is proposed. Figure 2 A flowchart of a data processing method for unmanned system modeling provided in this application is shown below. Figure 2 As shown, the method includes the following steps: S201: Perform abstract processing on the device data to be processed based on the first device characteristics to obtain the first device characteristic data; The first set of equipment characteristic data consists of feature data representing the basic information of unmanned equipment. This basic information is determined by the equipment manufacturer at the time of manufacture and includes core identification information, manufacturing information, and technical specifications. It is read-only and cannot be altered. Core identification information describes the set of codes and attributes assigned by the equipment manufacturer to distinguish the equipment, including equipment type and serial number. Manufacturing information records key information from the equipment manufacturing process, including manufacturer, factory, and production batch, facilitating quality control and iterative upgrades. Technical specifications describe various characteristics of the equipment, including its physical characteristics and functional performance, such as hardware version information, operating environment requirements (e.g., temperature, humidity, altitude, electromagnetic compatibility standards), and the equipment's own physical characteristic parameters.

[0025] S202: Perform abstract processing on the data of the device to be processed based on the second device characteristics to obtain the second device characteristic data; The second set of equipment characteristic data represents the static attributes of unmanned equipment. Static attributes of unmanned equipment are a set of stable attributes that rarely change within the unmanned system platform. These attributes include three dimensions: basic equipment attribute information, organizational affiliation, and task binding information. This provides support for the entire lifecycle management of the equipment. Basic equipment attribute information is the essential configuration information required when the equipment connects to the system. It is used to uniquely identify the equipment, define communication capabilities, and standardize control interfaces. This includes equipment identification information (such as a globally unique identifier, equipment name, and equipment type), communication configuration (network address and protocol list), driver configuration information, and capability description information. Organizational affiliation information describes the organization to which the equipment belongs, facilitating cross-organizational collaboration. A structure is used to describe the organization ID and organization name, where the ID is the organization's unique identifier. Task binding information describes the task information the equipment is currently participating in, using a structure to describe the task ID, task name, and task location.

[0026] S203: Perform abstract processing on the data of the device to be processed based on the characteristics of the third device to obtain the third device characteristic data; The third type of equipment feature data represents the dynamic changes of unmanned equipment. Equipment status information describes the dynamic characteristics of the equipment during operation; its values ​​are updated in real time as the equipment's operating environment and physical conditions change, ensuring that the equipment management module has real-time control over the equipment's operational status, including data types such as connection status, location information, and battery status. A certain equipment status is described through four aspects: status identifier, data features, values, and associated information. The status identifier uniquely identifies the equipment status, including a status ID as a globally unique identifier and a semantic description field as the status name. Data features define the structured description specifications of status parameters in the system, including the field names used, units of measurement, value types and ranges, measurement accuracy, and update frequency. Values ​​record the status at a specific point in time, including the initial and current values. Associated information records the source of the status data, such as data acquisition equipment and software algorithms.

[0027] S204: Obtain equipment feature data based on the first equipment feature data, the second equipment feature data, and the third equipment feature data.

[0028] By abstracting the basic information, static attributes, and status information of the equipment, a logical model of the equipment layer of the unmanned system is constructed. The unmanned equipment is used as the data node in the unmanned system. Each "unmanned equipment" node is associated with the basic information, static attributes, and status information of the equipment. The first equipment feature data, the second equipment feature data, and the third equipment feature data mentioned above are all associated with the unmanned equipment entity node.

[0029] S103: Perform abstract processing based on capability characteristics on the data of the device to be processed to obtain capability characteristic data.

[0030] Capability characteristic data refers to the feature data used to represent the functional modules of unmanned equipment. Capability abstraction is performed on the unmanned equipment, abstracting it into multiple modules based on capability characteristics. For example, an unmanned equipment includes various core components, such as a perception module, navigation module, planning module, control module, communication module, human-machine interaction module, and payload module. Each module can provide one or more capabilities. For instance, the perception module of an unmanned equipment uses various sensors to perceive the environment; the navigation module integrates a navigation satellite system to provide timing, positioning, and path planning capabilities.

[0031] In some optional embodiments of this application, a data processing method for modeling unmanned systems is proposed. Figure 3 A flowchart of a data processing method for unmanned system modeling provided in this application is shown below. Figure 3 As shown, the method includes the following steps: S301: Perform abstract processing on the data of the device to be processed based on the first capability feature to obtain the first capability feature data; The first capability feature data is feature data used to represent the capability module identifier; the first capability feature data is data used to represent the basic capability information, which is information used to uniquely identify the capability, such as capability ID, capability name, capability type, and description.

[0032] S302: Perform abstract processing on the data of the device to be processed based on the second capability feature to obtain the second capability feature data; The second capability feature data is the feature data used to represent the capability module support; the capability module support information describes the support conditions required for the operation of the capability, including the dependent hardware devices, software libraries or processing algorithms.

[0033] S303: Perform abstract processing on the data of the device to be processed based on the third capability feature to obtain the third capability feature data; The third capability feature data is the feature data used to represent the interaction specifications of capability modules; the interaction specifications of capability modules define the input and output data formats when capability modules interact with the management platform and unmanned applications, including data types, value ranges, precision, etc.

[0034] S304: Perform abstract processing on the data of the device to be processed based on the fourth capability feature to obtain the fourth capability feature data; The fourth capability feature data is the feature data used to represent the capability module interface; the capability module interface information is the information defining the capability interface, which includes the name, description, calling commands and parameters, return value, and other information of the interface provided by the capability module to the outside world.

[0035] S305: Obtain capability feature data based on the first capability feature data, the second capability feature data, the third capability feature data, and the fourth capability feature data.

[0036] By breaking down the achievable functions of unmanned equipment and performing capability-based abstraction, multiple basic capabilities are obtained. Each capability is then abstractly modeled, and a unified capability interface specification is constructed from four dimensions: basic capability information, hardware and software dependencies, input and output specifications, and standardized interface definitions. This enables the management and invocation of various functional modules within the unmanned system.

[0037] S104: Process the equipment feature data and capability feature data into a model based on the collaborative scenario of unmanned systems to obtain the unmanned system information model.

[0038] This application aims to achieve collaborative management of unmanned equipment based on an unmanned system information model. The unmanned system information model in this application is developed based on OpenHarmon. The unmanned system information model obtained by abstracting and modeling unmanned equipment is adapted to OpenHarmon, and an unmanned equipment type model is constructed according to the OpenHarmony equipment management subsystem architecture specification. Unmanned equipment is then incorporated into the equipment management system as a new resource node.

[0039] In some optional embodiments of this application, a data processing method for modeling unmanned systems is proposed. Figure 4 A flowchart of a data processing method for unmanned system modeling provided in this application is shown below. Figure 4 As shown, the method includes the following steps: S401: Perform structure-based equipment information model construction on the equipment feature data to obtain the equipment information model; The equipment information model is a model used to represent equipment information; Based on device characteristic data, a new "unmanned device" category is added to the distributed device management module of OpenHarmony. The standardized definition is completed by extending the DeviceType enumeration class. A new "umannedDevice" unmanned device type identifier is added and assigned a unique code to ensure the uniqueness of the unmanned device type in the system.

[0040] The DeviceInfo structure describes the information and attributes of a device, providing a unified information structure for device management and collaborative interaction. It includes basic device information and some static attribute information. The DeviceInfo structure is supplemented based on device characteristic data, including: clarifying the organizational structure to which the device belongs by nesting an Organization structure, introducing a Mission structure to describe associated task parameters, and adding status information to it, resulting in a supplemented DeviceInfo structure used to describe the information and attributes of unmanned devices.

[0041] S402: Perform equipment function model construction processing on the capability feature data based on the capability bitmap to obtain the equipment capability model; A device capability model is a model used to represent the functions that a device has; Based on capability characteristic data, the device service capabilities are enumerated through a capability bitmap, and this capability bitmap is stored as a core attribute in the DeviceInfo structure, realizing the mapping relationship between capabilities and device entities. Bitmaps are set for core functional modules such as navigation and positioning, environmental perception, path planning, and motion control. The scalable bits of the capability bitmap support the dynamic expansion of the capability set, so that unmanned equipment can flexibly configure functional hardware according to task requirements in complex environments, meeting the needs of various application scenarios of unmanned systems.

[0042] Each capability is described in a standardized manner using the capabilityINFO structure. The basic information of the capability defines its global identifier and type. Capability types are categorized according to the functional modules of the unmanned equipment, such as perception, navigation, and control. Hardware dependencies are defined by specifying the names of the hardware and software, the hardware model or the version number of the corresponding software algorithm library, and the dependency level (required or optional). Input / output specifications define various attributes of input and output data, including parameter names, data types, value ranges, precision, and units of measurement. Hardware device interface specifications are defined, including the interface name, communication protocol, calling method (synchronous or asynchronous), input / output parameters, and status return information.

[0043] Taking a LiDAR functional module as an example, the basic information of the capability is defined by the global identifier and type of the capability. The global identifier of the LiDAR functional module is "LiDAR", and the capability type is perception. For the radar module, the hardware dependency points to a specific model of radar equipment, and the software dependency points to the point cloud algorithm library used to realize radar data visualization. All of the above hardware and software dependencies are necessary to ensure the complete implementation of the radar module's functions. The radar module's input data is the acquisition frequency, and the output data is point cloud data. The radar hardware device interface specification is defined, including the interface name, communication protocol, calling method (synchronous or asynchronous), input and output parameters, and status return information.

[0044] S403: Perform mapping processing based on equipment entities on the equipment information model and equipment capability model to obtain the unmanned information system model.

[0045] In some optional embodiments of this application, a data processing method for unmanned system modeling is proposed. After obtaining the unmanned system information model, the method further includes: The process involves: acquiring updated equipment data, which represents data related to newly added unmanned equipment; performing abstraction processing on the updated equipment information based on equipment features and capability features to obtain updated equipment feature data and updated capability feature data; performing model update processing on the equipment information model of the unmanned system information model based on the updated equipment feature data to obtain an updated equipment information model; performing model update processing on the equipment capability model of the unmanned system information model based on the updated capability feature data to obtain an updated equipment capability model; and performing update mapping processing on the updated equipment information model and the updated equipment capability model based on equipment entities to obtain an updated unmanned system information model.

[0046] In some optional embodiments of this application, after obtaining the unmanned system information model, the method further includes: The process involves: acquiring task data to be processed, which represents data used to describe collaborative tasks of unmanned systems; parsing the task data based on functional requirements to obtain functional requirement data, which represents data used to describe the functional requirements of the unmanned system needed to execute the task; performing device matching processing based on function mapping on the functional requirement data to obtain process device data, which represents data used to describe devices with the required functions; establishing associations between devices and their affiliated organizations through the unmanned system information model to clarify the affiliation relationship, enabling the scheduling of unmanned resources between organizations, and supporting cross-organizational collaboration of unmanned systems; and filtering the process device data based on device status to obtain execution device data, which represents data used to describe devices executing collaborative tasks of the unmanned system. Maintaining device connection status through heartbeat detection, including uninitialized, registered, task group online, offline / deregistered, etc.

[0047] In unmanned system business scenarios, when task requirements change, the functional modules on the unmanned equipment are adjusted according to the updated task requirements. After the equipment is connected, if the task requirements change, the identifier of the new functional module can be added to the attribute of the equipment's "capability information", thereby realizing the on-demand loading and real-time switching of the equipment's functional modules, ensuring the scalability of the equipment's capabilities, and reducing the workload of development and maintenance through code reuse.

[0048] In some optional embodiments of this application, a data processing device for modeling unmanned systems is proposed, applied to collaborative unmanned systems, to achieve collaborative management of unmanned equipment in the unmanned system. Figure 5 A schematic diagram of a data processing device for unmanned system modeling provided in this application is shown below. Figure 5 As shown, it includes: The data acquisition module 51 is used to acquire data of the device to be processed, wherein the data of the device to be processed is relevant data representing the unmanned device; The device abstraction module 52 is used to perform abstraction processing on the device data to be processed based on device features to obtain device feature data, wherein the device feature data is feature data used to represent the device entity of the unmanned device; Capability abstraction module 53 is used to perform capability feature-based abstraction processing on the data of the device to be processed to obtain capability feature data, wherein the capability feature data is feature data used to represent the functional modules of the unmanned device; The model building module 54 is used to perform model building processing on the equipment feature data and the capability feature data based on the unmanned system collaborative scenario to obtain the unmanned system information model, so as to realize the collaborative management of unmanned equipment according to the unmanned system information model.

[0049] In some optional embodiments of this application, a data processing device for modeling unmanned systems is proposed, wherein the device abstraction module includes: The first device abstraction module is used to perform abstraction processing on the device data to be processed based on the first device features to obtain the first device feature data, wherein the first device feature data is feature data used to represent the basic information of the unmanned device. The second device abstraction module is used to perform abstraction processing on the device data to be processed based on the second device features to obtain the second device feature data, wherein the second device feature data is feature data used to represent the static attributes of the unmanned device. The third device abstraction module is used to perform abstraction processing on the device data to be processed based on the third device features to obtain the third device feature data, wherein the third device feature data is feature data used to represent the dynamic changes of unmanned equipment. The device feature data is obtained based on the first device feature data, the second device feature data, and the third device feature data.

[0050] The specific methods of execution of each unit in the above embodiments have been described in detail in the embodiments of the method, and will not be elaborated here.

[0051] In summary, this application involves: acquiring device data to be processed, wherein the device data to be processed is relevant data representing unmanned equipment; performing abstract processing based on device characteristics on the device data to obtain device feature data, wherein the device feature data is feature data representing the device entity of the unmanned equipment; performing abstract processing based on capability characteristics on the device data to be processed to obtain capability feature data, wherein the capability feature data is feature data representing the functional modules of the unmanned equipment; and performing model construction processing based on unmanned system collaborative scenarios on the device feature data and the capability feature data to obtain an unmanned system information model, thereby realizing collaborative management of unmanned equipment based on the unmanned system information model. By abstracting and modeling unmanned equipment based on OpenHarmony, the problem of low collaborative efficiency caused by the difficulty in interconnection in existing collaborative unmanned systems is solved, achieving the technical effect of improving the collaborative operation capability and intelligence level of unmanned systems.

[0052] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0053] Obviously, those skilled in the art should understand that the various units or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0054] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A data processing method for modeling unmanned systems, characterized in that, The method is applied to a cooperative unmanned system to realize cooperative management of unmanned devices in the unmanned system, and the method comprises: Obtaining to-be-processed device data, wherein the to-be-processed device data is related data for representing an unmanned device; Performing device feature-based abstraction processing on the to-be-processed device data to obtain device feature data, wherein the device feature data is feature data for representing a device entity of the unmanned device; Performing capability feature-based abstraction processing on the to-be-processed device data to obtain capability feature data, wherein the capability feature data is feature data for representing a functional module of the unmanned device; Performing model construction processing on the device feature data and the capability feature data based on a cooperative scenario of the unmanned system to obtain an unmanned system information model, so as to realize cooperative management of the unmanned device according to the unmanned system information model.

2. The data processing method according to claim 1, characterized in that, The device feature-based abstraction processing on the to-be-processed device data to obtain device feature data comprises: Performing first device feature-based abstraction processing on the to-be-processed device data to obtain first device feature data, wherein the first device feature data is feature data for representing basic information of the unmanned device; Performing second device feature-based abstraction processing on the to-be-processed device data to obtain second device feature data, wherein the second device feature data is feature data for representing static attributes of the unmanned device; Performing third device feature-based abstraction processing on the to-be-processed device data to obtain third device feature data, wherein the third device feature data is feature data for representing dynamic changes of the unmanned device; The device feature data is obtained according to the first device feature data, the second device feature data, and the third device feature data.

3. The data processing method of claim 1, wherein, The capability feature-based abstraction processing on the to-be-processed device data to obtain capability feature data comprises: Performing first capability feature-based abstraction processing on the to-be-processed device data to obtain first capability feature data, wherein the first capability feature data is feature data for representing an identifier of a capability module; Performing second capability feature-based abstraction processing on the to-be-processed device data to obtain second capability feature data, wherein the second capability feature data is feature data for representing support of the capability module; Performing third capability feature-based abstraction processing on the to-be-processed device data to obtain third capability feature data, wherein the third capability feature data is feature data for representing interaction specifications of the capability module; Performing fourth capability feature-based abstraction processing on the to-be-processed device data to obtain fourth capability feature data, wherein the fourth capability feature data is feature data for representing an interface of the capability module; The capability feature data is obtained according to the first capability feature data, the second capability feature data, the third capability feature data, and the fourth capability feature data.

4. The data processing method of claim 1, wherein, The model construction processing on the device feature data and the capability feature data based on the cooperative scenario of the unmanned system to obtain the unmanned system information model comprises: The device feature data is subjected to structure-based device information model construction processing to obtain a device information model, wherein the device information model is a model for representing device information; The capability feature data is subjected to capability bitmap-based device function model construction processing to obtain a device capability model, wherein the device capability model is a model for representing functions possessed by the device; The device information model and the device capability model are subjected to device entity-based mapping processing to obtain the unmanned information system model.

5. The data processing method of claim 1, wherein, After the device feature data and the capability feature data are subjected to unmanned system collaborative scenario-based model construction processing to obtain an unmanned system information model, the method further comprises: obtaining updated device data, wherein the updated device data is related data for representing newly added unmanned devices; subjecting the updated device information to device feature and capability feature-based abstract processing to obtain updated device feature data and updated capability feature data; subjecting the device information model of the unmanned system information model to model update processing based on the updated device feature data to obtain an updated device information model; subjecting the device capability model of the unmanned system information model to model update processing based on the updated capability feature data to obtain an updated device capability model; subjecting the updated device information model and the updated device capability model to device entity-based update mapping processing to obtain an updated unmanned system information model.

6. The data processing method of claim 1, wherein, After the device feature data and the device capability feature data are subjected to unmanned system collaborative scenario-based model construction processing to obtain an unmanned system information model, the method further comprises: obtaining to-be-processed task data, wherein the to-be-processed task data is data for representing unmanned system collaborative tasks; subjecting the to-be-processed task data to function requirement-based analysis processing to obtain function requirement data, wherein the function requirement data is data for representing function requirements of the unmanned system required for executing the to-be-processed tasks; subjecting the function requirement data to function mapping-based device matching processing to obtain process device data, wherein the process device data is data for representing devices having the required functions; subjecting the process device data to device state-based screening processing to obtain execution device data, wherein the execution device data is data for representing devices executing the unmanned system collaborative tasks.

7. A data processing apparatus for modeling of unmanned systems, comprising: The application is applied to a collaborative unmanned system to realize collaborative management of unmanned devices in the unmanned system, comprising: a data acquisition module configured to acquire to-be-processed device data, wherein the to-be-processed device data is related data for representing unmanned devices; a device abstracting module configured to subject the to-be-processed device data to device feature-based abstract processing to obtain device feature data, wherein the device feature data is feature data for representing device entities of the unmanned devices; a capability abstracting module configured to subject the to-be-processed device data to capability feature-based abstract processing to obtain capability feature data, wherein the capability feature data is feature data for representing function modules of the unmanned devices; A model construction module is configured to perform model construction processing on the device feature data and the capability feature data based on a collaborative scenario of an unmanned system, to obtain an unmanned system information model, and to implement collaborative management of unmanned devices based on the unmanned system information model.

8. The data processing apparatus according to claim 7, characterized in that, The device abstraction module includes: A first device abstraction module is configured to perform abstraction processing on the to-be-processed device data based on a first device feature, to obtain first device feature data, wherein the first device feature data is feature data used to represent basic information of unmanned devices. A second device abstraction module is configured to perform abstraction processing on the to-be-processed device data based on a second device feature, to obtain second device feature data, wherein the second device feature data is feature data used to represent static attributes of unmanned devices. A third device abstraction module is configured to perform abstraction processing on the to-be-processed device data based on a third device feature, to obtain third device feature data, wherein the third device feature data is feature data used to represent dynamic changes of unmanned devices. The device feature data is obtained based on the first device feature data, the second device feature data, and the third device feature data.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the data processing method for unmanned system modeling according to any one of claims 1-6.

10. An electronic device, comprising: includes: at least one processor; and a memory connected in communication with the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to make the at least one processor execute the data processing method for unmanned system modeling according to any one of claims 1-6.

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