A heterogeneous inter-system semantic interaction method, device and system

Abstract

The application discloses a heterogeneous system semantic interaction method, device and system, which is applied to semantic interaction of multiple systems, wherein the system at least includes a management platform, a first subsystem and a second subsystem, and the first subsystem includes an unmanned system, and the method comprises the following steps: in the case that an interaction instruction sent by the management platform is received, the first subsystem receives data information sent by the second subsystem; the data information is decoded based on a first private data model to obtain decoded data information; and the decoded data information is coded based on a public metadata model to obtain semantic information of the second subsystem. The received data information is decoded and coded through the private data model and the public metadata model, so that the semantic information is obtained, the steps of semantic interoperation are simplified, and the semantic information is more efficient and more accurate.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a method, apparatus and system for semantic interaction between heterogeneous systems. Background Technology

[0002] With the rapid development and widespread application of unmanned systems such as drones, unmanned vehicles, and unmanned surface vessels, the data perception, intelligent decision-making, and collaborative control capabilities of various unmanned systems are constantly improving. This places increasingly higher demands on data exchange, data understanding, and data application during collaborative task execution by heterogeneous unmanned systems. Typically, due to the diversity of data exchange formats, syntactic and semantic interoperability between heterogeneous systems is achieved through one-to-one format conversion. This often leads to ambiguity. Furthermore, the rapid pace of unmanned system updates and the frequent changes in data exchange formats between different versions of the same type of unmanned system due to new platform capabilities or new task capabilities further exacerbate syntactic interoperability problems, while semantic interoperability issues are even more challenging.

[0003] In view of this, how to efficiently and accurately achieve syntactic interoperability and semantic interoperability between unmanned systems in heterogeneous systems has become an urgent problem to be solved in the process of intelligent development. Summary of the Invention

[0004] This application provides a method for semantic interaction between heterogeneous systems, a semantic device for semantic interaction between heterogeneous systems, a semantic interaction system for semantic interaction between heterogeneous systems, a computing device, and a computer-readable storage medium, solving the problem of difficult semantic interaction operation between heterogeneous systems in the prior art.

[0005] According to a first aspect of the embodiments of this specification, a semantic interaction method between heterogeneous systems is provided, applied to the semantic interaction of multiple systems, wherein the systems at least include a management platform, a first subsystem, and a second subsystem, and the first subsystem includes an unmanned system, characterized in that it includes:

[0006] Upon receiving an interactive instruction from the management platform, the first subsystem receives data information sent by the second subsystem;

[0007] Based on the first private data model, the data information is decoded to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, which is shared with the first subsystem before receiving the collaborative task and executing the interaction instruction, and is generated according to actual needs.

[0008] Based on the public metadata model, the decoded data information is decoded to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in the multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

[0009] Optionally, before receiving the interaction instruction sent by the management platform, the process includes:

[0010] Obtain the interactive semantic metadata generated during the execution of collaborative tasks by the multiple systems;

[0011] The interaction semantic metadata is abstracted and classified to obtain interaction semantic fields;

[0012] The interaction semantic fields are standardized to construct an interaction semantic list;

[0013] By formatting and converting the data to represent the interactive semantic list, human-computer readable interactive semantic metadata is generated.

[0014] Based on the interactive semantic metadata, a public metadata model is generated and pre-stored in the multiple systems.

[0015] Optionally, before receiving the interaction instruction sent by the management platform, the process further includes:

[0016] Based on the type of the collaborative task and the public metadata model pre-stored in the multiple systems, a private data model is constructed in each system, wherein the private data model includes at least: a first private data model of the second subsystem and a second private data model of the first subsystem.

[0017] Optionally, the step of constructing a private data model in each system based on the type of the collaborative task and the public metadata model pre-stored in the multiple systems includes:

[0018] Based on the type of the collaborative task, determine the interactive semantic metadata related to the type of collaborative task in the public metadata model;

[0019] Based on the interactive semantic metadata and the semantic metadata in the process of each system executing collaborative tasks, an initial private data model is constructed.

[0020] By formatting the initial private data model for data storage, a private data model is generated and pre-stored in various systems.

[0021] Optionally, upon receiving an interaction instruction from the management platform, the first subsystem receives data information sent by the second subsystem, including:

[0022] The data information sent by the second subsystem is received through wired or wireless communication, wherein the data information is encoded data information obtained by the second subsystem after encoding the transmitted data according to the first private data model.

[0023] Optionally, the step of decoding the data information based on the first private data model to obtain decoded data information includes:

[0024] Based on the encoded data information, a first private data model of the system corresponding to the encoded data information is determined;

[0025] Based on the first private data model of the system, the encoded data information is decoded to obtain decoded data information.

[0026] Optionally, the step of decoding the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem includes:

[0027] Based on the aforementioned public metadata model, the decoded data information is format-converted to obtain human-computer readable interactive semantic data;

[0028] The semantic information of the second subsystem is obtained by semantically parsing the human-computer readable interactive semantic data through the public metadata model.

[0029] Optionally, the method further includes:

[0030] The system receives collaborative task instructions from the first subsystem and the second subsystem sent by the management platform, wherein the collaborative task instructions include a collaborative task type.

[0031] Send the second private data model of the first subsystem and the first private data model of the second subsystem to the management platform;

[0032] Receive the execution instructions sent by the management platform, which are generated based on the collaborative task type and the first private data model and the second private data model;

[0033] If the first private data model and the second private data model satisfy the collaborative task type, execute the interaction instruction;

[0034] If the first private data model and / or the second private data model does not meet the collaborative task type, an update instruction is executed.

[0035] According to a second aspect of the embodiments of this specification, a semantic interaction device for heterogeneous systems is provided, characterized in that it includes:

[0036] The data receiving module is configured such that, upon receiving an interactive instruction from the management platform, the first subsystem receives data information sent by the second subsystem;

[0037] The decoding module is configured to decode the data information based on the first private data model to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, which is shared with the first subsystem before the second subsystem receives the collaborative task and executes the interaction instruction, and is generated according to actual needs.

[0038] The decoding module is configured to decode the decoded data information based on a public metadata model to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in the multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

[0039] According to a third aspect of the embodiments of this specification, a semantic interaction system between heterogeneous systems is provided, applied to a management platform, a first subsystem, and a second subsystem, characterized in that it includes:

[0040] A management platform is used to send interactive instructions to the first subsystem and the second subsystem;

[0041] The second subsystem is used to send the first private data model to the first subsystem and send data information to the first subsystem when it receives the interaction instructions sent by the management platform.

[0042] The first subsystem is used to decode the data information based on the first private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem. The public metadata model is human-computer readable interactive semantic metadata that is pre-stored in the multiple systems and obtained by the multiple systems during the execution of collaborative tasks.

[0043] The first subsystem is used to send the second private data model to the second subsystem and send data information to the second subsystem upon receiving an interactive instruction from the management platform.

[0044] The second subsystem is used to decode the data information based on the second private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the first subsystem.

[0045] According to a fourth aspect of the embodiments of this specification, a computing device is provided, comprising:

[0046] Memory and processor;

[0047] The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-described semantic interaction method between heterogeneous systems.

[0048] According to a fifth aspect of the embodiments of this specification, a computer-readable storage medium is provided that stores computer-executable instructions, which, when executed by a processor, implement the steps of the above-described semantic interaction method between heterogeneous systems.

[0049] The heterogeneous system semantic interaction method provided in this application embodiment is applied to the semantic interaction of multiple systems. Each system includes at least a management platform, a first subsystem, and a second subsystem. The first subsystem includes an unmanned system. Specifically, when the first and second subsystems need to exchange information while working collaboratively, taking the first subsystem as the data information receiver as an example, firstly, upon receiving an interaction instruction from the management platform, the first subsystem receives data information sent by the second subsystem. Then, based on a first private data model, the data information is decoded to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, generated according to actual needs and shared with the first subsystem before receiving the collaborative task and executing the interaction instruction. Finally, based on a public metadata model, the decoded data information is decoded to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in the multiple systems and is human-machine readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

[0050] Upon receiving interactive instructions from the management platform, each system with interactive needs shares its private data model. By using the private data models of each system and the pre-stored public metadata model, the system decodes and encodes the data information to obtain the semantic information of the system. This greatly simplifies the steps of semantic interoperability and makes the acquisition of semantic information of each system more efficient and accurate.

[0051] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0052] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the scope of this application. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings:

[0053] Figure 1 This is a schematic diagram illustrating a scenario of a semantic interaction method between heterogeneous systems provided in the embodiments of this specification;

[0054] Figure 2 This is a flowchart of a semantic interaction method between heterogeneous systems provided in the embodiments of this specification;

[0055] Figure 3 This is a schematic diagram of a semantic interaction method between heterogeneous systems provided in the embodiments of this specification;

[0056] Figure 4 This is a schematic diagram of another semantic interaction method between heterogeneous collaborative systems provided in an embodiment of this application;

[0057] Figure 5 This is a block diagram of a semantic interaction device between heterogeneous systems provided in an embodiment of this application;

[0058] Figure 6 This is a flowchart of a semantic interaction system between heterogeneous systems provided in an embodiment of this application. Detailed Implementation

[0059] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0060] With the rapid development and widespread application of unmanned systems (UAVs), unmanned vehicles, and unmanned surface vessels (USVs), the data perception, intelligent decision-making, and collaborative control capabilities of various UAVs are constantly improving. This places increasingly higher demands on data exchange, data understanding, and data application during collaborative task execution by heterogeneous UAVs. However, semantic interoperability of UAVs is mainly constrained by two factors. First, the diverse data exchange formats often require one-to-one format conversion for syntactic interoperability between different UAVs. This can easily lead to ambiguity when engineers try to understand and apply the data. Second, the rapid upgrades and replacements of UAVs result in frequent changes in data exchange formats between different versions of the same type of UAV, leading to numerous syntactic interoperability problems, with semantic interoperability becoming even more challenging. Therefore, comprehensively addressing the syntactic and semantic interoperability issues of heterogeneous UAVs from the perspective of data semantic understanding, while also considering the interoperability of UAVs at different stages of development, has become a crucial issue that urgently needs to be addressed for the intelligent development of UAVs.

[0061] Currently, there are three main methods for achieving semantic interoperability among heterogeneous information systems. The first is to develop a unified data model that all heterogeneous information systems must follow. This method is simple and efficient, but it is difficult to implement and lacks flexibility. It requires modifying the data exchange of existing information systems and creates a conflict between upgrading information system capabilities and maintaining and managing the unified data model. The second method involves each information system having its own data model. When data exchange is needed, a one-to-one conversion is performed based on the data models of both systems. This method is straightforward, but the model conversion grows exponentially with the number of heterogeneous system types. When there are many heterogeneous system types, the computational and storage resource overhead increases dramatically. At the same time, upgrading the capabilities of heterogeneous systems also makes model conversion and maintenance difficult. The third method is to adopt a common data model. When exchanging information, heterogeneous systems first convert their own data model to a common data model, and then convert the common data model to the target information system's data model. This method breaks the tight coupling relationship in information exchange between heterogeneous systems. However, the common data model is similar to the unified data model in the first method. Therefore, it remains very difficult to form a consensus-based common data model and maintain its stability in the long term.

[0062] In summary, although the three methods mentioned above have differences, they all integrate data semantic parsing on the basis of syntax encoding and decoding. That is, they establish semantic correspondences between different fields in the data exchange format of heterogeneous information systems. Essentially, they still translate the semantic data of other systems into semantic information that they can understand. Therefore, the loss of semantic information caused by semantic translation is unavoidable in all three methods.

[0063] This invention addresses the semantic information interaction problem of heterogeneous unmanned systems by proposing a semantic interaction method between heterogeneous systems, namely a semantic interoperability method based on a metadata model. By constructing a common metadata model that describes the data model, all heterogeneous systems can have a unified semantic when describing their own private data models, thus transforming the semantic interoperability method of "syntactic interoperability + semantic translation" into a semantic interoperability method of "syntactic interoperability + unified semantics".

[0064] This specification provides a method for semantic interaction between heterogeneous systems, a device for semantic interaction between heterogeneous systems, a system for semantic interaction between heterogeneous systems, a computing device, and a computer-readable storage medium, which will be described in detail in the following embodiments.

[0065] See Figure 1 , Figure 1 This is a schematic diagram illustrating a scenario of a semantic interaction method between heterogeneous systems provided in an embodiment of this specification, including a management platform 102, unmanned system A104, and unmanned system B106. Taking the execution of a collaborative task by unmanned system A104 and unmanned system B106 as an example, with unmanned system A as the message receiver and unmanned system B as the message sender, and assuming there is one unmanned system A104 and one unmanned system B106, it should be noted that both unmanned system A and unmanned system B can act as both message receiver and message sender.

[0066] During the collaborative task execution by unmanned systems A104 and B106, based on the overall control of the collaborative task, the management platform 102 simultaneously sends interaction instructions to both unmanned systems A104 and B106. The specific interaction process includes: First, before the management platform 102 sends interaction instructions to the system with collaborative needs, unmanned system B106 sends a first private data model to unmanned system A104. Then, when the management platform 102 sends interaction instructions to the system with collaborative needs, unmanned system B106 sends data information to unmanned system A104. This data information includes, but is not limited to, platform information, payload information, and location information. Next, unmanned system A104 decodes the data information according to the received first private data model of unmanned system B106 to obtain the decoded information of unmanned system B106. Finally, unmanned system A104 decodes the decoded information according to the public metadata model to obtain the semantic information of unmanned system B106, thereby obtaining the platform information, payload information, and location information of unmanned system B106. It should be noted that the private data model is sent only once between systems that have interaction requirements, before receiving the interaction instructions from the management platform; the data information is sent in real time to the systems that have interaction requirements after receiving the interaction instructions from the management platform, based on the real-time changes in the system information.

[0067] By applying the embodiments of this application, upon receiving a collaborative task sent by the management platform and before receiving an interaction instruction, each system with interaction needs shares its private data model. This enables the decoding and encoding of data information through the private data models of each system and the pre-stored public metadata model, thereby obtaining the semantic information of the system. This greatly simplifies the steps of semantic interoperability and makes the acquisition of semantic information of each system more efficient and accurate.

[0068] Figure 2 This is a flowchart of a semantic interaction method between heterogeneous systems provided in the embodiments of this specification. It is applied to the semantic interaction of multiple systems. The system includes at least a management platform, a first subsystem, and a second subsystem. The first subsystem includes an unmanned system. The method specifically includes the following steps.

[0069] Step 202: Upon receiving the interaction instruction sent by the management platform, the first subsystem receives the data information sent by the second subsystem.

[0070] It should be noted that the interaction instructions here refer to the data information interaction instructions sent by the management platform to the first and second subsystems with collaboration needs. These data information interaction instructions include, on the one hand, controlling the first and second subsystems with collaboration needs to interact with data information, and on the other hand, controlling the first and second subsystems with collaboration needs to update their models.

[0071] It should also be noted that the management platform here can, on the one hand, act as an intermediary system to participate in the data information interaction process of the first and second subsystems with collaborative needs, realizing a three-way interaction process among the management platform, the first subsystem, and the second subsystem; on the other hand, it can also act only as the sender of interaction instructions, without participating in the data information interaction process of the first and second subsystems with collaborative needs, realizing a two-way interaction process between the first and second subsystems.

[0072] According to a first aspect of the embodiments of this application, the management platform is determined as the sender of the interaction command and does not participate in the data interaction process between the first subsystem and the second subsystem. That is, the data information interaction process is a two-way interaction between the first subsystem and the second subsystem.

[0073] Specifically, upon receiving an interaction instruction from the management platform, the first subsystem receives data information sent by the second subsystem, including:

[0074] The data information sent by the second subsystem is received through wired or wireless communication, wherein the data information is encoded data information obtained by the second subsystem after encoding the transmitted data according to the first private data model.

[0075] Specifically, data sharing and exchange with corresponding unmanned systems are carried out using wired or wireless communication methods.

[0076] After the first subsystem receives the data information sent by the second subsystem, it needs to process the data information to obtain the semantic information of the second subsystem. The data processing here includes decoding and decoding operations, and the specific implementation steps are as follows.

[0077] Step 204: Based on the first private data model, decode the data information to obtain decoded data information, wherein the first private data model is the second subsystem's own interactive semantic metadata, which is shared with the first subsystem before receiving the collaborative task and executing the interaction instruction, and is generated according to actual needs.

[0078] The step of decoding the data information based on the first private data model to obtain decoded data information includes:

[0079] Based on the encoded data information, a first private data model of the system corresponding to the encoded data information is determined;

[0080] Based on the first private data model of the system, the encoded data information is decoded to obtain decoded data information.

[0081] Specifically, the data information is syntactically decoded based on the corresponding private data model library to obtain the decoded data information.

[0082] It should be noted that upon receiving a collaborative task from the management platform but before receiving any interaction instructions, any system requiring interaction with the first subsystem will share its private data model with the first subsystem in advance. Here, the first subsystem is an unmanned system, which can be a regular information system or other heterogeneous unmanned systems; no specific limitation is made here. This private data model is pre-built, and each system also includes a pre-stored public metadata model. The specific steps for building the public metadata model are described below.

[0083] Before receiving the interactive instructions sent by the management platform, the process includes:

[0084] Obtain the interactive semantic metadata generated during the execution of collaborative tasks by the multiple systems;

[0085] The interaction semantic metadata is abstracted and classified to obtain interaction semantic fields;

[0086] The interaction semantic fields are standardized to construct an interaction semantic list;

[0087] By formatting and converting the data to represent the interactive semantic list, human-computer readable interactive semantic metadata is generated.

[0088] Based on the interactive semantic metadata, a public metadata model is generated and pre-stored in the multiple systems.

[0089] Specifically, the abstract classification of interactive semantic metadata involves categorizing the interactive information during the collaborative task completion process of heterogeneous unmanned systems into metadata such as entities, numbers, dimensions, reference systems, and physical quantities. Entity metadata includes, but is not limited to, platform type, payload type, mission type, navigation type, prohibited area type, hovering type, hovering direction, speed type, altitude type, turning type, command equipment type, route movement mode, and route upload mode. Number metadata includes, but is not limited to, computable numbers, ordinal numbers, symbolic numbers, platform identification numbers, payload identification numbers, and pi. Dimensional metadata includes, but is not limited to, international standard dimensions such as meters, kilograms, and seconds, and their derived combined dimensions, as well as other commonly used non-international standard dimensions. Reference system metadata includes, but is not limited to, time reference systems such as International Atomic Time and Coordinated Universal Time, and spatial reference systems such as the Earth coordinate system and the WGS84 geodetic coordinate system. Physical quantity metadata includes, but is not limited to, basic physical quantities such as length, mass, and time, and their derived combined physical quantities. It should be noted that the interactive semantic metadata here includes metadata that has already been used or may be used.

[0090] By applying the method provided in the embodiments of this application, the semantic features of the interaction information of heterogeneous unmanned systems are abstracted, and the metadata describing the interaction information of unmanned systems is divided into fine-grained semantic fields. This not only improves the universality of representing the semantics of interaction information, but also supports flexible syntactic combinations in the information transmission process.

[0091] After performing fine-grained analysis on the interaction semantic metadata of heterogeneous unmanned systems to obtain the interaction semantic fields, the interaction semantic fields will be normalized to construct an interaction semantic list.

[0092] The step of normalizing the interaction semantic fields and constructing an interaction semantic list includes:

[0093] The interaction semantic fields are standardized according to metadata number, metadata type, metadata name, metadata meaning, metadata alias, and version number to construct an interaction semantic list. There is a unique correspondence between the metadata number and the metadata name, and the metadata number or the metadata name has multiple metadata aliases.

[0094] Specifically, interactive semantic fields are standardized and described by means of metadata number, metadata type, metadata name, metadata meaning, metadata alias, and version number, thereby constructing an interactive semantic list.

[0095] After obtaining the constructed list of interactive semantics, it is necessary to process the list of interactive semantics using data storage and exchange formats including but not limited to Extensible Markup Language (XML) or JavaScript Object Representation (JSON) to obtain a public metadata model that can be read by both humans and machines.

[0096] By applying the methods provided in the embodiments of this specification, and by standardizing and normalizing the description of metadata and using formatted storage methods, relevant users and unmanned systems can reach a consensus on the use and understanding of various metadata.

[0097] After completing the construction of the public metadata model, it is also necessary to construct the private data model. The specific implementation steps are as follows.

[0098] Before receiving the interactive instructions sent by the management platform, the process also includes:

[0099] Based on the type of the collaborative task and the public metadata model pre-stored in the multiple systems, a private data model is constructed in each system, wherein the private data model includes at least: a first private data model of the second subsystem and a second private data model of the first subsystem.

[0100] The step of constructing a private data model in each system based on the type of the collaborative task and the public metadata models pre-stored in multiple systems includes:

[0101] Based on the type of the collaborative task, determine the interactive semantic metadata related to the type of collaborative task in the public metadata model;

[0102] Based on the interactive semantic metadata and the semantic metadata in the process of each system executing collaborative tasks, an initial private data model is constructed.

[0103] By formatting the initial private data model for data storage, a private data model is generated and pre-stored in various systems.

[0104] Specifically, various unmanned systems establish their own data models based on a public metadata model library, and standardize and describe the data format of the information they need to interact with, thereby constructing an initial private data model, including but not limited to message format definitions, field definitions, and version numbers. The message format definitions include but are not limited to message numbers and field numbers, and the field definitions include but are not limited to field names, field lengths, field length units, field value units, and field value scaling ratios.

[0105] After obtaining the initial private data model, it is necessary to process the initial private data model using data storage and exchange formats including but not limited to XML or JSON, so as to construct a private data model that can be read by both humans and machines.

[0106] In practical applications, taking the collaborative task performed by heterogeneous unmanned systems as an example, unmanned system A and unmanned system B perform a collaborative task, requiring the exchange of their respective platform information, payload information, and location information during the task. Assume there are two unmanned systems A, numbered 1000 and 1001, with UAVs as the platform type and visible light cameras as the payload, flying along a predetermined route. During flight, the UAVs periodically send real-time location information using their own message format. There are three unmanned systems B, numbered 1002, 1003, and 1004, where 1002 is the formation leader, an unmanned vehicle platform type, carrying infrared sensors as the payload, and moving along a predetermined route. During movement, the unmanned vehicle periodically sends real-time location information using its own message format. To better realize the unmanned systems and their information exchange needs, a general unmanned system metadata model needs to be constructed in advance.

[0107] Unmanned System A and Unmanned System B standardize and describe their message formats based on a common metadata model, constructing corresponding data models for Unmanned System A and Unmanned System B, as shown in Tables 2 and 3. Table 1 is an example of the data model for Unmanned System A, and Table 2 is an example of the data model for Unmanned System B. After the data models are constructed, the corresponding common metadata model files and private data model files are stored and shared within Unmanned System A and Unmanned System B.

[0108] Table 1. Example of a data model for an unmanned system.

[0109]

[0110]

[0111] Table 2. Examples of Data Models for Unmanned Systems

[0112]

[0113]

[0114] By applying the methods provided in the embodiments of this specification, and by standardizing and normalizing the format of its own interactive information and using formatted storage methods, users and unmanned systems involved in information interaction can perform corresponding syntax encoding and decoding.

[0115] Step 206: Based on the public metadata model, decode the decoded data information to obtain the semantic information of the second subsystem, wherein the public metadata model is pre-stored in the multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

[0116] The decoding of the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem includes:

[0117] Based on the aforementioned public metadata model, the decoded data information is format-converted to obtain human-computer readable interactive semantic data;

[0118] The semantic information of the second subsystem is obtained by semantically parsing the human-computer readable interactive semantic data through the public metadata model.

[0119] Specifically, based on the public metadata model, the decoded data information is converted to the appropriate format and semantically parsed to obtain the semantic information of the second subsystem.

[0120] By applying the method provided in the embodiments of this application, syntax decoding and semantic parsing are performed based on a public metadata model library and a corresponding private data model library, enabling information exchange and understanding that supports heterogeneous unmanned systems, thereby laying the foundation for collaborative task completion.

[0121] Continuing with the previous example, the information exchange process between system A and system B is as follows: Figure 3 As shown, where, Figure 3 This is a schematic diagram of a semantic interaction method between heterogeneous systems provided in the embodiments of this specification. Assume that at system time 1654789 milliseconds, the position of unmanned system 1000 is (longitude, latitude, altitude) = (125.2, 26.1, 1000), and the position of unmanned system 1001 is (longitude, latitude, altitude) = (125.3, 26.3, 1000). Unmanned systems 1000 and 1001 generate and send messages according to the unmanned system A data model, which are as follows:

[0122] 000000000000001000000000000000000110010100000000000101000000000000000000000011111010000000000100010110010000111111101100010010100011111101100010010100011110101101101101100000000101001, denoted as message A1, and

[0123] 00000000000000010000000000000000001100101000000000001010000000000000000000000011111010010000000100000000000000000000000000000100010001011001000110100010101011001001010101100111100101000000000101001, denoted as message A2;

[0124] Unmanned systems 1002, 1003, and 1004 form a formation, with their formation position information sent by the formation leader, 1002. At this point, the positions of unmanned systems 1002, 1003, and 1004 are (longitude, latitude, altitude) = (124, 24, 0), (124.2, 24.3, 0), and (124.4, 24.6, 0), respectively. Unmanned system 1002 generates and sends a formation message according to the B unmanned system data model. The message content is as follows:

[0125] 00000000000001010000110010100000000000101111000000011111010101000000000110010110000010110110000010100010001000110010111000000000000011100000001111101011100000000010 The string 100101100001010001111010111000100010100011110101110100000000000011100000001111101100100000000011100101100001110110010101001000101111110010010111110010111000000000000 is denoted as message B1.

[0126] After completing the data exchange, i.e., when unmanned systems 1000 and 1001 receive message B1 sent by unmanned system 1002, they perform syntax decoding according to the unmanned system data model in Table 2 to obtain a series of values, including:

[0127] (1654789,1002,4,1,124.0,24,0,1003,4,2,124.2,24.3,0,1004,4,3,124.4,24.6,0).

[0128] Semantic parsing using the public metadata model yields the following semantic meaning for message B1: At system time 1654789 milliseconds, the real-time location of driverless vehicle number 1002 is 124.0 degrees east longitude and 24 degrees north latitude, with an altitude of 0; the real-time location of driverless vehicle number 1003 is 124.2 degrees east longitude and 24.3 degrees north latitude, with an altitude of 0; and the real-time location of driverless vehicle number 1004 is 124.4 degrees east longitude and 24.6 degrees north latitude, with an altitude of 0.

[0129] Similarly, when unmanned systems 1002, 1003, and 1004 receive messages A1 and A2, they perform syntax decoding based on the unmanned system data model in Table 1 and semantic parsing in conjunction with the public metadata model, which will not be elaborated here.

[0130] By applying the methods provided in the embodiments of this specification, data information is decoded and decoded through a shared public metadata model and a private data model, thereby obtaining the semantic information of the system. This enables syntactic interaction and semantic understanding between heterogeneous systems, greatly simplifies the steps of semantic interoperability, and makes the acquisition of semantic information from various systems more efficient and accurate.

[0131] Due to differences in the type of collaborative tasks, the level of the management platform (including upgrades to the management platform), or the payload carried, it is necessary to further update and expand the private data model and the public metadata model to decode and encode data more efficiently and accurately. Therefore, this application also provides a method for data model expansion, the specific implementation steps of which are as follows.

[0132] The method further includes:

[0133] The system receives collaborative task instructions from the first subsystem and the second subsystem sent by the management platform, wherein the collaborative task instructions include a collaborative task type.

[0134] Send the second private data model of the first subsystem and the first private data model of the second subsystem to the management platform;

[0135] Receive the execution instructions sent by the management platform, which are generated based on the collaborative task type and the first private data model and the second private data model;

[0136] If the first private data model and the second private data model satisfy the collaborative task type, execute the interaction instruction;

[0137] If the first private data model and / or the second private data model does not meet the collaborative task type, an update instruction is executed.

[0138] Specifically, if the first private data model and / or the second private data model does not meet the collaborative task type, the first private data model and / or the second private data model are extended through the public metadata model to obtain an updated private data model;

[0139] If the updated model does not meet the collaborative task type, the public metadata model is extended according to the collaborative task type to obtain an updated public metadata model;

[0140] Repeat the above steps until the first private data model and / or the second private data model satisfy the collaborative task type.

[0141] In practical applications, once an unmanned system generates new needs for shared and interactive information due to platform capability upgrades, the addition of new payloads, or the undertaking of new tasks, it is necessary to extend its own private data model based on the public metadata model. In necessary cases, the public metadata model can also be extended. The extended public metadata model and the private data model are distinguished by version numbers. After being shared with other unmanned systems, they support semantic interoperability involving the new task capabilities of the unmanned system.

[0142] Specifically, based on the public metadata model, new fields or messages are added to the private data model, and the corresponding data model version number is updated to maintain compatibility. If this still does not meet the requirements, new metadata names are added to the public metadata model, and the corresponding metadata model version number is updated to maintain compatibility, enabling data exchange and shared understanding between heterogeneous unmanned systems.

[0143] By applying the method provided in the embodiments of this application, semantic interoperability can be achieved after the unmanned system's capabilities are enhanced by extending the private data model and / or the public metadata model.

[0144] According to a second aspect of the embodiments of this application, the management platform is determined to participate as an intermediate system in the data information interaction process of the first subsystem and the second subsystem that have collaborative needs, that is, the data information interaction process is a three-way interaction between the management platform, the first subsystem and the second subsystem.

[0145] See Figure 4 , Figure 4 This is a schematic diagram of another semantic interaction method between heterogeneous collaborative systems provided in the embodiments of this application. Taking the collaborative task performed by unmanned system A 404 and unmanned system B 406 as an example, the first unmanned system acts as the message receiver with a quantity of 1, and the B unmanned system acts as the message sender with a quantity of 1.

[0146] During the collaborative task execution by unmanned system A 404 and unmanned system B 406, based on the overall control of the collaborative task, the management platform 402 first receives the private data models of unmanned system A 404 and unmanned system B 406 respectively. If it is determined that all private data models meet the requirements of the collaborative task type, it sends interaction instructions to unmanned system A 404 and unmanned system B 406. If the private data model of at least one unmanned system does not meet the requirements of the collaborative task type, it needs to be updated first to obtain the updated private data model. If the updated private data model meets the requirements of the collaborative task type, it sends interaction instructions to unmanned system A 404 and unmanned system B 406.

[0147] Then, the system receives data information sent by the B unmanned system 406 and decodes the data information according to the private data model corresponding to the B unmanned system 406 to obtain decoded data information.

[0148] Secondly, based on the public metadata model, the decoded data information is decoded to obtain the semantic information of unmanned system B, and then sent to unmanned system A 404.

[0149] It should be noted that while unmanned system B 406 is sending data information to management platform 402, unmanned system A is also sending data information to management platform 402. Management platform 402 will process the received data information and send it to the corresponding system, thereby realizing three-way interaction between management platform 402, management platform A 404, and management platform B 406.

[0150] It should be noted that the semantic interaction method between heterogeneous systems provided in this application embodiment involves the same data information interaction process as the semantic interaction method between heterogeneous systems provided in the above application embodiment, and will not be described again in this application embodiment.

[0151] See Figure 5 , Figure 5 This is a block diagram of a semantic interaction device between heterogeneous systems provided in an embodiment of this application, such as... Figure 5 As shown, the device includes the following modules.

[0152] The data receiving module 502 is configured to receive data information sent by the second subsystem from the first subsystem when an interactive instruction is received from the management platform.

[0153] The decoding module 504 is configured to decode the data information based on the first private data model to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, which is generated according to actual needs and shared with the first subsystem before receiving the collaborative task and executing the interaction instruction.

[0154] The decoding module 506 is configured to decode the decoded data information based on a public metadata model to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in the multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

[0155] It should be noted that the specific implementation of the semantic interaction device between heterogeneous systems provided in this application embodiment is the same as the semantic interaction method between heterogeneous systems described above, and will not be elaborated further here.

[0156] See Figure 6 , Figure 6 This is a flowchart of a semantic interaction system between heterogeneous systems provided in an embodiment of this application, such as... Figure 6 As shown, this heterogeneous system semantic interaction system is applied to a management platform, a first subsystem, and a second subsystem, and is characterized by comprising:

[0157] Management platform 602 is used to send interactive instructions to the first subsystem and the second subsystem;

[0158] The second subsystem 604 is used to send the first private data model to the first subsystem and send data information to the first subsystem when it receives an interactive instruction from the management platform.

[0159] The first subsystem 606 is used to decode the data information based on the first private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem. The public metadata model is human-computer readable interactive semantic metadata that is pre-stored in the multiple systems and obtained by the multiple systems during the execution of collaborative tasks.

[0160] The first subsystem 606 is used to send the second private data model to the second subsystem and send data information to the second subsystem when it receives the interaction instructions sent by the management platform.

[0161] The second subsystem 604 is used to decode the data information based on the second private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the first subsystem.

[0162] It should be noted that the specific implementation steps of the heterogeneous system semantic interaction system provided in this application embodiment are the same as those of the heterogeneous system semantic interaction method described above, and will not be repeated here.

[0163] By applying the embodiments of this application, when receiving an interaction instruction sent by the management platform, each system with interaction needs shares its private data model. Through the received private data models of each system and the pre-stored public metadata model, the data information is decoded and decoded to obtain the semantic information of the system. This can greatly simplify the steps of semantic interoperability and make the acquisition of semantic information of each system more efficient and accurate.

[0164] This application also proposes a computer device, which includes a processor and a memory. The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the steps of the above-described semantic interaction method between heterogeneous systems.

[0165] This application also proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the aforementioned semantic interaction method between heterogeneous systems.

[0166] It should be noted that, in the embodiments of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0167] The sequence numbers of the embodiments in this application are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0168] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0169] The embodiments of this application have been described above with reference to the accompanying drawings. However, this application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit and scope of the claims. All of these forms are within the protection scope of this application.

Claims

1. A semantic interaction method between heterogeneous systems, applied to the semantic interaction of multiple systems, wherein, The system includes at least a management platform, a first subsystem, and a second subsystem, wherein the first subsystem includes an unmanned system, characterized in that it includes: Upon receiving an interactive instruction from the management platform, the first subsystem receives data information sent by the second subsystem; Based on the first private data model, the data information is decoded to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, which is shared with the first subsystem before receiving the collaborative task and executing the interaction instruction, and is generated according to actual needs. Based on the public metadata model, the decoded data information is decoded to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in the multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

2. The method according to claim 1, characterized in that, Before receiving the interactive instructions sent by the management platform, the process includes: Obtain the interactive semantic metadata generated during the execution of collaborative tasks by the multiple systems; The interaction semantic metadata is abstracted and classified to obtain interaction semantic fields; The interaction semantic fields are standardized to construct an interaction semantic list; By formatting and converting the data to represent the interactive semantic list, human-computer readable interactive semantic metadata is generated. Based on the interactive semantic metadata, a public metadata model is generated and pre-stored in the multiple systems.

3. The method according to claim 2, characterized in that, Before receiving the interactive instructions sent by the management platform, the process also includes: Based on the type of the collaborative task and the public metadata model pre-stored in the multiple systems, a private data model is constructed in each system, wherein the private data model includes at least: a first private data model of the second subsystem and a second private data model of the first subsystem.

4. The method according to claim 3, characterized in that, The step of constructing a private data model in each system based on the type of the collaborative task and the public metadata model pre-stored in the multiple systems includes: Based on the type of the collaborative task, determine the interactive semantic metadata related to the type of collaborative task in the public metadata model; Based on the interactive semantic metadata and the semantic metadata in the process of each system executing collaborative tasks, an initial private data model is constructed. By formatting the initial private data model for data storage, a private data model is generated and pre-stored in various systems.

5. The method according to claim 1, characterized in that, Upon receiving an interaction instruction from the management platform, the first subsystem receives data information sent by the second subsystem, including: The system receives data information sent by the second subsystem, wherein the data information is encoded data information obtained by the second subsystem after encoding the transmitted data according to the first private data model.

6. The method according to claim 1, characterized in that, The process of decoding the data information based on the first private data model to obtain decoded data information includes: Based on the encoded data information, a first private data model of the system corresponding to the encoded data information is determined; Based on the first private data model of the system, the encoded data information is decoded to obtain decoded data information.

7. The method according to claim 1, characterized in that, The decoding of the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem includes: Based on the aforementioned public metadata model, the decoded data information is format-converted to obtain human-computer readable interactive semantic data; The semantic information of the second subsystem is obtained by semantically parsing the human-computer readable interactive semantic data through the public metadata model.

8. The method according to claim 3, characterized in that, The method further includes: The system receives collaborative task instructions from the first subsystem and the second subsystem sent by the management platform, wherein the collaborative task instructions include a collaborative task type. Send the second private data model of the first subsystem and the first private data model of the second subsystem to the management platform; Receive the execution instructions sent by the management platform, which are generated based on the collaborative task type and the first private data model and the second private data model; If the first private data model and the second private data model satisfy the collaborative task type, execute the interaction instruction; If the first private data model and / or the second private data model does not meet the collaborative task type, an update instruction is executed.

9. A semantic interaction device for heterogeneous systems, characterized in that, include: The data receiving module is configured to receive data information sent by the second subsystem from the first subsystem upon receiving an interactive instruction sent by the management platform. The decoding module is configured to decode the data information based on the first private data model to obtain decoded data information. The first private data model is the second subsystem's own interactive semantic metadata, which is generated according to actual needs and shared with the first subsystem before receiving the collaborative task and executing the interaction instruction. The decoding module is configured to decode the decoded data information based on a public metadata model to obtain the semantic information of the second subsystem. The public metadata model is pre-stored in multiple systems and is human-computer readable interactive semantic metadata obtained by the multiple systems during the execution of collaborative tasks.

10. A semantic interaction system between heterogeneous systems, applied to a management platform, a first subsystem, and a second subsystem, characterized in that, include: A management platform is used to send interactive instructions to the first subsystem and the second subsystem; Upon receiving the interaction command sent by the management platform, the second subsystem sends the first private data model to the first subsystem and sends data information to the first subsystem. The first subsystem is used to decode the data information based on the first private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the second subsystem. The public metadata model is human-computer readable interactive semantic metadata pre-stored in multiple systems and obtained by the multiple systems during the execution of collaborative tasks. The first subsystem is used to send the second private data model to the second subsystem and send data information to the second subsystem upon receiving an interactive instruction from the management platform. The second subsystem is used to decode the data information based on the second private data model to obtain decoded data information, and to decode the decoded data information based on the public metadata model to obtain the semantic information of the first subsystem.

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