Unmanned aerial vehicle networking method and system based on open source gap system and soft bus

Abstract

The invention discloses an unmanned aerial vehicle networking method and system based on an open source gap system and a soft bus. The method comprises the following steps: determining a target application scene and a target function demand of the unmanned aerial vehicle networking system; designing a special operating system for the unmanned aerial vehicle and a soft bus communication protocol stack; developing an intelligent collaborative operation algorithm and a modular architecture; integrating an intelligent collaborative operation algorithm and all functional modules in the modular architecture to the unmanned aerial vehicle platform, and performing function test and performance optimization on the unmanned aerial vehicle platform according to a preset test mode to obtain an unmanned aerial vehicle networking system meeting requirements; and verifying the effect of the unmanned aerial vehicle networking system in the target application scene, collecting verified feedback information, and performing iterative optimization on the unmanned aerial vehicle networking system according to the feedback information. The invention aims to realize autonomous networking, collaborative operation, flexible expansion and intelligent management of the unmanned aerial vehicle cluster by integrating the cross-device collaborative capability of the open-source Gawan system and the efficient communication mechanism of the soft bus.

Description

Technical Field

[0001] The present invention relates to the field of drone technology, and in particular to a drone networking method, system, terminal and computer-readable storage medium based on an open source Hongmeng system and a soft bus. Background Art

[0002] Currently, drone networking faces a number of technical challenges: first, the communication protocols between devices are diverse, resulting in high networking complexity and poor compatibility; second, the traditional hardware bus is limited by physical connections, making it difficult to achieve flexible deployment and dynamic adjustment of large-scale drone clusters; third, the system has poor scalability and is difficult to adapt to the rapidly changing needs in different mission scenarios; fourth, data processing and decision-making capabilities are limited, making it difficult to achieve efficient collaborative operations and intelligent decision-making.

[0003] Therefore, the prior art still needs to be improved and developed. Summary of the invention

[0004] The main purpose of the present invention is to provide a drone networking method, system, terminal and computer-readable storage medium based on the open source Hongmeng system and soft bus, aiming to solve the problems of high networking complexity, poor compatibility and scalability in drone networking in the prior art, difficulty in flexible deployment and dynamic adjustment of large-scale drone clusters, and difficulty in achieving efficient collaborative operations and intelligent decision-making.

[0005] To achieve the above object, the present invention provides a drone networking method based on an open source Hongmeng system and a soft bus, and the drone networking method based on an open source Hongmeng system and a soft bus comprises the following steps:

[0006] Determine the target application scenarios and target functional requirements of the UAV networking system;

[0007] Design a dedicated operating system and soft bus communication protocol stack for drones based on the target application scenarios and target functional requirements;

[0008] Develop intelligent collaborative operation algorithms and modular architectures based on the target application scenarios and target functional requirements;

[0009] Integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the UAV platform, perform functional testing and performance optimization on the UAV platform according to a preset test method, and obtain a UAV networking system that meets the requirements;

[0010] The effect of the drone networking system is verified in the target application scenario, feedback information after verification is collected, and the drone networking system is iteratively optimized according to the feedback information.

[0011] Optionally, in the drone networking method based on the open source Hongmeng system and the soft bus, the step of determining the target application scenarios and target functional requirements of the drone networking system specifically includes:

[0012] Determine the target application scenarios for the assembled UAV networking system, wherein the target application scenarios include agricultural plant protection scenarios, environmental monitoring scenarios, and emergency rescue scenarios;

[0013] Determine the target functional requirements that the UAV networking system needs to achieve after being established, and the target functional requirements include autonomous flight, data collection, image recognition and collaborative operation.

[0014] Optionally, the UAV networking method based on the open source Hongmeng system and soft bus, wherein the UAV-specific operating system and soft bus communication protocol stack are designed according to the target application scenario and the target functional requirements, specifically including:

[0015] Customized development of OpenHarmony system for drones;

[0016] Based on the UAV-specific version of OpenHarmony system, design a UAV-specific operating system and soft bus communication protocol stack according to the target application scenario and the target functional requirements;

[0017] Among them, the soft bus communication protocol stack is used for communication between various drones in the drone networking system.

[0018] Optionally, the UAV networking method based on the open source Hongmeng system and soft bus, wherein the intelligent collaborative operation algorithm and modular architecture are developed according to the target application scenario and the target functional requirements, specifically including:

[0019] Develop an intelligent collaborative operation algorithm according to the target application scenario and the target functional requirements, wherein the intelligent collaborative operation algorithm includes a path planning algorithm, a task allocation algorithm, a conflict avoidance algorithm, a collaborative control algorithm, a machine learning algorithm, and a data fusion algorithm;

[0020] According to the target application scenario and the target functional requirements, a modular architecture is developed, which includes a communication module, a control module, a perception module, a power module, a user interface module, a data processing and storage module, a security module and an expansion module.

[0021] Optionally, the UAV networking method based on the open source Hongmeng system and soft bus, wherein the intelligent collaborative operation algorithm and all functional modules in the modular architecture are integrated into the UAV platform, and the UAV platform is functionally tested and performance optimized according to a preset test method to obtain a UAV networking system that meets the requirements, specifically includes:

[0022] Integrate path planning algorithms, task allocation algorithms, conflict avoidance algorithms, cooperative control algorithms, machine learning algorithms, and data fusion algorithms into UAV platforms;

[0023] Integrate the communication module, control module, perception module, power module, user interface module, data processing and storage module, security module and expansion module into the UAV platform;

[0024] Performing a functional test on the UAV platform according to a functional test method, and optimizing the performance of the UAV platform according to a performance test method, so as to obtain a UAV networking system that meets the requirements;

[0025] Among them, the functional testing includes unit testing, integration testing, system testing, interface testing, boundary condition testing and regression testing; the performance optimization includes performance monitoring, bottleneck analysis, code optimization, hardware optimization, network optimization, load balancing and redundant design.

[0026] Optionally, the UAV networking method based on the open source Hongmeng system and soft bus, wherein the verification of the effect of the UAV networking system in the target application scenario, collecting feedback information after verification, and iteratively optimizing the UAV networking system according to the feedback information, specifically includes:

[0027] Apply the drone networking system that meets the requirements to agricultural plant protection scenarios, environmental monitoring scenarios and emergency rescue scenarios for effect verification. The agricultural plant protection scenarios include crop monitoring, precision spraying, terrain mapping and intelligent scheduling. The environmental monitoring scenarios include air quality monitoring, water body monitoring, biological monitoring and disaster warning.

[0028] When the verification is completed, the test results and user feedback after verification of each scenario are collected, and the drone networking system is iteratively optimized based on the test results and the user feedback.

[0029] Optionally, the UAV networking method based on the open source Hongmeng system and the soft bus, wherein the effect of the UAV networking system is verified in the target application scenario, feedback information after verification is collected, and the UAV networking system is iteratively optimized according to the feedback information, and then further includes:

[0030] Based on the verification results, technical standards for the UAV networking system are formulated, and the technical standards include communication protocol standards, interface standards, safety standards, performance standards and interoperability standards.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also provides a drone networking system based on an open source Hongmeng system and a soft bus, wherein the drone networking system based on an open source Hongmeng system and a soft bus includes:

[0032] Demand analysis module, used to determine the target application scenarios and target functional requirements of the drone networking system;

[0033] A system architecture design module, used to design a dedicated operating system and a soft bus communication protocol stack for the drone according to the target application scenario and the target functional requirements;

[0034] A function development module, used to develop intelligent collaborative operation algorithms and modular architectures according to the target application scenarios and the target function requirements;

[0035] An integration and testing module, used to integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the UAV platform, perform functional testing and performance optimization on the UAV platform according to a preset testing method, and obtain a UAV networking system that meets the requirements;

[0036] The verification and optimization module is used to verify the effect of the drone networking system in the target application scenario, collect feedback information after verification, and iteratively optimize the drone networking system according to the feedback information.

[0037] In addition, to achieve the above-mentioned purpose, the present invention also provides a terminal, wherein the terminal includes: a memory, a processor, and a drone networking program based on the open source Hongmeng system and a soft bus stored in the memory and runnable on the processor, and when the drone networking program based on the open source Hongmeng system and a soft bus is executed by the processor, the steps of the drone networking method based on the open source Hongmeng system and a soft bus as described above are implemented.

[0038] In addition, to achieve the above-mentioned purpose, the present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a drone networking program based on the open source Hongmeng system and a soft bus, and when the drone networking program based on the open source Hongmeng system and a soft bus is executed by a processor, the steps of the drone networking method based on the open source Hongmeng system and a soft bus as described above are implemented.

[0039] In the present invention, the target application scenario and target functional requirements of the drone networking system are determined; according to the target application scenario and the target functional requirements, a drone-specific operating system and a soft bus communication protocol stack are designed; according to the target application scenario and the target functional requirements, an intelligent collaborative operation algorithm and a modular architecture are developed; the intelligent collaborative operation algorithm and all functional modules in the modular architecture are integrated into the drone platform, and the drone platform is functionally tested and performance optimized according to a preset test method to obtain a drone networking system that meets the requirements; the effect of the drone networking system is verified in the target application scenario, feedback information after verification is collected, and the drone networking system is iteratively optimized according to the feedback information. The present invention aims to achieve autonomous networking, collaborative operation, flexible expansion and intelligent management of drone clusters by integrating the cross-device collaborative capabilities of the open source Hongmeng system and the efficient communication mechanism of the soft bus. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a flow chart of a preferred embodiment of the drone networking method based on the open source Hongmeng system and soft bus of the present invention;

[0041] Figure 2 It is a structural diagram of a preferred embodiment of the drone networking system based on the open source Hongmeng system and soft bus of the present invention;

[0042] Figure 3 It is a structural diagram of a preferred embodiment of the terminal of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer and more specific, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] The drone networking method based on the open source Hongmeng system and soft bus described in the preferred embodiment of the present invention is as follows: Figure 1 As shown, the drone networking method based on the open source Hongmeng system and soft bus includes the following steps:

[0045] Step S10: Determine the target application scenario and target functional requirements of the drone networking system.

[0046] Specifically, determine the target application scenarios for the assembled UAV networking system, which include agricultural plant protection scenarios, environmental monitoring scenarios, and emergency rescue scenarios; determine the target functional requirements that need to be achieved by the assembled UAV networking system, which include autonomous flight, data collection, image recognition, and collaborative operations.

[0047] In the present invention, the UAV networking system refers to the use of network communication technology to connect multiple UAVs to form a network system that can cooperate with each other, share information, and be managed in a unified manner. In this system, each UAV is not only an independent operating unit, but also a node in the entire network. They are interconnected through the communication network to jointly perform tasks or achieve specific goals. The following are some key features of the UAV networking system:

[0048] (1) Autonomy: Drones can perform tasks autonomously based on preset algorithms or external instructions without human intervention.

[0049] (2) Collaboration: Multiple drones can work together to complete complex tasks such as search, monitoring, and transportation.

[0050] (3) Flexibility: UAVs can quickly adjust network structure and operation mode according to mission requirements.

[0051] (4) Intelligent management: The system can intelligently dispatch and manage drones to optimize task allocation and execution efficiency.

[0052] In the demand analysis, the following are several aspects that need to be considered in the UAV networking system during the demand analysis phase:

[0053] (1) Application scenarios: clarify the scenarios in which the drone will be used, such as agricultural plant protection, environmental monitoring, emergency rescue, etc.

[0054] (2) Functional requirements: Determine the basic functions that the system needs to achieve, such as autonomous flight, data collection, image recognition, collaborative operation, etc.

[0055] (3) Performance indicators: Set expected indicators of system performance, such as communication delay, data transmission rate, positioning accuracy, etc.

[0056] (4) Environmental adaptability: Analyze the operating environments that the UAV may face, such as cities, mountains, waters, etc., and the impact of these environments on system design.

[0057] (5) Security requirements: Consider the security requirements of the system, including drone flight safety, data security, and privacy protection.

[0058] Through detailed requirements analysis, clear directions and goals can be provided for the design and implementation of the UAV networking system, ensuring that the system can meet the expected functional and performance requirements.

[0059] Step S20: designing a drone-specific operating system and a soft bus communication protocol stack according to the target application scenario and the target functional requirements.

[0060] Specifically, a customized UAV-specific version of the OpenHarmony system is developed; based on the UAV-specific version of the OpenHarmony system, a UAV-specific operating system and a soft bus communication protocol stack are designed according to the target application scenario and the target functional requirements; wherein the soft bus communication protocol stack is used for communication between various UAVs in the UAV networking system.

[0061] The OpenHarmony system specially developed for drones in the present invention has the following special features, which make it very suitable for drone networking systems:

[0062] (1) Distributed soft bus technology: The system uses OpenHarmony’s distributed soft bus technology to achieve seamless connection and efficient communication between drones. This means that drones can quickly connect wirelessly without the need for a physical bus, which improves the flexibility and reliability of networking.

[0063] (2) Cross-device collaboration capability: The drone-specific version of the OpenHarmony system has powerful cross-device collaboration capabilities and can support multiple communication protocols, allowing drones of different brands and models to easily access the network and share data and tasks.

[0064] (3) Customized UAV operating system: The system is deeply customized to the specific needs of the UAV, including flight control, data collection, mission execution, etc., and optimizes the performance and power consumption of the operating system to adapt to the long-term operation of the UAV in the air.

[0065] (4) Compatibility and flexibility: Through customization, the system enhances compatibility with other drones and equipment (such as sensors, ground control stations, etc.), while maintaining a high degree of flexibility and being able to quickly adapt to different application scenarios and mission requirements.

[0066] (5) Efficient data processing and decision-making capabilities: The system integrates efficient data processing and decision-making algorithms, which can process data from multiple sensors in real time and make quick decisions, which is crucial for the autonomous operation and intelligent decision-making of drone clusters.

[0067] (6) Modular design: The OpenHarmony system for drones uses a modular design, which allows for rapid iteration and expansion of hardware and software functions. This design allows drones to quickly replace or upgrade modules based on mission requirements, improving the maintainability and upgrade convenience of the system.

[0068] (7) Safety and stability: The system was designed with the safe flight requirements of drones in mind, including fault detection, automatic obstacle avoidance, and encrypted data transmission, ensuring the stable operation of drones in complex environments.

[0069] (8) Low-latency communication: The design of the soft bus communication protocol stack focuses on reducing communication latency, which is crucial for real-time control and state synchronization of drone clusters, especially in application scenarios that require fast response.

[0070] Through these special features, the drone-specific OpenHarmony system can provide powerful technical support for drone networking, realize efficient and intelligent drone cluster operations, and meet diverse application needs.

[0071] In this invention, the distributed soft bus technology is a core technology in the open source Hongmeng system (OpenHarmony). It is a communication framework for distributed devices, aiming to achieve efficient, flexible and reliable connection and data transmission between devices. The following are several key features of the distributed soft bus technology:

[0072] (1) Device discovery and connection: Distributed soft bus technology can automatically discover devices in the network and support fast connection between devices. It does not require a complicated configuration process, and devices can be plug-and-play.

[0073] (2) Efficient communication: This technology provides a high-bandwidth and low-latency communication mechanism, ensuring the real-time and efficient data transmission between devices.

[0074] (3) Protocol independence: Distributed soft bus technology supports multiple communication protocols, such as Bluetooth, Wi-Fi, USB, etc., to achieve seamless communication between different devices regardless of the transmission medium they use.

[0075] (4) Distributed architecture: This technology is based on a distributed system architecture, which enables multiple devices to form a unified whole and achieve resource sharing and collaborative work.

[0076] (5) Virtualized bus: Distributed soft bus technology creates a logical bus through virtualization technology, so that communication between devices no longer depends on the traditional physical bus, thereby improving the flexibility and scalability of the system.

[0077] (6) Service sharing: Distributed soft bus technology allows devices to share services and resources. For example, one device can call functions or data on another device.

[0078] (7) Reliability: This technology provides reliable data transmission guarantees, including error detection and retransmission mechanisms, ensuring communication stability and data integrity.

[0079] In the UAV networking system, the application of distributed soft bus technology has the following advantages:

[0080] (1) Simplify the networking process: Drones can easily join or leave the network without complex configuration.

[0081] (2) Improve communication efficiency: Data can be transmitted quickly between drones, reducing communication delays and improving control response speed.

[0082] (3) Enhanced compatibility: UAVs of different models and brands can interoperate through distributed soft bus technology.

[0083] (4) Dynamically adjust the network: UAV clusters can dynamically adjust the network structure according to mission requirements to achieve flexible networking.

[0084] Through distributed soft bus technology, the drone networking system can manage and control drone clusters more intelligently and efficiently, thereby playing a greater role in agricultural plant protection, environmental monitoring, emergency rescue and other fields.

[0085] The present invention is based on the UAV operating system of OpenHarmony, and customizes and develops a special version of OpenHarmony system for UAVs. It utilizes its distributed soft bus technology to achieve seamless connection and efficient communication between UAVs, support multiple communication protocols, and enhance system compatibility and flexibility.

[0086] In the present invention, the soft bus communication protocol stack has the following special features in the technical solution of the drone networking system based on the open source Hongmeng system and the soft bus, which makes it particularly critical in drone applications:

[0087] (1) High integration: The soft bus communication protocol stack is designed specifically for UAV networking systems. It integrates multiple communication protocols, enabling UAVs to communicate through different transmission media, such as Wi-Fi, Bluetooth, NFC, etc., thereby improving the compatibility and applicability of the system.

[0088] (2) Low latency: The protocol stack optimizes the data transmission delay to meet the needs of real-time control of drones, ensuring that control commands can reach each drone quickly, which is crucial for drone operations that require fast response.

[0089] (3) Reliability: The soft bus communication protocol stack is designed with an error detection and correction mechanism to ensure the reliability of data transmission. In UAV cluster operations, accurate data transmission is the basis for ensuring the successful execution of the mission.

[0090] (4) Flexible networking capabilities: The protocol stack supports dynamic networking. Drones can join or leave the network at any time according to mission requirements without restarting the entire network, which facilitates the flexible deployment of drone clusters.

[0091] (5) Data sharing and synchronization: The protocol stack enables data sharing and state synchronization between drones, which is crucial for collaborative operations. For example, a drone can instantly obtain the location information and mission progress of other drones, thereby better coordinating actions.

[0092] (6) Task allocation mechanism: The soft bus communication protocol stack contains a task allocation algorithm that can intelligently allocate tasks to the most suitable drone based on the drone’s status and capabilities, thereby improving operational efficiency and mission success rate.

[0093] (7) Network self-healing capability: When a node failure or communication interruption occurs in the network, the protocol stack can automatically find alternative paths to maintain network connectivity, which enhances the robustness of the drone cluster.

[0094] (8) Security: The protocol stack takes into account the security of data transmission and provides encryption and authentication mechanisms to protect the drone network from unauthorized access and interference.

[0095] Through these special features, the soft bus communication protocol stack provides an efficient, stable and reliable communication foundation for the drone networking system, enabling drone clusters to perform complex tasks more intelligently and efficiently.

[0096] The present invention designs and implements a soft bus communication protocol stack suitable for UAV networking, uses wireless channels to build a virtual bus, realizes data sharing, task allocation and status synchronization between UAVs, reduces communication delays and improves networking efficiency.

[0097] Step S30: Develop an intelligent collaborative operation algorithm and a modular architecture according to the target application scenario and the target functional requirements.

[0098] Specifically, according to the target application scenario and the target functional requirements, an intelligent collaborative work algorithm is developed, and the intelligent collaborative work algorithm includes a path planning algorithm, a task allocation algorithm, a conflict avoidance algorithm, a collaborative control algorithm, a machine learning algorithm and a data fusion algorithm; according to the target application scenario and the target functional requirements, a modular architecture is developed, and the modular architecture includes a communication module, a control module, a perception module, a power module, a user interface module, a data processing and storage module, a security module and an expansion module.

[0099] In the present invention, intelligent collaborative operation algorithms are key components of the drone networking system. These algorithms ensure that the drone cluster can perform tasks efficiently and safely. The following are some key algorithms that may be included in the intelligent collaborative operation algorithm:

[0100] (1) Path planning algorithm:

[0101] Dijkstra's algorithm: It is used to find the shortest path between two vertices in a graph.

[0102] RRT (Rapidly-exploring Random Trees): Applicable to dynamic environments and complex spaces, and can quickly generate paths that cover the space.

[0103] RRT* (RRT-Optimized): Improved RRT algorithm that provides a better path.

[0104] (2) Task allocation algorithm:

[0105] Particle Swarm Optimization (PSO): An optimization tool based on swarm intelligence to solve task allocation problems.

[0106] Genetic Algorithms: Algorithms that mimic natural selection and genetics and are used to optimize task allocation.

[0107] Multi-agent system (MAS) algorithm: allows multiple agents to work together to complete tasks.

[0108] (3) Conflict avoidance algorithm:

[0109] Dynamic Window Algorithm (DWA): An algorithm for mobile robots to avoid obstacles, which can adjust speed and direction in real time.

[0110] VECTOR Field Histogram (VFH): Avoid collisions by building a histogram of the surrounding environment.

[0111] Collision detection and obstacle avoidance algorithms: such as potential field-based methods, which use virtual force fields to guide drones to avoid obstacles.

[0112] (4) Collaborative control algorithm:

[0113] Leader-Follower Algorithm: A simple cooperative control strategy where a leader UAV sets the path and the follower UAVs follow the leader.

[0114] Distributed Model Predictive Control (MPC): An advanced control strategy that can achieve accurate cooperative control in multi-UAV systems.

[0115] (5) Machine Learning Algorithms:

[0116] Reinforcement learning: learning optimal strategies by interacting with the environment, applicable to complex environments and tasks.

[0117] Deep learning: used to process large amounts of sensor data for situational awareness and decision making.

[0118] (6) Data fusion algorithm:

[0119] Kalman filter: used to estimate the state of a dynamic system and can fuse data from different sensors.

[0120] Data association and fusion technology: used to process data collected by multiple drones to improve the accuracy of situational awareness.

[0121] The combination and application of these algorithms enable drone swarms to perform complex tasks such as collaborative search, monitoring, plant protection and rescue operations while maintaining efficiency and safety. During the development process, these algorithms need to be adjusted and optimized according to the actual application scenarios and the specific needs of the drones.

[0122] The present invention uses intelligent collaborative operation algorithms, integrates advanced path planning, task allocation and conflict avoidance algorithms, and combines them with an AI decision-making engine to enable drone clusters to complete complex tasks autonomously and improve operational efficiency and safety.

[0123] In this invention, modular architecture refers to decomposing the system into a series of independent and replaceable modules, each of which is responsible for a specific function or a group of related functions of the system. The design concept of modular architecture can improve the maintainability, scalability and reusability of the system. The following are some modular architectures that may be used in drone networking systems:

[0124] (1) Communication module:

[0125] Wireless communication module: responsible for wireless data transmission between drones.

[0126] Wired communication module: used for wired connection between drone and ground station or other equipment.

[0127] (2) Control module:

[0128] Flight control module: responsible for the flight attitude control, navigation and positioning of the UAV.

[0129] Mission control module: manages and assigns UAV tasks, including flight path planning and mission execution.

[0130] (3) Perception module:

[0131] Perception sensor module: includes cameras, radars, laser rangefinders, etc., used for environmental perception and obstacle avoidance.

[0132] Data processing module: processes the data collected by perception sensors to perform image recognition, obstacle detection, etc.

[0133] (4) Power module:

[0134] Battery management module: monitors battery status and manages battery charging and discharging.

[0135] Power output module: controls the motor and propeller to provide flight power.

[0136] (5) User interface module:

[0137] Ground Control Station Interface: Allows the operator to monitor the status of the drone, send commands and receive data.

[0138] Mobile device application interface: remotely control the drone via a mobile device.

[0139] (6) Data processing and storage module:

[0140] Data storage module: responsible for storing flight data and mission records.

[0141] Data analysis module: Analyze the collected data for decision support and post-processing.

[0142] (7) Security module:

[0143] Encrypted communication module: ensures the security of data transmission.

[0144] Safety monitoring module: real-time monitoring of the safety status of the drone system, including flight safety and data security.

[0145] (8) Extension modules:

[0146] Modular payload interface: allows the drone to carry different payloads such as pesticide sprayers, cameras, life-saving equipment, etc.

[0147] Function extension interface: An interface reserved for new functions that may be added in the future.

[0148] Through modular architecture design, the drone networking system can adapt to different application scenarios and changing needs more flexibly. Each module can be independently developed, tested and upgraded without affecting other modules, thus improving the overall efficiency and reliability of the system.

[0149] The present invention adopts a modular architecture design and a modular design concept to support the rapid iteration and expansion of drone hardware and software functions, making it easy to adapt to changing requirements in different application scenarios.

[0150] Step S40: Integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the drone platform, perform functional testing and performance optimization on the drone platform according to a preset test method, and obtain a drone networking system that meets the requirements.

[0151] Specifically, the path planning algorithm, task allocation algorithm, conflict avoidance algorithm, cooperative control algorithm, machine learning algorithm and data fusion algorithm are integrated into the UAV platform; the communication module, control module, perception module, power module, user interface module, data processing and storage module, security module and expansion module are integrated into the UAV platform; the UAV platform is functionally tested in a functional testing manner, and the performance of the UAV platform is optimized in a performance testing manner to obtain a UAV networking system that meets the requirements; wherein the functional testing includes unit testing, integration testing, system testing, interface testing, boundary condition testing and regression testing; the performance optimization includes performance monitoring, bottleneck analysis, code optimization, hardware optimization, network optimization, load balancing and redundant design.

[0152] Here are some specific methods and steps:

[0153] Functional testing:

[0154] (1) Unit testing:

[0155] Each module of the system is tested individually to ensure that they can independently perform their designed functions.

[0156] Use simulated data and actual hardware (e.g. sensors, communication modules) to test the functionality of the module.

[0157] (2) Integration testing:

[0158] Combine the modules together and test whether the interactions between them meet the design requirements.

[0159] Verify that data and control flows are passing correctly between parts of the system.

[0160] (3) System testing:

[0161] The entire system is comprehensively tested, including the networking, collaborative operations, and data sharing of drone clusters.

[0162] Test system responsiveness and stability in simulated and real environments.

[0163] (4) Interface test:

[0164] Test that the system’s interfaces with external systems (such as ground control stations, other drones, cloud services, etc.) are functioning properly.

[0165] (5) Boundary condition test:

[0166] Test system performance under extreme conditions such as communication loss, sensor failure, battery depletion, etc.

[0167] (6) Regression testing:

[0168] After each update or modification, rerun the test cases to ensure that the new changes have not introduced errors.

[0169] Performance optimization:

[0170] (1) Performance monitoring: Monitor key performance indicators during the test, such as communication delay, data processing speed, system response time, etc.

[0171] (2) Bottleneck analysis: Identify system performance bottlenecks, such as network bandwidth limitations, CPU processing power, memory usage, etc.

[0172] (3) Code optimization: Optimize the code related to performance bottlenecks, such as algorithm improvement, data structure optimization, and reduction of unnecessary calculations.

[0173] (4) Hardware optimization: Adjust the hardware configuration according to the test results, such as increasing memory, using a more efficient processor, upgrading the communication module, etc.

[0174] (5) Network optimization: Optimize network protocols and topology to reduce communication delays and improve data transmission efficiency.

[0175] (6) Load balancing: Implement load balancing in the drone cluster to ensure even distribution of tasks and avoid overloading of a single drone.

[0176] (7) Redundant design: Implement redundant design on key components to improve the reliability and fault tolerance of the system.

[0177] Through these functional testing and performance optimization steps, we can ensure that the drone networking system performs well in actual applications and meets design goals and user needs.

[0178] Step S50: verifying the effect of the drone networking system in the target application scenario, collecting feedback information after verification, and iteratively optimizing the drone networking system according to the feedback information.

[0179] Specifically, the drone networking system that meets the requirements is applied to agricultural plant protection scenarios, environmental monitoring scenarios and emergency rescue scenarios for effect verification. The agricultural plant protection scenarios include crop monitoring, precision spraying, terrain mapping and intelligent scheduling, and the environmental monitoring scenarios include air quality monitoring, water body monitoring, biological monitoring and disaster warning. When the verification is completed, the test results and user feedback after verification of each scenario are collected, and the drone networking system is iteratively optimized based on the test results and user feedback.

[0180] The specific methods of applying drone networking systems to agricultural plant protection, environmental monitoring and other fields are as follows:

[0181] Agricultural plant protection applications:

[0182] (1) Crop monitoring: Use drones equipped with high-resolution cameras to monitor crop growth conditions and collect data for analyzing crop health, pest and disease occurrence, etc.

[0183] (2) Precision spraying: The drone formulates a spraying plan based on monitoring data and works collaboratively through a networking system to achieve precise fertilization and pesticide spraying, reducing resource waste and environmental pollution.

[0184] (3) Topographic mapping: Use drones to map farmland topography and generate accurate 3D maps to help farmers better plan their planting plans.

[0185] (4) Intelligent scheduling: The networking system intelligently dispatches drones to perform plant protection tasks based on the crop growth cycle and weather conditions, thereby improving operational efficiency.

[0186] Specific application steps:

[0187] (1) Data collection: Drones are equipped with sensors and cameras to collect farmland data.

[0188] (2) Data analysis: The collected data is transmitted to the ground station for analysis to identify areas that need fertilization or spraying.

[0189] (3) Task allocation: The networking system allocates drones to perform specific plant protection tasks based on the analysis results.

[0190] (4) Operation execution: The drone performs precise plant protection operations according to the mission plan.

[0191] Environmental monitoring applications:

[0192] (1) Air quality monitoring: Drones carry air quality monitoring equipment to monitor air quality in real time and collect pollutant data.

[0193] (2) Water body monitoring: Drones monitor rivers, lakes and other water bodies, and detect water quality indicators such as pH value and dissolved oxygen.

[0194] (3) Wildlife monitoring: Use drones to monitor the population size and activity range of wild animals to protect biodiversity.

[0195] (4) Disaster warning: Before a natural disaster occurs, drones can conduct rapid monitoring of large areas through a networking system, providing data support for the early warning system.

[0196] Specific application steps:

[0197] (1) Development of monitoring plan: Develop UAV flight routes and monitoring plans based on monitoring objectives.

[0198] (2) Data collection: The drone performs monitoring tasks according to the plan and collects environmental data.

[0199] (3) Data analysis: Data is transmitted to the processing center for real-time analysis.

[0200] (4) Feedback: The monitoring results will be fed back to relevant departments for use in environmental management and decision-making.

[0201] When applied to these fields, the advantage of drone networking systems lies in their efficient information sharing and collaborative operation capabilities, which can quickly respond to environmental changes and provide accurate data support, thereby improving the intelligence and automation level of agricultural plant protection and environmental monitoring.

[0202] The process of verifying the effectiveness of the system usually includes the following key links:

[0203] (1) Scenario simulation and testing:

[0204] Simulated environment: simulate actual application scenarios in a controlled environment, such as simulated farmland, forests, rivers, etc., to test the performance of drones in different environments.

[0205] Functional testing: testing the various functions of the drone, including flight control, data collection, communication capabilities, mission execution, etc.

[0206] (2) Field deployment and operation:

[0207] On-site deployment: Deploy drones into actual application environments, such as real farmlands, monitoring areas, etc.

[0208] Real-time monitoring: The flight status, data transmission and mission execution of the UAV can be monitored in real time through the ground control station.

[0209] (3) Data collection and analysis:

[0210] Data collection: Drones collect relevant data while performing their missions, such as crop health data in plant protection operations and pollution data in environmental monitoring.

[0211] Data Analysis: Detailed analysis of the collected data is performed to evaluate the accuracy and efficiency of the system.

[0212] (4) Performance evaluation:

[0213] Operational efficiency: Evaluates how quickly and accurately a drone can complete a specific task.

[0214] System stability: Observe the stability and reliability of the system during continuous operation.

[0215] Communication Quality: Evaluate the quality of communication connections between drones, including signal strength, data transmission rate, and latency.

[0216] (5) Safety and reliability testing:

[0217] Fault simulation: simulate the failure of drones or communication systems to test the emergency response and recovery capabilities of the system.

[0218] Safety testing: Ensure that the drone does not cause harm to people and the environment during operation.

[0219] (6) User feedback and iteration:

[0220] User participation: Invite end users to participate in testing and collect their feedback and suggestions.

[0221] Iterative optimization: Make necessary adjustments and optimizations to the system based on test results and user feedback.

[0222] The specific steps are as follows:

[0223] (1) Develop a verification plan: clarify the verification objectives, methods, and timetable.

[0224] (2) Execution test: Conduct simulation test and field test according to the verification plan.

[0225] (3) Record results: Record the data and problems encountered during the test in detail.

[0226] (4) Evaluate the effect: Compare the test results with the expected goals and evaluate the system effect.

[0227] (5) Report preparation: Write a test report summarizing system performance and improvement suggestions.

[0228] (6) Feedback loop: Feedback test results and improvement suggestions to the R&D team for system iteration.

[0229] Through these steps, the effect of the drone networking system in actual application can be fully verified to ensure that the system can meet the design goals and user needs.

[0230] After the application scenario is verified, iterative optimization is a continuous improvement process based on the collected data, user feedback and test results. The following are the specific steps of iterative optimization:

[0231] (1) Data analysis and problem identification:

[0232] Analyze test data: Conduct in-depth analysis of the data collected by drones during field tests to identify performance bottlenecks, functional defects, or user experience issues.

[0233] User feedback summary: Summarize user feedback during the use of the system, including operational convenience, system response, task execution effect and other aspects.

[0234] (2) Problem classification and priority sorting:

[0235] Classify problems: Classify the identified problems according to functionality, performance, user experience, etc.

[0236] Prioritization: Determine the priority for resolving issues based on their severity and impact on the system.

[0237] (3) Plan formulation:

[0238] Propose solutions: For each problem identified, propose possible solutions.

[0239] Technical review: Organize a technical team to review the solution to ensure its feasibility and effectiveness.

[0240] (4) Development and implementation:

[0241] Coding implementation: Software development and hardware adaptation based on the determined solution.

[0242] Version control: Manage code changes through a version control system to ensure traceability and maintainability.

[0243] (5) Test verification:

[0244] Unit testing: Perform unit testing on modified or newly added code to ensure the correctness of individual components.

[0245] Integration testing: Integration testing is performed on the modified system to verify whether the interaction between components is as expected.

[0246] Regression testing: Ensure that modifications have not introduced new problems and that existing functions still work properly.

[0247] (6) Deployment and feedback:

[0248] Deployment update: Deploy the optimized system to the drone platform for actual operation testing.

[0249] Collect feedback: Collect user feedback and performance data again to evaluate the optimization effect.

[0250] (7) Repeated iteration:

[0251] Continuous improvement: Repeat the above steps to continuously optimize the system based on new data and feedback.

[0252] Documentation Update: Update technical documentation and user manuals to reflect the latest system changes.

[0253] The specific steps are as follows:

[0254] (1) Summarize the verification results: organize the achievements and shortcomings of the application scenario verification phase.

[0255] (2) Develop an optimization plan: Based on the verification results, develop a specific optimization plan and schedule.

[0256] (3) Execute optimization work: Carry out system optimization work according to the plan.

[0257] (4) Verify the optimization effect: Verify the optimization effect through testing and actual application.

[0258] (5) Adjust optimization strategy: Adjust optimization strategy according to verification results to ensure continuous improvement.

[0259] Through such an iterative optimization process, the drone networking system can continuously adapt to new demands and challenges, improve its performance and reliability, and ultimately achieve design goals and user satisfaction.

[0260] Furthermore, based on the verification results, technical standards and promotion plans will be formulated to promote the widespread application of drone networking systems.

[0261] In this invention, the formulation of technical standards and promotion plans is to ensure that the drone networking system can maintain consistency, security and reliability in a wider range of applications. The following are some possible technical standards and promotion plan contents:

[0262] Technical standards:

[0263] (1) Communication protocol standards:

[0264] Define a unified soft bus communication protocol stack standard to ensure seamless communication between different drones and devices.

[0265] Establish communication specifications such as data format, transmission rate, encryption mechanism, etc.

[0266] (2) Interface standards:

[0267] Specify the interface standards between UAVs and ground stations, and between UAVs and other UAVs, including physical interfaces and software interfaces.

[0268] Set up standardized payload interfaces to facilitate quick access to different mission modules.

[0269] (3) Safety standards:

[0270] Develop safety standards for drone operations, including flight safety, data security, and privacy protection.

[0271] Set safety certification processes and standards for drone systems.

[0272] (4) Performance standards:

[0273] Clarify the performance indicators of the drone system, such as flight time, communication distance, data processing capability, etc.

[0274] Develop performance testing methods and evaluation criteria.

[0275] (5) Interoperability standards:

[0276] Ensure interoperability of UAV systems with other systems (e.g. satellite navigation, ground control systems).

[0277] Establish cross-platform and cross-device working standards and compatibility requirements.

[0278] Promotion plan:

[0279] (1) Market research:

[0280] Research the target market to understand potential users' needs and existing competition.

[0281] (2) Partnership:

[0282] Establish partnerships with other companies in the industry to jointly promote drone networking systems.

[0283] Cooperate with research institutions and universities to conduct technical exchanges and talent training.

[0284] (3) Education and training:

[0285] Provide training courses on drone operation and maintenance to improve users' technical level.

[0286] Produce operation manuals and instructional videos to facilitate user learning and use.

[0287] (4) Demonstration projects:

[0288] Establish demonstration projects in different application scenarios to demonstrate the actual effects of the drone networking system.

[0289] Collect data through demonstration projects to prove the reliability and economic benefits of the system.

[0290] (5) Marketing and publicity:

[0291] Use various media channels to promote products and increase brand awareness.

[0292] Attend industry trade shows to meet face-to-face with potential customers.

[0293] (6) Policies and regulations:

[0294] Cooperate with government departments to promote the introduction of policies and regulations that are conducive to the development of drones.

[0295] Participate in the development of standards and regulations for the drone industry.

[0296] (7) After-sales service:

[0297] Establish a complete after-sales service system to provide technical support, maintenance services and parts supply.

[0298] Through these technical standards and promotion plans, drone networking systems can be more widely recognized and applied in the market, thereby promoting the development of the entire industry.

[0299] Through the above steps, the present invention will build an efficient, flexible and intelligent drone networking system, providing strong technical support for drone applications in the era of the Internet of Things.

[0300] Beneficial effects of the present invention:

[0301] (1) Enhanced compatibility: Through the cross-device collaboration capabilities of the OpenHarmony system, the compatibility of the drone networking system is improved and communication barriers between devices are reduced.

[0302] (2) Improve flexibility: Soft bus technology breaks the limitations of physical connections and enables dynamic networking and flexible adjustment of drone clusters.

[0303] (3) Improve scalability: Modular design supports rapid function expansion to meet the needs of diverse application scenarios.

[0304] (4) Enhanced intelligence: Integrate AI decision-making engines to improve the autonomous operation capabilities and intelligent decision-making level of drone clusters.

[0305] This invention aims to realize autonomous networking, collaborative operation, flexible expansion and intelligent management of drone clusters by integrating the cross-device collaboration capabilities of the open source Hongmeng system and the efficient communication mechanism of the soft bus, providing strong technical support and solutions for future application scenarios such as agricultural plant protection, environmental monitoring, emergency rescue, and logistics distribution.

[0306] Furthermore, if Figure 2As shown, based on the above-mentioned drone networking method based on the open source Hongmeng system and the soft bus, the present invention also provides a drone networking system based on the open source Hongmeng system and the soft bus, wherein the drone networking system based on the open source Hongmeng system and the soft bus includes:

[0307] The demand analysis module 51 is used to determine the target application scenarios and target functional requirements of the UAV networking system;

[0308] A system architecture design module 52, used to design a dedicated operating system and a soft bus communication protocol stack for the drone according to the target application scenario and the target functional requirements;

[0309] Function development module 53, used to develop intelligent collaborative operation algorithm and modular architecture according to the target application scenario and the target function requirements;

[0310] An integration and testing module 54 is used to integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the UAV platform, perform functional testing and performance optimization on the UAV platform according to a preset testing method, and obtain a UAV networking system that meets the requirements;

[0311] The verification and optimization module 55 is used to verify the effect of the drone networking system in the target application scenario, collect feedback information after verification, and iteratively optimize the drone networking system according to the feedback information.

[0312] Furthermore, if Figure 3 As shown, based on the above-mentioned drone networking method and system based on the open source Hongmeng system and soft bus, the present invention also provides a terminal accordingly, and the terminal includes a processor 10, a memory 20 and a display 30. Figure 3 Only some components of the terminal are shown, but it should be understood that it is not required to implement all of the components shown, and more or fewer components may be implemented instead.

[0313] In some embodiments, the memory 20 may be an internal storage unit of the terminal, such as a hard disk or memory of the terminal. In other embodiments, the memory 20 may also be an external storage device of the terminal, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc. equipped on the terminal. Further, the memory 20 may also include both an internal storage unit of the terminal and an external storage device. The memory 20 is used to store application software and various types of data installed on the terminal, such as the program code of the installation terminal. The memory 20 can also be used to temporarily store data that has been output or is to be output. In one embodiment, a drone networking program 40 based on an open source Hongmeng system and a soft bus is stored on the memory 20, and the drone networking program 40 based on the open source Hongmeng system and a soft bus can be executed by the processor 10, thereby realizing the drone networking method based on the open source Hongmeng system and a soft bus in this application.

[0314] In some embodiments, the processor 10 can be a central processing unit (CPU), a microprocessor or other data processing chip, used to run the program code or process data stored in the memory 20, such as executing the drone networking method based on the open source Hongmeng system and soft bus.

[0315] In some embodiments, the display 30 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch device, etc. The display 30 is used to display information on the terminal and to display a visual user interface. The components 10-30 of the terminal communicate with each other via a system bus.

[0316] In one embodiment, when the processor 10 executes the drone networking program 40 based on the open source Hongmeng system and the soft bus in the memory 20, the steps of the drone networking method based on the open source Hongmeng system and the soft bus as described above are implemented.

[0317] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a drone networking program based on the open source Hongmeng system and a soft bus, and when the drone networking program based on the open source Hongmeng system and a soft bus is executed by a processor, the steps of the drone networking method based on the open source Hongmeng system and a soft bus as described above are implemented.

[0318] In summary, the present invention provides a method, system, terminal and computer-readable storage medium for unmanned aerial vehicle networking based on an open source Hongmeng system and a soft bus, the method comprising: determining the target application scenario and target functional requirements of the unmanned aerial vehicle networking system; designing a dedicated unmanned aerial vehicle operating system and a soft bus communication protocol stack according to the target application scenario and the target functional requirements; developing an intelligent collaborative operation algorithm and a modular architecture according to the target application scenario and the target functional requirements; integrating the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the unmanned aerial vehicle platform, and performing functional testing and performance optimization on the unmanned aerial vehicle platform according to a preset test method to obtain a unmanned aerial vehicle networking system that meets the requirements; verifying the effect of the unmanned aerial vehicle networking system in the target application scenario, collecting feedback information after verification, and iteratively optimizing the unmanned aerial vehicle networking system according to the feedback information. The present invention aims to realize autonomous networking, collaborative operation, flexible expansion and intelligent management of unmanned aerial vehicle clusters by integrating the cross-device collaborative capabilities of the open source Hongmeng system and the efficient communication mechanism of the soft bus.

[0319] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or terminal including the element.

[0320] Of course, those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing related hardware (such as a processor, a controller, etc.) through a computer program, and the program can be stored in a computer-readable storage medium that can be read by a computer, and the program can include the processes of the above-mentioned method embodiments when executed. The computer-readable storage medium can be a memory, a disk, an optical disk, etc.

[0321] It should be understood that the application of the present invention is not limited to the above examples. For ordinary technicians in this field, improvements or changes can be made based on the above description. All these improvements and changes should fall within the scope of protection of the claims attached to the present invention.

Claims

1. A method for networking drones based on the open source Hongmeng system and soft bus, characterized in that: The drone networking method based on the open source Hongmeng system and soft bus includes: Determine the target application scenarios and target functional requirements of the UAV networking system; Design a dedicated operating system and soft bus communication protocol stack for drones based on the target application scenarios and target functional requirements; Develop intelligent collaborative operation algorithms and modular architectures based on the target application scenarios and target functional requirements; Integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the UAV platform, perform functional testing and performance optimization on the UAV platform according to a preset test method, and obtain a UAV networking system that meets the requirements; The effect of the drone networking system is verified in the target application scenario, feedback information after verification is collected, and the drone networking system is iteratively optimized according to the feedback information.

2. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 1 is characterized in that: Determining the target application scenarios and target functional requirements of the drone networking system specifically includes: Determine the target application scenarios for the assembled UAV networking system, wherein the target application scenarios include agricultural plant protection scenarios, environmental monitoring scenarios, and emergency rescue scenarios; Determine the target functional requirements that the UAV networking system needs to achieve after being established, and the target functional requirements include autonomous flight, data collection, image recognition and collaborative operation.

3. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 1 is characterized in that: According to the target application scenario and the target functional requirements, designing a dedicated operating system and a soft bus communication protocol stack for the drone specifically includes: Customized development of OpenHarmony system for drones; Based on the UAV-specific version of OpenHarmony system, design a UAV-specific operating system and soft bus communication protocol stack according to the target application scenario and the target functional requirements; Among them, the soft bus communication protocol stack is used for communication between various drones in the drone networking system.

4. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 1 is characterized in that: The development of intelligent collaborative operation algorithms and modular architectures based on the target application scenarios and target functional requirements specifically includes: Develop an intelligent collaborative operation algorithm according to the target application scenario and the target functional requirements, wherein the intelligent collaborative operation algorithm includes a path planning algorithm, a task allocation algorithm, a conflict avoidance algorithm, a collaborative control algorithm, a machine learning algorithm, and a data fusion algorithm; According to the target application scenario and the target functional requirements, a modular architecture is developed, which includes a communication module, a control module, a perception module, a power module, a user interface module, a data processing and storage module, a security module and an expansion module.

5. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 4 is characterized in that: The intelligent collaborative operation algorithm and all functional modules in the modular architecture are integrated into the UAV platform, and the UAV platform is functionally tested and performance optimized according to a preset test method to obtain a UAV networking system that meets the requirements, specifically including: Integrate path planning algorithms, task allocation algorithms, conflict avoidance algorithms, cooperative control algorithms, machine learning algorithms, and data fusion algorithms into UAV platforms; Integrate the communication module, control module, perception module, power module, user interface module, data processing and storage module, security module and expansion module into the UAV platform; Performing a functional test on the UAV platform according to a functional test method, and optimizing the performance of the UAV platform according to a performance test method, so as to obtain a UAV networking system that meets the requirements; Among them, the functional testing includes unit testing, integration testing, system testing, interface testing, boundary condition testing and regression testing; the performance optimization includes performance monitoring, bottleneck analysis, code optimization, hardware optimization, network optimization, load balancing and redundant design.

6. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 2 is characterized in that: The verifying the effect of the drone networking system in the target application scenario, collecting feedback information after verification, and iteratively optimizing the drone networking system according to the feedback information specifically includes: Apply the drone networking system that meets the requirements to agricultural plant protection scenarios, environmental monitoring scenarios and emergency rescue scenarios for effect verification. The agricultural plant protection scenarios include crop monitoring, precision spraying, terrain mapping and intelligent scheduling. The environmental monitoring scenarios include air quality monitoring, water body monitoring, biological monitoring and disaster warning. When the verification is completed, the test results and user feedback after verification of each scenario are collected, and the drone networking system is iteratively optimized based on the test results and the user feedback.

7. The method for networking unmanned aerial vehicles based on the open source Hongmeng system and soft bus according to claim 1 is characterized in that: The method further comprises verifying the effect of the drone networking system in the target application scenario, collecting feedback information after verification, and iteratively optimizing the drone networking system according to the feedback information, and then further comprising: Based on the verification results, technical standards for the UAV networking system are formulated, and the technical standards include communication protocol standards, interface standards, safety standards, performance standards and interoperability standards.

8. A drone networking system based on the open source Hongmeng system and soft bus, characterized in that: The UAV networking system based on the open source Hongmeng system and soft bus includes: Demand analysis module, used to determine the target application scenarios and target functional requirements of the drone networking system; A system architecture design module, used to design a dedicated operating system and a soft bus communication protocol stack for the drone according to the target application scenario and the target functional requirements; A function development module, used to develop intelligent collaborative operation algorithms and modular architectures according to the target application scenarios and the target function requirements; An integration and testing module, used to integrate the intelligent collaborative operation algorithm and all functional modules in the modular architecture into the UAV platform, perform functional testing and performance optimization on the UAV platform according to a preset testing method, and obtain a UAV networking system that meets the requirements; The verification and optimization module is used to verify the effect of the drone networking system in the target application scenario, collect feedback information after verification, and iteratively optimize the drone networking system according to the feedback information.

9. A terminal, characterized in that: The terminal includes: a memory, a processor, and a drone networking program based on an open source Hongmeng system and a soft bus, which is stored in the memory and can be run on the processor. When the drone networking program based on the open source Hongmeng system and the soft bus is executed by the processor, the steps of the drone networking method based on the open source Hongmeng system and the soft bus are implemented as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a drone networking program based on the open source Hongmeng system and a soft bus. When the drone networking program based on the open source Hongmeng system and a soft bus is executed by the processor, the steps of the drone networking method based on the open source Hongmeng system and a soft bus as described in any one of claims 1 to 7 are implemented.

Images