Design and implementation of unmanned swarm network simulation experimental teaching platform
[Objective]The integration of diverse unmanned platforms into swarm systems,especially to bolster their efficacy in intricate and ever-changing environments,has become a central focus in unmanned technology research.The progression of communication and network technology for unmanned swarms necessitates enhancements in education and training to foster professionals adept at navigating emerging technologies.To tackle the challenges in experimental teaching concerning unmanned swarm networks,including the disparity between theory and practice,high experimental costs,inadequate testing stability,and potential hazards,this study introduces an unmanned swarm network simulation teaching platform.[Methods]This platform relies on high-fidelity self-organizing network simulation technology,integrating unmanned swarm algorithms,flight control simulation,and network performance evaluation.The platform achieves multi-system distributed joint simulation,effectively supporting the simulation verification of unmanned swarm networks.Specifically,the overall design of the experimental platform begins with the integration of simulation experiment requirements,using scenario models as input,which include the fundamental parameters of unmanned swarm autonomous control strategies and communication network configurations.The platform is primarily divided into two core simulation subsystems:the unmanned swarm autonomous control simulation subsystem and the distributed self-organizing network simulation subsystem.The unmanned swarm autonomous control simulation subsystem can validate various swarm intelligence algorithms,generate swarm motion planning results,and transmit them to the swarm network simulation subsystem for high-fidelity simulation of its communication network performance.Finally,the performance evaluation module comprehensively analyzes the control strategies and network configurations of unmanned swarms,validating their capability to undertake complex tasks and sustain communication network functionalities within a simulated environment.Through simulation,testing,and analysis,the performance evaluation subsystem of this experimental platform provides a comprehensive assessment of the stability of unmanned swarm systems.This facilitates the optimization of system design,ensuring the efficiency and reliability of unmanned swarms during the execution of intricate tasks.[Results]Two task scenarios are studied and verified using the proposed platform:1)The experimental results of the unmanned aerial vehicle(UAV)swarm cooperative intelligence reconnaissance network demonstrate the achievement of real-time interactive data sharing among UAVs and successful transmission of information to the ground control center.In the same reconnaissance area,the unmanned swarm system displays higher accuracy and robustness.Moreover,increasing the number of swarm nodes effectively enhances reconnaissance and tracking performance.2)The validation of rapid reconstruction algorithms for UAV swarm network topology destruction reveals that after network topology failure,the network can autonomously diagnose faults and repair topological failures.Consequently,when certain UAVs are unable to communicate,the execution of tasks by other UAVs is not impeded.[Conclusions]The proposed platform facilitates multi-system distributed joint simulation,enhancing the efficiency and effectiveness of both teaching and research endeavors.Throughout the teaching process,the platform's intuitive demonstrations contribute to deepening students'comprehension of unmanned swarm network theories and enhance their enthusiasm for learning.Furthermore,the platform offers an open interface,enabling students to autonomously design and verify communication models,network protocols,and cluster algorithms.This fosters a"learning by doing"approach,stimulating innovative practical abilities among students.
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