| Citation: | XUE Y，HE F，GU X Y. UAV information interaction topology generation considering task allocation[J]. Journal of Beijing University of Aeronautics and Astronautics，2023，49（7）：1787-1795 （in Chinese） doi: 10.13700/j.bh.1001-5965.2021.0486
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The optimization of information interaction topology for persistent unmanned aerial vehicle (UAV) formation is an important basis for the stability of UAV formation structure and the timeliness of task execution. The existing formation generation algorithms assign weights and generate topologies based on the factor of distance rather than task allocation; therefore, the overall task execution may be too long or even fail, causing unnecessary loss of UAV energy. This study proposes an information interaction topology optimization algorithm considering the factor of task allocation, with the task message transmission time and energy loss being the key optimization objectives, and with the premise of ensuring the stability of UAV formation structure. The key aggregation links performing high real-time communication tasks are preferentially connected, and the penalty term is introduced for the remaining links. Furthermore, the weight factor of task message transmission is taken into account to generate the final information interaction topology. OMNet++ is used for simulation verification. Compared with the information interaction topology generation algorithm considering only the distance factor, the algorithm considering the task factor can reduce the message transmission time by 57.3% and 28.1% at the highest and lowest levels in the formation scenario of 20 UAVs, respectively. The arrival delay of mission-critical messages is reduced by 45.2% to 51.6%. During the mission execution, the energy loss of a single UAV is reduced by 17.5% overall, and the loss per node is reduced by 16.1% on average.
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