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基于脑机接口的无人机编队控制系统设计

Design of UAV Formation Control System Based on Brain-Computer Interface Data

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【作者】 李家伟张洪欣徐瑞林

【Author】 Li Jiawei;Zhang Hongxin;Xu Ruilin;Beijing University of Posts and Telecommunications;

【机构】 北京邮电大学

【摘要】 随着脑机接口(BCI)技术的不断发展,越来越多基于脑机接口的应用被不断研究并实现。为提高无人机编队的工作效率,针对无人机编队的常用控制命令,本文设计了一种8目标的稳态视觉诱发电位(SSVEP)脑机接口控制无人机编队系统。该系统允许用户通过脑机接口的8个命令对无人机编队进行队形切换等灵活控制。本系统采用典型相关分析(CCA)方法对脑电进行解码,并将解码结果使用Leader-Follower的方法对无人机编队进行控制。来自6例健康受试者的试验结果表明,研究所设计的脑控无人机编队系统具有较好的性能,平均识别准确率高达97%,验证了基于非侵入式脑机接口技术控制无人机编队的可行性。

【Abstract】 With the continuous development of brain-computer interface(BCI) technology, more and more applications based on BCI have been studied and implemented. In order to improve the working efficiency of UAV formation, an 8-target steady state visual evoked potential(SSVEP) brain-computer interface control UAV formation system is designed for the common control commands of UAV formation. The system allows users to flexibly control the formation of UAV through 8 commands of brain-computer interface,adpots canonical correlation analysis(CCA)method to decode EEG, and uses Leader-Follower method to control UAV formation. The experimental results from 6healthy subjects show that the brain controlled UAV formation system designed in the research has good performance, and the average recognition accuracy is up to 97%, which verifies the feasibility of controlling UAV formation based on non-invasive brain-computer interface technology.

【基金】 航空科学基金(2019ZG073001);国家自然科学基金(62006024);北京邮电大学中央高校基本科研专项资金(2019XD17);广东省重点领域研发计划(2018B030339001);国家重点基础研究发展规划项目(2017YFB1002505)~~
  • 【文献出处】 航空科学技术 ,Aeronautical Science & Technology , 编辑部邮箱 ,2023年02期
  • 【分类号】V279;V249.1
  • 【下载频次】71
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