基于脑机接口与人机闭环的远程脑控无人机系统

With the rapid evolution of modern military warfare, the remote brain-controlled unmanned aerial vehicle (UAV) systems are playing an increasingly important role in battlefield information gathering, target surveillance, and tactical deployment. This research proposes a compressed sensing control paradigm and a human-machine closed-loop control algorithm for remote brain-controlled UAV. Based on this control paradigm and algorithm, a remote brain-controlled UAV system for military applications is constructed. Online experiments conducted in this study demonstrate that eight participants successfully completed the navigation tasks using the brain-controlled UAV system based on the compressed sensing control paradigm and human-machine closed-loop control algorithm. The average task completion rate of the proposed brain-controlled UAV system is 0. 95, and its average task completion time is 100. 46 s, which significantly outperformes the brain-controlled UAV system based on human-machine open-loop control algorithms. In the future, the proposed brain-controlled UAV system can be used for battlefield reconnaissance in military scenarios, significantly enhancing the remote-control capabilities of military personnel and expanding their battlefield awareness.