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为了解放水下机械手操作人员的双手,本文将脑-机接口(BCI)技术应用到水下机器人作业中,通过解析脑电信号并将其映射为具体指令从而控制机械手.现有的脑电波控制机械手方法在实时性、准确性方面无法满足实际的水下作业要求,提出了基于视觉诱发模式的ERP(事件相关电位)脑电信号来控制水下机械手的策略.通过融合脑电波控制与水下机械手作业的各自特点和优化ERP视觉诱发界面,使操作人员能够快速地完成给定任务.8位被试被邀请在建立的实验平台上进行控制实验,最终得到的辨识操作人员意图平均准确率、系统信息传输率与完成任务平均控制时间分别为91.5%、27.7 bits/min与90.1 s.与同类系统相比,本文所提控制策略系统性能更好,且作业效率满足实际作业要求.
In order to unleash the hands of the operators of underwater robots, this paper applies the Brain-Machine Interface (BCI) technology to underwater robotics and controls the robots by resolving the EEG signals and mapping them into specific instructions.The existing brainwave control The robot method can not meet the requirement of underwater operation in real time and accuracy, and put forward the strategy of controlling the underwater manipulator based on the ERP (event-related potential) based on the visual evoked mode.Through the fusion of EEG control and underwater Robot manipulator’s own characteristics and optimize the ERP visual interface to enable the operator to quickly complete a given task.8 participants were invited to control the experiment on the established experimental platform, and finally get the average accuracy of operator intent identification, The average transmission rate of system information and the average control time of completing tasks are 91.5%, 27.7 bits / min and 90.1 s, respectively.Compared with other systems, the proposed control strategy has better system performance and the operating efficiency meets the requirements of the actual operation.