基于事件相关电位的水下机械手脑电波控制

doi:10.13973/j.cnki.robot.2017.0395

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俞建成, 张进, 李伟. 基于事件相关电位的水下机械手脑电波控制[J]. 机器人, 2017, 39(4): 395-404.DOI: 10.13973/j.cnki.robot.2017.0395. YU Jiancheng, ZHANG Jin, LI Wei. Controlling an Underwater Manipulator via Event-Related Potentials of Brainwaves. ROBOT, 2017, 39(4): 395-404. DOI: 10.13973/j.cnki.robot.2017.0395.

摘要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%、27.7bits/min与90.1s．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．

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关键词 ：水下机械手, 复杂任务, 事件相关电位(ERP), 脑-机接口(BCI), 信息传输率(ITR)

Abstract：To free two hands of the underwater manipulator operator, the BCI (brain-computer interface) technology is applied to underwater operational tasks in this paper, where the manipulator follows instructions transformed from the brainwaves. As the current brainwave-based manipulator control methods can't satisfy requirements for the actual underwater tasks in terms of real-time performance and accuracy, a control strategy is proposed for controlling the underwater manipulator via event-related potentials (ERP) of brainwaves (evoked by visual stimuli). The operator can quickly complete a given task after optimizing the visual evoked ERP interface and combining the characteristics of the brainwaves control and the underwater manipulator operation. Eight subjects are invited to conduct experiments on a self-developed experimental platform. The average accuracy of identifying an operator's intention, the system information transfer rate and the average control time of completing the task are 91.5%, 27.7 bits/min and 90.1 s, respectively. Comparing with the similar systems, the system performance of the proposed control strategy is better, and the operational efficiency satisfies the practical operational requirements.

Key words： underwater manipulator complicated task event-related potentials (ERP) brain-computer interface (BCI) information transfer rate (ITR)

收稿日期: 2017-03-28 录用日期: 2017-05-30

TP24

基金资助:国家重点研发计划项目（2016YFC0300801）；中国科学院前沿科学重点研究项目（QYZDY-SSW-JSC005）；国家自然科学基金重点项目（61233013）

通讯作者: 李伟,E-mail:wli@csub.edu E-mail: wli@csub.edu

作者简介: 俞建成(1976-),男,博士,研究员.研究领域:水下机器人,水下机器人设计.
张进(1987-),男,博士生.研究领域:水下机械手建模与控制,脑-机接口.
李伟(1957-),男,博士,研究员.研究领域:脑-机器人交互,模糊控制与建模.

链接本文:

https://robot.sia.cn/CN/10.13973/j.cnki.robot.2017.0395 或 https://robot.sia.cn/CN/Y2017/V39/I4/395

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