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半自主连续机器人手臂控制使用增强现实大脑计算机接口.

Kirill Kokorin, Syeda R Zehra, Jing Mu

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    概括
    此摘要是机器生成的。

    使用稳定状态视觉唤起潜能 (SSVEP) 的增强现实脑电脑接口 (AR-BCI) 的共享控制 (SC) 增强了机器人控制. 与直接控制相比,这种SSVEP AR-BCI系统提高了任务成功率并减少了工作负载.

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    科学领域:

    • 神经科学是一个神经科学.
    • 机器人技术 机器人技术 机器人技术
    • 人与计算机的交互

    背景情况:

    • 使用稳定状态视觉唤起潜能 (SSVEP) 的非侵入性增强现实脑电脑接口 (AR-BCI) 通常依赖于机器人控制的完全自动化.
    • 虽然自动化提高了性能,但用户可能希望对机器人运动进行更直接的控制 (DC).

    研究的目的:

    • 开发和评估使用SSVEP AR-BCI的机器人翻译共享控制 (SC) 系统.
    • 为用户提供自主辅助和直接手动控制之间的平衡.

    主要方法:

    • 通过SSVEP AR-BCI设计了一个SC系统,用于通过SSVEP AR-BCI连续控制机器人翻译.
    • 该系统预测了用户的意图,生成了辅助信号,并根据信心调整了辅助.
    • 18名参与者在DC和SC条件下执行了3D达标任务.

    主要成果:

    • 与DC相比,SC显著提高了任务成功率,达到36.1%.
    • SC将正常化到达轨道的长度减少了26.8%.
    • 用NASA任务负载指数衡量的参与者工作量在SC下显著减少.

    结论:

    • 开发的SC系统通过SSVEP AR-BCI实现了有效的机器人控制,增强了用户代理.
    • 该系统允许通过允许用户选择他们想要的自主辅助水平来实现个性化的辅助技术.