The integration of augmented reality (AR) and EEG-based brain-computer interfaces (BCIs) offers a promising path for enabling intuitive control of robots for assistive purposes. However, existing AR brain-robot interface (BRI) systems are often constrained to task-specific structures, limiting their utility in real-world environments. We present an AR BRI designed for generalist robot arm manipulation that combines gaze-based object selection with motor imagery action control. Our system uses eye-tracking for intuitive object targeting and context-aware visual overlays ("Place" and "Use") to guide the user through tasks within a shared autonomy framework. We evaluated the interface through a feasibility study with 18 healthy participants performing three multi-step activities of daily living: drinking, using a drawer, and operating an oven. Our results demonstrate that this interaction paradigm enables effective sequential task execution and high user engagement, achieving a "Good" usability rating (SUS > 70). These findings support the feasibility of the proposed interaction paradigm for complex BCI-driven robotic assistance, and motivate future evaluation with the intended target population. Project website: https://ar-bri-manip.github.io/.

翻译：增强现实（AR）与基于脑电图（EEG）的脑-机接口（BCI）的融合为开发直观的辅助型机器人控制提供了有前景的路径。然而，现有AR脑-机器人接口（BRI）系统通常受限于特定任务结构，削弱了其在真实环境中的适用性。我们提出一种面向通用机器人臂操控的AR BRI，该接口将基于眼动的目标选择与基于运动想象的动作控制相结合。本系统通过眼动追踪实现直观的目标定位，并利用上下文感知的视觉覆盖层（“放置”与“使用”）在共享自主框架内引导用户完成任务。我们通过一项可行性研究评估该接口，该研究包含18名健康受试者执行三项多步日常活动：饮水、使用抽屉及操作烤箱。结果表明，该交互范式能够实现高效的顺序任务执行与高用户参与度，获得“良好”可用性评分（SUS > 70）。这些发现支持了所提议交互范式用于复杂BCI驱动型机器人辅助的可行性，并推动未来在目标人群中开展进一步评估。项目网站：https://ar-bri-manip.github.io/。