An Augmented Reality Brain-Robot Interface for Generalist Robot Arm Manipulation

Abstract: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: this https URL.

Robotics (cs.RO); Human-Computer Interaction (cs.HC)

arXiv:2606.16413 [cs.RO]

(or arXiv:2606.16413v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2606.16413 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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