Brain-robot interaction (BRI) empowers individuals to control (semi-)automated machines through their brain activity, either passively or actively. In the past decade, BRI systems have achieved remarkable success, predominantly harnessing electroencephalogram (EEG) signals as the central component. This paper offers an up-to-date and exhaustive examination of 87 curated studies published during the last five years (2018-2023), focusing on identifying the research landscape of EEG-based BRI systems. This review aims to consolidate and underscore methodologies, interaction modes, application contexts, system evaluation, existing challenges, and potential avenues for future investigations in this domain. Based on our analysis, we present a BRI system model with three entities: Brain, Robot, and Interaction, depicting the internal relationships of a BRI system. We especially investigate the essence and principles on interaction modes between human brains and robots, a domain that has not yet been identified anywhere. We then discuss these entities with different dimensions encompassed. Within this model, we scrutinize and classify current research, reveal insights, specify challenges, and provide recommendations for future research trajectories in this field. Meanwhile, we envision our findings offer a design space for future human-robot interaction (HRI) research, informing the creation of efficient BRI frameworks.

翻译：脑-机器人交互（BRI）使个体能够通过其脑活动（被动或主动地）控制（半）自动化机器。过去十年间，BRI系统取得了显著成功，主要利用脑电图（EEG）信号作为核心组件。本文对过去五年（2018-2023年）发表的87篇精选研究进行了最新且详尽的审视，聚焦于识别基于EEG的BRI系统的研究格局。本综述旨在整合并强调该领域的方法学、交互模式、应用场景、系统评估、现有挑战及未来研究的潜在方向。基于我们的分析，我们提出了一个包含三个实体——脑、机器人和交互——的BRI系统模型，描绘了BRI系统的内部关系。我们特别探究了人脑与机器人之间交互模式的本质与原理，这是一个尚未被界定的领域。随后，我们从不同维度讨论了这些实体。在此模型框架内，我们审视并分类了当前研究，揭示了洞见，明确了挑战，并为该领域的未来研究轨迹提供了建议。同时，我们期望我们的发现能为未来人机交互（HRI）研究提供设计空间，助力高效BRI框架的构建。