Czeszumski Artur, Gert Anna L, Keshava Ashima, Ghadirzadeh Ali, Kalthoff Tilman, Ehinger Benedikt V, Tiessen Max, Björkman Mårten, Kragic Danica, König Peter
Institute of Cognitive Science, Universität Osnabrück, Osnabrück, Germany.
Robotics, Perception and Learning, School of Electrical Engineering and Computer Science, Kungliga Tekniska Högskolan Royal Institute of Technology, Stockholm, Sweden.
Front Neurorobot. 2021 Aug 11;15:686010. doi: 10.3389/fnbot.2021.686010. eCollection 2021.
Robots start to play a role in our social landscape, and they are progressively becoming responsive, both physically and socially. It begs the question of how humans react to and interact with robots in a coordinated manner and what the neural underpinnings of such behavior are. This exploratory study aims to understand the differences in human-human and human-robot interactions at a behavioral level and from a neurophysiological perspective. For this purpose, we adapted a collaborative dynamical paradigm from the literature. We asked 12 participants to hold two corners of a tablet while collaboratively guiding a ball around a circular track either with another participant or a robot. In irregular intervals, the ball was perturbed outward creating an artificial error in the behavior, which required corrective measures to return to the circular track again. Concurrently, we recorded electroencephalography (EEG). In the behavioral data, we found an increased velocity and positional error of the ball from the track in the human-human condition vs. human-robot condition. For the EEG data, we computed event-related potentials. We found a significant difference between human and robot partners driven by significant clusters at fronto-central electrodes. The amplitudes were stronger with a robot partner, suggesting a different neural processing. All in all, our exploratory study suggests that coordinating with robots affects action monitoring related processing. In the investigated paradigm, human participants treat errors during human-robot interaction differently from those made during interactions with other humans. These results can improve communication between humans and robot with the use of neural activity in real-time.
机器人开始在我们的社会环境中发挥作用,并且它们在身体和社交方面正逐渐变得具有响应能力。这就引出了一个问题:人类如何以协调的方式对机器人做出反应并与之互动,以及这种行为的神经基础是什么。这项探索性研究旨在从行为层面和神经生理学角度了解人与人以及人与机器人互动之间的差异。为此,我们改编了文献中的一种协作动力学范式。我们让12名参与者握住平板电脑的两个角,同时与另一名参与者或机器人协作,引导一个球在圆形轨道上运动。球会不定期地向外受到干扰,从而在行为中产生人为误差,这就需要采取纠正措施才能再次回到圆形轨道。同时,我们记录了脑电图(EEG)。在行为数据中,我们发现与人类-机器人条件相比,在人与人条件下球偏离轨道的速度和位置误差有所增加。对于脑电图数据,我们计算了事件相关电位。我们发现,额中央电极处的显著簇驱动了人与机器人伙伴之间的显著差异。与机器人伙伴互动时的振幅更强,这表明神经处理方式有所不同。总而言之,我们的探索性研究表明,与机器人协作会影响与动作监测相关的处理过程。在研究的范式中,人类参与者在人与机器人互动过程中对待误差的方式与在与其他人互动时不同。这些结果可以通过实时利用神经活动来改善人与机器人之间的沟通。