Wudarczyk Olga A, Kirtay Murat, Kuhlen Anna K, Abdel Rahman Rasha, Haynes John-Dylan, Hafner Verena V, Pischedda Doris
Department of Psychology, Humboldt-Universität zu Berlin, Berlin, Germany.
Adaptive Systems Group, Department of Computer Science, Humboldt-Universität zu Berlin, Berlin, Germany.
Front Hum Neurosci. 2021 Mar 29;15:630789. doi: 10.3389/fnhum.2021.630789. eCollection 2021.
The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience, and Psychology as the three fields have quite different perspectives and approaches to offer. Nonetheless, aligning backgrounds and interdisciplinary expectations can present challenges due to varied research cultures and practices. Overcoming these challenges stands at the beginning of each productive collaboration and thus is a mandatory step in cognitive neurorobotics. In this article, we share eight lessons that we learned from our ongoing interdisciplinary project on human-robot and robot-robot interaction in social settings. These lessons provide practical advice for scientists initiating interdisciplinary research endeavors. Our advice can help to avoid early problems and deal with differences between research fields, prepare for and anticipate challenges, align project expectations, and speed up research progress, thus promoting effective interdisciplinary research across Robotics, Neuroscience, and Psychology.
跨学科研究团队多样化的方法和专业知识提供了克服单一学科有限视角的机会。在机器人学、神经科学和心理学的交叉领域尤其如此,因为这三个领域有着截然不同的视角和方法。然而,由于研究文化和实践的差异,协调背景和跨学科期望可能会带来挑战。克服这些挑战是每一项富有成效的合作的起点,因此也是认知神经机器人学中的必要步骤。在本文中,我们分享了从正在进行的关于社交场景中人与机器人以及机器人与机器人交互的跨学科项目中学到的八点经验。这些经验为开展跨学科研究的科学家提供了实用建议。我们的建议有助于避免早期问题,应对研究领域之间的差异,为挑战做好准备并提前预判,协调项目期望,加快研究进展,从而促进机器人学、神经科学和心理学领域的有效跨学科研究。