Hedayati Hooman, Suzuki Ryo, Rees Wyatt, Leithinger Daniel, Szafir Daniel
Department of Computer Science, University of Colorado, Boulder, CO, United States.
Department of Computer Science, University of Calgary, Calgary, AB, Canada.
Front Robot AI. 2022 Apr 11;9:719639. doi: 10.3389/frobt.2022.719639. eCollection 2022.
In this paper, we survey the emerging design space of expandable structures in robotics, with a focus on how such structures may improve human-robot interactions. We detail various implementation considerations for researchers seeking to integrate such structures in their own work and describe how expandable structures may lead to novel forms of interaction for a variety of different robots and applications, including structures that enable robots to alter their form to augment or gain entirely new capabilities, such as enhancing manipulation or navigation, structures that improve robot safety, structures that enable new forms of communication, and structures for robot swarms that enable the swarm to change shape both individually and collectively. To illustrate how these considerations may be operationalized, we also present three case studies from our own research in expandable structure robots, sharing our design process and our findings regarding how such structures enable robots to produce novel behaviors that may capture human attention, convey information, mimic emotion, and provide new types of dynamic affordances.
在本文中，我们考察了机器人领域中可扩展结构这一新兴的设计空间，重点关注此类结构如何改善人机交互。我们详细阐述了研究人员在将此类结构集成到自己的工作中时需要考虑的各种实施因素，并描述了可扩展结构如何为各种不同的机器人和应用带来新颖的交互形式，包括使机器人能够改变其形态以增强或获得全新能力的结构，如增强操作或导航能力；提高机器人安全性的结构；实现新通信形式的结构；以及用于机器人集群的结构，使集群能够单独或集体改变形状。为了说明如何将这些因素付诸实践，我们还展示了来自我们自己在可扩展结构机器人研究中的三个案例研究，分享我们的设计过程以及关于此类结构如何使机器人产生可能吸引人类注意力、传达信息、模仿情感并提供新型动态功能的新颖行为的研究结果。
