Handovers are basic yet sophisticated motor tasks performed seamlessly by humans. They are among the most common activities in our daily lives and social environments. This makes mastering the art of handovers critical for a social and collaborative robot. In this work, we present an experimental study that involved human-human handovers by 13 pairs, i.e., 26 participants. We record and explore multiple features of handovers amongst humans aimed at inspiring handovers amongst humans and robots. With this work, we further create and publish a novel data set of 8672 handovers, bringing together human motion and the forces involved. We further analyze the effect of object weight and the role of visual sensory input in human-human handovers, as well as possible design implications for robots. As a proof of concept, the data set was used for creating a human-inspired data-driven strategy for robotic grip release in handovers, which was demonstrated to result in better robot to human handovers.
翻译:交接是人类无缝完成的基本且复杂的运动任务之一。它们是我们日常生活和社交环境中最常见的活动之一,这使得掌握交接艺术对于社交和合作机器人至关重要。在这项工作中,我们提出了一项涉及13对人类交接的实验研究,即26名参与者。我们记录并探索了人类交接中的多种特征,旨在激发人类和机器人之间的交接。通过本次工作,我们进一步创建并发布了一个包含8672个交接的新型数据集,将人体运动和涉及力量结合在一起。我们进一步分析了物体重量和视觉感官输入在人类间交接中的影响,以及对机器人的可能设计启示。作为概念证明,该数据集被用于创建一种基于数据驱动的人类启发式策略,用于机器人在交接中释放抓握,证明其可以实现更好的机器人-人类交接。