论文标题
图表机器人手的视觉印象
Charting Visual Impression of Robot Hands
论文作者
论文摘要
迄今为止，已经设计了各种各样的机器人手。但是，我们不知道用户如何看待这些双手，并且对与它们进行互动的感觉。为了告知社交机器人的手工设计，我们编制了73台机器人手的数据集并进行了一项在线研究，其中160位用户使用17个评分量表对手的印象进行了评价。接下来，我们开发了17个回归模型，可以从手的设计特征（例如手指数）中预测用户评分（例如，类人）。在0-100比例预测用户评分时，这些模型的误差小于10分。指尖，配色方案和手的大小影响用户评分最大。我们提出了简单的准则，以改善机器人手的印象，并概述将来工作的剩余问题。
A wide variety of robotic hands have been designed to date. Yet, we do not know how users perceive these hands and feel about interacting with them. To inform hand design for social robots, we compiled a dataset of 73 robot hands and ran an online study, in which 160 users rated their impressions of the hands using 17 rating scales. Next, we developed 17 regression models that can predict user ratings (e.g., humanlike) from the design features of the hands (e.g., number of fingers). The models have less than a 10-point error in predicting the user ratings on a 0-100 scale. The shape of the fingertips, color scheme, and size of the hands influence the user ratings the most. We present simple guidelines to improve user impression of robot hands and outline remaining questions for future work.
