Generation of expressive motions for a tabletop robot interpolating from hand-made animations

Gonzalo Mier, F. Caballero, Keisuke Nakamura, L. Merino, R. Gomez
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Abstract

Motion is an important modality for human-robot interaction. Besides a fundamental component to carry out tasks, through motion a robot can express intentions and expressions as well. In this paper, we focus on a tabletop robot in which motion, among other modalities, is used to convey expressions. The robot incorporates a set of pre-programmed motion animations that show different expressions with various intensities. These have been created by designers with expertise in animation. The objective in the paper is to analyze if these examples can be used as demonstrations, and combined by the robot to generate additional richer expressions. Challenges are the representation space used, and the scarce number of examples. The paper compares three different learning from demonstration approaches for the task at hand. A user study is presented to evaluate the resultant new expressive motions automatically generated by combining previous demonstrations.
桌面机器人从手工动画插值生成富有表现力的动作
运动是人机交互的一种重要形式。除了作为执行任务的基本部件外,机器人还可以通过运动表达意图和表情。在本文中,我们关注的是一个桌面机器人,其中运动,在其他模式中,被用来传达表情。该机器人集成了一组预先编程的运动动画,可以显示不同强度的不同表情。这些都是由具有动画专业知识的设计师创造的。本文的目的是分析这些示例是否可以作为演示,并由机器人组合以生成额外的更丰富的表达式。挑战在于所使用的表示空间,以及样本数量的稀缺。本文比较了当前任务的三种不同的示范学习方法。提出了一项用户研究,以评估通过结合先前的演示自动生成的新表达动作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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