We present in-hand manipulation skills on a dexterous, compliant, anthropomorphic hand. Even though these skills were derived in a simplistic manner, they exhibit surprising robustness to variations in shape, size, weight, and placement of the manipulated object. They are also very insensitive to variation of execution speeds, ranging from highly dynamic to quasi-static. The robustness of the skills leads to compositional properties that enable extended and robust manipulation programs. To explain the surprising robustness of the in-hand manipulation skills, we performed a detailed, empirical analysis of the skills' performance. From this analysis, we identify three principles for skill design: 1) Exploiting the hardware's innate ability to drive hard-to-model contact dynamics. 2) Taking actions to constrain these interactions, funneling the system into a narrow set of possibilities. 3) Composing such action sequences into complex manipulation programs. We believe that these principles constitute an important foundation for robust robotic in-hand manipulation, and possibly for manipulation in general.
翻译:尽管这些技能是以一种简单的方式获得的,但它们在形状、大小、重量和被操纵对象的位置上表现出惊人的强健性。它们对于执行速度的变化也非常不敏感,从高度动态到准静态不等。这些技能的坚固性导致组成性能,使得能够进行扩展和有力的操纵程序。为了解释手动操作技能的惊人强健性,我们对技能的性能进行了详细的实验性分析。我们从这一分析中确定了技能设计的三个原则:(1) 开发硬件的内在能力,以驱动硬模范接触动态。(2) 采取行动限制这些相互作用,将系统整合到一套狭窄的可能性中。(3) 将此类行动序列整合到复杂的操纵程序中。我们认为,这些原则构成了强有力的机器人手动操纵的重要基础,并有可能是一般操纵的重要基础。