In this paper we present an early prototype of the Digger Finger that is designed to easily penetrate granular media and is equipped with the GelSight sensor. Identifying objects buried in granular media using tactile sensors is a challenging task. First, particle jamming in granular media prevents downward movement. Second, the granular media particles tend to get stuck between the sensing surface and the object of interest, distorting the actual shape of the object. To tackle these challenges we present a Digger Finger prototype. It is capable of fluidizing granular media during penetration using mechanical vibrations. It is equipped with high resolution vision based tactile sensing to identify objects buried inside granular media. We describe the experimental procedures we use to evaluate these fluidizing and buried shape recognition capabilities. A robot with such fingers can perform explosive ordnance disposal and Improvised Explosive Device (IED) detection tasks at a much a finer resolution compared to techniques like Ground Penetration Radars (GPRs). Sensors like the Digger Finger will allow robotic manipulation research to move beyond only manipulating rigid objects.
翻译:在本文中,我们展示了用于容易穿透颗粒介质并配有GelSight传感器的挖掘器早期原型。使用触摸传感器识别颗粒介质中埋藏的物体是一项艰巨的任务。首先,颗粒介质干扰防止向下移动。第二,颗粒介质颗粒颗粒在感测表面和受关注对象之间被卡住,扭曲了物体的实际形状。为了应对这些挑战,我们展示了一个挖掘器原型。它能够在使用机械振动的渗透过程中流出颗粒介质。它配备基于高分辨率的触动感测仪,用以识别颗粒介质中埋藏的物体。我们描述了我们用来评估这些流化和掩埋形状识别能力的实验程序。一个有这种手指的机器人可以比地面穿透雷达(GPRs)等技术更精细的分辨率来进行爆炸性弹药处置和简易爆炸装置探测任务。像Digger手指这样的传感器将允许机器人操纵研究超越仅仅操纵僵硬物体的范围。