Most current anthropomorphic robotic hands can realize part of the human hand functions, particularly for object grasping. However, due to the complexity of the human hand, few current designs target at daily object manipulations, even for simple actions like rotating a pen. To tackle this problem, we introduce a gesture based framework, which adopts the widely-used 33 grasping gestures of Feix as the bases for hand design and implementation of manipulation. In the proposed framework, we first measure the motion ranges of human fingers for each gesture, and based on the results, we propose a simple yet dexterous robotic hand design with 13 degrees of actuation. Furthermore, we adopt a frame interpolation based method, in which we consider the base gestures as the key frames to represent a manipulation task, and use the simple linear interpolation strategy to accomplish the manipulation. To demonstrate the effectiveness of our framework, we define a three-level benchmark, which includes not only 62 test gestures from previous research, but also multiple complex and continuous actions. Experimental results on this benchmark validate the dexterity of the proposed design and our video is available in \url{https://drive.google.com/file/d/1wPtkd2P0zolYSBW7_3tVMUHrZEeXLXgD/view?usp=sharing}.
翻译:目前大多数人类变形机器人手可以实现人体手功能的一部分功能,特别是物体捕捉功能。 但是,由于人类手的复杂程度,日常物体操纵,甚至旋转笔等简单动作,目前设计的目标很少。 为了解决这个问题,我们引入了一个基于手势的框架,将广泛使用的33个Feix握手手势作为手式设计和实施操作的基础。在拟议框架中,我们首先测量每个动作的人体手指运动范围,并根据结果,我们提议一个简单但灵活的机器人手设计,带有13度动作。此外,我们采用了基于框架的内插法,我们把基本手势视为代表操纵任务的关键框架,并使用简单的线性内插战略完成操纵。为了展示我们框架的有效性,我们确定了一个三级基准,其中不仅包括以往研究的62个测试手势,而且还包括多重复杂和连续的行动。这个基准的实验结果验证了拟议设计的外延性,我们的视频可以在\DP2/Prgrv_SBSBA/DMU_MUMUG_MUGR=NVGR_MUGR_MU_MUGO_MUGO_MUGO_ZGRGRGRQ_X_X_XGO_ZGRVGO_X_BYGO_Z_ZGRGO_BYGO}xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx