On Force Synergies in Human Grasping Behavior

J. Starke, Konstantinos Chatzilygeroudis, A. Billard, T. Asfour
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引用次数: 12

Abstract

The human hand is a versatile and complex system with dexterous manipulation capabilities. For the transfer of human grasping capabilities to humanoid robotic and prosthetic hands, an understanding of the dynamic characteristics of grasp motions is fundamental. Although the analysis of grasp synergies, especially for kinematic hand postures, is a very active field of research, the description and transfer of grasp forces is still a challenging task. In this work, we introduce a novel representation of grasp synergies in the force space, socalled force synergies, which describe forces applied at contact locations in a low dimensional space and are inspired by the correlations between grasp forces in fingers and palm. To evaluate this novel representation, we conduct a human grasping study with eight subjects performing handover and tool use tasks on 14 objects with varying content and weight using 16 different grasp types. We capture contact forces at 18 locations within the hand together with the joint angle values of a data glove with 22 degrees of freedom. We identify correlations between contact forces and derive force synergies using dimensionality reduction techniques, which allow to represent grasp forces applied during grasping with only eight parameters.
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人类抓取行为中的力协同作用研究
人的手是一个多功能和复杂的系统,具有灵巧的操作能力。为了将人类抓取能力转移到类人机器人和假手,理解抓取运动的动态特性是基础。尽管对抓取协同效应的分析,特别是对运动学手部姿势的分析,是一个非常活跃的研究领域,但抓取力的描述和传递仍然是一项具有挑战性的任务。在这项工作中,我们引入了一种力空间中抓取协同作用的新表示,即所谓的力协同作用,它描述了施加在低维空间接触位置的力,并受到手指和手掌抓取力之间相关性的启发。为了评估这种新颖的表征,我们进行了一项人类抓取研究,8名受试者使用16种不同的抓取类型对14个不同内容和重量的物体执行交接和工具使用任务。我们捕获了手部18个位置的接触力以及22个自由度的数据手套的关节角度值。我们确定了接触力之间的相关性,并使用降维技术推导出力协同效应,该技术允许仅用八个参数表示抓取过程中施加的抓取力。
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