A model-based strategy for mapping human grasps to robotic hands using synergies
A model-based strategy for mapping human grasps to robotic hands using synergies
复制标题
基于模型的策略，利用协同作用将人类抓握映射到机器人手
DOI：
10.1109/aim.2013.6584348
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发表时间：
2013
期刊：
影响因子：
--
通讯作者：
B. Siciliano
中科院分区：
文献类型：
--
作者：
F. Ficuciello;G. Palli;C. Melchiorri;B. Siciliano
本文的目的是推导出一个拟人机器人手的协同子空间使用人手作为主。一组抓取姿势由五个科目在把握常用的对象已被映射到机器人手假设自己的运动学作为一个简化的模型的人手。使用RGB相机和深度传感器进行3D运动捕获，对于抓取的参考集，已经测量了人手手掌姿势和指尖位置。从所测量的指尖位置的闭环逆运动学算法已被应用到再现的机器人手的关节空间配置依赖于其运动学，缩放使用人类和机器人手指的长度比。一旦一组抓取已经映射到机器人手上，协同子空间已经计算应用主成分分析的关节配置。所获得的子空间进行测试与实验上的DEXMART手通过执行达到把握选定的对象上使用前三个主要的协同作用的行动。这些协同作用的分析和比较，在文献中提供的人手的结果进行通过图形和数值工具。
The aim of this paper is to derive the synergies subspace of an anthropomorphic robotic hand using the human hand as a master. A set of grasping postures performed by five subjects in grasping commonly used objects has been mapped to a robotic hand assuming its own kinematics as a simplified model of the human hand. Using an RGB camera and depth sensor for 3D motion capture, the human hand palm pose and fingertip positions have been measured for the reference set of grasping. From the measured fingertip positions a closed-loop inverse kinematics algorithm has been applied to reproduce the joint space configuration of the robotic hand relying on its kinematics, scaled using the human and robotic fingers length ratio. Once the set of grasping has been mapped on the robotic hand, the synergies subspace has been computed applying principal component analysis on the joint configurations. The obtained subspace is tested with experiments on the DEXMART Hand by performing reach to grasp actions on selected objects using the first three predominant synergies. The analysis of these synergies and a comparison with the results on the human hand available in the literature are performed by means of graphical and numerical tools.