Data-Driven Human Grasp Movement Analysis

Konferenz: ISR 2016 - 47st International Symposium on Robotics
21.06.2016 - 22.06.2016 in München, Germany

Tagungsband: ISR 2016

Seiten: 8Sprache: EnglischTyp: PDF

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Autoren:
Marino, Hamal; Bicchi, Antonio (Dept. of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy, and Centro di Ricerca “E. Piaggio”, University of Pisa, 56122 Pisa, Italy)
Gabiccini, Marco (DICI and Centro di Ricerca “E. Piaggio”, University of Pisa, 56122 Pisa, Italy, and Dept. of Advanced Robotics, Istituto Italiano di Tecnologia, 16163 Genova, Italy)
Leonardis, Ales (School of Computer Science and Centre for Computational Neuroscience and Cognitive Robotics, The University of Birmingham, Edgbaston, Birmingham B15 2TT, UK)

Inhalt:
Humans tend to simplify the space of possible grasps they can perform. Yet, the description of human hand motions is very complex, and methods to reduce this complexity have attracted much attention in the motor control literature. Important implications in robot hand design and programming have also generated a wide interest in the robotics research community. Early studies prevalently used direct analysis methods such as visual inspection to define grasp taxonomies. More recently, analytical methods have been employed to perform grasping data dimensionality reduction. In this paper, we present a methodology to reconcile these two distinct and apparently incompatible approaches under a unified framework: this allows us to obtain a data-generated grasp taxonomy along with low-dimensional representations which could be used for human grasping data classification and posture reconstruction, as well as for simplifying grasp planning algorithms and robotic hands programming.