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Anthropomorphic grasp generation through probabilistic modelling in an optimised eigen-space.
- Source :
-
Electronics Letters (Wiley-Blackwell) . 4/27/2017, Vol. 53 Issue 9, p582-583. 2p. 1 Color Photograph, 1 Diagram, 1 Chart, 2 Graphs. - Publication Year :
- 2017
-
Abstract
- Artificial cognitive systems are increasingly drawn towards human-like' gestural exhibits while performing various manipulative acts. Representing such actions in a natural settings requires temporal extractions of their grasp progressions. A novel optimisation-based hidden Markov framework is offered, to generate natural hand prehensions through maximisation of a composite grasp function built of individual finger trajectory likelihoods. In order to produce the desired motion in an intuitive framework, the final grasp frame (represented in terms of standard discriminants z ∈ R² in a condensed grasp eigen-space) is extended in a temporal sequence by equi-spaced increments of z, over their conventional joint-space representations. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00135194
- Volume :
- 53
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- Electronics Letters (Wiley-Blackwell)
- Publication Type :
- Academic Journal
- Accession number :
- 122756723
- Full Text :
- https://doi.org/10.1049/el.2016.4260