Journal article
Optimization-based posture prediction for human upper body
Robotica, Vol.27(4), pp.607-620
07/2009
DOI: 10.1017/S0263574708004992
Abstract
A general methodology and associated computational algorithm for predicting postures of the digital human upper body is presented. The basic plot for this effort is an optimization-based approach, where we believe that different human performance measures govern different tasks. The underlying problem is characterized by the calculation (or prediction) of the human performance measure in such a way as to accomplish a specified task. In this work, we have not limited the number of degrees of freedom associated with the model. Each task has been defined by a number of human performance measures that are mathematically represented by cost functions that evaluate to a real number. Cost functions are then optimized, i.e., minimized or maximized, subject to a number of constraints, including joint limits. The formulation is demonstrated and validated. We present this computational formulation as a broadly applicable algorithm for predicting postures using one or more human performance measures.
Details
- Title: Subtitle
- Optimization-based posture prediction for human upper body
- Creators
- Zan Mi - University of IowaJingzhou (James) Yang - University of IowaKarim Abdel-Malek - University of Iowa
- Resource Type
- Journal article
- Publication Details
- Robotica, Vol.27(4), pp.607-620
- Publisher
- Cambridge University Press
- DOI
- 10.1017/S0263574708004992
- ISSN
- 0263-5747
- eISSN
- 1469-8668
- Number of pages
- 14
- Language
- English
- Date published
- 07/2009
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Mechanical Engineering
- Record Identifier
- 9984196659602771
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