Movement Primitives and Principal Component Analysis View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Frank C. Park , Kyoosang Jo

ABSTRACT

Robot trajectory generation based on the optimization of physical criteria is by now a well-established means of motion programming, but the computational burden still remains a formidable challenge for real-time implementation. Motivated by results from the biological motor control literature, we propose a method for constructing movement primitives based on principal component analysis (PCA) of a set of reference motions. The movement primitives provide an efficient and task-specific set of basis functions for the representation of general motions; by using the basis functions constructed from a set of reference motions associated with a given task, sub-optimal motions that closely resemble the reference motions can be generated rapidly. Experimental results obtained from motion capture data of human arm motions are offered to support the merits of our PCA-based approach. More... »

PAGES

421-430

References to SciGraph publications

Book

TITLE

On Advances in Robot Kinematics

ISBN

978-90-481-6622-0
978-1-4020-2249-4

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4020-2249-4_45

DOI

http://dx.doi.org/10.1007/978-1-4020-2249-4_45

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022059780


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