Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/12905

TitleNonlinear optimization for human-like movements of a high degree of freedom robotics arm-hand system
Author(s)Silva, Eliana Oliveira Costa
Costa, M. Fernanda P.
Bicho, E.
Erlhagen, Wolfram
KeywordsAnthropomorphic robotic system
Reach-to-grasp
Human like collision-free arm movements
Large-scale nonlinear optimization
Interior-point methods
Sequential quadratic programming
Issue date2011
PublisherSpringer
JournalLecture Notes in Computer Science
Abstract(s)The design of autonomous robots, able to closely cooperate with human users in shared tasks, provides many new challenges for robotics research. Compared to industrial applications, robots working in human environments will need to have human-like abilities in their cognitive and motor behaviors. Here we present a model for generating trajectories of a high degree of freedom robotics arm-hand system that reflects optimality principles of human motor control. The process of finding a human-like trajectory among all possible solutions is formalized as a large-scale nonlinear optimization problem. We compare numerically three existing solvers, IPOPT, KNITRO and SNOPT, in terms of their real-time performance in different reach-to-grasp problems that are part of a human-robot interaction task. The results show that the SQP methods obtain better results than the IP methods. SNOPT finds optimal solutions for all tested problems in competitive computational times, thus being the one that best serves our purpose.
TypeConference paper
URIhttp://hdl.handle.net/1822/12905
ISBN978-3-642-21930-6
DOI10.1007/978-3-642-21931-3_26
ISSN0302-9743
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CMAT - Artigos em atas de conferências e capítulos de livros com arbitragem / Papers in proceedings of conferences and book chapters with peer review
DEI - Artigos em atas de congressos internacionais

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