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Erschienen in:
Comparative Analysis of Swarm-Based Metaheuristic Algorithms on Benchmark Functions Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

Solving Inverse Kinematics with Vector Evaluated Particle Swarm Optimization

verfasst von : Zühnja Riekert, Mardé Helbig

Erschienen in: Advances in Swarm Intelligence

Verlag: Springer International Publishing

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Abstract

Inverse kinematics (IK) is an optimization problem solving the path or trajectory a multi-jointed body should take for an extremity to reach a specified target location. When also considering the flow of movement, IK becomes a multi-objective optimization problem (MOP). This study proposes the use of the vector evaluated particle swarm optimization (VEPSO) algorithm to solve IK. A 3D character arm, with 7 degrees of freedom, is used during experimentation. VEPSO’s results are compared to single-objective optimizers, as well as an optimizer that uses weighted aggregation to solve MOPs. Results show that the weighted aggregation approach can outperform IK-VEPSO if the correct weight combination (that is problem dependent) has been selected. However, IK-VEPSO produces a set of possible solutions.

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Vorheriges Kapitel Immersed Tunnel Element Translation Control Under Current Flow Based on Particle Swarm Optimization
Nächstes Kapitel Particle Swarm Optimization for the Machine Repair Problem with Working Breakdowns
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Metadaten
Titel
Solving Inverse Kinematics with Vector Evaluated Particle Swarm Optimization
verfasst von
Zühnja Riekert
Mardé Helbig
Copyright-Jahr
2017
Buch
Advances in Swarm Intelligence

Print ISBN: 978-3-319-61823-4

Electronic ISBN: 978-3-319-61824-1

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-61824-1_25

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