Metaheuristics in Modeling Humanoid Robots: A Literature Review

Cengiz Kahraman; Eda Bolturk

doi:10.1007/978-3-030-67163-1_5

Metaheuristics in Modeling Humanoid Robots: A Literature Review

Cengiz Kahraman^*, Eda Bolturk

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Metaheuristics are designed to find, generate, or select a heuristic that can provide a sufficiently good solution to a complex optimization problem, especially with incomplete, imperfect, vague and imprecise information. Fuzzy set theory is an excellent tool to capture this kind of information. Metaheuristics can be used as important building blocks in humanoid robots together with fuzzy set theory. In this chapter, we present a literature review on metaheuristics used in modeling robots.

Original language	English
Title of host publication	Studies in Systems, Decision and Control
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	135-147
Number of pages	13
DOIs	https://doi.org/10.1007/978-3-030-67163-1_5
Publication status	Published - 2021

Publication series

Name	Studies in Systems, Decision and Control
Volume	344
ISSN (Print)	2198-4182
ISSN (Electronic)	2198-4190

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Keywords

Ant colony optimization
Artificial bee colony
Humanoid robots
Literature review
Metaheuristics
Particle swarm optimization

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10.1007/978-3-030-67163-1_5

Cite this

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KW - Artificial bee colony

KW - Humanoid robots

KW - Literature review

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Metaheuristics in Modeling Humanoid Robots: A Literature Review

Abstract

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Keywords

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