Dynamic performance evaluation of evolutionary multi-objective optimization algorithms for gait cycle optimization of a 25-DOFs NAO humanoid robot

Researchers are increasingly using optimization methods to achieve optimal dynamic performance of humanoid robots, often involving multiple conflicting objectives. Multi-objective optimization algorithms (MOAs) aim to find a Pareto front of optimal solutions, but selecting the best algorithm based o...

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Veröffentlicht in:	Swarm and evolutionary computation Jg. 99; S. 102144
Hauptverfasser:	Gupta, Pushpendra, Pratihar, Dilip Kumar, Deb, Kalyanmoy
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.12.2025
Schlagworte:	Evolutionary algorithms Multi-objective optimization NAO humanoid robot Performance metrics Swarm intelligence Performance metrics Multi-objective optimization Swarm intelligence Evolutionary algorithms NAO humanoid robot
ISSN:	2210-6502
Online-Zugang:	Volltext
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