Optimal nature-walking gait for humanoid robot using Jaya optimization algorithm

This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters in...

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Bibliographic Details
Published in:Advances in mechanical engineering 2019-11, Vol.11 (11)
Main Authors: Huan, Tran Thien, Anh, Ho Pham Huy, Van Kien, Cao
Format: Article
Language:English
Subjects:
Computer simulation
Design optimization
Evolutionary algorithms
Evolutionary computation
Gait
Humanoid
Optimization algorithms
Parameter uncertainty
Robots
Walking
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Summary:This article proposes a new method used to optimize the design process of nature-walking gait generator that permits biped robot to stably and naturally walk with preset foot-lift magnitude. The new Jaya optimization algorithm is innovatively applied to optimize the biped gait four key parameters initiatively applied to ensure the uncertain nonlinear humanoid robot walks robustly and steadily. The efficiency of the proposed Jaya-based identification approach is compared with the central force optimization and improved differential evolution (modified differential evolution) algorithms. The simulation and experimental results tested on the original small-sized biped robot HUBOT-4 convincingly demonstrate that the novel proposed algorithm offers an efficient and stable gait for humanoid robots with precise height of foot-lift value.
ISSN:1687-8132
1687-8140
DOI:10.1177/1687814019888082