EvoRobogami

Huang, Zhilong; Wu, Quinn; Howard, David; Sung, Cynthia

doi:10.1145/3512290.3528867

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…Additionally, Artificial intelligence algorithms can be utilized to optimize the parameters and settings of evolutionary models, further enhancing their performance [27][28][29][30]. Moreover, by integrating AI and robotics, evolutionary models can create intelligent [31][32][33][34][35] and adaptive robotic systems [36][37][38][39][40][41][42][43][44][45][46][47][48][49][50] that learn, evolve, and perform complex tasks [51][52][53][54][55][56][57][58][59][60].…”

Section: Introductionmentioning

confidence: 99%

Design a wing flange lever mechanism using Giza pyramid algorithm

Al-Shabi

Abouelazm

Nassif

et al. 2023

Sensors and Systems for Space Applications XVI

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In this work, a well-known mechanism that is referred to as piston lever mechanism is design to control the wing's flange. The design targets the mechanism components and their location while maintaining the minimum oil level required to lift the flanges from 0 to 45 degrees. The design is considered a multi-objective optimization problem; in which we propose the Giza Pyramid Algorithm (GPA) to optimize. GPA is a newly developed metaheuristic technique of type ancientinspired that was developed in 2021. The GPA shall obtain the best design while satisfying four constrains. The algorithm will be tested in Monte Carlo simulation to show its effectiveness in terms of stability and robustness. The performance is then compared to the particle swarm optimization. The proposed method shows a superior result compared to the PSO.

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