Motion control of deep sea vehicle ‘OTOHIME’: modeling with neural network

Fujii, Shun; Tahara, Junichiro; Zhang, F.; Koike, Masayuki; Ohta, Yoshihiro; Watanabe, Yoshito

doi:10.1080/01691864.2021.1985606

Cited by 4 publications

(1 citation statement)

References 17 publications

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“…Deep-sea exploration is a strategic approach and important means for human sustainable development, and it is also one of the most prominent fields in recent years [1]. Deep-sea carriers [2] are the main transportation platforms that carry various electronic devices, mechanical apparatus, and technical personnel to reach different deep-sea environments quickly and accurately for precise exploration. Deep-sea carriers are divided into two categories: humanned submersibles (HOV) and unmanned underwater vehicles (UUV).…”

Section: Introductionmentioning

confidence: 99%

Optimization Method for Control Panel Layout of Manned Submarine Vehicle Based on Genetic-Ant Colony Algorithm

Xie,

Qiao,

Shi

et al. 2024

Preprint

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In traditional computer-aided design methods for manned submersible control panel layout, interactive input and modification are commonly used, which can’t support a global optimization process for the design layout. Therefore, the genetic-ant algorithm is introduced into the design of manned submersible control panel layouts. Based on the cognitive characteristics of humans, layout optimization principles are summarized and incorporated into the objective function variables during the optimization process. The fitness function, pheromone, and heuristic information expressions for optimizing the control panel layout of manned submersibles are studied to establish the genetic-ant algorithm flow for use in the optimization design process. Taking the control panel layout design of a certain type of manned submersible as an example, multi-objective optimization calculations are performed to quantify the layout principles and combine them with the algorithm, thus verifying the feasibility of the proposed method.

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Section: Introductionmentioning

confidence: 99%