Path Planning for Underwater Information Gathering Based on Genetic Algorithms and Data Stochastic Models

Recent technological developments have paved the way to the employment of Autonomous Underwater Vehicles (AUVs) for monitoring and exploration activities of marine environments. Traditionally, in information gathering scenarios for monitoring purposes, AUVs follow predefined paths that are not effic...

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Autores principales:	Matteo Bresciani, Francesco Ruscio, Simone Tani, Giovanni Peralta, Andrea Timperi, Eric Guerrero-Font, Francisco Bonin-Font, Andrea Caiti, Riccardo Costanzi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	genetic algorithm path planning Gaussian Process AUVs optimal sampling Posidonia Oceanica Naval architecture. Shipbuilding. Marine engineering VM1-989 Oceanography GC1-1581
Acceso en línea:	https://doaj.org/article/7cb8ecfc1b78463db6da0d5b7d120e71
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Path Planning for Underwater Information Gathering Based on Genetic Algorithms and Data Stochastic Models

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