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

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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Bibliographic Details
Main Authors: Matteo Bresciani, Francesco Ruscio, Simone Tani, Giovanni Peralta, Andrea Timperi, Eric Guerrero-Font, Francisco Bonin-Font, Andrea Caiti, Riccardo Costanzi
Format: Article
Language:English
Published: MDPI AG 2021-10-01
Series:Journal of Marine Science and Engineering
Subjects:
genetic algorithm
path planning
Gaussian Process
AUVs
optimal sampling
Posidonia Oceanica
Online Access:https://www.mdpi.com/2077-1312/9/11/1183

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