2026-04-13T02:09:35Zhttps://recercat.cat/oai/request

oai:recercat.cat:10256/172952024-05-22T09:50:12Zcom_2072_452955com_2072_2054col_2072_452957

2024-05-22T09:50:12Z urn:hdl:10256/17295 Active SLAM for Autonomous Underwater Exploration Palomeras Rovira, Narcís Carreras Pérez, Marc Andrade-Cetto, Juan Robots submarins Underwater robots Vehicles submergibles Submersibles Exploration of a complex underwater environment without an a priori map is beyond the state of the art for autonomous underwater vehicles (AUVs). Despite several efforts regarding simultaneous localization and mapping (SLAM) and view planning, there is no exploration framework, tailored to underwater vehicles, that faces exploration combining mapping, active localization, and view planning in a unified way. We propose an exploration framework, based on an active SLAM strategy, that combines three main elements: a view planner, an iterative closest point algorithm (ICP)-based pose-graph SLAM algorithm, and an action selection mechanism that makes use of the joint map and state entropy reduction. To demonstrate the benefits of the active SLAM strategy, several tests were conducted with the Girona 500 AUV, both in simulation and in the real world. The article shows how the proposed framework makes it possible to plan exploratory trajectories that keep the vehicle’s uncertainty bounded; thus, creating more consistent map This research was funded by the Spanish State Research Agency through grants DPI2015-73978-JIN and DPI2017-89564-P, and the María de Maeztu Seal of Excellence to IRI (MDM-2016-0656). 2024-05-22T09:50:12Z 2024-05-22T09:50:12Z 2019-11-28 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion peer-reviewed http://hdl.handle.net/10256/17295 info:eu-repo/semantics/altIdentifier/doi/10.3390/rs11232827 info:eu-repo/semantics/altIdentifier/eissn/2072-4292 info:eu-repo/grantAgreement/MINECO//DPI2015-73978-JIN/ES/INSPECCION AUTOMATICA DE ENTORNOS SUBMARINOS 3D MEDIANTE UN AUV./ Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess MDPI (Multidisciplinary Digital Publishing Institute) © Remote Sensing, 2019, vol. 11, núm. 23, p. 2827 Articles publicats (D-ATC)