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Open AccessArticle

Active SLAM for Autonomous Underwater Exploration

Computer Vision and Robotics Institute (VICOROB), Universitat de Girona, 17003 Girona, Spain
Institut de Robòtica i Informàtica Industrial, CSIC-UPC, Llorens Artigas 4-6, 08028 Barcelona, Spain
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(23), 2827;
Received: 25 October 2019 / Revised: 21 November 2019 / Accepted: 27 November 2019 / Published: 28 November 2019
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 maps. View Full-Text
Keywords: autonomous underwater vehicles; robot exploration; active SLAM; view planning autonomous underwater vehicles; robot exploration; active SLAM; view planning
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Palomeras, N.; Carreras, M.; Andrade-Cetto, J. Active SLAM for Autonomous Underwater Exploration. Remote Sens. 2019, 11, 2827.

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