期刊
REMOTE SENSING
卷 11, 期 23, 页码 -出版社
MDPI
DOI: 10.3390/rs11232827
关键词
autonomous underwater vehicles; robot exploration; active SLAM; view planning
类别
资金
- Spanish State Research Agency [DP12015-73978-JIN, DP12017-89564-P]
- Maria de Maeztu Seal of Excellence [MDM-2016-0656]
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.
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