Publication
Active SLAM for autonomous underwater exploration
Journal Article (2019)
Journal
Remote Sensing
Pages
2827:1-19
Volume
11
Number
23
Doc link
https://doi.org/10.3390/rs11232827
File
Abstract
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.
Categories
robots.
Author keywords
autonomous underwater vehicles; robot exploration; active SLAM; view planning
Scientific reference
N. Palomeras, M. Carreras and J. Andrade-Cetto. Active SLAM for autonomous underwater exploration. Remote Sensing, 11(23): 2827:1-19, 2019.
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