Next Article in Journal
Self-Training Classification Framework with Spatial-Contextual Information for Local Climate Zones
Previous Article in Journal
Sea Clutter Amplitude Prediction Using a Long Short-Term Memory Neural Network
Previous Article in Special Issue
Wave Height and Wave Period Derived from a Shipboard Coherent S-Band Wave Radar in the South China Sea
Open AccessArticle

Active SLAM for Autonomous Underwater Exploration

1
Computer Vision and Robotics Institute (VICOROB), Universitat de Girona, 17003 Girona, Spain
2
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; https://doi.org/10.3390/rs11232827
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
Show Figures

Figure 1

MDPI and ACS Style

Palomeras, N.; Carreras, M.; Andrade-Cetto, J. Active SLAM for Autonomous Underwater Exploration. Remote Sens. 2019, 11, 2827.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop