An information-driven and disturbance-aware planning method for long-term ocean monitoring
Kai-Chieh Ma, Lantao Liu, Gaurav S. Sukhatme
Abstract
We propose an efficient path planning method for an autonomous underwater vehicle (AUV) used for the long-range and long-term ocean monitoring. We consider both the spatio-temporal variations of ocean phenomena and the disturbances caused by ocean currents, and design an approach integrating the information-theoretic and decision-theoretic planning frameworks. Specifically, the information-theoretic component employs a hierarchical structure and plans the most informative observation way-points for reducing the uncertainty of ocean phenomena modeling and prediction; whereas the decision-theoretic component plans local motions by taking into account the non-stationary ocean current disturbances. We validated the method through simulations with real ocean data.
BibTeX
@inproceedings{iros2016_aninformationdri,
title = {An information-driven and disturbance-aware planning method for long-term ocean monitoring},
author = {Kai-Chieh Ma and Lantao Liu and Gaurav S. Sukhatme},
booktitle = {IROS 2016},
year = {2016}
}