Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties

Huynh, Van T., Dunbabin, Matthew, & Smith, Ryan N. (2015) Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties. In Proceedings of the 2015 IEEE International Conference on Robotics & Automation (ICRA), IEEE, Seattle, Washington, pp. 1144-1151.

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Abstract

This paper presents a novel path planning method for minimizing the energy consumption of an autonomous underwater vehicle subjected to time varying ocean disturbances and forecast model uncertainty. The algorithm determines 4-Dimensional path candidates using Nonlinear Robust Model Predictive Control (NRMPC) and solutions optimised using A-like algorithms. Vehicle performance limits are incorporated into the algorithm with disturbances represented as spatial and temporally varying ocean currents with a bounded uncertainty in their predictions. The proposed algorithm is demonstrated through simulations using a 4-Dimensional, spatially distributed time-series predictive ocean current model. Results show the combined NRMPC and A approach is capable of generating energy-efficient paths which are resistant to both dynamic disturbances and ocean model uncertainty.

Impact and interest:

2 citations in Scopus
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26 since deposited on 15 May 2015
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ID Code: 84160
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Autonomous underwater vehicle, Energy consumption, Path planning, Nonlinear Robust Model Predictive Control
DOI: 10.1109/ICRA.2015.7139335
ISBN: 978-1-4799-6924-1
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Please consult the authors
Deposited On: 15 May 2015 00:17
Last Modified: 10 Sep 2015 16:59

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