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

Huynh, Van T., Dunbabin, Matthew and Smith, Ryan N. 2015, Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties, in ICRA 2015 : Proceedings of the IEEE Robotics and Automation 2015 International Conference, IEEE, Piscataway, N.J., pp. 1144-1151, doi: 10.1109/ICRA.2015.7139335.

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Title Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties
Author(s) Huynh, Van T.ORCID iD for Huynh, Van T. orcid.org/0000-0001-8668-3145
Dunbabin, Matthew
Smith, Ryan N.
Conference name IEEE Robotics and Automation. International Conference (2015 : Seattle, Wash.)
Conference location Seattle, Wash.
Conference dates 26-30 May 2015
Title of proceedings ICRA 2015 : Proceedings of the IEEE Robotics and Automation 2015 International Conference
Editor(s) [Unknown]
Publication date 2015
Conference series IEEE Robotics and Automation International Conference
Start page 1144
End page 1151
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Keyword(s) Autonomous underwater vehicles
Nonlinear control systems
Path planning
Predictive control
Robust control
Time series
Oceans
Summary 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.
Notes 28/6/16 BR added conf info including IEEE URL for evidence.
ISSN 1050-4729
Language eng
DOI 10.1109/ICRA.2015.7139335
Field of Research 091302 Automation and Control Engineering
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1.1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2015, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30084451

Document type: Conference Paper
Collection: School of Engineering
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