Predictive motion planning for AUVs subject to strong time-varying currents and forecasting uncertainties
Contribuinte(s) |
[Unknown] |
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Data(s) |
01/01/2015
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Resumo |
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. |
Identificador | |
Idioma(s) |
eng |
Publicador |
IEEE |
Relação |
http://dro.deakin.edu.au/eserv/DU:30084451/huynh-predictivemotion-2015.pdf http://www.dx.doi.org/10.1109/ICRA.2015.7139335 |
Direitos |
2015, IEEE |
Palavras-Chave | #Autonomous underwater vehicles #Nonlinear control systems #Path planning #Predictive control #Robust control #Time series #Oceans |
Tipo |
Conference Paper |