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.
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.
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|Item Type:||Conference Paper|
|Keywords:||Autonomous underwater vehicle, Energy consumption, Path planning, Nonlinear Robust Model Predictive Control|
|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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