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

• Published in: Proceedings - IEEE International Conference on Robotics and Automation pp. 1144 - 1151
• Main Authors: Huynh, Van T., Dunbabin, Matthew, Smith, Ryan N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.05.2015
• Subjects: Mathematical model; Oceans; Path planning; Prediction algorithms; Predictive models; Uncertainty; Vehicles
• ISSN: 1050-4729
• DOI: 10.1109/ICRA.2015.7139335

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.