Trajectory Design for Autonomous Underwater Vehicles Based on Ocean Model Predictions for Feature Tracking
UNIVERSITY OF SOUTHERN CALIFORNIA LOS ANGELES
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Trajectory design for Autonomous Underwater Vehicles AUVs is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight SCB off the coast of Los Angeles.
- Physical and Dynamic Oceanography
- Submarine Engineering