Subramani, D. N., P. F. J. Lermusiaux, P.J. Haley, Jr., C. Mirabito, S. Jana,
C. S. Kulkarni, A. Girard, D. Wickman, J. Edwards, J. Smith, 2017. Time-Optimal Path Planning: Real-Time Sea Exercises. In: Oceans '17 MTS/IEEE Aberdeen, 19-22 June 2017, Sub-judice.
Autonomous underwater vehicles (AUVs) are employed in many applications such as ocean
sensing, search and rescue operations, acoustic surveillance, and oil and gas exploitation. With advances in
AUV capability and increasing mission complexity, there is a demand for predicting all reachable locations,
prolonging endurance, and reducing operational costs by optimally utilizing ocean flow forecasts for navigation.
For such optimal navigation, we recently developed new theory, schemes, and computational systems for exact
partial differential equation-based path planning. This new level-set path planning was applied in
realistic re-analysis simulations for the sustained coordinated operation of multiple collaborative AUVs for
time-, coordination- and energy- optimal missions. In the present paper, our goal is to demonstrate
our level-set path planning in real-time sea exercises with real AUVs in shallow coastal ocean regions with
strong and dynamic currents. Our specific objectives are to report the (i) improvements to our 4-D primitive
equation ocean modeling system for accurately forecasting the currents in the Buzzard’s Bay and Vineyard
Sound region, (ii) results of the time-optimal path planning of REMUS 600 AUVs using our fundamental
theory and real-time forecasts, (iii) portability of our software systems for real-time optimal path prediction
in multiple regions and its ability to work with the AUV navigation software. These exercises were the first sea tests of our new theory and software. Our ocean forecasts had skill and time-optimal path forecasts worked with REMUS 600’s. We also identified relationships between
the REMUS 600’s rpm and nominal in-water speed. The results open a new era of optimal AUV missions.