CENS Technical Seminar Series

AUV Trajectory Design Based on Ocean Model Predictions

Invited Speaker: Dr. Ryan N. Smith
Date: August 7, 2009
Time: 1:00 PM - 2:00 PM
Venue: Boelter Hall 4760

Abstract

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 to collect data with scientific merit. 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 the predictions. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature and not the low-level path planning of the vehicle. 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.

Biography

Ryan N. Smith is a Postdoctoral Research Assistant in the Robotics Embedded Systems Laboratory, Department of Computer Science at the University of Southern California (USC). Ryan attended Miami University (Oxford, OH) for his undergraduate education where he received B.S. degrees in both Mathematics and Engineering Physics. He received a M.A. degree in Mathematics, and a Ph.D. in Ocean & Resources Engineering from the University of Hawaii at Manoa. Ryan's research interests lie in control and trajectory design for Autonomous Underwater Vehicles (AUVs). His thesis work focused on low-level control design for thruster powered AUVs by use of a differential geometric formulation of the equations of motion and a reduction procedure on these equations. Currently, he is working on autonomous retasking of mobile sensor platforms based on predictive ocean models and remotely sensed data to optimally sample an ocean feature or process. A common thread throughout Ryan's research is to bridge the gap between theory and implementation in the area of marine robotics