Pubblicazione scientifica

Feedback-Based Informative AUV Planning from Kriging Errors

FILONE TECNOLOGICO	TEMA
economia circolare e sostenibilità

RIASSUNTO

This paper presents a methodology to find a feedback-based plan for AUVs to visit important locations to estimate spatiotemporal fields. A model based on Kriging method is created containing predictions and errors in prediction. These errors are then used to develop a reward function that gives a high reward to a location with large error prediction and penalizes the energy consumption is created. A feedback plan is found using value-iteration based Markov Decision Model (MDP). The feedback plan helps adjust the paths or trajectories of AUVs in the presence of modeling errors and other forms of uncertainty due to the unpredictability of future states. Moreover, if the AUV deviates from its path during a mission, there will not be any need to re-plan since the plan will be calculated over the entire free space. Data were used from a mission at Big Fisherman’s Cover, at Santa Catalina Island, California, USA. Results show that the Kriging method can be used as a prediction model for several properties of the water in an oceanic environment. Furthermore, an optimal navigation policy was presented in the 2-D marine environment that generates the best possible action in the simulated policy from any location of the environment to the goal location.

DATA

Data di pubblicazione: 01/11/2018

AUTORI

GREGORY MURAD REIS
TAUHIDUL ALAM
LEONARDO BOBADILLA
RYAN N SMITH

ENTE DI AFFERENZA

SCHOOL OF COMPUTING & INFO SCIENCES FLORIDA INTL UNIV MIAMI FL 33199 USA
DEPT MATHEMATICS COMPUTER & INFO SCIENCE SUNY OLD WESTBURY OLD WESTBURY NY USA
DEPT PHYSICS & ENG FORT LEWIS COLLEGE DURANGO CO 81301 USA

RIVISTA

2018 IEEE/OES Autonomous Underwater Vehicle Workshop (AUV) (Page(s): 1-6)

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