Marine vehicles have been used for various scientific missions where information over features of interest is collected. In order to maximise efficiency in collecting information over a large search space, we should be able to deploy a large number of autonomous vehicles that make a decision based on the latest understanding of the target feature in the environment. In our previous work, we have presented a hierarchical framework for the multi-vessel multi-float (MVMF) problem where surface vessels drop and pick up underactuated floats in a time-minimal way. In this paper, we present the field trial results using the framework with a number of drifters and floats. We discovered a number of important aspects that need to be considered in the proposed framework, and present the potential approaches to address the challenges.
@article{arxiv.2106.09279,
title = {Field trial on Ocean Estimation for Multi-Vessel Multi-Float-based Active perception},
author = {Giovanni D'urso and James Ju Heon Lee and Ki Myung Brian Lee and Jackson Shields and Brenton Leighton and Oscar Pizarro and Chanyeol Yoo and Robert Fitch},
journal= {arXiv preprint arXiv:2106.09279},
year = {2021}
}
Comments
7 pages, 6 figures, presented at "ICRA2021, 1st Advanced Marine Robotics TC Workshop: Active Perception"