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Can underwater environment simulation contribute to vision tasks for autonomous systems?

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conference contribution
posted on 18.03.2019 by Jiangtao Wang, Yang Zhou, Baihua Li, Qinggang Meng, Emanuele Rocco, Andrea Saiani
To simulate the underwater environment and test algorithms for autonomous underwater vehicles, we developed an underwater simulation environment with the Unreal Engine 4 to generate underwater visual data such as seagrass and landscape. We then used such data from the Unreal environment to train and verify an underwater image segmentation model, which is an important technology to later achieve visual based navigation. The simulation environment shows the potentials for dataset generalization and testing robot vision algorithms.

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  • Science

Department

  • Computer Science

Published in

UK-RAS, 2019

Citation

WANG, J. .... et al., 2019. Can underwater environment simulation contribute to vision tasks for autonomous systems? Presented at the 2nd UK Robotics and Autonomous Systems Conference, (UK-RAS 2019), Loughborough University, 24th January.

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This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Publication date

2019

Notes

This is a conference paper

Language

en

Location

uk

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