Full-Scale Continuous Synthetic Sonar Data Generation with Markov Conditional Generative Adversarial Networks

Marija Jegorova, Antti Ilari Karjalainen, Jose Vazquez, Timothy Hospedales

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Deployment and operation of autonomous underwater vehicles is expensive and time-consuming. High-quality realistic sonar data simulation could be of benefit to multiple applications, including training of human operators for postmission analysis, as well as tuning and validation of autonomous target recognition (ATR) systems for underwater vehicles. Producing realistic synthetic sonar imagery is a challenging problem as the model has to account for specific artefacts of real acoustic sensors, vehicle attitude, and a variety of environmental factors. We propose a novel method for generating realistic-looking sonar side-scans of full-length missions, called Markov Conditional pix2pix (MC-pix2pix). Quantitative assessment results confirm that the quality of the produced data is almost indistinguishable from real. Furthermore, we show that bootstrapping ATR systems with MC-pix2pix data can improve the performance. Synthetic data is generated 18
times faster than real acquisition speed, with full user control over the topography of the generated data.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Robotics and Automation (ICRA)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3168-3174
Number of pages7
ISBN (Electronic)978-1-7281-7395-5
ISBN (Print)978-1-7281-7396-2
DOIs
Publication statusPublished - 15 Sep 2020
Event2020 International Conference on Robotics and Automation - Virtual conference, France
Duration: 31 May 202031 Aug 2020
https://www.icra2020.org/

Publication series

Name
PublisherIEEE
ISSN (Print)1050-4729
ISSN (Electronic)2577-087X

Conference

Conference2020 International Conference on Robotics and Automation
Abbreviated titleICRA 2020
Country/TerritoryFrance
CityVirtual conference
Period31/05/2031/08/20
Internet address

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