Multibeam Data Processing for Underwater Mapping
Name
Teixeira18iros.pdf
Description
Accepted version
Size
678.33 KB
Format
Adobe PDF
Checksum (MD5)
3005e8f4f9a99c560d304284863a3aad
Author(s)
Teixeira, Pedro V.
Kaess, Michael
Hover, Franz S.
Leonard, John J.
Date Issued
October 2018
Journal
IEEE International Conference on Intelligent Robots and Systems
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Teixeira, Pedro V., Kaess, Michael, Hover, Franz S. and Leonard, John J. 2018. "Multibeam Data Processing for Underwater Mapping." IEEE International Conference on Intelligent Robots and Systems.
Version
Author's final manuscript
Abstract
© 2018 IEEE. From archaeology to the inspection of subsea structures, underwater mapping has become critical to many applications. Because of the balanced trade-off between range and resolution, multibeam sonars are often used as the primary sensor in underwater mapping platforms. These sonars output an image representing the intensity of the received acoustic echos over space, which must be classified into free and occupied regions before range measurements are determined and spatially registered. Most classifiers found in the underwater mapping literature use local thresholding techniques, which are highly sensitive to noise, outliers, and sonar artifacts typically found in these images. In this paper we present an overview of some of the techniques developed in the scope of our work on sonar-based underwater mapping, with the aim of improving map accuracy through better segmentation performance. We also provide experimental results using data collected with a DIDSON imaging sonar that show that these techniques improve both segmentation accuracy and robustness to outliers.
MIT Department
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/IROS.2018.8594128
