Review of underwater SLAM techniques

Franco Hidalgo; Thomas Braunl

doi:10.1109/ICARA.2015.7081165

Review of underwater SLAM techniques

Franco Hidalgo, Thomas Braunl

Research output: Contribution to conference › Conference Paper

45 Scopus citations

Abstract

© 2015 IEEE. SLAM (Simultaneous Localization and Mapping) for underwater vehicles is a challenging research topic due to the limitations of underwater localization sensors and error accumulation over long-term operations. Furthermore, acoustic sensors for mapping often provide noisy and distorted images or low-resolution ranging, while video images provide highly detailed images but are often limited due to turbidity and lighting. This paper presents a review of the approaches used in state-of-the-art SLAM techniques: Extended Kalman Filter SLAM (EKF-SLAM), FastSLAM, GraphSLAM and its application in underwater environments.

Original language	American English
Pages	306-311
Number of pages	6
DOIs	https://doi.org/10.1109/ICARA.2015.7081165
State	Published - 1 Jan 2015
Externally published	Yes
Event	ICARA 2015 - Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications - Duration: 1 Jan 2015 → …

Conference

Conference	ICARA 2015 - Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications
Period	1/01/15 → …

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10.1109/ICARA.2015.7081165

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title = "Review of underwater SLAM techniques",

abstract = "{\textcopyright} 2015 IEEE. SLAM (Simultaneous Localization and Mapping) for underwater vehicles is a challenging research topic due to the limitations of underwater localization sensors and error accumulation over long-term operations. Furthermore, acoustic sensors for mapping often provide noisy and distorted images or low-resolution ranging, while video images provide highly detailed images but are often limited due to turbidity and lighting. This paper presents a review of the approaches used in state-of-the-art SLAM techniques: Extended Kalman Filter SLAM (EKF-SLAM), FastSLAM, GraphSLAM and its application in underwater environments.",

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AB - © 2015 IEEE. SLAM (Simultaneous Localization and Mapping) for underwater vehicles is a challenging research topic due to the limitations of underwater localization sensors and error accumulation over long-term operations. Furthermore, acoustic sensors for mapping often provide noisy and distorted images or low-resolution ranging, while video images provide highly detailed images but are often limited due to turbidity and lighting. This paper presents a review of the approaches used in state-of-the-art SLAM techniques: Extended Kalman Filter SLAM (EKF-SLAM), FastSLAM, GraphSLAM and its application in underwater environments.

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Review of underwater SLAM techniques

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