PeRL STUDIES AUTONOMOUS NAVIGATION & MAPPING FOR MOBILE ROBOTS IN A PRIORI UNKNOWN ENVIRONMENTS.

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Pose-Graph SLAM Using Forward-Looking Sonar

Summary


Jie Li, Michael Kaess, Ryan M. Eustice and Matthew Johnson-Roberson, Pose-Graph SLAM Using Forward-Looking Sonar. IEEE Robotics and Automation Letters, 3(3):2330-2337, 2018.

Abstract

This letter reports on a real-time simultaneous localization and mapping (SLAM) algorithm for an underwater robot using an imaging forward-looking sonar and its application in the area of autonomous underwater ship hull inspection. The proposed algorithm overcomes challenges associated with deliverable underwater acoustic SLAM, including feature and false-positive data association when utilizing sonar imagery. An advanced machine technique is used to provide saliency-aware loop closure proposals. A more reliable association approach using different available constraints is also developed. Our evaluation is presented on the real-world data collected in a ship hull inspection application, which the system's performance and robustness.

Bibtex entry

@ARTICLE { jli-2018b,
    AUTHOR = { Jie Li and Michael Kaess and Ryan M. Eustice and Matthew Johnson-Roberson },
    TITLE = { Pose-Graph {SLAM} Using Forward-Looking Sonar },
    JOURNAL = { IEEE Robotics and Automation Letters },
    YEAR = { 2018 },
    VOLUME = { 3 },
    NUMBER = { 3 },
    PAGES = { 2330-2337 },
}