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http://dx.doi.org/10.5302/J.ICROS.2013.12.1837

Extended Kalman Filter-based Localization with Kinematic Relationship of Underwater Structure Inspection Robots  

Heo, Young-Jin (Seoul National University of Science and Technology)
Lee, Gi-Hyeon (Seoul National University of Science and Technology)
Kim, Jinhyun (Seoul National University of Science and Technology)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.19, no.4, 2013 , pp. 372-378 More about this Journal
Abstract
In this paper, we research the localization problem of the crawler-type inspection robot for underwater structure which travels an outer wall of underwater structure. Since various factors of the underwater environment affect an encoder odometer, it is hard to localize robot itself using only on-board sensors. So in this research we used a depth sensor and an IMU to compensate odometer which has extreme error in the underwater environment through using Extended Kalman Filter(EKF) which is normally used in mobile robotics. To acquire valid measurements, we implemented precision sensor modeling after assuming specific situation that robot travels underwater structure. The depth sensor acquires a vertical position of robot and compensates one of the robot pose, and IMU is used to compensate a bearing. But horizontal position of robot can't be compensated by using only on-board sensors. So we proposed a localization algorithm which makes horizontal direction error bounded by using kinematics relationship. Also we implemented computer simulations and experiments in underwater environment to verify the algorithm performance.
Keywords
extended Kalman filter; localization; underwater environment; depth sensor; IMU sensor;
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Times Cited By KSCI : 4  (Citation Analysis)
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