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\(NH\infty \)-SLAM Algorithm for Autonomous Underwater Vehicle

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Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 50))

Abstract

This paper describes an approach that combines the navigation data given by a Doppler Velocity Logs (DVL), the MTi Motion Reference Unit (MRU) and a Mechanically Scanned Imaging Sonar (MSIS) as a principal sensor to efficiently solve underwater Simultaneous Localization and Mapping (SLAM) problem in structured environments such as marine platforms, harbors, or dams, etc. The MSIS has been chosen of its capacity to produce a rich representation of the environment. In recent years, to solve the SLAM Autonomous Underwater Vehicle (AUV) problem, very few solutions have been proposed. Our contribution has introduced a method based on the Nonlinear H-infinity filter \((NH\infty )\) to solve the SLAM-AUV problem. In this work, the \(NH\infty \)-SLAM algorithm is implemented to construct a map in partially structured environments and localize the AUV within this map. The data-set used in this paper are taken from the experiments carried out in a marina located in the Costa Brava (Spain) with the Ictineu AUV which is necessary to test different SLAM algorithms. The validation of the proposed algorithm through simulation in offline is presented and compared to the EKF-SLAM algorithm. The \(NH\infty \)-SLAM algorithm provides an accurate estimate than EKF-SLAM and good results were obtained.

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Acknowledgment

A data-set obtained during an experiment performed with the Ictineu AUV serves as a test for our proposed SLAM algorithm in off-line. The authors are grateful to David Ribas, Pere Ridao, Juan Domingo Tardos and Jose Neira for their help with the experimental setup and data-set acquisition. The data-set of this work has been funded in part by projects DPI2005-09001-C03-01 and DPI2006-13578 of the Direction General Investigation of Spain.

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Correspondence to Fethi Demim .

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Demim, F., Nemra, A., Abdelkadri, H., Louadj, K., Hamerlain, M., Bazoula, A. (2019). \(NH\infty \)-SLAM Algorithm for Autonomous Underwater Vehicle. In: Demigha, O., Djamaa, B., Amamra, A. (eds) Advances in Computing Systems and Applications. CSA 2018. Lecture Notes in Networks and Systems, vol 50. Springer, Cham. https://doi.org/10.1007/978-3-319-98352-3_21

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