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Monte Carlo Localization for an Autonomous Underwater Vehicle with a Low-Cost Sonar

Jiang, Keyong and Chen, Ling and Yang, Aolei and Hu, Huosheng (2020) Monte Carlo Localization for an Autonomous Underwater Vehicle with a Low-Cost Sonar. In: 2019 5th International Conference on Environmental Science and Material Application, 2019-12-15 - 2019-12-16, Xi'an, China.

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This paper proposes a Monto Carlo based localization (MCL) algorithm for autonomous underwater vehicle (AUV) with a low-cost mechanical scanning imaging sonar (MSIS). As MSIS has a slow-sampling characteristic, its scan is distorted by the vehicle motion during the scan interval and the sonar readings are sparse. Our contribution is introducing this two-stage approach to overcome the shortages of MSIS to achieve accurate localization: 1) the scan formation module is devised to eliminate the motion induced distortion of sonar scan; 2) MCL is applied to estimate the AUV pose accurately by the Dead Reckoning (DR) result and the formed sonar scan. Results of simulation verify that the proposed algorithm performs well in terms of effectiveness and accuracy.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: IOP Conference Series: Earth and Environmental Science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 07 Aug 2020 14:06
Last Modified: 07 Aug 2020 14:15

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