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Title of Journal: Wireless Pers Commun

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Abbravation: Wireless Personal Communications

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Springer US

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1572-834X

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Underwater Localization and Environment Mapping Us

Authors: Sen Wang Ling Chen Huosheng Hu Zhibin Xue Wei Pan
Publish Date: 2013/03/24
Volume: 70, Issue: 3, Pages: 1147-1170
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Abstract

Localization and mapping are the fundamental ability for underwater robots to carry out exploration and searching tasks autonomously This paper presents a novel approach to localization and mapping of a school of wirelessly connected underwater robotic fish URF It is based on both Cooperative Localization Particle Filter CLPF scheme and Occupancy Grid Mapping Algorithm OGMA Using the probabilistic framework the proposed CLPF has the major advantage that no prior knowledge about the kinematic model of URF is required to achieve accurate 3D localization It works well when the number of mobile beacons is less than four which is the minimum number for some traditional localization algorithms The localization result of CLPF is fed into OGMA to build the environment map The performance of the proposed algorithms is evaluated through extensive simulation experiments and results verify the feasibility and effectiveness of the proposed strategyThis research has been financially supported by National Natural Science foundation of China Grant number 61165016 and by the University of Essex Grant of Building Partnerships for Knowledge Exchange Sen Wang and Ling Chen have been financially supported by Essex University Scholarship and China Scholarship Council Our thanks also go to Robin Dowling for his technical support during the experiments

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