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- W3149842131 abstract "In this paper,a cooperative localization algorithm for autonomous underwater vehicles (AUVs) is proposed.A parallel model is adopted to describe the cooperative localization problem instead of the traditional leader-follower model,and a linear programming associated with convex optimization method is used to deal with the problem.After an unknown-but-bounded model for sensor noise is assumed,bearing and range measurements can be modeled as linear constraints on the configuration space of the AUVs.Merging these constraints induces a convex polyhedron representing the set of all configurations consistent with the sensor measurements.Estimates for the uncertainty in the position of a single AUV or the relative positions of two or more nodes can then be obtained by projecting this polyhedron onto appropriate subspaces of the configuration space.Two different optimization algorithms are given to recover the uncertainty region according to the number of the AUVs.Simulation results are presented for a typical localization example of the AUV formation.The results show that our positioning method offers a good localization accuracy,although a small number of low-cost sensors are needed for each vehicle,and this validates that it is an economical and practical positioning approach compared with the traditional approach." @default.
- W3149842131 created "2021-04-13" @default.
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- W3149842131 date "2010-01-01" @default.
- W3149842131 modified "2023-09-23" @default.
- W3149842131 title "Convex Optimization Algorithms for Cooperative Localization in Autonomous Underwater Vehicles" @default.
- W3149842131 hasPublicationYear "2010" @default.
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