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https://hdl.handle.net/2440/111701
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Type: | Journal article |
Title: | A collaborative control framework with multi-leaders for AUVs based on unscented particle filter |
Author: | Zhao, Y. Xing, W. Yuan, H. Shi, P. |
Citation: | Journal of the Franklin Institute, 2016; 353(3):657-669 |
Publisher: | Elsevier |
Issue Date: | 2016 |
ISSN: | 0016-0032 1879-2693 |
Statement of Responsibility: | Yunxin Zhao, Wen Xing, Huarun Yuan, Peng Shi |
Abstract: | In view of problems of low independent self-positioning accuracy of autonomous underwater vehicle (AUV) with low precision sensors, and the strong nonlinear characteristics of motion control model and non-Gaussian noise when filtering using the distances between leaders and followers, a collaborative localization framework with multi-leaders for AUVs is presented, which is based on the unscented particle filter. This approach lets unscented Kalman filter act on each particle of particle filter algorithm, which makes particle mix the latest posterior information of measurement when updating. It solves the depletion problem of particles to some extent and improves the effectiveness of filtering method. Collaborative location simulating experiments are carried out in two leaders model with different noises conditions. The implementation results show that this method effectively enhances the estimation accuracy of followers position. |
Description: | Available online 23 December 2015 |
Rights: | Crown Copyright © 2015 Published by Elsevier Ltd. on behalf of The Franklin Institute. All rights reserved. |
DOI: | 10.1016/j.jfranklin.2015.11.016 |
Grant ID: | http://purl.org/au-research/grants/arc/DP140102180 http://purl.org/au-research/grants/arc/LP140100471 http://purl.org/au-research/grants/arc/LE150100079 |
Published version: | http://dx.doi.org/10.1016/j.jfranklin.2015.11.016 |
Appears in Collections: | Aurora harvest 3 Electrical and Electronic Engineering publications |
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