Adaptive navigation systems for an unmanned surface vehicle

被引:32
|
作者
Sutton, R. [1 ]
Sharma, S. [1 ]
Xao, T. [2 ]
机构
[1] Univ Plymouth, Marine & Ind Dynam Anal Res Grp, Sch Marine Sci & Engn, Plymouth PL4 8AA, Devon, England
[2] Univ Durham, New & Renewable Energy Grp, Sch Engn & Comp Sci, Durham DH1 3HP, England
来源
基金
英国工程与自然科学研究理事会;
关键词
GUIDANCE; FILTER; DESIGN;
D O I
10.1080/20464177.2011.11020248
中图分类号
U6 [水路运输]; P75 [海洋工程];
学科分类号
0814 ; 081505 ; 0824 ; 082401 ;
摘要
This paper reports the design of two potential navigation systems for use in an unmanned surface vehicle (USV) named Springer.The approaches adopted are based on fuzzy multisensor data fusion (MSDF) and multiple model adaptive estimation (MMAE) algorithms with adaptive capabilities. A general description of the Springer USV is given along with details of its navigation sensor suite. Of particular interest are the three different types of electronic compass used to supply heading information. Using a system identification technique, state space models of the compasses are derived for use in a simulation study to compare the navigation systems. From the results presented, it is concluded the fuzzy MSDF algorithm is 'better than the MMAE methodology in terms of heading (yaw error) accuracy and robustness.
引用
收藏
页码:3 / 20
页数:18
相关论文
共 50 条
  • [1] Adaptive Semantic Segmentation for Unmanned Surface Vehicle Navigation
    Zhan, Wenqiang
    Xiao, Changshi
    Wen, Yuanqiao
    Zhou, Chunhui
    Yuan, Haiwen
    Xiu, Supu
    Zou, Xiong
    Xie, Cheng
    Li, Qiliang
    [J]. ELECTRONICS, 2020, 9 (02)
  • [2] Visual Navigation and Landing Control of an Unmanned Aerial Vehicle on a Moving Autonomous Surface Vehicle via Adaptive Learning
    Zhang, Hai-Tao
    Hu, Bin-Bin
    Xu, Zhecheng
    Cai, Zhi
    Liu, Bin
    Wang, Xudong
    Geng, Tao
    Zhong, Sheng
    Zhao, Jin
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2021, 32 (12) : 5345 - 5355
  • [3] Basic navigation, guidance and control of an Unmanned Surface Vehicle
    Caccia, Massimo
    Bibuli, Marco
    Bono, Riccardo
    Bruzzone, Gabriele
    [J]. AUTONOMOUS ROBOTS, 2008, 25 (04) : 349 - 365
  • [4] System Design of an Unmanned Surface Vehicle for Autonomous Navigation
    Kim, Taejin
    Choi, Jinwoo
    Lee, Yeongjun
    Jung, Jongdae
    Choi, Hyun-Taek
    [J]. AETA 2016: RECENT ADVANCES IN ELECTRICAL ENGINEERING AND RELATED SCIENCES: THEORY AND APPLICATION, 2017, 415 : 874 - 879
  • [5] Basic navigation, guidance and control of an Unmanned Surface Vehicle
    Massimo Caccia
    Marco Bibuli
    Riccardo Bono
    Gabriele Bruzzone
    [J]. Autonomous Robots, 2008, 25 : 349 - 365
  • [6] Visual Tracking of Objects for Unmanned Surface Vehicle Navigation
    Chae, Kyung Hwa
    Moon, Yong Seon
    Ko, Nak Yong
    [J]. 2016 16TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2016, : 335 - 337
  • [7] Unmanned ground vehicle-unmanned aerial vehicle relative navigation robust adaptive localization algorithm
    Dai, Jun
    Liu, Songlin
    Hao, Xiangyang
    Ren, Zongbin
    Yang, Xiao
    Lv, Yunzhu
    [J]. IET SCIENCE MEASUREMENT & TECHNOLOGY, 2023, 17 (05) : 183 - 194
  • [8] Target Tracking of Navigation Radar for Unmanned Surface Vehicle Based on an Improved Adaptive Kalman Filtering
    Chen, Si
    Fan, Yunsheng
    Qiao, Shuanghu
    Zhang, Haoyan
    [J]. 2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, : 4323 - 4328
  • [9] Unmanned Aerial Vehicle Integrated Navigation Complex with Adaptive Tuning
    Zakharin, F.
    Ponomarenko, S.
    [J]. 2017 IEEE 4TH INTERNATIONAL CONFERENCE ACTUAL PROBLEMS OF UNMANNED AERIAL VEHICLES DEVELOPMENTS (APUAVD), 2017, : 23 - 26
  • [10] A Robust Localization Method for Unmanned Surface Vehicle (USV) Navigation Using Fuzzy Adaptive Kalman Filtering
    Liu, Wenwen
    Liu, Yuanchang
    Bucknall, Richard
    [J]. IEEE ACCESS, 2019, 7 : 46071 - 46083