面向海洋环境自适应采样的多AUV协同定位

张佳欣; 张森林; 刘妹琴; 董山玲; 郑荣濠

doi:10.11959/j.issn.2096-6652.202250

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面向海洋环境自适应采样的多AUV协同定位

专题：水下机器人 | 更新时间：2024-06-05

- 面向海洋环境自适应采样的多AUV协同定位
- Multi-AUV cooperative localization in adaptive sampling for marine environmental monitoring
- 智能科学与技术学报 2022年4卷第4期页码：503-512
- 作者机构：
  
  1. 浙江大学电气工程学院，浙江杭州 310027
  2. 浙江大学工业控制技术国家重点实验室，浙江杭州 310027
  3. 西安交通大学人工智能与机器人研究所，陕西西安 710049
- 作者简介：
  
  [ "张佳欣（1996- ），男，浙江大学电气工程学院博士生，主要研究方向为自主水下航行器路径规划" ]
  [ "张森林（1964- ），男，浙江大学电气工程学院教授、博士生导师，主要研究方向为水下无人系统、智能系统和多传感器网络等" ]
  [ "刘妹琴（1972- ），女，博士，西安交通大学人工智能与机器人研究所教授、博士生导师，主要研究方向为人工智能理论与应用、水下信息感知与处理、多传感器信息融合" ]
  [ "董山玲（1990- ），女，博士，浙江大学电气工程学院特聘研究员、博士生导师，主要研究方向为马尔可夫跳变系统、模糊系统和多智能体系统等" ]
  [ "郑荣濠（1984- ），男，博士，浙江大学电气工程学院副教授、博士生导师，主要研究方向为分布式算法和控制、多机器人系统等" ]
- 基金信息：
  
  NSFC-浙江两化融合联合基金资助;The NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1809212);NSFC-浙江两化融合联合基金资助;The NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1909206);浙江省属基本科研业务费专项资金资助;The Fundamental Research Funds for the Zhejiang Provincial Universities(2021XZZX014)
- DOI：10.11959/j.issn.2096-6652.202250
  中图分类号： TP242.6
- 网络出版日期：2022-12，
  
  纸质出版日期：2022-12-15
- 稿件说明：
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张佳欣, 张森林, 刘妹琴, 等. 面向海洋环境自适应采样的多AUV协同定位[J]. 智能科学与技术学报, 2022,4(4):503-512.

Jiaxin ZHANG, Senlin ZHANG, Meiqin LIU, et al. Multi-AUV cooperative localization in adaptive sampling for marine environmental monitoring[J]. Chinese journal of intelligent science and technology, 2022, 4(4): 503-512.
张佳欣, 张森林, 刘妹琴, 等. 面向海洋环境自适应采样的多AUV协同定位[J]. 智能科学与技术学报, 2022,4(4):503-512. DOI： 10.11959/j.issn.2096-6652.202250.

Jiaxin ZHANG, Senlin ZHANG, Meiqin LIU, et al. Multi-AUV cooperative localization in adaptive sampling for marine environmental monitoring[J]. Chinese journal of intelligent science and technology, 2022, 4(4): 503-512. DOI： 10.11959/j.issn.2096-6652.202250.

摘要

高效、准确的水质监测对海洋资源开发具有重要意义，自治式潜水器（AUV）在海洋环境监测中有广阔的应用前景。针对单个 AUV 执行面向海洋标量场估计的水质采样任务时存在的效率低、可靠性差、覆盖率不足和定位准确性差等问题，提出了一种基于多AUV的协同定位与自适应采样系统。系统中每个AUV定期向队友广播自己收集到的采样数据，并根据接收到的队友数据，基于扩展卡尔曼滤波器进行自定位矫正。根据收集到的采样数据，AUV 以高斯过程建模环境标量场，使用差分进化路径规划器在线规划后续采样路径。仿真结果表明，所提方案有效降低了多AUV系统的定位误差，提升了对环境标量场的估计精度。

Abstract

Efficient and accurate water quality monitoring is of great significance to the development of marine resources

and Special Topic: Autonomous Underwater Vehicle (AUV) has broad application prospects in marine environmental monitoring.There are problems such as low efficiency

poor reliability

insufficient coverage and poor positioning accuracy when a single AUV performs water quality sampling tasks for ocean scalar field estimation.The multi-AUV-based cooperative localization and adaptive sampling system was proposed.Each AUV in the system broadcasted the collected sampling data to its teammates

and based on the data received

it corrected the location of itself based on the extended Kalman filter.With the collected sampling data

the AUV modeled the environmental scalar field with a Gaussian process and used a differential evolution path planner to plan its subsequent sampling path online.Simulation results showed that the proposed method effectively reduced the positioning error of AUVs

and improved the estimation accuracy of the environmental scalar field.

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Keywords

references

GENTRY R R , FROEHLICH H E , GRIMM D , et al . Mapping the global potential for marine aquaculture [J ] . Nature Ecology ＆ Evolution , 2017 , 1 ( 9 ): 1317 - 1324 .

MOORE S K , CLINE M R , BLAIR K , et al . An index of fisheries closures due to harmful algal blooms and a framework for identifying vulnerable fishing communities on the US West Coast [J ] . Marine Policy , 2019 , 110 : 103543 .

SAKAMOTO S , LIM W A , LU D D , et al . Harmful algal blooms and associated fisheries damage in East Asia:current status and trends in China,Japan,Korea and Russia [J ] . Harmful Algae , 2021 , 102 : 101787 .

CLARK S , HUBBARD K A , ANDERSON D M , et al . Pseudo-nitzschia bloom dynamics in the Gulf of Maine:2012-2016 [J ] . Harmful Algae , 2019 , 88 : 101656 .

KAMAPANTULA B K , MAHDY A M . Forecasting red tides using a novel multi-metric adaptive routing algorithm in underwater wireless sensor networks [J ] . Journal of Communications and Information Sciences , 2011 , 1 ( 2 ): 22 - 31 .

BUMA W G , LEE S I . Evaluation of sentinel-2 and landsat 8 images for estimating chlorophyll-a concentrations in lake Chad,Africa [J ] . Remote Sensing , 2020 , 12 ( 15 ): 2437 .

BRESCIANI M , RUSCIO F , TANI S , et al . Path planning for underwater information gathering based on genetic algorithms and data stochastic models [J ] . Journal of Marine Science and Engineering , 2021 , 9 ( 11 ): 1183 .

STANKIEWICZ P , TAN Y T , KOBILAROV M . Adaptive sampling with an Special Topic:Autonomous Underwater Vehicle in static marine environments [J ] . Journal of Field Robotics , 2021 , 38 ( 4 ): 572 - 597 .

ABBASI A , MAHMOUDZADEH S , YAZDANI A . A cooperative dynamic task assignment framework for COTSBot AUVs [J ] . IEEE Transactions on Automation Science and Engineering , 2022 , 19 ( 2 ): 1163 - 1179 .

XU B , GUO Y , WANG L Z , et al . A novel robust Gaussian approximate smoother based on EM for cooperative localization with sensor fault and outliers [J ] . IEEE Transactions on Instrumentation and Measurement , 2021 , 70 : 1 - 14 .

HAN G J , GONG A N , WANG H , et al . Multi-AUV collaborative data collection algorithm based on Q-learning in underwater acoustic sensor networks [J ] . IEEE Transactions on Vehicular Technology , 2021 , 70 ( 9 ): 9294 - 9305 .

施琳琳 . 多自主水下航行器的协同流场估计与分布式目标围捕 [D ] . 杭州:浙江大学 , 2022 .

SHI L L . Cooperative flow field estimation and distributed target enclosing of AUVs [D ] . Hangzhou:Zhejiang University , 2022 .

KEMNA S , ROGERS J G , NIETO-GRANDA C , et al . Multi-robot coordination through dynamic Voronoi partitioning for informative adaptive sampling in communication-constrained environments [C ] // Proceedings of 2017 IEEE International Conference on Robotics and Automation . Piscataway:IEEE Press , 2017 : 2124 - 2130 .

CUI R X , LI Y , YAN W S . Mutual information-based multi-AUV path planning for scalar field sampling using multidimensional RRT [J ] . IEEE Transactions on Systems,Man,and Cybernetics:Systems , 2016 , 46 ( 7 ): 993 - 1004 .

ZHANG J X , LIU M Q , ZHANG S L , et al . Multi-AUV adaptive path planning and cooperative sampling for ocean scalar field estimation [J ] . IEEE Transactions on Instrumentation and Measurement , 2022 , 71 : 1 - 14 .

LI Y C , LI B C , YU W B , et al . Cooperative localization based multi-AUV trajectory planning for target approaching in anchor-free environments [J ] . IEEE Transactions on Vehicular Technology , 2022 , 71 ( 3 ): 3092 - 3107 .

RASMUSSEN C E , WILLIAMS C K I . Gaussian processes for machine learning [M ] . Cambridge : The MIT Press , 2005 .

MAHMOUDZADEH S , POWERS D M W , ATYABI A . UUV’s hierarchical DE-based motion planning in a semi dynamic underwater wireless sensor network [J ] . IEEE Transactions on Cybernetics , 2019 , 49 ( 8 ): 2992 - 3005 .

WOODMAN O J . An introduction to inertial navigation [R ] . 2007 .

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