面向海洋环境自适应采样的多AUV协同定位

doi:10.11959/j.issn.2096-6652.202250

智能科学与技术学报 ›› 2022, Vol. 4 ›› Issue (4): 503-512.doi: 10.11959/j.issn.2096-6652.202250

面向海洋环境自适应采样的多AUV协同定位

张佳欣¹, 张森林¹^,², 刘妹琴¹^,²^,³, 董山玲¹^,², 郑荣濠¹^,²

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

修回日期:2022-11-04 出版日期:2022-12-15 发布日期:2022-12-01
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
基金资助:
NSFC-浙江两化融合联合基金资助(U1809212);NSFC-浙江两化融合联合基金资助(U1909206);浙江省属基本科研业务费专项资金资助(2021XZZX014)

Multi-AUV cooperative localization in adaptive sampling for marine environmental monitoring

Jiaxin ZHANG¹, Senlin ZHANG¹^,², Meiqin LIU¹^,²^,³, Shanling DONG¹^,², Ronghao ZHENG¹^,²

¹ College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
² State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China
³ Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, China

Revised:2022-11-04 Online:2022-12-15 Published:2022-12-01
Supported by:
The NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1809212);The NSFC-Zhejiang Joint Fund for the Integration of Industrialization and Informatization(U1909206);The Fundamental Research Funds for the Zhejiang Provincial Universities(2021XZZX014)

摘要/Abstract

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。

关键词: 自治式潜水器, 协同定位, 高斯过程, 自适应采样, 路径规划

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.

Key words: Special Topic: Autonomous Underwater Vehicle, cooperative localization, Gaussian process, adaptive sampling, path planning

中图分类号:

TP242.6

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.

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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

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