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一种自主水下机器人追踪深海热液浮力羽流的基于行为规划算法
Alternative TitleA Behavior-Based Planning Algorithm for Tracking of Deep-sea Hydrothermal Buoyant Plumes with Autonomous Underwater Vehicles
田宇; 张艾群; 李伟
Department水下机器人研究室
Conference Name2013 32nd Chinese Control Conference
Conference DateJuly 26-28, 2013
Conference PlaceXi'an, China
Source PublicationProceedings of the 32nd Chinese Control Conference
PublisherIEEE
Publication PlaceNEW YORK
2013
Pages5819-5826
Indexed ByEI ; CPCI(ISTP)
EI Accession number20135217122960
WOS IDWOS:000393046005181
Contribution Rank1
Keyword热液喷口探测 自主水下机器人 羽流追踪 基于行为规划 仿生行为
Abstract赋予自主水下机器人(Autonomous Underwater Vehicle, AUV) 追踪深海热液羽流的能力是实现AUV高效探测海底热液喷口的一个关键问题基子热液羽流的特点和基于AUV的海底热液喷口探测作业分析,研究了热液浮力羽流追踪问题针对AUV 自主追踪热液浮力羽流,研究了一种AUV模仿飞峨行为在三维空间追踪热液浮力羽流的仿生追踪策略:并设计了AUV实现该策略的基子行为的规划算法,包括AUV检测到浮力羽流时向海底方向运动的浮力羽流追踪行为,追踪丢失后AUV在二维水平面寻找浮力羽流的探索行为,和AUV追踪浮力羽流到达喷口后的喷口位置估计行为此外,在此基础上还设计了AUV定位喷口后获取其上方热液浮力羽流示踪物水平横截面分布数据的测绘行为,藉此获取的浮力羽流数据可以进一步精确估计喷口位置并发现该喷口临近的其它喷口利用研发的仿真环境对采用的策略和设计的基子行为的规划算法进行了仿真,结果表明AUV利用提出的规划算法能够在三维空间中对热液浮力羽流进行有效的追踪、和最终对热液喷口的位置进行精确定位。
Other AbstractDeep-sea hydrothermal plume tracing capability is important for autonomous underwater vehicles (AUVs) to efficiently perform hydrothermal vents prospecting missions. This paper addresses the hydrothermal buoyant plume tracing problem. Based on the nature of hydrothermal plumes, a moth-inspired strategy for the tracking of hydrothermal buoyant plumes in three dimensions is investigated. And a behavior-based planning algorithm that implements the strategy is designed, which consists of three behaviors, tracking, reacquiring, and declaring. The tracking behavior is to navigate an AUV to move toward the sea bottom when the plume is detected. The reacquiring behavior maneuvers the AUV in two-dimensional horizontal plane to find the plume if the plume is lost during the tracking. The declaring behavior is to estimate the vent’s location when the AUV has tracked the plume to the vent. In addition, a mapping behavior is designed to collect the buoyant plume data above the vent after the vent has been localized, with which the vent’s location could be accurately estimated and the adjacent vents could be found. The behavior-based planning algorithm is implemented on a developed simulation environment. The simulation results demonstrate that the presented algorithm is effective for navigating an AUV to track a hydrothermal buoyant plume in three dimensions to its vent and finally localize the vent accurately.
Language中文
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/13861
Collection水下机器人研究室
Recommended Citation
GB/T 7714
田宇,张艾群,李伟. 一种自主水下机器人追踪深海热液浮力羽流的基于行为规划算法[C]. NEW YORK:IEEE,2013:5819-5826.
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