详细信息
自主水下机器人系统感知-决策-控制技术综述 ( EI收录) 被引量:118
Review of Perception-Decision-Control Technologies for Autonomous Underwater Robotic Systems
文献类型:期刊文献
中文题名:自主水下机器人系统感知-决策-控制技术综述
英文题名:Review of Perception-Decision-Control Technologies for Autonomous Underwater Robotic Systems
作者:Chu, Hubo[1]; Chen, Shouyan[2]; Liu, Haitao[1]; Yang, Zhou[1,3]
机构:[1] School of Mechanical Engineering, Guangdong Ocean University, Zhanjiang, 524091, China; [2] School of Mechanical and Electrical Engineering, Guangzhou University, Guangzhou, 510006, China; [3] College of Engineering, South China Agricultural University, Guangzhou, 510642, China
年份:2026
卷号:57
期号:19
起止页码:18
外文期刊名:Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery
收录:EI(收录号:20264021602232)
语种:中文
外文关键词:Behavioral research - Computer vision - Decision making - Manipulators - Motion control - Robust control - Underwater imaging
外文摘要:Underwater vehicle-manipulator systems (UVMS) integrated the mobility of underwater vehicles with the dexterous manipulation capability of manipulators, thereby providing essential technological support for complex deep-sea operations such as inspection, maintenance, and intervention. A systematic review of recent research on the key technologies of UVMS was presented. Firstly, from the perspective of perception, underwater environment sensing methods, underwater image enhancement, and target detection techniques were summarized, and their application performance in complex underwater operational scenarios was analyzed. Secondly, from the decision-making perspective, obstacle avoidance, path planning, and motion trajectory planning methods were reviewed, with a discussion on the impact of task complexity and environmental uncertainty on planning and decision performance. Thirdly, from the control perspective, motion control and force interaction control methods for UVMS were examined, and the applicability of model-based, adaptive, and data-driven control strategies in underwater operations was comparatively analyzed. Finally, from the perspectives of multimodal robust perception, intelligent decision-making and task planning, and motion-force control, the future development trends of UVMS were discussed, and frontier technologies with potential application prospects were identified. ? 2026 Chinese Society of Agricultural Machinery. All rights reserved.
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