水下机器人运动控制与环境感知技术研究
摘要
水下机器人作为海洋开发与探测的关键装备，其运动控制与环境感知技术是实现复杂任务的核心。本文针对深海复杂环境下水下机器人的自主作业需求，提出了一种融合多源传感器信息的智能控制框架，旨在提高水下机器人在动态环境中的适应性和鲁棒性。研究基于视觉、声呐等多模态感知系统，构建了三维环境模型，实现了对复杂海底地形的有效识别；通过引入深度强化学习算法优化轨迹规划，解决了传统方法难以应对非结构化环境的问题。实验结果表明，所提出的控制策略能够显著提升水下机器人在复杂环境下的定位精度和避障能力，特别是在低光照、高浑浊度条件下表现优异。该研究创新性地将人工智能技术应用于水下机器人领域，为实现智能化、自主化的水下作业提供了新的思路和技术手段，不仅拓展了水下机器人的应用范围，也为未来深海资源勘探、海洋环境保护等提供了有力支持。研究成果对于推动我国海洋工程装备技术进步具有重要意义，为后续相关研究奠定了坚实基础。
关键词：水下机器人；智能控制框架；多模态感知系统
Abstract
Underwater robots, as critical equipment for marine development and exploration, rely on advanced motion control and environmental perception technologies to accomplish complex tasks. This study addresses the autonomous operation requirements of underwater robots in deep-sea complex environments by proposing an intelligent control fr amework that integrates information from multiple sensor sources, aiming to enhance adaptability and robustness in dynamic conditions. Based on multimodal perception systems including visual and sonar sensors, a three-dimensional environmental model was constructed, enabling effective recognition of complex seafloor topographies. By incorporating deep reinforcement learning algorithms to optimize trajectory planning, the proposed approach overcomes challenges posed by unstructured environments that traditional methods struggle with. Experimental results demonstrate that the control strategy significantly improves positioning accuracy and obstacle avoidance capabilities of underwater robots in complex environments, particularly under low-light and high-turbidity conditions. Innovatively applying artificial intelligence technology to the field of underwater robotics, this research provides new ideas and technical means for achieving intelligent and autonomous underwater operations, thereby expanding the application scope of underwater robots. It also offers strong support for future deep-sea resource exploration and marine environmental protection. The findings are of great significance in promoting the advancement of marine engineering equipment technology in China and lay a solid foundation for subsequent related research.
Keywords：Underwater Robot; Intelligent Control fr amework; Multimodal Perception System
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状 1
(三) 研究方法概述 2
二、水下机器人运动控制技术 2
(一) 运动模型建立 2
(二) 控制算法设计 3
(三) 实验验证分析 4
三、水下环境感知技术 4
(一) 传感器选型与布局 4
(二) 数据融合处理 5
(三) 环境建模方法 6
四、集成与应用探索 6
(一) 系统集成方案 6
(二) 关键技术挑战 7
(三) 应用案例分析 7
结 论 9
参考文献 10
摘要
水下机器人作为海洋开发与探测的关键装备，其运动控制与环境感知技术是实现复杂任务的核心。本文针对深海复杂环境下水下机器人的自主作业需求，提出了一种融合多源传感器信息的智能控制框架，旨在提高水下机器人在动态环境中的适应性和鲁棒性。研究基于视觉、声呐等多模态感知系统，构建了三维环境模型，实现了对复杂海底地形的有效识别；通过引入深度强化学习算法优化轨迹规划，解决了传统方法难以应对非结构化环境的问题。实验结果表明，所提出的控制策略能够显著提升水下机器人在复杂环境下的定位精度和避障能力，特别是在低光照、高浑浊度条件下表现优异。该研究创新性地将人工智能技术应用于水下机器人领域，为实现智能化、自主化的水下作业提供了新的思路和技术手段，不仅拓展了水下机器人的应用范围，也为未来深海资源勘探、海洋环境保护等提供了有力支持。研究成果对于推动我国海洋工程装备技术进步具有重要意义，为后续相关研究奠定了坚实基础。
关键词：水下机器人；智能控制框架；多模态感知系统
Abstract
Underwater robots, as critical equipment for marine development and exploration, rely on advanced motion control and environmental perception technologies to accomplish complex tasks. This study addresses the autonomous operation requirements of underwater robots in deep-sea complex environments by proposing an intelligent control fr amework that integrates information from multiple sensor sources, aiming to enhance adaptability and robustness in dynamic conditions. Based on multimodal perception systems including visual and sonar sensors, a three-dimensional environmental model was constructed, enabling effective recognition of complex seafloor topographies. By incorporating deep reinforcement learning algorithms to optimize trajectory planning, the proposed approach overcomes challenges posed by unstructured environments that traditional methods struggle with. Experimental results demonstrate that the control strategy significantly improves positioning accuracy and obstacle avoidance capabilities of underwater robots in complex environments, particularly under low-light and high-turbidity conditions. Innovatively applying artificial intelligence technology to the field of underwater robotics, this research provides new ideas and technical means for achieving intelligent and autonomous underwater operations, thereby expanding the application scope of underwater robots. It also offers strong support for future deep-sea resource exploration and marine environmental protection. The findings are of great significance in promoting the advancement of marine engineering equipment technology in China and lay a solid foundation for subsequent related research.
Keywords：Underwater Robot; Intelligent Control fr amework; Multimodal Perception System
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状 1
(三) 研究方法概述 2
二、水下机器人运动控制技术 2
(一) 运动模型建立 2
(二) 控制算法设计 3
(三) 实验验证分析 4
三、水下环境感知技术 4
(一) 传感器选型与布局 4
(二) 数据融合处理 5
(三) 环境建模方法 6
四、集成与应用探索 6
(一) 系统集成方案 6
(二) 关键技术挑战 7
(三) 应用案例分析 7
结 论 9
参考文献 10
