CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 先进机器人
Thesis Advisor谭民
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline控制理论与控制工程
Keyword仿生推进 水下作业机器人 图像增强 视觉定位 艇臂协调控制 自主抓取 目标追踪



一、面向水下自主作业任务,设计了一种新型波动鳍推进水下作业机器人。在实验室原有波动鳍推进水下作业机器人RobCutt II的基础上,改进了机械臂和波动鳍推进器机构,增加了视觉感知系统,优化模块布局,给出了波动鳍推进水下作业机器人的机构设计方案。此外,构建了水下机器人控制系统和通信系统,通过软硬件集成研制开发了波动鳍推进水下作业机器人实验样机。




Other Abstract

Underwater vehicle-manipulator system (UVMS) is playing an increasingly important role with the transformation from ocean exploration to ocean exploitation. By virtue of the underwater environment sensing and autonomous manipulation of the UVMS, the efficiency of underwater exploration and exploitation could be increased greatly. Furthermore, it would contribute to the underwater rescue and salvage, installation and maintenance of the equipment, seafood farming and fishing, and environmental protection. This thesis focuses on the system design of the UVMS propelled by undulatory fins, real-time underwater image enhancement and vision localization, coordinated plan and control of the vehicle-manipulator, and object tracking. The main contents of this thesis are as follows.

        Firstly, one novel UVMS propelled by undulatory fins is developed for the underwater autonomous manipulation tasks. Based on the research experience of RobCutt II , the structure of the manipulator and biomimetic underwater propulsor is improved significantly, and one visual sensing subsystem is constructed. The layout of all modules is optimized well, and the mechanical design of the novel UVMS propelled by undulatory fins is presented. The control system and communication system are also developed. Furthermore, the prototype of the UVMS propelled by undulatory fins is constructed by integrating the software and hardware.

        Secondly, the underwater image enhancement, object detection and object localization applied to the UVMS are addressed. For solving the problems of the underwater image with poor quality, low contrast, and color degradation, one real-time underwater image and video enhancement method is presented. Then based on the deep learning and neural networks, one real-time lightweight object detector is designed. In addition, the pose and the size of the object are estimated based on the three dimensional position of the key points and lines. Meanwhile, the ray refraction is considered to improve the positioning accuracy. Experimental results on the UVMS propelled by undulatory fins show that the given method is effective and practical.         

        Thirdly, aiming at performing underwater autonomous grasping task, one coordinated plan and control method of the UVMS propelled by undulatory fins is proposed. The online motion plan is firstly performed based on the tracking differentiator. One task-priority kinematics control method with state observers is presented. Additionally, with the consideration of the disturbance on the vehicle caused by the motion of the manipulator, the vehicle control is performed by adaptive wave parameters adjusting. Simulation and experimental results show the effectiveness of the given method.

    Fourthly, underwater moving object tracking by  the UVMS propelled by undulatory fins is studied. Based on the Actor-Critic reinforcement learning framework, one deterministic policy gradient algorithm with the supervised controller is proposed. The policy network and critic network could converge fast. Then the UVMS propelled by undulatory fins could track the moving object successfully under the control of  the trained actor network. Simulation and experimental results show that the proposed method is effective

Document Type学位论文
Recommended Citation
GB/T 7714
唐冲. 波动鳍推进水下作业机器人视觉定位与自主控制研究[D]. 北京. 中国科学院大学,2019.
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