基于视觉的小型水下航行器的控制系统设计

发布时间：2019-01-05 01:25

【摘要】：水下机器人是复杂海洋环境工作中的重要运载工具,随着世界各国对海洋资源开发的日益重视,水下机器人在海洋矿产勘探、海底地形探测和深海基础设施检查等的应用需求越来越大。而水下光视觉可以在水下机器人近距离观测作业中提供更丰富的高分辨率信息,受到国内外学者的广泛关注。因此开展基于视觉的小型水下航行器控制系统研究,对于提高水下机器人自主能力及智能化水平,具有重要地理论研究意义和实际应用价值。在对水下航行器的光视觉目标检测方法研究中。首先,针对水下图像降质问题,建立水下光传播的衰减模型和水下成像系统模型,通过水介质中光的衰减对颜色进行恢复的算法来复原图像完成预处理工作;然后,采用基于HSV的自适应彩色图像分割方法来对水下目标物体进行分割,并通过区域几何形状特征参数约束提取方法,最终实现对运动目标区域的提取。最后,对动目标跟踪方法的研究中,采用基于Kalman预测器结合动态检测窗口的目标跟踪算法,通过提取图像中目标质心位置信息来实时对预测结果进行更新校正,并进行了水下航行器动目标跟踪实验研究,以验证所用的目标跟踪方法的实时性和有效性。在水下航行器光视觉目标识别跟踪系统的基础上,对其控制系统进行研究和设计,首先,对控制系统的总体结构及其通信总线进行了设计;然后,分别详细设计了分布式系统的各个子系统,包括主控计算机系统、通信系统、推进器控制系统、电源管理与安全系统和传感器信息采集系统;并对控制系统的软件结构进行了设计,最终形成了由软硬件系统组成的基于视觉的分布式控制系统。在基于视觉的控制系统基础上,为了实现水下航行器的自主目标跟踪功能,对其运动控制系统进行了仿真研究。首先,本文对所设计的小型水下航行器的艇体结构及各传感器分布进行介绍;然后,对所研究的水下航行器的六自由度运动模型进行了分析,并解耦升沉和航向的动力学方程表达式;最后对解耦的航向子系统与升沉子系统的控制进行了设计与仿真,为后文的水下目标识别跟踪控制实验做了理论上的铺垫工作。最后,对该小型水下航行器进行了大量的水池实验,包括传感器滤波实验,深度、航向控制实验,结合本文研究的基于光视觉的目标识别跟踪系统设计了自主水下目标跟踪撞球实验,验证本文所设计的基于视觉的控制系统的实时性和稳定性。
[Abstract]:Underwater vehicle is an important vehicle in the work of complex marine environment. With the increasing attention paid to the exploitation of marine resources by countries all over the world, underwater vehicles are being explored in marine mineral resources. The application needs of submarine topography exploration and deep-sea infrastructure inspection are increasing. Underwater light vision can provide more high resolution information in the close observation operation of underwater vehicle, and it has been widely concerned by scholars at home and abroad. Therefore, the research on the control system of small underwater vehicle based on vision has important theoretical research significance and practical application value for improving the autonomous ability and intelligent level of underwater vehicle. In the research of optical visual target detection method for underwater vehicle. Firstly, aiming at the degradation problem of underwater image, the attenuation model of underwater light propagation and the model of underwater imaging system are established, and the image preprocessing is completed by the algorithm of color restoration by the attenuation of light in water medium. Then, adaptive color image segmentation method based on HSV is used to segment underwater object, and the geometric feature parameter constraint extraction method is used to extract the moving object region. Finally, in the research of moving target tracking method, the target tracking algorithm based on Kalman predictor and dynamic detection window is used to update and correct the prediction results by extracting the target centroid position information from the image. Experimental research on moving target tracking of underwater vehicle is carried out to verify the real time and effectiveness of the target tracking method. Based on the optical visual target recognition and tracking system of underwater vehicle, the control system is studied and designed. Firstly, the overall structure of the control system and its communication bus are designed. Then, each subsystem of the distributed system is designed in detail, including the main control computer system, the communication system, the propeller control system, the power management and safety system and the sensor information collection system. The software structure of the control system is designed and a distributed control system based on vision is formed. In order to realize the autonomous target tracking function of underwater vehicle, the motion control system of underwater vehicle is simulated on the basis of the control system based on vision. Firstly, the hull structure and sensor distribution of the designed small underwater vehicle are introduced in this paper. Then, the six-degree-of-freedom motion model of underwater vehicle is analyzed, and the dynamic equations of heave and heading are decoupled. Finally, the control of decoupled heading subsystem and heave subsystem is designed and simulated, which lays the groundwork for the later underwater target recognition and tracking control experiment. Finally, a large number of experiments are carried out on the small underwater vehicle, including sensor filtering experiment, depth control experiment and course control experiment. Combined with the object recognition and tracking system based on optical vision studied in this paper, an autonomous underwater target tracking and billiard experiment is designed, which verifies the real-time and stability of the visual based control system designed in this paper.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41;TP242

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