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基于嵌入式视觉的仿生机器鱼跟踪控制
其他题名Embedded Vision Based Tracking Control of Biomimetic Robotic Fish
孙飞虎
学位类型工学博士
导师徐德 ; 喻俊志
2015-05-27
学位授予单位中国科学院大学
学位授予地点中国科学院自动化研究所
学位专业控制理论与控制工程
关键词仿生机器鱼 嵌入式视觉 平稳性控制 三维跟踪控制 Biomimetic Robotic Fish Embedded Vision Stability Control 3-d Tracking Control
摘要基于嵌入式视觉的仿生机器鱼跟踪控制是具有挑战性的任务,但也是极具吸引力的研究方向,可为未来水下潜器向智能化方向的发展奠定基础。本文从具有嵌入式视觉的仿生机器鱼系统设计入手,研究了机器鱼的头部平稳性控制、基于人工地标的三维定位以及基于视觉的三维跟踪控制问题,并且通过实验分别验证了所提出算法的可靠性与有效性。 首先,对水下机器人视觉测量与控制的研究现状进行了综述,指出了水下视觉的特点与存在的难点;分析了当前仿生机器鱼运动性能研究的现状。指出当前基于视觉的仿生机器鱼研究处于初级阶段,虽然面临重重困难,但是极具发展潜力。 其次,设计了具有嵌入式视觉的仿生机器鱼系统。具体来说,包括了具有嵌入式视觉的机械结构以及适用于嵌入式视觉处理的硬件电路,采用了Codec Engine 架构以应对大数据量的视觉伺服控制。同时,为了提高系统开发效率,开发了软件仿真平台与硬件调试平台。并且,设计了机器鱼的三维运动步态,通过实验验证了机器鱼灵活的运动性能。 第三,研究了仿生机器鱼水面跟踪控制问题。给出了一种改进的CAMSHIFT(Continuous Adaptive Mean Shift)方法实现自动目标识别与跟踪,包括基于自适应颜色阈值的目标自动识别、基于加权颜色直方图描述的目标模型以及基于CAMSHIFT 算法的目标跟踪。提出了基于CPG(Central Pattern Generator)模型的模糊运动控制方法,以视觉定位为基础,通过模糊逻辑确定CPG 模型的输入,控制机器鱼游动向目标。 第四,研究了具有视觉的仿生机器鱼头部平稳性控制问题,以获取稳定的图像数据。改进了传统的鱼体波模型以减小机器鱼头部的摆动;基于牛顿–欧拉方法建立机器鱼的水动力学模型,以头部摆动最小为目标建立优化模型,并且通过遗传算法优化得到控制机器鱼头部摆动最小的参数。 第五,研究了基于嵌入式视觉的仿生机器鱼三维跟踪控制。给出了基于人工地标的三维识别与定位方法,快速准确地获取目标三维位置信息。提出了高效简洁的三维跟踪控制框架,将三维跟踪控制划分为定向控制与定深控制。具体来说,提出了基于模糊滑模的定深控制方法,保证机器鱼准确地保持在目标所在的深度;提出了多阶段的定向控制方法,通过可靠的控制策略协调机器鱼灵活运动与控制精度。 最后,对全文的工作和研究成果进行总结,并且指出了进一步开展的工 作。
其他摘要Embedded vision-based tracking control for biomimetic robotic fish is a challenging task, but it is still an attractive research direction, which lays a foundation for the development of intelligent underwater vehicles. System design for the biomimetic robotic fish with embedded vision is addressed in this dissertation.Furthermore, stability control of the head of the robotic fish, 3-D positioning based on an artificial landmark and vision guided 3-D tracking control are investigated. Experiments are conducted to verify the effectiveness and feasibility of proposed algorithms. Firstly, the state of the art of visual measurement and control for underwater robots is reviewed, which emphasizes features of underwater vision and existing difficulties. In addition, locomotion performance of the robotic fish is also summarized. The fact that vision-based research of biomimetic robotic fish is still in the primary stage is indicated. This means that there exist both difficulties and potentials in this field. Secondly, the system design of the robotic fish with embedded vision is addressed. Specifically, the mechanical structure with embedded vision and hardware circuits appropriate for visual processing are designed. Specially, the architecture of Codec Engine is presented to handle visual servoing based on large amount of data. At the same time, in order to improve the efficiency of system development, a software simulation platform and a hardware debugging platform are also developed. Further more, 3-D motion gaits, which are verified by experiments on locomotion performance, are designed. Thirdly, the tracking control in the water surface is investigated. An improved CAMSHIFT (Continuous Adaptive Mean Shift) method is proposed to realize automatic recognition and continuous tracking. Specifically, an automatic recognition algorithm based on adaptive color thresholds is presented; An improved real-time positioning method based on the weighed histogram representation of the target model that synthesizes the CAMSHIFT algorithm is putforward. After that, a fuzzy logic controller based on the CPG (Central Pattern Generator) model is employed to generate control signals related to the desired target. The inputs of CPG model are determined by the fuzzy logic, which are from visual positioning. Fourthly, the issue of stability control of the head is explored, which aims at guaranteeing the steady acquisition of image data. Specifically, the traditional model o...
其他标识符201218014628014
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6701
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
孙飞虎. 基于嵌入式视觉的仿生机器鱼跟踪控制[D]. 中国科学院自动化研究所. 中国科学院大学,2015.
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