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一种全自主移动机器人的视觉系统研究
Alternative TitleResearch on Vision System in a Kind of Autonomous Mobile Robot
刘晋东
Subtype工学硕士
Thesis Advisor原魁
2002-04-01
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword全自主移动机器人 视觉系统 目标跟踪 进化agent Kalman滤波 Autonomous Mobile Robot Vision System Object Tracking Evolution Agent Kalman Filter
Abstract本文主要针对移动机器人视觉系统进行了研究。其中,主要在目标跟踪方面 进行了重点研究,并且对目标定位的方法进行了探讨。本文的研究目标是使用低 成本摄像机实现目标的实时跟踪,提高整个视觉系统乃至整个移动机器人系统的 性能价格比。本文主要包括如下几个方面的工作: 1.在基于颜色的目标搜索方面,选取了YCrCb颜色空间表示方法,克服了图像 亮度对目标跟踪的影响,并综合数学形态学和进化Agent算法,提出改进的 进化Agent算法。该算法大大提高了目标搜索的速度,提高了图像处理的实 时性。实验表明,该种方法确实可行。 2.在目标实时跟踪方面,将Kalman滤波应用于目标位置预测,利用前后两帧 图像中目标位置信息和运动信息的相关性,在图像的实时采集和目标搜索的 过程中,动态改变搜索窗的位置和大小,进一步减少了目标搜索时间,同时 增加了目标搜索的准确性。 3.在处理由于光照变化引起目标在图像中的颜色变化的问题上,使用了动态颜 色模型的方法,在目标跟踪的过程中,实时改变目标颜色模型,基本上解决 了光照对目标跟踪的影响。 4.在处理目标误检的问题上,结合使用平均马氏距离和Kalman滤波中的新息, 并利用D-S证据理论进行信息融合,使用多个信息源联合判定分割区域为真 实目标的概率,取得了较好的效果。 5.在复杂背景下的目标跟踪中,利用目标的形状信息,针对不同情况选取适当 的形状描述符,同时利用D-S证据理论进行信息融合,排除了伪目标对目标 跟踪的影响。 6.在目标定位方面,结合移动机器人视觉系统的实际使用情况,推导了双目视 觉定位的一般性公式,实现了一种结构光测距的模型,并用实验证明了中低 性能摄像机在目标定位中的可行性。同时,通过认真分析和论证各种视觉系 统方案的优劣,最终选择了一种性能价格比较高的硬件组成方案,经过实验 表明,这种方案是可行的。
Other AbstractThe thesis does some researches on the vision system of autonomous mobile robot. The main research of the thesis is about object tracking. The object orientation is the second research field. The research target of the thesis is realize the real-time object tracking and orientation by low price camera and so improve the ratio of performance to cost of whole vision system and mobile robot. The main work and contribution are following: 1. About the object searching based on color, the YCrCb color space is selected in order to relieve the influence of illumination. The improved evolution Agent algorithm is proposed by combining the mathematical morphology and evolution Agent algorithm. The algorithm proposed shortens the time of object region searching and improves the real-time performance. Experiment results show that it is efficient. 2. About the real-time object tracking, the Kalman filter algorithm is implemented on the prediction of object position. It takes advantage of the object's position information and motion information in the two continuous images to real-time change the position and scope of searching window during the image sampling and object tracking. It also shortens the time and improves the accuracy of object region searching. 3. In order to deal with the change of object surface color due to the change of illumination, dynamical color model is used during the real-time object tracking. It solves the problem brought out by illumination in a scope. 4. To the problem of object mis-searching, the mean Mahalanobis distance and the innovation in Kalman filter are fused by D-S evidential reasoning theory to determine the probability that a region is true object. The experiment results show that it is efficient. 5. On the complex background, the shape information of object is added into the tracking algorithm. The different shape descriptor is chosen according to different object shape. The D-S evidential reasoning theory is also used to deal with the problem of fault object in tracking. 6. About the object orientation, the common equation of binocular orientation is deduced according to the real condition of vision system. The thesis realizes a kind of distance finding model by structured light and proves that the camera with low performance could be used in object orientation. At the same time, a hardware scheme of vision system with higher ratio of performance to cost is chosen after careful analysis and argument. The experiment results show that the scheme is efficient.
shelfnumXWLW622
Other Identifier622
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6860
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
刘晋东. 一种全自主移动机器人的视觉系统研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2002.
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