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题名: 基于激光测距仪的动态环境建模与优化导航
其他题名: Dynamic Environmental Modeling and Optimal Guidance Based on Laser Scanner
作者: 邱权
导师: 韩建达
分类号: TP242.6
关键词: 动态环境建模 ; 优化导航 ; 自主定位 ; 局部避障 ; 目标跟踪
索取号: TP242.6/Q81/2010
学位专业: 模式识别与智能系统
学位类别: 博士
答辩日期: 2010-05-23
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 机器人学研究室
中文摘要: 机器人的智能性研究,是集合了传感器技术、数据处理算法和人工智能理论等各种尖端技术理论的复合型研究方向。随着现代社会对机器人能力要求的不断提升,高智能性的机器人产品以其巨大的市场潜力和广泛的应用背景,已经越来越受到世界各国研究开发人员的重视。机器人的智能性包涵两个基本要素:机器人的感知分析能力和机器人的规划决策能力。在对国内外研究现状充分调研和“机器人学国家重点实验室”已有硬件条件的基础上,本文针对这两个基本要素在地面移动机器人载体上的具体表现形式:动态环境建模问题和实时优化导航问题,展开了深入的研究,为实现搭建一个简化的智能性地面移动机器人系统的目标进行了有益的尝试。本文的主要研究工作如下: 1) 研究了地面移动机器人自主定位算法。根据非结构化应用环境的要求和激光测距仪测量数据的特点,选择基于地图匹配的方法作为主要的自主定位算法研究方向。提出了基于激光测距仪的快速直方图匹配定位算法和基于特征分量的复合直方图匹配定位算法,利用建立多层直方图和特征分量直方图的方法,实现了机器人在二维环境下的快速准确自主定位。2) 研究了地面移动机器人的环境建模方法。采用了栅格高程地图作为存储环境信息的环境模型,在原有的高斯混合模型算法的基础上进行改进,提出了可变选择窗口策略,用来限定测量点高度分量在水平栅格上的散布;提出了虚拟点向量方法,用来避免复杂的雅可比矩阵计算;在二点五维环境建模中引入了分簇策略,用来保证不同物体在环境模型中的几何独立表示。 3) 研究了地面移动机器人的实时优化导航算法。在全局路径规划和局部避障导航这两个分支中,选定局部避障导航作为研究的突破口,将原有的二维平面导航方法提升为二点五维导航方法,提出了基于激光测距仪的二点五维实时局部避障导航算法。该算法能够在凹凸不平的地面上对机器人进行导航,引导机器人躲避地面凸起和凹陷障碍物。 4) 研究了地面移动机器人的目标跟踪问题。分析了解决目标跟踪问题所需要用到的几个步骤及其相关技术,针对比较难以实现的目标探测识别和运动性能估计问题,给出了基于扩展集员滤波估计方法的具体解决方案。本文的工作丰富了地面移动机器人智能性研究的内容,对搭建高智能性的地面移动机器人系统进行了有益的尝试,有助于推动机器人智能性研究和相关技术的发展。
英文摘要: The research on the robotic intelligence is an integration of sensor technologies, data processing algorithms and artificial intelligence theories. With the fast growing demands that modern society lays on the robots’ complicated functions, robots with high intelligence level are drawing more and more attentions with their tremendous market potential. The robotic intelligence consists of two basic factors: the perception capacity and the decision-making capacity. Based on the comprehensive literature review and the hardware conditions of the State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, the achievements of this thesis include the dynamic environmental modeling problem and the optimal guidance problem, which are the respective derivatives of the two basic factors on the terrain mobile robot, for constructing a simplified intelligent terrain mobile robot system. The main contents include: 1) The self-localization algorithms of the terrain mobile robot are researched. According to the application requirements of the unstructured environment and the features of the data coming from the laser range finders, we mainly research on the map-matching based localization algorithms. For matching the laser scan maps, a fast histogram matching algorithm and a multiple-histogram matching algorithm based on feature components are proposed. In the algorithms, hierarchical histograms and multiple histograms with feature components are employed to carry out the fast and accurate self-localization for terrain mobile robots under 2D space. 2) The environmental modeling algorithms are researched. The Cartesian height map is chosen as the model to restore the environmental information. Improvements are added to the original Gaussian Mixture Algorithm: a “3σ-principle” based variable selection window strategy is given to limit the probability distribution area of each measurement point on the planar grids; “Virtual Point Vector” is used to avoid the complex computation of Jacobian matrix; a clustering approach is presented to distinguish objects efficiently and decrease the operation area of one laser scan. 3) The real-time optimal guidance algorithms are researched. Between the two branches of the optimal guidance problem, local obstacle avoidance is chosen as the research focus. To extend the traditional 2D planar guidance problem into 2.5D cases, a new 2.5D real-time local obstacle avoidance algorithm based on laser range finder is proposed. The new algorithm can navigate the robot on off-road uneven terrain and help the robot to choose the safe path that is out of salient and pits.  4) The moving target tracking problem is discussed. The implementation process and the related techniques of the problem are analyzed first. Then, for the most troublesome part, the detection and abstraction of the target, an Extended Set-Membership Filter based solution is given and tested.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9385
Appears in Collections:机器人学研究室_学位论文

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Recommended Citation:
邱权.基于激光测距仪的动态环境建模与优化导航.[博士 学位论文 ].中国科学院沈阳自动化研究所 .2010
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