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基于不确定性分析的移动机器人环境感知及其应用研究
其他题名UNCERTAINTY ANALYSIS BASED MOBILE ROBOT ENVIRONMENT PERCEPTION AND ITS APPLICATION
罗本成
学位类型工学博士
导师原魁
2003-07-01
学位授予单位中国科学院研究生院
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
关键词移动机器人 不确定性分析 环境感知与建模 多传感器信息融合 自适应定位 实时导航与避障 Mobile Robot Uncertainty Analysis Environment Perception And Modeling Multi-sensors Data Fusion Adaptively Self-localization Rea
摘要随着科学技术的深入发展,人们对高智能移动机器人系统的需求越来越迫 切,移动机器人研究也进入了崭新的发展阶段。目前,移动机器人环境感知和 不确定性分析能力成为衡量其智能化程度高低的重要标志。本文在国家“863” 高技术项目“足球机器人关键技术研究”和中国科学院研究生院创新基金项目 “移动机器人智能环境感知系统”的资助下,针对移动机器人环境感知问题展 开了深入研究。本论文基于不确定性分析方法,以移动机器人环境感知为中心, 展开了感知技术、环境感知与建模、机器人定位、实时导航与避障等方面的研 究。本论文的研究工作包括以下几方面: 首先,本论文综述了移动机器人应用背景、发展状况,阐述了移动机器人 中不确定性分析研究现状和主要的研究问题,并对本文的选题背景、意义和主 要内容进行了介绍。 其次,分析了移动机器人传感器技术,提出一种“嵌入式环境感知”的概 念,并对机器人传感器技术的未来趋势进行了展望。研制了一种面向移动机器 人的嵌入式非视觉类环境感知系统,并介绍了软、硬件系统实验平台。 第三,针对超声传感器存在的不确定性,在深入分析超声测距工作机理和 工作特性的基础上,提出了一种自适应滤波的新方法,以克服超声探测的不确 定性。接着,通过数学推导及实验比较,提出了一种基于模糊测度的超声测距 数学建模方法。实验分析表明这些策略和方法的合理性和有效性。 第四,结合超声测距存在的不确定性特点,深入研究了移动机器人自主环 境地图构建与环境建模等相关问题。提出一种 “有限探测视场”VLS的探测 策略,以改善超声环境探测性能,并采用主观Bayesian推理方法实现环境地 图的构建。为作深入对比分析,提出了一种基于不确定测度DOI的D-S证据 推理的环境地图构建方法。对比实验表明,上述方法比较适合于存在许多不确 定性的基于超声传感器的环境建模。 第五,探讨了不确定环境中移动机器人的自适应定位问题。首先,论述了 移动机器人自适应定位的研究现状,提出了一种基于栅格模式不变矩匹配的机 器人定位新方法。为保证该算法的鲁棒性和适应性,本文采用部分Hausdorff 距离测度方法实现机器人的细定位。接着,从码盘定位的数学机理角度进行了 深入分析,提出一种基于X2检验分析的码盘定位效果评价方法。在前两者基 础上,给出个一种解决机器人自适应定位问题的有效方法,并通过具体定位实 验进行了验证分析。 第六,探讨了动态不确定环境下,移动机
其他摘要With the development of the science and technology, the need of high level intelligent mobile robot systems is more and more urgent in many fields. Accordingly, the mobile robotics research comes into a new age. Currently, the capability of environment perception & uncertainty reasoning has become the most important feature of an intelligent mobile robot. Under the support of Chinese 863 High-tech Plan project "Some key technologies of soccer robotics", and the Graduate School of the Chinese Academy of Sciences Innovation project "Intelligent environment perception system for mobile robots", this thesis investigates the problem of environment perception by a mobile robot operating in real world environments. On the basis of uncertainty analysis technology, this thesis focuses on the problem of environment perception, and some related issues are addressed by details, including sensing technology, environment perception & modeling, robot self-localization, real-time navigation & obstacle avoidance. The main work and specific contributions of this research are as follows: Firstly, the application background and development status of mobile robotics are briefly reviewed. Some issues about reasoning with uncertainty in mobile robotics, as well as its scientific context, are addressed. This is followed by details of the research background, structure and main work about the thesis. Secondly, by means of analyzing sensing technology of mobile robotics, an concept of "embedded environment perception system (EEPS)" is presented. Based on the analysis of the potential development of sensing technology, a novel mobile robot oriented EEPS is developed. And then the software & hardware experimental platform in our work is also described in details. Thirdly, due to the fundamental unreliability of the sonar, by investigating the physics of sonar and its working mechanism, a new self-adaptive filtering method for sonar readings is presented, so as to overcome its uncertainty. Then a detailed fuzzy-based sonar sensor model is provided. Experimental results demonstrate the model with high effectiveness and flexibility. Fourthly, by taking into account of the uncertainty of sonar sensors, the discussion turns to the problem of map-building and environment modeling for a mobile robot under real world situations. For the purpose of advancing the performance of sonar, a vision limited sensing (VLS) strategy is employed. To solve the problem of map-building, an approach based on subjective Bayesian reasoning technology is described. To make comparative study, an uncertainty measure D-S evidence reasoning based map-building method is presented. Experimental results show the proposed methods are suitable for sonar-based environment modeling. Fifthly, the problem of adaptively self-localization for a mobile robot in realistic uncertain environments is discussed. The research status of self-localization for mobile robots is
馆藏号XWLW839
其他标识符839
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/5780
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
罗本成. 基于不确定性分析的移动机器人环境感知及其应用研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2003.
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