中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
基于传感器信息的移动机器人导航与控制研究

文献类型:学位论文

作者叶涛
学位类别工学博士
答辩日期2003-05-01
授予单位中国科学院研究生院
授予地点中国科学院自动化研究所
导师谭民
关键词移动机器人 导航与控制 多传感器信息融合 轨迹跟踪 mobile robot navigation and control multi-sensor information fusion trajectory tracking
其他题名Research on Navigation and Control of a Mobile Robot Based on Sensors' Information
学位专业控制理论与控制工程
中文摘要移动机器人要实现在未知和不确定环境下自主的工作,应具有感受作业环 境和规划自身动作的能力。为此,必须提高移动机器人对当前环境的快速感知、 理解和识别能力以及导航功能。本文针对未知环境下基于传感器信息的移动机 器人导航与控制问题开展研究。 本文首先综述了国内外移动机器人的研究概况、研究背景,对多传感器信 息融合、机器人路径规划和跟踪控制技术的研究进展、研究方法进行了综述, 介绍了本文的选题背景、主要研究内容和研究意义。 其次,针对我们开发研制的移动机器人CASIA—I,提出适用于信息融合的基 于多DSP系统的分布式多传感器信息融合体系结构,并分析了基于DSP处理的 超声、红外传感阵列数据采集系统的软硬件设计。 第三,研究了全局环境未知情况下的移动机器人实时导航问题,将栅格法 描述环境与基于滚动窗口的路径规划相结合,提出了一种新的移动机器人导航 方法。将超声传感阵列探测到的环境信息以基于栅格的概率值进行表示,利用 不确定性证据推理对其进行数据融合,得到机器人的局部环境信息;在此基础 上,采用基于滚动窗口的方法进行机器人路径规划,实现机器人的实时导航。 第四,将CCD的视觉信息与超声传感器阵列采集的信息进行融合,提出一 种新的融合方法,实现机器人对环境中物体的准确描述。根据CCD,提出采用 边缘检测和摄像机标定的方法获取物体与地面相交的边缘的,几何表达式;对超 声传感阵列采集的数据,依据三角测量方法获耳义物体边缘顶点的坐标,进一步 计算得到物体边缘的几何表达式。最后将两种传感器获得的关于同一物体边缘 的几何表达式进行融合,得到对环境中物体更准确和更可靠的描述。 第五,研究了移动机器人的全局轨迹跟踪问题。首先针对CASIA—I,推导了 其运动学模型和跟踪模型。然后采用变结构控制方法对移动机器人的轨迹跟踪 问题进行研究,非线性系统变结构控制器设计的关键之一是寻求切换函数使得 滑动模念渐近稳定,本文提出利用后退(backstepping)方法的思想,设计变结 构控制的切换函数,并由此构造了具有全局渐近稳定性的滑模跟踪控制器。 最后,总结了本文所取得的研究成果,并指出了需要进一步研究的工作。
英文摘要To work in unknown or uncertain environment, mobile robots should be able to sense the environment and plan their actions.So, it is essential to enchance the ability of environment perception, environment understanding, environment recognition and navigation of mobile robots. This thesis focuses on the problems of navigation and control of mobile robot based on sensors' information in unknown environment. Firstly, the historical context of mobile robot is introduced. The research development and main research directions of multi-sensor information fusion, path planning, and tracking control are reviewed. The background and structure of this thesis are also introduced. Secondly, for mobile robot CASIA-I which is designed by us, a distributed architecture based on multi DSPs system for multi-sensor information fusion is proposed. The hardware and software design of data collection system of sonar and infrared sensors using DSP is also analyzed. Thirdly, real-time navigation of mobile robot in globally unknown environment is studied. A new method for mobile robot's navigation is proposed by combining describing environment based on grids and path planning based on rolling windows. The environment information detected by sonar is represented in the form of probability based on grids, and is fused by evidential reasoning with uncertainty based on Dempster-Shafer theory to describe the local environment around the mobile robot. And then, path planning based on rolling windows is implemented to realize real-time navigation of mobile robot. Fourthly, a new algorithm of multi-sensor fusion for a mobile robot to represent object accurately in the environment is proposed using sensory information from CCD camera and ultrasonic sonar ring. For CCD camera, we propose to use edge detect method and CCD calibration to obtain the geometric representation of object's boundary intersecting with the ground. Using ultrasonic sonar ring, we obtain the vertex's coordinate of object's boundary using triangulation-based fusion (TBF) and then compute the geometric representation of object's boundary. Finally, by fusing the geometric representations of the same object's boundary that were obtained by two kinds of sensor, a more reliable and accurate representation of object in environment is realized Fifthly, globally trajectory tracking control of mobile robot is studied. For CASIA-I's architecture, its kinematics models and tracking models is deduced. And then the variable structure control is applied to the trajectory tracking control of mobile robots. The key to VSC for nonlinear system is the design of a switch function which should ensure the stabilization of sliding mode. We propose to use the backstepping method to design the switch function for VSC and then construct a sliding mode controller with globally asymptotic stability Finally, the obtained results are summarized and future work is addressed.
语种中文
其他标识符721
源URL[http://ir.ia.ac.cn/handle/173211/5746]  
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
叶涛. 基于传感器信息的移动机器人导航与控制研究[D]. 中国科学院自动化研究所. 中国科学院研究生院. 2003.

入库方式: OAI收割

来源:自动化研究所

浏览0
下载0
收藏0
其他版本

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。