CASIA OpenIR  > 毕业生  > 博士学位论文
基于多传感器信息的移动式服务机器人定位与控制技术
Alternative TitleMulti-Sensor based Localization and Control Theory for Mobile Service Robot
王华伟
Subtype工学博士
Thesis Advisor徐德
2010-05-27
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服务机器人 主动视觉 多传感器 系统标定 机器人定位 Service Robot Active Vision Multi Sensor System Calibration Robot Localization
Abstract移动式服务机器人是一类具有现实应用和实际需求的机器人,正成为机器人领域的研究热点。机器人自主导航与定位是服务机器人技术的基础与关键。未知环境下,视觉与其他传感器结合构成的多传感器系统,被认为是提高机器人位姿估计精度和鲁棒性的有效途径,对于提高自主机器人的性能、推动智能服务机器人的发展具有重要的理论意义及应用价值。近年来,基于多传感器数据融合的机器人定位与导航正受到越来越多的关注。但是在这个领域内还存在很多的理论与技术问题有待进一步解决与完善。 本文对未知环境下基于多传感器信息的移动式服务机器人定位及操作等相关技术进行了研究,主要涉及到视觉检测与特征匹配、主动视觉及其多传感器系统标定、基于多传感器数据的机器人位姿估计、视觉引导下的机器人目标操作等基本问题。具体来说,论文主要工作包括: 1. 为快速、准确地获取图像特征匹配对应点信息,提出了一种改进的SIFT算法:引入了状态标记及颜色约束,提高了点特征检测及匹配的效率;引入极线约束,提出了基于伪随机的匹配检验方法,提高了点匹配正确率。同时,还提出了一种基于分类霍夫变换的直线提取方法,提高了色标边缘直线的检测效率及精度。 2. 针对一类主动立体视觉系统,提出了其外参数快速标定方法,提高了视觉系统测量方便性。 3. 探讨了非结构环境下里程计、惯性及主动视觉所构成的多传感器系统标定问题,提出了基于运动的多传感器系统参数的自标定算法,实现了非结构环境下多传感器系统参数的快速估计,增强了标定算法的灵活性及方便性。 4. 提出了基于里程计、惯性及视觉传感器信息融合的机器人定位策略,实现了里程计与惯性传感器数据融合定位;利用图像特征对应点信息,提出了基于扩展卡尔曼滤波的机器人定位与环境同时创建算法,实现了移动机器人定位与环境特征测量;在机器人视觉处理中,通过融合里程计、惯性传感信息,实现了目标特征的快速搜索及跟踪。 5. 针对机器人趋近与抓取作业,建立了一种新的视觉测量模型,提出了一种基于单个特征点的主动视觉系统自标定算法,提高主动视觉系统标定的简便性及灵活性;在此基础上,构建了立体视觉测量及控制系统,实现视觉引导下的机器人目标趋近及抓取。 总之,本文对视觉检测与特征匹配、视觉及其多传感器系统的标定问题、基于多传感器数据的机器人位姿估计等方面进行了有益的探索。
Other AbstractMobile service robot of much reality application is becoming an active topic in robot °ied. Navigation and localization are the key and fundament for service robot technology. Multi-sensor system combining vision and other sensors is desirable to improve robot localization such as accuracy,real-time and robustness, and of great theory and application value for the improvement and development of service robot. Therefore, multi-sensor based robot navigation and localization have attracted more attention in mobile service robot field in the past years. In this thesis, multi-sensor based localization technology is explored for mobile service robot in unstructured environment. Some relevant topics such as vision detection and feature matching, active vision modelling, multi-sensor calibration, multi-sensor based localization, and vision-guided approaching and grasping are discussed in this thesis. The main contributions of this thesis include following issues: 1. A modified SIFT algorithm is proposed to extract feature and find correspondence in real environment. In this algorithm, state tag and color constrain are introduced to speed the feature extraction and matching, and an epipolar constrain based pseudo algorithm is developed to improve matching accuracy. Meanwhile, a classified Hough Transform is proposed to improve the effectiveness and accuracy of line extraction for rectangular mark. 2. An extrinsic parameter calibration method is proposed for a kind of active stereovision system with independent-rotation cameras to improve convenient of visual system measurement. 3. Motion-based self calibration approach is proposed for the multi-sensor system with odometer, inertial measurement unit and active vision platform in unstructured environment, and make the system calibration more flexible and convenient. 4. Multi-sensor based localization algorithm is developed for mobile service robot. The Kalman filter is introduced to fuse the data captured by odometry and Inertial measured unit and to improve localization's robust. With the correspondences in series images, maximum likelihood motion estimation algorithm is developed to estimate robot's position as well as those features'. The epipola constrain is introduced to speed prediction and track of visual features. 5. A new visual measurement model is developed for robot approaching and grasping. A more flexible translation based calibration approach using single point is proposed for this visual model. A...
shelfnumXWLW1478
Other Identifier200718014628018
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6247
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
王华伟. 基于多传感器信息的移动式服务机器人定位与控制技术[D]. 中国科学院自动化研究所. 中国科学院研究生院,2010.
Files in This Item:
File Name/Size DocType Version Access License
CASIA_20071801462801(8616KB) 暂不开放CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[王华伟]'s Articles
Baidu academic
Similar articles in Baidu academic
[王华伟]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[王华伟]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.