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基于视觉里程计的未知环境中移动机器人导航研究
其他题名Research on Mobile Robots Navagition under Unknown Environments Based on Visual Odometry
刘宏林
学位类型工学博士
导师原魁 ; 李成荣
2011-07-25
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 视觉里程计 点模式匹配 模糊控制 局部路径规划 Mobile Robot Visual Odometry Point Pattern Matching Fuzzy Control Local Path Planning
摘要定位与导航策略是实现移动机器人自主导航的关键问题。本文以运行于室内环境的轮式移动机器人为研究对象,对视觉自定位与未知环境下导航策略两个子问题展开深入研究。本文的主要内容和贡献如下: 室内环境纹理简单且边缘直线较多,针对这一特点,以图像边缘直线连接点作为室内移动机器人自定位的主要视觉特征。实验证明,与常用的角点和团块特征相比,连接点特征在光照条件变化情况下鲁棒性更高。 提出一种基于单应映射关系估计的点模式特征匹配算法。建立特征点集之间的单应映射关系,通过优化迭代获得最优的变换参数,最终求出匹配点集。该算法在匹配中仅考虑特征点位置,与图像灰度对比度无关。将该算法应用于特征点的匹配与跟踪,在灰度对比度均匀的室内天花板图像上的跟踪效果优于KLT特征跟踪方法。 设计实现一种双目视觉里程计,采用分段优化的运动参数估计算法提高定位精度。双目图像序列按照重叠区域分段,段首帧进行三维重建得到空间点坐标的初始估计,后续各帧相对段首帧估计相对运动参数,以反投影误差为优化函数同时对空间点坐标和运动参数进行迭代优化。该算法采用光束平差法实现,取得了良好的运动估计结果。 提出一种适用于室内未知环境下导航控制的反应式模糊控制器。该控制器借鉴人工势场法的基本思想,建立转向角和线速度的控制规则,按照反应式策略驱动机器人以局部最优路径的方式趋向目标。导航过程中,机器人可对周围环境的变化做出快速的反应并获得平滑的运动轨迹和稳定的速度变化。 提出一种虚目标切换方法,解决了反应式导航控制中普遍存在的陷阱问题。该方法以移动机器人与目标相对方向的变化作为陷阱区域判断条件,当检测到陷阱情况时,引入合理的虚拟子目标并面向其运动,直到脱离陷阱状态并恢复实际目标。实验结果证明了这一方法的有效性。 进行室内未知环境下实验,验证了本文提出的视觉里程计自定位方法和未知环境下导航策略。
其他摘要Localization and navigation strategy play an important role in the realization of autonomous mobile robots. In this thesis, we focus on the vision based self-localization and navigation problem of wheeled mobile robots under unknown indoor environment. The main contributions of this thesis can be summarized as follows: Take into consideration that the texture characteristic of indoor environments is simple and there are many edge lines in the image, we proposed a stable feature detector through calculating the intersecting point of edge lines. Experimental results show that intersections are more robust to illumination changes than corners and blob features. A matching method of feature point set was proposed based on the estimation of homographs transformation. This method makes an assumption of homography relationship between the feature point sets, the matching result and the exact homography parameter can be achieved after repeated iteration. This method only involves the position of feature points, and has no relationship with the gray contract of images. Once this method was applied to the feature tracking, its tracking effect is much better than KLT tracking method, especially in inner ceiling images where the grey contract is homogenous. A stereo visual odometry is realized, and the motion parameters are estimated by stage to improve the location accuracy. The image sequence is segmented into several subsequences according to overlapped regions. The initial estimation of spatial point coordinates can be obtained through three-dimensional reconstruction, then the relative motion parameters of the subsequent frames are estimated with respect to the first frame, meanwhile the motion parameters and the locations of spatial points are optimized iteratively by the error of back-projection. This algorithm was realized using bundle adjustment method and achieves satisfied performance. A reactive fuzzy controller is designed for mobile robots navigation in unknown indoor environment. This controller follows the basic concept of artificial potential field method to build fuzzy rules for steering angle and linear velocity, and drives the robot to reach target along the local optimal path according to the reactive navigation strategy. During navigation, the robot can move along a smooth trajectory at a steadily changed speed due to its quick response to the obstacle changes. A virtual target switching approach is proposed to solve local trap situation prob...
馆藏号XWLW1688
其他标识符200618014628004
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/6394
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
刘宏林. 基于视觉里程计的未知环境中移动机器人导航研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2011.
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