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浙江大学学报(工学版)
J4  2012, Vol. 46 Issue (9): 1572-1579    DOI: 10.3785/j.issn.1008-973X.2012.09.004
无线电电子学、电信技术     
基于不确定性分析的视觉里程计优化
欧阳柳,徐进,龚小谨,刘济林
浙江大学 信息与电子工程学系,浙江 杭州 310027
Optimization of visual odometry based on uncertainty analysis
OUYANG Liu, XU Jin, GONG Xiao-jin, LIU Ji-lin
Department of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
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摘要：

通过推导视觉里程计中运动参数估计的不确定度,分析了视觉里程计的定位精度.采用矩阵扰动理论,准确计算了基于最小二乘法运动估计算法给出的6个自由度运动参数估计的不确定性,此方法的计算复杂度为O(1).采用扩展卡尔曼滤波器对视觉里程计和惯性测量单元数据进行融合优化,获得了更加准确的机器人定位和姿态信息.融合实验结果表明,融合后的闭合误差比单一的视觉里程计闭合误差减少近49.5%.
Abstract:

The accuracy of visual odometry (VO) was analyzed by deriving the uncertainty of the VO's motion estimation. The proposed uncertainty analysis method, based on matrix perturbation theory, estimates the uncertainty of motion parameters in six degrees of freedom (DOF) those are computed by least-squares-method. The computational complexity is O(1). Then an extended Kalman filter (EKF) is used for fusing VO and inertial measurement unit (IMU) data based on above analysis results to obtain more accurate position and attitude values of the robot. Experimental results show that the closed-loop error is reduced by 49.5% at most when the uncertainty data fusion with IMU is applied to VO.
出版日期: 2012-09-01
:  TP 242.6  
基金资助:

国家自然科学基金资助项目(60534070，90820306，61001171).
通讯作者: 龚小谨，女，讲师.     E-mail: gongxj@zju.edu.cn
作者简介: 欧阳柳（1985-），男，硕士生，从事机器视觉研究. E-mail：liuoy1025@gmail.com
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引用本文:

欧阳柳,徐进,龚小谨,刘济林. 基于不确定性分析的视觉里程计优化[J]. J4, 2012, 46(9): 1572-1579.

OUYANG Liu, XU Jin, GONG Xiao-jin, LIU Ji-lin. Optimization of visual odometry based on uncertainty analysis. J4, 2012, 46(9): 1572-1579.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2012.09.004    或    http://www.zjujournals.com/eng/CN/Y2012/V46/I9/1572

［1］ MAIMONE M, CHENG Y, MATTHIES L. Two years of visual odometry on the Mars Exploration Rovers ［J］. Journal of Field Robotics, 2007, 24(3): 169-186.
［2］ YOUNG G S J, CHELLAPPA R. Statisticalanalysis of inherent ambiguities in recovering 3D Motion from a noisy flow field ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1992, 14(10): 995-1013．
［3］ CHOWDHURY A R, CHELLAPPA R. Statistical error propagation in 3D Modeling from monocular video ［C］ ∥Computer Vision and Pattern Recognition Workshop. Los Alamitos: IEEE Computer Society, 2003: 89-89.
［4］ 吴功伟. 立体视觉里程计的关键技术研究［D］. 杭州,浙江大学, 2007.
［5］ 彭勃, 周文晖, 刘济林. 基于Harris角点检测的立体视觉里程计［J］. 兵工学报,2007,28(12)：1498-1502．
PENG Bo, ZHOU Wenhui, LIU Jilin. Harris corner detectionbased stereo visual odometry ［J］. Acta Armamentarii, 2007,28(12)：1498-1502．
［6］ 李智, 周文晖, 刘济林. 动态场景下基于视差空间的立体视觉里程计［J］. 浙江大学学报：工学版,2008,42(10)：1661-1665．
LI Zhi, ZHOU Wenhui, LIU Jilin. Stereo visual odometry from disparity space in dynamic environments ［J］. Journal of Zhejiang University: Engineering Science, 2008,42(10)：1661-1665．
［7］ HORN B K P. Closedform solution of absolute orientation using unit quaternions ［J］. Journal of the Optical Society of America aOptics Image Science and Vision, 1987, 4(4): 629-642.
［8］ FISCHLER M A, BOLLES R C. Random sample consensus  a paradigm for modelfitting with applications to imageanalysis and automated cartography ［J］. Communications of the ACM, 1981, 24(6): 381-395．
［9］ MATTHIES L, SHAFER S A. Error modeling in stereo navigation ［J］. IEEE Journal of Robotics and Automation, 1987, 3(3): 239-248．
［10］ ZHANG P, GU J, MILIOS E E. Registration uncertainty for robot selflocalization in 3D ［C］∥Proceedings of The 2nd Canadian Conference on Computer and Robot Vision. Victoria, BC, Canada: IEEE Computer Society, 2005: 490-497．
［11］ MORENO F, BLANCO J, GONZ LEZ J. An efficient closedform solution to probabilistic 6D visual odometry for a stereo camera［C］∥ Advanced Concepts for Intelligent Vision Systems. Berlin/ Heidelberg: Springer, 2007: 932-942．
［12］ LOWE D G. Distinctive image features from scaleinvariant keypoints ［J］. International Journal of Computer Vision, 2004, 60(2): 91-110．
［13］ ZEISL B, GEORGEL P, SCHWEIGER F, et al. Estimation of location uncertainty for scale invariant feature points ［C］ ∥ Proceedings of British Machine Vision Conference (BMVC). London: British Machine Vision Association, 2009．
［14］ ARRAS K O. An introduction to error propagation: Derivation, meaning and examples of Cy=Fx Cx Fx′ ［R］. \
[S.l.\]:Swiss Federal Institute of Technology Lausanne, 1998．
［15］ CHEN S. Matrix perturbation theory in structural dynamic design ［M］.Beijing: Science Press, 2007．
［16］ RONNBACK S. Development of a INS/GPS navigation loop for an UAV ［D］. Lulea: Lulea Tekniska University of Technology, 2000.
［17］ SIMON D. Optimal state estimation: Kalman Hinfinity, and nonlinear approaches ［M］. New York: Wiley Interscience, 2006.
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