全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

基于假设检验的室内环境多特征检测方法

DOI: 10.3969/j.issn.1006-7043.201310040

Keywords: 室内环境, 假设检验, 特征, 机器人, 多特征检测, 最小二乘法

Full-Text   Cite this paper   Add to My Lib

Abstract:

为解决移动机器人室内环境特征提取适应性问题,提出了基于假设检验的室内多特征检测方法.该方法首先构建多维数据空间.通过定义距离概率函数,结合χ2假设检验理论,在估计采样点的特征区域基础上,通过极值法进行角点检测,然后采用约束最小二乘法提取线段与圆弧特征.最后,实验验证了该方法可以提取较稳定的角点、线段以及圆弧特征,同时特征的识别率达到94%以上.

References

[1]  LEONARD J, HOW J, TELLER S, et a1.A perception-driven autonomous urban vehicle[J]. Journal of Field Robotics, 2008, 25(10): 727-774.
[2]  杨明, 王宏. 基于激光雷达的移动机器人位姿估计方法综述[J]. 机器人,2002, 24(2): 177-183.YANG Ming, WANG Hong. Overview of laser radar based pose estimation for mobile robots[J]. Robot,2002, 24(2): 177-183.
[3]  MINGUEZ J, MONTESANO L, LAMIRAUX F. Metric-based iterative closest point scan matching for sensor displacement estimation[J]. IEEE Transactions on Robotics, 2006, 22(5): 1047-1054.
[4]  ELFES A. Sonar-based real-world mapping and navigation[J]. IEEE Journal of Robotics & Automation, 1987(6): 249-265.
[5]  LINGEMANN K, SURMANN H, NUCHTER A, et al. Indoor and outdoor location for fast mobile robots[C]// Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’04).Sendai, Japan, 2004: 2185-2190.
[6]  KNIERIEMEN T, Von PUTTKAMER E, ROTH J. Extracting lines, circular segments and clusters from radar pictures in real time for an autonomous mobile robot[C]//IEEE Workshop on Real Time Systems. Piscataway, USA,1991: 127-135.
[7]  WEBER J, J?RG K W, PUTTKAMER E. APR-global scan matching using anchor point relationships[C]//6th Int Conf Intelligent Autonomous Systems. Venice, Italy, 2000: 471-478.
[8]  YAN R, WU J, WANG W, et al. Natural corners extraction algorithm in 2D unknown indoor environment with laser sensor[C]//2012 12th International Conference on Control, Automation and Systems (ICCAS). JeJu, Island,2012: 983-987.
[9]  BORGES G A, ALDON M J. A split-and-merge segmentation algorithm for line extraction in 2D range images [C] //Rroceedings of 15th International Conference on Pattern Recognition. Los Alamitos: IEEE Computer Society, 2000: 441-444.
[10]  NOYER J C, LHERBIER R, FORTIN B. Automatic feature extraction in laser rangefinder data using geometric invariance[C]// 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals, Systems and Computers (ASILOMAR). Pacific Grove, CA, 2010: 199-203.
[11]  AN S Y, KANG J G, LEE L K, et al. SLAM with salient line feature extraction in indoor environments[C]// 2010 11th International Conference on Control Automation Robotics & Vision (ICARCV). Singapore,2010: 410-416.
[12]  JAFRI S R U N, ZHAO L, CHANDIO A A, et al. Laser only feature based multi robot SLAM[C]// 2012 12th International Conference on Control Automation Robotics & Vision (ICARCV). Guangzhou, 2012: 1012-1017.
[13]  FENG X, GUO S, LI X, et al. Robust mobile robot localization by tracking natural landmarks[C]//International Conference on Artificial Intelligence and Computational Intelligence. Berlin: Springer, 2009: 278-287.
[14]  LIU M, LEI X, ZHANG S, et al. Natural landmark extraction in 2D laser data based on local curvature scale for mobile robot navigation[C]// 2010 IEEE International Conference on Robotics and Biomimetics (ROBIO). Tianjin, 2010: 525-530.
[15]  DIOSI A, KLEEMAN L. Laser scan matching in polar coordinates with application to SLAM[C]//Proceedings of 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems. Edmonton, Canada, 2005: 3317-3322.

Full-Text

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133