Vision-based extended Monte Carlo localization for mobile robot

被引：0
|
作者：
Ma, Xudong [1 ]
Dai, Xianzhong [1 ]
Shang, Wen [1 ]
机构：
[1] SE Univ, Dept Automat Control, Nanjing, Jiangsu Prov, Peoples R China
来源：
2005 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATIONS, VOLS 1-4, CONFERENCE PROCEEDINGS | 2005年
关键词：
mobile robot; Monte Carlo Localization; triangulation-based; Bayesian networks; networked robotic system;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Extended Monte Carlo localization, augmentation of conventional Monte Carlo Localization (MCL) appropriately with triangulation-based re-sampling, is proposed in this paper in order to increase computational efficiency and avoid over-convergence. The over-convergence and uniformity validations are used to verify correspondence between sample distribution and sensor information for the integration of different resampling processes. Vision-based extended MCL is realized that is applied to a networked robotic system, in which Bayesian networks are introduced to recognize polyhedron features in office environments for localization. Experimental results demonstrate the validity of the approach.
引用
收藏
页码：1831 / 1836
页数：6
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