Efficient and Reliable Monte Carlo Localization with Thinning Edges

被引：2

作者：

Kwon, Tae-Bum ^{[1
]}

Yang, Ju-Ho ^{[1
,2
]}

Song, Jae-Bok ^{[1
]}

机构：

[1] Korea Univ, Sch Mech Engn, Seoul 136713, South Korea

[2] Mando Corp, Seoul, South Korea

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2010年 / 8卷 / 02期

关键词：

Kidnapped robot problems; Monte Carlo localization; particle filters; thinning edges; MOBILE ROBOT LOCALIZATION;

D O I：

10.1007/s12555-010-0219-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The global convergence of MCL is time-consuming because of a large number of random samples. Moreover, its success is not guaranteed at all times. This paper presents a novel approach to reduce the number of samples of MCL and one heuristic approach to detect localization failure using thinning edges extracted in real time. Random samples are drawn only around the neighborhood of the thinning edges rather than over the entire free space and localization quality is estimated through the probabilistic analysis of samples added around the thinning edges. A series of experiments verified the performance of the proposed scheme.

引用

页码：328 / 338

页数：11

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