A visual based extended Monte Carlo localization for autonomous mobile robots

被引：3
作者：
Shang, Wen [1 ,2 ]
Sun, Dong [2 ]
Ma, Xudong [3 ]
Dai, Xianzhong [3 ]
机构：
[1] Suzhou Res Inst CityU, Dept Mfg Engg & Engg Management, Suzhou, Peoples R China
[2] City Univ Hong Kong, Dept Mfg Engg & Engg Management, Kowloon, Hong Kong, Peoples R China
[3] Southeast Univ, Dept Automat Control, Nanjing, Peoples R China
来源：
2006 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, VOLS 1-12 | 2006年
关键词：
extended MCL; mobile robots; localization; visual features;
D O I：
10.1109/IROS.2006.281769
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
As a probabilistic localization algorithm, Monte Carlo localization (MCL) method has been widely used for mobile robot localization over the past decade. In this paper, an extended MCL method (EMCL) is developed by incorporating two different resampling processes, namely importance resampling and sensor-based resampling, to conventional MCL for improvement of localization performance. Different resampling processes are utilized based on a matching of sample distribution and observations. Two additional processes for validating over-convergence and uniformity are introduced for examination of such matching. A visual based EMCL is further implemented using a triangulation-based resampling from visual features recognized by Bayesian networks. Experiments are conducted to demonstrate the validity of the proposed approach.
引用
收藏
页码：928 / +
页数：2
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