An optimal data association method based on the minimum weighted bipartite perfect matching

被引:0
|
作者
Zhang, Xinzheng [1 ]
Rad, A. B. [2 ]
Huang, Guoquan [3 ]
Wong, Y. K. [4 ]
机构
[1] Jinan Univ, Sch Elect & Informat Engn, Zhuhai, Guangdong, Peoples R China
[2] Simon Fraser Univ, Sch Engn Sceince, Mechatron Syst Engn, 250-13450 102 Ave, Surrey, BC V3T 0A3, Canada
[3] Univ Delaware, Spencer Lab 208, Mech Engn, Newark, DE 19716 USA
[4] Hong Kong Polytech Univ, Dept Elect Engn, Kowloon, Hong Kong, Peoples R China
基金
中国国家自然科学基金;
关键词
Bipartite matching; Data association; Mobile robot; SLAM; SIMULTANEOUS LOCALIZATION; TRACKING; ALGORITHM;
D O I
10.1007/s10514-015-9439-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Data association is an important problem in simultaneous localization and mapping, however, many single frame based methods only provide suboptimal solutions. In this paper an optimal graph theoretic approach is proposed. We formulate the data association as an integer programming (IP) and then prove that it is equivalent to a minimum weight bipartite perfect matching problem. Therefore, optimally solving the bipartite matching problem implies optimally resolving the IP, i.e. the data association problem. We compare the proposed approach with other widely used data association methods. Experimental results validate the effectiveness and accuracy of the proposed approach, and manifest that this graph based data association method can be used for online application.
引用
收藏
页码:77 / 91
页数:15
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