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中文摘要：
数据关联是移动机器人同时定位与建图（SLAM）中的一个难点问题．将经典的单匹配最近邻（ICNN）算法和分枝限界联合匹配（JCBB）算法结合起来，提出了一种基于局部地图的混合数据关联方法．在SLAM数据关联过程中，首先采用ICNN算法在局部地图中进行数据关联，并判断关联结果的正确性，若有错则采用JCBB算法在错误匹配处周围的局部区域内重新进行数据关联。以纠正错误的关联结果．实验结果表明，该方法实时性强，精确度高，适用于不同复杂程度的环境．
英文摘要：
Data association is a difficult problem in Simultaneous Localization and Mapping （SLAM ） for mobile robot. This paper presents a hybrid approach of data association based on local maps by combining the classic Individual Compatibility Nearest Neighbor （ICNN） algorithm and Joint Compatibility Branch and Bound （ JCBB ） algorithm. First, ICNN is used for data association in the local map, and the correctness of the result is determined. If the result is incorrect, JCBB is used to correct the result in the local area around mismatched points. The experimental results show that the performance of the proposed method is satisfactory on the speed and accuracy, even in the complex environments.
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