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题名: Data Association for A Hybrid Metric Map Representation
作者: Ma SG(马书根) ; Guo S(郭帅) ; Wang MH(王明辉) ; Li B(李斌)
作者部门: 机器人学研究室
会议名称: IEEE International Conference on Multisensor Fusion and Information Integration (MFI 2012)
会议日期: September 13-15, 2012
会议地点: Hamburg, Germany
会议主办者: IEEE Robotics and Automation Society
会议录: Proceedings of the IEEE International Conference on Multisensor Fusion and Information Integration
会议录出版者: IEEE
会议录出版地: New York, USA
出版日期: 2012
页码: 168-173
收录类别: EI
ISBN号: 978-1-4673-2511-0
摘要: This paper presents an approach to solve the data association problem for a hybrid metric map representation. The hybrid metric map representation uses Voronoi diagram to partition the global map space into a series of local subregions, and then a local dense map is built in each subregion. Finally the global feature map and the local maps make up of the hybrid metric map, which can represent all the observed environment. In the proposed map representation, there exists an important property that global feature map and local maps have clear one-to-one correspondence. Benefited from this property, an identifying rule of the data association based on compatibility testing is proposed. The identifying rule can efficiently reject the wrong data association hypothesis in the application of dense environment. Two experiments validated the efficiency of data association approach and also demonstrated the feasibility of the hybrid metric map presentation.
语种: 英语
产权排序: 1
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/10196
Appears in Collections:机器人学研究室_会议论文

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Recommended Citation:
马书根; 郭帅; 王明辉; 李斌.Data Association for A Hybrid Metric Map Representation.见:IEEE.Proceedings of the IEEE International Conference on Multisensor Fusion and Information Integration,New York, USA,2012,168-173
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文件名: Data Association for A Hybrid Metric Map Representation.pdf
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