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Data Association for A Hybrid Metric Map Representation
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
会议录名称Proceedings of the IEEE International Conference on Multisensor Fusion and Information Integration
出版者IEEE
出版地New York, USA
2012
页码168-173
收录类别EI
EI收录号20125015785014
产权排序1
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
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/10196
专题机器人学研究室
作者单位1.Department of Robotics, Ritsumeikan University, 1-1-1 Noji-Higashi, Kusatsu-Shi, Shiga 525-8577, Japan
2.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, 110016, China
3.Graduate School of the Chinese Academy of Sciences, Beijing 100039, China
推荐引用方式
GB/T 7714
Ma SG,Guo S,Wang MH,et al. Data Association for A Hybrid Metric Map Representation[C]//IEEE Robotics and Automation Society. New York, USA:IEEE,2012:168-173.
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