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作者:

Jia, Songmin (Jia, Songmin.) (学者:贾松敏) | Li, Yuchen (Li, Yuchen.) | Wang, Ke (Wang, Ke.) | Li, Xiuzhi (Li, Xiuzhi.) | Guo, Bing (Guo, Bing.)

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摘要:

For large-scale unknown environments, a method of topological node matching based on visual feature is presented, and a local scan matching strategy is integrated to realize map merging for multi-robot system under RTM (robot technology middleware) framework. A main-auxiliary structure model of multiple robots is developed, and an improved SP2ATM algorithm is adopted to incrementally constructing topological map in unknown environments. Based on this, the hierarchical topology structure including SIFT (scale-invariant feature transform) feature information is presented, which is combined with ICP (iterative closest point) algorithm to realize map merging of multi-robot systems. RTM is taken as communication platform to improve the realtime performance, flexibility and robustness of the system. Simulation on USARSim and experimental results in actual environments verify the effectiveness of the proposed method.

关键词:

Hierarchical systems Industrial robots Iterative methods Merging Middleware Multipurpose robots Robot learning Topology

作者机构:

  • [ 1 ] [Jia, Songmin]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 2 ] [Li, Yuchen]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 3 ] [Wang, Ke]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 4 ] [Li, Xiuzhi]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
  • [ 5 ] [Guo, Bing]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China

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来源 :

Robot

ISSN: 1002-0446

年份: 2013

期: 3

卷: 35

页码: 292-298

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 2

ESI高被引论文在榜: 0 展开所有

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