• DocumentCode
    2704978
  • Title

    Research on map merging for multi-robotic system based on RTM

  • Author

    Ke Wang ; Songmin Jia ; Yuchen Li ; Xiuzhi Li ; Bing Guo

  • Author_Institution
    Coll. of Electron. Inf. & Control Eng, Beijing Univ. of Technol., Beijing, China
  • fYear
    2012
  • fDate
    6-8 June 2012
  • Firstpage
    156
  • Lastpage
    161
  • Abstract
    Multi-robotic system is widely used in exploring in large-scale unknown environment and performing the complex tasks. This paper presents a method of local map merging for Multi-robotic system using RTM as communication platform. We integrate Scale-Invariant Feature Transform (SIFT) feature matching information with iterative closest point (ICP) algorithm to realize the local map merging. We use the USARSim as simulation platform to realize topological map and map merging for the environment in which mobile robots moving using the proposed method. The paper details the architecture of the proposed method and gives some experiments to verify the effectiveness.
  • Keywords
    SLAM (robots); control engineering computing; feature extraction; image matching; iterative methods; middleware; mobile robots; multi-robot systems; robot vision; transforms; ICP; RTM; SIFT; USARSim; iterative closest point algorithm; local map merging method; mobile robots; multirobotic system; robot technology middleware; scale-invariant feature transform feature matching information; topological map; Feature extraction; Merging; Mobile robots; Path planning; Robot sensing systems; Topology; ICP; Multi-robotic system; RTM; SIFT; map merging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2012 International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4673-2238-6
  • Electronic_ISBN
    978-1-4673-2236-2
  • Type

    conf

  • DOI
    10.1109/ICInfA.2012.6246800
  • Filename
    6246800