• DocumentCode
    109250
  • Title

    Group Mapping: A Topological Approach to Map Merging for Multiple Robots

  • Author

    Saeedi, Saeed ; Paull, Liam ; Trentini, Michael ; Seto, Mae ; Li, Huaqing

  • Author_Institution
    COBRA Group, Univ. of New Brunswick, Fredericton, NB, Canada
  • Volume
    21
  • Issue
    2
  • fYear
    2014
  • fDate
    Jun-14
  • Firstpage
    60
  • Lastpage
    72
  • Abstract
    Simultaneous localization and mapping (SLAM) is required for mobile robots to be able to explore a prior unknown space without a global positioning reference. Multiple robots can achieve exploration tasks more quickly but with added complexity. A useful representation of the map for SLAM purposes is as an occupancy grid map. In the most general case of multiple-robot SLAM, occupancy grid maps from multiple agents must be merged in real time without any prior knowledge of their relative transformation. In addition, the probabilistic information of the maps must be accounted for and fused accordingly. In this article, the generalized Voronoi diagram (GVD) is extended to encapsulate the probabilistic information encoded in the occupancy grid map. The new construct called the probabilistic GVD (PGVD) operates directly on occupancy grid maps and is used to determine the relative transformation between maps and fuse them. This approach has three major benefits over past methods: 1) it is effective at finding relative transformations quickly and reliably, 2) the uncertainty associated with transformations used to fuse the maps is accounted for, and 3) the parts of the maps that are more certain are preferentially used in the merging process because of the probabilistic nature of the PGVD.
  • Keywords
    SLAM (robots); computational geometry; mobile robots; multi-robot systems; probability; PGVD; generalized Voronoi diagram; global positioning reference; group mapping; merging process; mobile robots; multiple-robot SLAM; occupancy grid map; probabilistic GVD; probabilistic information; simultaneous localization and mapping; topological approach; Mobile radio mobility management; Mobile robots; Probabilistic logic; Simultaneous localization and mapping;
  • fLanguage
    English
  • Journal_Title
    Robotics & Automation Magazine, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9932
  • Type

    jour

  • DOI
    10.1109/MRA.2014.2304091
  • Filename
    6811207