A Probabilistic Online Mapping Algorithmfor Teams of Mobile Robots

Sebastian Thrun

We present an efficient probabilistic algorithm for the concurrent mapping and localization problem that arises in mobile robotics. The algorithm addresses the problem in which a team of robots builds a map online, while simultaneously accommodating errors in their odometry. At the core of the algorithm is a technique that combines fast maximum likelihood map growing with a Monte Carlo localizer that uses particle representations. The combination of both yields an online algorithm that can cope with large odometric errors typically found when mapping environments with cycles. The algorithm can be implemented distributedly on multiple robot platforms, enabling a team of robots to cooperatively generate a single map of their environment. Finally, an extension is described for acquiring three-dimensional maps, which capture the structure and visual appearance of indoor environments in 3D.

Paper available in postscript (gzipped) and PDF.

@ARTICLE{Thrun00m,
  AUTHOR         = {Thrun, S.},
  TITLE          = {A Probabilistic Online Mapping Algorithm for 
                    Teams of Mobile Robots},
  JOURNAL        = {International Journal of Robotics Research},
  YEAR           = {2001},
  VOLUME         = {20},
  NUMBER         = {5},
  PAGES          = {335--363}
}