Computer Science Department
School of Computer Science, Carnegie Mellon University


An Online Mapping Algorithm for Teams of Mobile Robots

Sebastian Thrun

October 2000

Keywords: Bayes filters, particle filters, mobile robots, multi-robot systems, probabilistic robotics, robotic exploration, robot mapping

We propose a new probabilistic algorithm for online mapping of unknown environments with teams of robots. 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 an environment 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.

27 pages

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