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A Probabilistic On-Line Mapping Algorithm for Teams of Mobile Robots

School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213thrun{at}cs.cmu.edu

An efficient probabilistic algorithm for the concurrent mapping and localization problem that arises in mobile robotics is presented. The algorithm addresses the problem in which a team of robots builds a map on-line while simultaneously accommodating errors in the robots’ 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 on-line algorithm that can cope with large odometric errors typically found when mapping environments with cycles. The algorithm can be implemented in a distributed manner 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 three dimensions.

Key Words: mobile robotics • map acquisition • localization • robotic exploration • multi-robot systems • three-dimensional modeling

The International Journal of Robotics Research, Vol. 20, No. 5, 335-363 (2001)
DOI: 10.1177/02783640122067435


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