Fast, on-line learning of globally consistent maps

Duckett, Tom and Marsland, S. and Shapiro, J. (2002) Fast, on-line learning of globally consistent maps. Autonomous Robots, 12 (3). pp. 287-300. ISSN 1573-7527

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Official URL: http://dx.doi.org/10.1023/A%3A1015269615729

Abstract

To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot be used to assign accurate global position information to a map because of cumulative drift errors. This paper introduces a fast, on-line algorithm for learning geometrically consistent maps using only local metric information. The algorithm works by using a relaxation technique to minimize an energy function over many small steps. The approach differs from previous work in that it is computationally cheap, easy to implement and is proven to converge to a globally optimal solution. Experiments are presented in which large, complex environments were successfully mapped by a real robot.

Item Type:Article
Additional Information:To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot be used to assign accurate global position information to a map because of cumulative drift errors. This paper introduces a fast, on-line algorithm for learning geometrically consistent maps using only local metric information. The algorithm works by using a relaxation technique to minimize an energy function over many small steps. The approach differs from previous work in that it is computationally cheap, easy to implement and is proven to converge to a globally optimal solution. Experiments are presented in which large, complex environments were successfully mapped by a real robot.
Keywords:Robotics, Global positioning, Mapping, Navigation
Subjects:H Engineering > H670 Robotics and Cybernetics
Divisions:College of Science > School of Computer Science
ID Code:1207
Deposited By: Bev Jones
Deposited On:20 Sep 2007
Last Modified:18 Jul 2011 16:17

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