A Fast Map Merging Algorithm in the Field of Multirobot SLAMReport as inadecuate

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The Scientific World JournalVolume 2013 2013, Article ID 169635, 8 pages

Research Article

School of Information Science and Engineering, Central South University, Changsha 410075, China

School of Information Engineering, East China Jiaotong University, Nanchang 330013, China

Received 17 August 2013; Accepted 11 September 2013

Academic Editors: C.-C. Chang and F. Yu

Copyright © 2013 Yanli Liu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In recent years, the research on single-robot simultaneous localization and mapping SLAM has made a great success. However, multirobot SLAM faces many challenging problems, including unknown robot poses, unshared map, and unstable communication. In this paper, a map merging algorithm based on virtual robot motion is proposed for multi-robot SLAM. The thinning algorithm is used to construct the skeleton of the grid map’s empty area, and a mobile robot is simulated in one map. The simulated data is used as information sources in the other map to do partial map Monte Carlo localization; if localization succeeds, the relative pose hypotheses between the two maps can be computed easily. We verify these hypotheses using the rendezvous technique and use them as initial values to optimize the estimation by a heuristic random search algorithm.

Author: Yanli Liu, Xiaoping Fan, and Heng Zhang

Source: https://www.hindawi.com/


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