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Publication type: Article
Author: Shoudong Huang, Zhan Wang, Gamini Dissanayake, Udo Frese
Title: Iterated D-SLAM Map Joining -- Evaluating its performance in terms of consistency, accuracy and efficiency
Volume: 27
Page(s): 409 – 429
Journal: Autonomous Robots, special issue on Characterizing Mobile Robot Localization and Mapping
Number: 4
Year published: 2009
Abstract: Abstract This paper presents a new map joining al- gorithm and a set of metrics for evaluating the perfor- mance of mapping techniques. The input to the new map joining algorithm is a sequence of local maps containing the feature positions and the final robot pose in a local frame of reference. The output is a global map containing the global po- sitions of all the features but without any robot poses. The algorithm builds on the D-SLAM mapping algo- rithm [1] and uses iterations to improve the estimates in the map joining step. So it is called Iterated D-SLAM Map Joining (I-DMJ). Both simulation and experimen- tal results show that the I-DMJ algorithm is efficient because the information matrix is exactly sparse and the size of the state vector only depends on the number of features. The paper proposes metrics for quantifying the per- formance of different mapping algorithms focused on evaluating their consistency, accuracy and efficiency. The I-DMJ algorithm and a number of existing SLAM algorithms are evaluated using the proposed metrics. The simulation data sets and a preprocessed Victoria Park data set used in this paper are made available to enable interested researchers to compare their mapping algorithms with I-DMJ.
PDF Version: http://www.informatik.uni-bremen.de/agebv/downloads/published/huang_ar_09.pdf
Keywords: SLAM
Status: Reviewed
Last updated: 29. 10. 2009

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