NDLI: Multi-robot simultaneous localization and mapping using D-SLAM framework

Content Provider	IEEE Xplore Digital Library
Author	Zhan Wang Shoudong Huang Dissanayake, G.
Copyright Year	2007
Description	Author affiliation: Univ. of Technol., Sydney (Zhan Wang; Shoudong Huang; Dissanayake, G.)
Abstract	This paper presents an algorithm for the multi-robot simultaneous localization and mapping (SLAM) problem with the robot initial locations completely unknown. Each robot builds its own local map using the traditional extended Kalman filter (EKF) SLAM algorithm. We provide a new method to fuse the local maps into a jointly maintained global map by first transforming the local map state estimate into relative location information and then conducting the fusion using the decoupled SLAM (D-SLAM) framework (Wang et al., 2007). An efficient algorithm to find the map overlap and corresponding beacons across the maps is developed from a point feature based medical image registration method and the joint compatibility test. By adding the robot initial pose of each local map into the global map state, the algorithm shows valuable properties. Simulation results are provided to illustrate the effectiveness of the algorithm.
Starting Page	317
Ending Page	322
File Size	355099
Page Count	6
File Format	PDF
ISBN	9781424415014
DOI	10.1109/ISSNIP.2007.4496863
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-12-03
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image registration Medical robotics Multi-robot SLAM Extended Information Filter Covariance matrix Map fusion Orbital robotics Simultaneous localization and mapping Robot kinematics Image Registration Information filters Medical tests Decoupled SLAM State estimation Biomedical imaging
Content Type	Text
Resource Type	Article

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