Fully Distributed Scalable Smoothing and Mapping with Robust Multi-robot Data Association

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1853/44686

Title: Fully Distributed Scalable Smoothing and Mapping with Robust Multi-robot Data Association
Author: Cunningham, Alexander ; Wurm, Kai M. ; Burgard, Wolfram ; Dellaert, Frank
Abstract: In this paper we focus on the multi-robot perception problem, and present an experimentally validated endto- end multi-robot mapping framework, enabling individual robots in a team to see beyond their individual sensor horizons. The inference part of our system is the DDF-SAM algorithm [1], which provides a decentralized communication and inference scheme, but did not address the crucial issue of data association. One key contribution is a novel, RANSAC-based, approach for performing the between-robot data associations and initialization of relative frames of reference. We demonstrate this system with both data collected from real robot experiments, as well as in a large scale simulated experiment demonstrating the scalability of the proposed approach.
Description: ©2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. Presented at the 2012 IEEE International Conference on Robotics and Automation (ICRA), 14-18 May 2012, St Paul, MN. DOI: 10.1109/ICRA.2012.6225356
Type: Proceedings
URI: http://hdl.handle.net/1853/44686
ISSN: 1050-4729
Citation: Cunningham, A.; Wurm, K.M.; Burgard, W.; & Dellaert, F. (2012). "Fully Distributed Scalable Smoothing and Mapping with Robust Multi-robot Data Association". Proceedings of the IEEE International Conference on Robotics and Automation (ICRA 2012), 14-18 May 2012, pp.1093-1100.
Date: 2012-05
Contributor: Georgia Institute of Technology. College of Computing
Georgia Institute of Technology. Center for Robotics and Intelligent Machines
Universität Freiburg im Breisgau. Institut für Informatik
Publisher: Georgia Institute of Technology
Institute of Electrical and Electronics Engineers
Subject: Data association
DDF-SAM algorithm
Decentralized communication
Inference scheme
Multi-robot mapping system
Multi-robot perception

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