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Distributed synchronization of euclidean transformations with guaranteed convergence
Thunberg, Johan; Goncalves, Jorge; Bernard, Florian
2017In 56th IEEE Conference on Decision and Control
Peer reviewed
 

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Keywords :
pose averaging; distributed optimization; multi-agent systems
Abstract :
[en] This paper addresses synchronization of Euclidean transformations over graphs. Synchronization in this context, unlike rendezvous or consensus, means that composite transformations over loops in the graph are equal to the identity. Given a set of non-synchronized transformations, the problem at hand is to find a set of synchronized transformations approximating well the non-synchronized transformations. This is formulated as a nonlinear least-squares optimization problem. We present a distributed synchronization algorithm that converges to the optimal solution to an approximation of the optimization problem. This approximation stems from a spectral relaxation of the rotational part on the one hand and from a separation between the rotations and the translations on the other. The method can be used to distributively improve the measurements obtained in sensor networks such as networks of cameras where pairwise relative transformations are measured. The convergence of the method is verified in numerical simulations.
Disciplines :
Electrical & electronics engineering
Author, co-author :
Thunberg, Johan ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Goncalves, Jorge ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB)
Bernard, Florian;  Saarland Informatics Campus > Max Planck Institute for Informatics
External co-authors :
yes
Language :
English
Title :
Distributed synchronization of euclidean transformations with guaranteed convergence
Publication date :
December 2017
Event name :
56th IEEE Conference on Decision and Control
Event organizer :
IEEE
Event place :
Melbourne, Australia
Event date :
from 12-12-2017 to 15-12-2017
Audience :
International
Main work title :
56th IEEE Conference on Decision and Control
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Funders :
FNR - Fonds National de la Recherche [LU]
Available on ORBilu :
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