000101174 001__ 101174
000101174 005__ 20210407143739.0
000101174 0247_ $$2doi$$a10.1109/CDC40024.2019.9029792
000101174 0248_ $$2sideral$$a122911
000101174 037__ $$aART-2019-122911
000101174 041__ $$aeng
000101174 100__ $$aCristofalo, E.
000101174 245__ $$aConsensus-based Distributed 3D Pose Estimation with Noisy Relative Measurements
000101174 260__ $$c2019
000101174 5060_ $$aAccess copy available to the general public$$fUnrestricted
000101174 5203_ $$aIn this paper we study consensus-based tributed estimation algorithms for estimating the global translation and rotation of each agent in a multi-agent system. We consider the case in which agents measure the noisy relative pose of their neighbors and communicate their estimates to agree upon the global poses in an arbitrary reference frame. The main contribution of this paper is a formal analysis that provides necessary and sufficient conditions to guarantee stability (in a Lyapunov sense) of the estimation system''s equilibria. We prove that consensus-based algorithms will diverge, even with arbitrarily small inconsistencies on the relative pose, unless the measurements satisfy minimum consistency conditions. We determine these consistency conditions for translation-only, rotation-only, and combined 3D pose estimation using the axis-angle rotation representation over undirected graphs. We then propose an initialization method based on these conditions that guarantees consistency and stability of the estimator''s equilibria. Additionally, we show that existing distributed estimation methods in literature exploit these conditions to guarantee convergence of their algorithms. Lastly, we perform simulations that show convergence when consistency conditions hold and divergence when they do not.
000101174 536__ $$9info:eu-repo/grantAgreement/ES/DGA/T04-FSE$$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/PGC2018-098817-A-I00
000101174 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000101174 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000101174 700__ $$0(orcid)0000-0002-5176-3767$$aMontijano, E.$$uUniversidad de Zaragoza
000101174 700__ $$aSchwager, M.
000101174 7102_ $$15007$$2520$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Ingen.Sistemas y Automát.
000101174 773__ $$g2019-December (2019), 2646-2653$$pProc. IEEE Conf. Decis. Control$$tProceedings of the IEEE Conference on Decision & Control$$x0743-1546
000101174 8564_ $$s830370$$uhttps://zaguan.unizar.es/record/101174/files/texto_completo.pdf$$yPostprint
000101174 8564_ $$s3101056$$uhttps://zaguan.unizar.es/record/101174/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000101174 909CO $$ooai:zaguan.unizar.es:101174$$particulos$$pdriver
000101174 951__ $$a2021-04-07-12:58:04
000101174 980__ $$aARTICLE