Semi-decentralized convex optimization on SO(3)

Dear Editor, This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on SO(3) over a multi-agent network. Inspired by the distributed subgradient method in [1], the algorithm combines a consensus protocol on SO(3) with a local Riemannian gradient...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2024-06, p.1-3
Main Authors: Li, Weijian, Yi, Peng
Format: Article
Language:English
Online Access:Get full text
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Summary:Dear Editor, This letter proposes a continuous-time semi-decentralized algorithm to minimize a sum of local cost functions on SO(3) over a multi-agent network. Inspired by the distributed subgradient method in [1], the algorithm combines a consensus protocol on SO(3) with a local Riemannian gradient term, but the state of each agent evolves on the nonlinear manifold. In absence of global information for each node, a coordinator is introduced in the communication network to ensure that all agents achieve convergence with consensus. Resorting to Lyapunov approaches, it is shown that the proposed algorithm reaches an optimal solution.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2024.124356