Introduces Full-Covariance-Consensus, Partial-Covariance-Consensus, and Mean-Consensus distributed covariance steering methods via non-convex ADMM, with convergence guarantees for the latter two and demonstrations of scalability to thousands of agents.
Convergence of alternating direction method for minimizing sum of two nonconvex functions with linear constraints
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Distributed Covariance Steering via Non-Convex ADMM for Large-Scale Multi-Agent Systems
Introduces Full-Covariance-Consensus, Partial-Covariance-Consensus, and Mean-Consensus distributed covariance steering methods via non-convex ADMM, with convergence guarantees for the latter two and demonstrations of scalability to thousands of agents.