A scheme for robust distributed sensor fusion based on average consensus
Lin Xiao,Stephen Boyd,Sanjay Lall +2 more
- pp 9
TLDR
This work proposes a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihood estimate of the parameters, and shows that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs are jointly connected.Abstract:
We consider a network of distributed sensors, where where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a simple distributed iterative scheme, based on distributed average consensus in the network, to compute the maximum-likelihood estimate of the parameters. This scheme doesn't involve explicit point-to-point message passing or routing; instead, it diffuses information across the network by updating each node's data with a weighted average of its neighbors' data (they maintain the same data structure). At each step, every node can compute a local weighted least-squares estimate, which converges to the global maximum-likelihood solution. This scheme is robust to unreliable communication links. We show that it works in a network with dynamically changing topology, provided that the infinitely occurring communication graphs are jointly connected.read more
Citations
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Journal ArticleDOI
Consensus and Cooperation in Networked Multi-Agent Systems
TL;DR: A theoretical framework for analysis of consensus algorithms for multi-agent networked systems with an emphasis on the role of directed information flow, robustness to changes in network topology due to link/node failures, time-delays, and performance guarantees is provided.
Journal ArticleDOI
Information consensus in multivehicle cooperative control
TL;DR: Theoretical results regarding consensus-seeking under both time invariant and dynamically changing communication topologies are summarized in this paper, where several specific applications of consensus algorithms to multivehicle coordination are described.
Journal ArticleDOI
Distributed average consensus with least-mean-square deviation
TL;DR: The problem of finding the (symmetric) edge weights that result in the least mean-square deviation in steady state is considered and it is shown that this problem can be cast as a convex optimization problem, so the global solution can be found efficiently.
BookDOI
Distributed Control of Robotic Networks: A Mathematical Approach to Motion Coordination Algorithms
TL;DR: This self-contained introduction to the distributed control of robotic networks offers a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation.
Journal ArticleDOI
Diffusion LMS Strategies for Distributed Estimation
TL;DR: This work motivates and proposes new versions of the diffusion LMS algorithm that outperform previous solutions, and provides performance and convergence analysis of the proposed algorithms, together with simulation results comparing with existing techniques.
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