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21
Algorithms for leader selection in stochastically forced consensus networks
 IEEE Trans. Automat. Control
"... Abstract—We are interested in assigning a prespecified number of nodes as leaders in order to minimize the meansquare deviation from consensus in stochastically forced networks. This problem arises in several applications including control of vehicular formations and localization in sensor networ ..."
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Abstract—We are interested in assigning a prespecified number of nodes as leaders in order to minimize the meansquare deviation from consensus in stochastically forced networks. This problem arises in several applications including control of vehicular formations and localization in sensor networks. For networks with leaders subject to noise, we show that the Boolean constraints (which indicate whether a node is a leader) are the only source of nonconvexity. By relaxing these constraints to their convex hull we obtain a lower bound on the global optimal value. We also use a simple but efficient greedy algorithm to identify leaders and to compute an upper bound. For networks with leaders that perfectly follow their desired trajectories, we identify an additional source of nonconvexity in the form of a rank constraint. Removal of the rank constraint and relaxation of the Boolean constraints yields a semidefinite program for which we develop a customized algorithm wellsuited for large networks. Several examples ranging from regular lattices to random graphs are provided to illustrate the effectiveness of the developed algorithms. Index Terms—Alternating direction method of multipliers (ADMMs), consensus networks, convex optimization, convex relaxations, greedy algorithm, leader selection, performance bounds, semidefinite programming (SDP), sensor selection, variance amplification. I.
Symmetrization for quantum networks: a continuoustime approach,” quantph, arXiv 1403.3582
, 2014
"... AbstractIn this paper we propose a continuoustime, dissipative Markov dynamics that asymptotically drives a network of ndimensional quantum systems to the set of states that are invariant under the action of the subsystem permutation group. The Lindbladtype generator of the dynamics is built wi ..."
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Cited by 4 (2 self)
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AbstractIn this paper we propose a continuoustime, dissipative Markov dynamics that asymptotically drives a network of ndimensional quantum systems to the set of states that are invariant under the action of the subsystem permutation group. The Lindbladtype generator of the dynamics is built with twobody subsystem swap operators, thus satisfying locality constraints, and preserve symmetric observables. The potential of the proposed generator in combination with local control and measurement is illustrated with two applications: generation of a global pure state and estimation of the network size.
on UF performance
 Water Res
"... of leaderfollower networks in directed trees and lattices ..."
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of leaderfollower networks in directed trees and lattices
Visual Feedback Leaderfollowing Pose Synchronization: Convergence Analysis
"... Abstract — This paper investigates visual feedback pose synchronization on SE(3) in leaderfollower type visibility structures. After defining visual robotic networks to be controlled, we propose a visual feedback pose synchronization law combining a visionbased observer with the pose synchroniza ..."
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Abstract — This paper investigates visual feedback pose synchronization on SE(3) in leaderfollower type visibility structures. After defining visual robotic networks to be controlled, we propose a visual feedback pose synchronization law combining a visionbased observer with the pose synchronization law presented in our previous works. We then prove that the visual robotic network with the control law achieves visual feedback pose synchronization in the absence of communication or any other measurements of the states. Finally, the validity of the proposed control law is demonstrated through experiments. I.
1 An asynchronous consensusbased algorithm for estimation from noisy relative measurements
"... Abstract—In this work we address the problem of optimal estimating the position of each agent in a network from relative noisy vectorial distances with its neighbors. Although the problem can be cast as a standard leastsquares problem, the main challenge is to devise scalable algorithms that allow ..."
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Cited by 2 (1 self)
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Abstract—In this work we address the problem of optimal estimating the position of each agent in a network from relative noisy vectorial distances with its neighbors. Although the problem can be cast as a standard leastsquares problem, the main challenge is to devise scalable algorithms that allow each agent to estimate its own position by means of only local communication and bounded complexity, independently of the network size and topology. We propose a consensusbased algorithm with the use of local memory variables which allows asynchronous implementation, has guaranteed exponential convergence to the optimal solution under mild deterministic and randomised communication protocols, and requires minimal packet transmission. In the randomized scenario we then study the rate of convergence in expectation of the estimation error and we argue that it can be used to obtain upper and lower bound for the rate of converge in mean square. In particular, we show that for regular graphs the convergence rate in expectation is reduced by a factor N, which is the number of nodes, which is the same asymptotic degradation of memoryless asynchronous consensus algorithms. Additionally, we show that the asynchronous implementation is also robust to delays and communication failures. We finally complement the analytical results with some numerical simulations comparing the proposed strategy with other algorithms which have been recently proposed in the literature. Index Terms—Wireless sensor networks, distributed localization algorithms, consensus algorithms I.
A New Perspective on Gossip Iterations: from Symmetrization to Quantum Consensus*
"... Abstract — This paper extends the gossip algorithm, widely studied in the literature on distributed computing and control algorithms, to networks of quantum systems. In doing so, we reinterpret the classical algorithm and the average consensus task as a symmetrization problem with respect to the act ..."
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Abstract — This paper extends the gossip algorithm, widely studied in the literature on distributed computing and control algorithms, to networks of quantum systems. In doing so, we reinterpret the classical algorithm and the average consensus task as a symmetrization problem with respect to the action of the permutation group. This allows us to extend in a natural way the gossip consensus algorithm to the quantum setting and prove its convergence properties to symmetric states while preserving the expectation of permutationinvariant global observables. I.
Structure identification and optimal design of largescale networks of dynamical systems
, 2012
"... ..."
Autonomous calibration algorithms for planar networks of cameras
 Automatica
"... Abstract This paper deals with the problem of the angular calibration for a network of cameras, namely the problem of estimating a common orientation reference frame. In the proposed setup each camera obtains noisy measurements of its relative orientation with respect to some other cameras. The se ..."
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Abstract This paper deals with the problem of the angular calibration for a network of cameras, namely the problem of estimating a common orientation reference frame. In the proposed setup each camera obtains noisy measurements of its relative orientation with respect to some other cameras. The set of measurements can be described by a graph having the cameras as nodes and having an edge between two cameras if a relative orientation measurement is available. The paper proposes a novel twostep algorithm based on a choice of a basis for the set of graph cycles. The first step consists in computing a set of integer numbers, which provides a first rough estimate of the orientations. The second step exploits this information to build up a suitable quadratic minimization problem. Two actual implementations, corresponding to two different basis of cycles, are described and compared in terms of the worstcase scenario. Finally, through numerical simulations the algorithm is compared with another algorithm proposed in the literature for solving the same problem.
An
"... exponentialrate consensusbased algorithms for estimation from relative measurements: implementation and performance analysis ..."
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exponentialrate consensusbased algorithms for estimation from relative measurements: implementation and performance analysis