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397
Distributed Kalman filtering based on consensus strategies
, 2007
"... In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own measurements and estimates from its neighbors. Estimation is performed via a two stage strategy, the first being a Kalman ..."
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Cited by 56 (1 self)
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In this paper, we consider the problem of estimating the state of a dynamical system from distributed noisy measurements. Each agent constructs a local estimate based on its own measurements and estimates from its neighbors. Estimation is performed via a two stage strategy, the first being a Kalmanlike measurement update which does not require communication, and the second being an estimate fusion using a consensus matrix. In particular we study the interaction between the consensus matrix, the number of messages exchanged per sampling time, and the Kalman gain. We prove that optimizing the consensus matrix for fastest convergence and using the centralized optimal gain is not necessarily the optimal strategy if the number of exchanged messages per sampling time is small. Moreover, we showed that although the joint optimization of the consensus matrix and the Kalman gain is in general a nonconvex problem, it is possible to compute them under some important scenarios. We also provide some numerical examples to clarify some of the analytical results and compare them with alternative estimation strategies.
AVERAGE CONSENSUS WITH PACKET DROP COMMUNICATION
, 2009
"... Average consensus consists in the problem of determining the average of some quantities by means of a distributed algorithm. It is a simple instance of problems arising when designing estimation algorithms operating on data produced by sensor networks. Simple solutions based on linear estimation a ..."
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Cited by 55 (8 self)
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Average consensus consists in the problem of determining the average of some quantities by means of a distributed algorithm. It is a simple instance of problems arising when designing estimation algorithms operating on data produced by sensor networks. Simple solutions based on linear estimation algorithms have already been proposed in the literature and their performance has been analyzed in detail. If the communication links which allow the data exchange between the sensors have some loss, then the estimation performance will degrade. In this contribution the performance degradation due to this data loss is evaluated.
Distributed average consensus with dithered quantization
 the IEEE Transactions of Signal Processing
, 2008
"... In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distribut ..."
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Cited by 55 (2 self)
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In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distributed algorithm in which the nodes utilize probabilistically quantized information, i.e., dithered quantization, to communicate with each other. The algorithm we develop is a dynamical system that generates sequences achieving a consensus at one of the quantization values almost surely. In addition, we show that the expected value of the consensus is equal to the average of the original sensor data. We derive an upper bound on the mean square error performance of the probabilistically quantized distributed averaging (PQDA). Moreover, we show that the convergence of the PQDA is monotonic by studying the evolution of the minimumlength interval containing the node values. We reveal that the length of this interval is a monotonically non–increasing function with limit zero. We also demonstrate that all the node values, in the worst case, converge to the final two quantization bins at the same rate as standard unquantized consensus. Finally, we report the results of simulations conducted to evaluate the behavior and the effectiveness of the proposed algorithm in various scenarios.
Multiagent Kalman consensus with relative uncertainty
 In Proceedings of the 2005 American Control Conference (ACC
, 2005
"... Abstract — In this paper, we propose discretetime and continuoustime consensus update schemes motivated by the discretetime and continuoustime Kalman filters. With certainty information encoded into each agent, the proposed consensus schemes explicitly account for relative confidence / reliabil ..."
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Cited by 55 (6 self)
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Abstract — In this paper, we propose discretetime and continuoustime consensus update schemes motivated by the discretetime and continuoustime Kalman filters. With certainty information encoded into each agent, the proposed consensus schemes explicitly account for relative confidence / reliability of information states from each agent in the team. We show mild sufficient conditions under which consensus can be achieved using the proposed consensus schemes in the presence of switching interaction topologies. I.
Cooperative forest fire surveillance using a team of small unmanned air vehicles
 International Journal of Systems Sciences
, 2006
"... The objective of this paper is to explore the feasibility of using multiple lowaltitude, short endurance (LASE) unmanned air vehicles (UAVs) to cooperatively monitor and track the propagation of large forest fires. A realtime algorithm is described for tracking the perimeter of fires with an onbo ..."
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Cited by 53 (3 self)
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The objective of this paper is to explore the feasibility of using multiple lowaltitude, short endurance (LASE) unmanned air vehicles (UAVs) to cooperatively monitor and track the propagation of large forest fires. A realtime algorithm is described for tracking the perimeter of fires with an onboard infrared sensor. Using this algorithm, we develop a decentralized multipleUAV approach to monitoring the perimeter of a fire. The UAVs are assumed to have limited communication and sensing range. The effectiveness of the approach is demonstrated in simulation using a six degreeoffreedom dynamic model for the UAV and a numerical propagation model for the forest fire. Salient features of the approach include the ability to monitor a changing fire perimeter, the ability to systematically add and remove UAVs from the team, and the ability to supply timecritical information to fire fighters. 1
Distributed average consensus using probabilistic quantization
, 2007
"... In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distribut ..."
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Cited by 53 (7 self)
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In this paper, we develop algorithms for distributed computation of averages of the node data over networks with bandwidth/power constraints or large volumes of data. Distributed averaging algorithms fail to achieve consensus when deterministic uniform quantization is adopted. We propose a distributed algorithm in which the nodes utilize probabilistically quantized information to communicate with each other. The algorithm we develop is a dynamical system that generates sequences achieving a consensus, which is one of the quantization values. In addition, we show that the expected value of the consensus is equal to the average of the original sensor data. We report the results of simulations conducted to evaluate the behavior and the effectiveness of the proposed algorithm in various scenarios. Index Terms — Distributed algorithms, average consensus, sensor networks
Multivehicle consensus with a timevarying reference state
, 2007
"... In this paper, we study the consensus problem in multivehicle systems, where the information states of all vehicles approach a timevarying reference state under the condition that only a portion of the vehicles (e.g., the unique team leader) have access to the reference state and the portion of th ..."
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Cited by 44 (11 self)
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In this paper, we study the consensus problem in multivehicle systems, where the information states of all vehicles approach a timevarying reference state under the condition that only a portion of the vehicles (e.g., the unique team leader) have access to the reference state and the portion of the vehicles might not have a directed path to all of the other vehicles in the team. We first analyze a consensus algorithm with a constant reference state using graph theoretical tools. We then propose consensus algorithms with a timevarying reference state and show necessary and sufficient conditions under which consensus is reached on the timevarying reference state. The timevarying reference state can be an exogenous signal or evolve according to a nonlinear model. These consensus algorithms are also extended to achieve relative state deviations among the vehicles. An application example to multivehicle formation control is given as a proof of concept.
Dynamic assignment in distributed motion planning with local information
 IEEE TRANSACTIONS ON ROBOTICS
, 2008
"... Distributed motion planning of multiple agents raises fundamental and novel problems in control theory and robotics. In particular, in applications such as coverage by mobile sensor networks or multiple target tracking, a great new challenge is the development of motion planning algorithms that dyna ..."
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Cited by 40 (4 self)
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Distributed motion planning of multiple agents raises fundamental and novel problems in control theory and robotics. In particular, in applications such as coverage by mobile sensor networks or multiple target tracking, a great new challenge is the development of motion planning algorithms that dynamically assign targets or destinations to multiple homogeneous agents, not relying on any aprioriassignment of agents to destinations. In this paper, we address this challenge using two novel ideas. First, distributed multidestination potential fields are developed that are able to drive every agent to any available destination. Second, nearest neighbor coordination protocols are developed ensuring that distinct agents are assigned to distinct destinations. Integration of the overall system results in a distributed, multiagent, hybrid system for which we show that the mutual exclusion property of the final assignment is guaranteed for almost all initial conditions. Furthermore, we show that our dynamic assignment algorithm will converge after exploring at most a polynomial number of assignments, dramatically reducing the combinatorial nature of purely discrete assignment problems. Our scalable approach is illustrated with nontrivial computer simulations.
On synchronous robotic networks Part I: models, tasks, and complexity notions
 44th IEEE Conference on Decision and Control, 2005 and 2005 European Control Conference (CDCECC ’05
, 2005
"... This paper proposes a formal model for a network of robotic agents that move and communicate. Building on concepts from distributed computation, robotics and control theory, we define notions of robotic network, control and communication law, coordination task, and time and communication complexity. ..."
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Cited by 40 (18 self)
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This paper proposes a formal model for a network of robotic agents that move and communicate. Building on concepts from distributed computation, robotics and control theory, we define notions of robotic network, control and communication law, coordination task, and time and communication complexity. We illustrate our model and compute the proposed complexity measures in the example of a network of locally connected agents on a circle that agree upon a direction of motion and pursue their immediate neighbors. I.
Asynchronous consensus in continuoustime multiagent systems with switching topology and timevarying delays
 IEEE Transactions on Automatic Control
, 2008
"... In this paper, we study asynchronous consensus problems of continuoustime multiagent systems with discontinuous information transmission. The proposed consensus control strategy is implemented only based on the state information at some discrete times of each agent’s neighbors. The asynchronization ..."
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Cited by 38 (1 self)
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In this paper, we study asynchronous consensus problems of continuoustime multiagent systems with discontinuous information transmission. The proposed consensus control strategy is implemented only based on the state information at some discrete times of each agent’s neighbors. The asynchronization means that each agent’s update times, at which the agent adjusts its dynamics, are independent of others’. Furthermore, it is assumed that the communication topology among agents is timedependent and the information transmission is with bounded timevarying delays. If the union of the communication topology across any time interval with some given length contains a spanning tree, the consensus problem is shown to be solvable. The analysis tool developed in this paper is based on the nonnegative matrix theory and graph theory. The main contribution of this paper is to provide a valid distributed consensus algorithm that overcomes the difficulties caused by unreliable communication channels, such as intermittent information transmission, switching communication topology, and timevarying communication delays, and therefore has its obvious practical applications. Simulation examples are provided to demonstrate the effectiveness of our theoretical results. Key words: Multiagent systems, asynchronous consensus, switching topology, timevarying delays, coordination. PACS: