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Coupled Distributed Estimation and Control for Mobile Sensor Networks

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2 Author(s)
Reza Olfati-Saber ; Engineering at the Thayer School of Engineering, Dartmouth College, Hanover, United States of America ; Parisa Jalalkamali

In this paper, we introduce a theoretical framework for coupled distributed estimation and motion control of mobile sensor networks for collaborative target tracking. We use a Fisher Information theoretic metric for quality of sensed data. The mobile sensing agents seek to improve the information value of their sensed data while maintaining a safe-distance from other neighboring agents (i.e., perform information-driven flocking). We provide a formal stability analysis of continuous Kalman-Consensus filtering (KCF) algorithm on a mobile sensor network with a flocking-based mobility control model. The discrete-time counterpart of this coupled estimation and control algorithm is successfully applied to tracking of two types of targets with stochastic linear and nonlinear dynamics.

Published in:

IEEE Transactions on Automatic Control  (Volume:57 ,  Issue: 10 )