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- W2800998522 abstract "We consider the problem of controlling the movement of multiple cooperating agents so as to minimize an uncertainty metric associated with a finite number of data sources. In a one-dimensional (1-D) mission space, we adopt an optimal control framework and show that the solution can be reduced to a simpler parametric optimization problem: Determining a sequence of locations where each agent may dwell for a finite amount of time and then switch direction. This amounts to a hybrid system which we analyze using the infinitesimal perturbation analysis (IPA) to obtain a complete online solution through an event-driven gradient-based algorithm which is also robust with respect to the uncertainty model used. The resulting controller depends on observing the events required to excite the gradient-based algorithm, which cannot be guaranteed. We solve this problem by introducing a new metric for the objective function which creates a potential field guaranteeing that gradient values are nonzero. This approach is compared to an alternative graph-based target-visit scheduling and dwell times optimization algorithm. The simulation examples are included to demonstrate the proposed methods." @default.
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- W2800998522 date "2018-12-01" @default.
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- W2800998522 title "Optimal Event-Driven Multiagent Persistent Monitoring of a Finite Set of Data Sources" @default.
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- W2800998522 doi "https://doi.org/10.1109/tac.2018.2829469" @default.
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