Optimal Multi-Agent Persistent Monitoring of the Uncertain State of a Finite Set of Targets

Pinto, Samuel C;Andersson, Sean B.;Hendrickx, Julien;Cassandras, Christos G.
(2019) 58th IEEE conference on Decision and Control (CDC19). — Location: Nice, France (11.December.2019)

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Authors
  • Pinto, Samuel CBoston University, Boston, MA 02215, USA
    Author
  • Andersson, Sean B.Boston University, Boston, MA 02215, USA
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  • Hendrickx, Julienorcid-logoUCLouvain
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  • Cassandras, Christos G.Boston University, Boston, MA 02215, USA
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Abstract
We approach the problem of persistent monitoring of a finite set of fixed targets located in a one-dimensional environment with internal, linear, stochastic dynamics. Monitoring is performed by a set of agents with limited sensing range and range-dependent sensing quality. The optimal estimator of the target dynamics from the agent measurements is the Kalman-Bucy Filter. We formulate an optimal control problem to minimize the estimation error across all the targets as a function of the trajectories of the agents. Using Hamiltonian analysis, the structure of the optimal controller is defined and, given this structure, we reformulate the problem as a hybrid systems optimization problem. Using Infinitesimal Perturbation Analysis (IPA), stochastic gradient estimates of the hybrid system are computed and gradient descent is used in order to achieve a locally optimal solution.
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Pinto, S. C., Andersson, S. B., Hendrickx, J., & Cassandras, C. G. (2019). Optimal Multi-Agent Persistent Monitoring of the Uncertain State of a Finite Set of Targets. IEEE Conference on Decision and Control, Including the Symposium on Adaptive Processes. Proceedings, 4280-4285. https://doi.org/10.1109/cdc40024.2019.9029521 (Original work published 2019)