Simulation-based optimal sensor scheduling with application to observer trajectory planning

DOI10.1016/j.automatica.2006.11.019zbMath1117.93377OpenAlexW2118053528MaRDI QIDQ883376

Robin J. Evans, Ba-Ngu Vo, Nikolaos Kantas, Arnaud Doucet, Sumeetpal S. Singh

Publication date: 4 June 2007

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2006.11.019

zbMATH Keywords

stochastic approximationstochastic controlsequential Monte Carlosensor schedulingparticle filter

Mathematics Subject Classification ID

Related Items (5)

Mathematical programming techniques for sensor networks ⋮ Optimal capacity allocation for sampled networked systems ⋮ Sensor management for multi-target tracking via multi-Bernoulli filtering ⋮ A Lagrangean-based heuristics for the target covering problem in wireless sensor network ⋮ Stochastic output-feedback model predictive control

Cites Work

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• Adaptive Markov control processes
• Linear stochastic approximation driven by slowly varying Markov chains
• Sequential Monte Carlo Methods in Practice
• Optimal waveform selection for tracking systems
• Gradient Convergence in Gradient methods with Errors
• Sensor scheduling in continuous time

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