Always choose second best: Tracking a moving target on a graph with a noisy binary sensor

  address = {Aalborg, Denmark},
  title = {Always choose second best: {Tracking} a moving target on a graph with a noisy binary sensor},
  isbn = {978-1-5090-2591-6},
  shorttitle = {Always choose second best},
  url = {},
  abstract = {In this work, we consider the problem of using a noisy binary sensor to optimally track a target that moves as a Markov Chain in a finite discrete environment. Our approach focuses on one-step optimality because of the apparent infeasibility of computing an optimal policy via dynamic programming. We prove that always searching in the second most likely location minimizes one-step variance while maximizing the belief about the target’s location over one step. Simulation results demonstrate the performance of our strategy and suggest the policy performs well over arbitrary horizons.},
  language = {en},
  urldate = {2020-09-15},
  booktitle = {2016 {European} {Control} {Conference} ({ECC})},
  publisher = {IEEE},
  author = {Leahy, Kevin and Schwager, Mac},
  month = jun,
  year = {2016},
  keywords = {target\_tracking},
  pages = {1715--1721},
  month_numeric = {6}