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Environmental boundary tracking and estimation using multiple autonomous vehicles
2007
2007 46th IEEE Conference on Decision and Control
In this paper, we develop a framework for environmental boundary tracking and estimation by considering the boundary as a hidden Markov model (HMM) with separated observations collected from multiple sensing vehicles. For each vehicle, a tracking algorithm is developed based on Page's cumulative sum algorithm (CUSUM), a method for changepoint detection, so that individual vehicles can autonomously track the boundary in a density field with measurement noise. Based on the data collected from
doi:10.1109/cdc.2007.4434857
dblp:conf/cdc/JinB07
fatcat:kh3d5paimrfdpa7tx5vazv4ita