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Unmanned aerial vehicles are increasingly being used and showing their advantages in many domains. However, their application to railway systems is very little studied. In this paper, we focus on controlling an AR.Drone UAV in order to follow the railway track. The method developed relies on vision-based detection and tracking of the vanishing point of the(More)
We consider an online planning algorithm for partially observable Markov decision processes (POMDPs), called Anytime Error Minimization Search 2 (AEMS2). Despite the considerable success it has enjoyed in robotics and other problems, no quantitative analysis exists of the relationship between its near-optimality and the computation invested. Exploiting(More)
We consider problems in which a maximizer and a minimizer agent take actions in turn, such as games or optimal control with uncertainty modeled as an opponent. We extend the ideas of optimistic optimization to this setting, obtaining a search algorithm that has been previously considered as the best-first search variant of the B* method. We provide a novel(More)
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