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Traditional coverage path planners create lawnmower-type paths in the operating area completely ignoring the uncertainty in the vehicle's position. However, in the presence of significant uncertainty in localization estimates, one can no longer guarantee that the vehicle will cover all the area according to plan. Aiming to bridge this gap, we present a coverage path planning technique for search operations...
In this paper, we compare deterministic and probabilistic path planning strategies for an autonomous unmanned aerial vehicle (UAV) network, where the objective is to explore a given area with obstacles and provide an overview image. We present both online and offline implementations of the algorithms as alternative solutions, where applicable, and analyze the performance of the offline implementations...
Sensor planning chiefly applies to optimizing surveillance tasks, such as persistent tracking by designing and utilizing camera placement strategies. Against substituting new optimized camera networks for those still in usage, online sensor planning hereby involves the design of vision algorithms that not only select cameras which yield the best results, but also improve the quality with which surveillance...
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