Continuous Exploitative Measurement Trajectories Using Bayesian Optimisation
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Line-based sampling strategies aim to capture as much information as possible along a trajectory, whilst minimizing the trajectory’s length. The current state of the art primarily contains exploration techniques that focus on uniformly sampling the measurement space. In this work, Bayesian optimization is used to create a novel exploitative line-based sampling strategy, that is able to guide the sampling process towards interesting regions.
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