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We propose a homing constrained bi-objective optimization variant of budget-limited informative path planning for monitoring a spatio-temporal environment. The objective function consists of weighted combination of two components: model performance which must be maximized and travel distance which must be bounded by the maximum operational range. Besides this, we have additional constraints that guarantee...
Environment monitoring is a challenging task owing to its ever changing dynamics. Furthermore, deploying a team of resource constrained robots to persistently monitor the environment encompasses intelligently selecting the training samples which are spread across a significantly large area to conservatively spend the resources allocated. In order to accomplish this using a team of fully autonomous...
We consider the problem of area coverage for robot teams operating under resource constraints, while modeling spatio-temporal environmental phenomena. The aim of the mobile robot team is to avoid exhaustive search and only visit the most important locations that can improve the prediction accuracy of a spatio-temporal model. We use a Gaussian Process (GP) to model spatially varying and temporally...
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