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arXiv · 2309.07981

Efficiently Identifying Hotspots in a Spatially Varying Field with Multiple Robots

Varun Suryan·Pratap Tokekar
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Abstract

In this paper, we present algorithms to identify environmental hotspots using mobile sensors. We examine two approaches: one involving a single robot and another using multiple robots coordinated through a decentralized robot system. We introduce an adaptive algorithm that does not require precise knowledge of Gaussian Processes (GPs) hyperparameters, making the modeling process more flexible. The robots operate for a pre-defined time in the environment. The multi-robot system uses Voronoi partitioning to divide tasks and a Monte Carlo Tree Search for optimal path planning. Our tests on synthetic and a real-world dataset of Chlorophyll density from a Pacific Ocean sub-region suggest that accurate estimation of GP hyperparameters may not be essential for hotspot detection, potentially simplifying environmental monitoring tasks.

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Varun Suryan, Pratap Tokekar. 2023-09-14. Efficiently Identifying Hotspots in a Spatially Varying Field with Multiple Robots. https://arxiv.org/abs/2309.07981

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