A learning-augmented model-based planner using GNN likelihood estimates reduces expected search-and-inspection cost for multi-robot teams in simulated and small real-world trials.
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Learning-Augmented Model-Based Multi-Robot Planning for Time-Critical Search and Inspection Under Uncertainty
A learning-augmented model-based planner using GNN likelihood estimates reduces expected search-and-inspection cost for multi-robot teams in simulated and small real-world trials.