Learning When to Observe: A Reinforcement Learning Strategy for Exploration Scheduling in Mobile Robot Systems
Accurate station-state information is essential for reliable fleet control in autonomous warehouse systems, but fixed sensing infrastructure is costly and difficult to scale. This paper studies exploration scheduling for warehouse station monitoring under partial observability, where autonomous mobile robots are used a...