Optimal Minimax Mobile Sensor Scheduling Over a Network

TL;DR

This paper addresses optimal scheduling of a mobile sensor to monitor multiple targets over a network, aiming to minimize the worst-case estimation error with a simplified, computationally efficient approach.

Contribution

It introduces a novel optimal observation time allocation principle and a simplified cyclic visiting policy for mobile sensor scheduling.

Findings

Peak uncertainty is equalized among all targets in optimal allocation.

A cyclic visiting policy simplifies the scheduling problem significantly.

The proposed method reduces computational complexity compared to previous approaches.

Abstract

We investigate the problem of monitoring multiple targets using a single mobile sensor, with the goal of minimizing the maximum estimation error among all the targets over long time horizons. The sensor can move in a network-constrained structure, where it has to plan which targets to visit and for how long to dwell at each node. We prove that in an optimal observation time allocation, the peak uncertainty is the same among all the targets. By further restricting the agent policy to only visit each target once every cycle, we develop a scheme to optimize the agent's behavior that is significantly simpler computationally when compared to previous approaches for similar problems.