This paper addresses the persistent monitoring problem defined on a network where a set of nodes (targets) needs to be monitored by a team of dynamic energy-aware agents. The objective is to control the agents’ motion to jointly optimize the overall agent energy consumption and a measure of overall node state uncertainty, evaluated over a finite period of interest. To achieve these objectives, we extend an established event-driven Receding Horizon Control (RHC) solution by adding an optimal controller to account for agent motion dynamics and associated energy consumption. The resulting RHC solution is computationally efficient, distributed and on-line. Finally, numerical results are provided highlighting improvements compared to an existing RHC solution that uses energy-agnostic first-order agents.

生成讲解博客的中文版本

生成AI智能校验的中文版本