Optimal Monitoring of Multiple Agents via Time Sequence-Based Modeling

Abstract

The multi-agent monitoring (surveillance) problem over graphs is to find trajectories of multiple agents that travel each node as evenly as possible. This problem has several applications such as city safety management and disaster rescue. in our previously proposed method, the finite-time optimal surveillance problem was formulated, and was reduced to a mixed integer linear programming (MILP) problem. Based on the policy of model predictive control, an optimal trajectory is generated by solving the MlLP problem at each discrete time. However, the computation time for solving the MlLP problem is frequently long. in this paper, to reduce the computation time of the MlLP problem, a modeling method of graphs is proposed. in this method, the adjacency relation is time varying depending on the current position of agents. Since redundant arcs are eliminated, the computation time is improved. The effectiveness of the proposed method is demonstrated by numerical simulations.