Multi-agent Persistent Surveillance with Time-interval Constraints Using Mixed Integer Linear Programming

Abstract

In the past years, cooperative operation of multiple robots has attracted considerable research interest for coverage and search of broad and complex areas. Unlike the complete coverage problem, in the basic persistent surveillance problem each location in the environment must be visited repeatedly while minimizing the time-interval between any two visits to the same location. In this paper, we propose a cooperative path planning algorithm for an efficient persistent surveillance operation of multiple heterogeneous agents using mixed integer linear programming. Since we specially consider a grid environment with different priories (time interval constraints), agents must visit the region at least once within the specific time interval constraint. The cost function is the maximum risk minimization. Also, we consider a protocol for cooperative movement of heterogeneous agents. The objectives of the proposed algorithm are: persistent surveillance operation with time interval constraints, obstacle avoidance, and collision avoidance among multiple agents. Simulation results conrm that a cell is visited at least once within its time interval constraints.