Persistent Monitoring with Refueling on a Terrain Using a Team of Aerial and Ground Robots

Abstract

There are many applications such as surveillance and mapping that require persistent monitoring of terrains. In this work, we consider a heterogeneous team of aerial and ground robots that are tasked with monitoring a terrain along a given path. Both types of robots are equipped with cameras that can monitor the terrain within their fields-of-view. We also consider the ability of the aerial robots to land occasionally on the terrain to recharge. The objective is to find a path for all the robots to reduce the time required. Determining optimal routes for the robots is a challenging problem because of constrained visibility due to the terrain and fuel limitations of the robots. We devise an MILP formulation for the problem using a 1.5 dimensional representation model. A branch-and-cut framework is used to implement the MILP and involves the design of a separation algorithm to compute valid inequalities. We report results from extensive simulations and proof-of-concept field experiments to show the efficacy of our approach.