  Significant advances in sensing, robotics, and wireless networks have enabled
the collaborative utilization of autonomous aerial, ground and underwater
vehicles for various applications. However, to successfully harness the
benefits of these unmanned ground vehicles (UGVs) in homeland security
operations, it is critical to efficiently solve UGV path planning problem which
lies at the heart of these operations. Furthermore, in the real-world
applications of UGVs, these operations encounter uncertainties such as
incomplete information about the target sites, travel times, and the
availability of vehicles, sensors, and fuel. This research paper focuses on
developing algebraic-based-modeling framework to enable the successful
deployment of a team of vehicles while addressing uncertainties in the distance
traveled and the availability of UGVs for the mission.
