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Significant advances in sensing, robotics, and wireless networks have enabledthe collaborative utilization of autonomous aerial, ground and underwatervehicles for various applications. However, to successfully harness thebenefits of these unmanned ground vehicles (UGVs) in homeland securityoperations, it is critical to efficiently solve UGV path planning problem whichlies at the heart of these operations. Furthermore, in the real-worldapplications of UGVs, these operations encounter uncertainties such asincomplete information about the target sites, travel times, and theavailability of vehicles, sensors, and fuel. This research paper focuses ondeveloping algebraic-based-modeling framework to enable the successfuldeployment of a team of vehicles while addressing uncertainties in the distancetraveled and the availability of UGVs for the mission.

Two-stage stochastic programming approach for path planning problems under travel time and availability uncertainties