Dynamic Heuristics for Surveillance Mission Scheduling
with Unmanned Aerial Vehicles in Heterogeneous Environments

Authors:
  • Dr. James Crowder, Colorado Engineering Inc.
  • Dylan Machovec, Dept of Electrical and Computer Engineering, Colorado State University
  • Howard Jay Siegel, Depts of Electrical and Computer Engineering and Computer Science, Colorado State University
  • Sudeep Pasricha, Depts of Electrical and Computer Engineering and Computer Science, Colorado State University
  • Anthony A. Maciejewski, Dept of Electrical and Computer Engineering, Colorado State University

Abstract:
In this study, our focus is on the design of mission scheduling techniques capable of working in dynamic environments with unmanned aerial vehicles, to determine effective mission schedules in real-time. The effectiveness of mission schedules for unmanned aerial vehicles is measured using a surveillance value metric, which incorporates information about the amount and usefulness of information obtained from surveilling targets. We design a set of dynamic heuristic techniques, which are compared and evaluated based on their ability to maximize surveillance value in a wide range of scenarios generated by a randomized model. We consider two comparison heuristics, three value-based heuristics, and a metaheuristic that intelligently switches between the best value-based heuristics. The novel metaheuristic is shown to find effective solutions that are the best on average as all other techniques that we evaluate in all scenarios that we consider.

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