Global Resource for Energy-Aware Efficient Navigation (GREEN)

The increasing use of autonomy, unmanned air vehicles (UAV), and electric air vehicles within the National Airspace has created a unique opportunity for advanced energy-aware optimization techniques to be applied to aircraft within this convergent space. Both military and commercial operations can benefit from the use of energy-aware optimization techniques to produce more efficient aircraft through increased range and endurance with the benefit of enhancing profitability and mission success. There are different areas upon which energy-aware optimization can be utilized to reduce the overall energy consumption of air operations. As such, Bihrle Applied Research, Inc. proposes investigations into techniques that can be applicable to any aircraft system, crewed or not, so that energy-aware optimization can be utilized throughout existing and future fleets. The goal is to produce methods that can be used to design flight plans and make more fuel-efficient control decisions while reducing disruptions to flight operations and mission performance. This project is called Global Resource for Energy-Aware Efficient Navigation (GREEN). GREEN seeks technologies that optimize aircraft trajectories and decision making at three different levels. First, GREEN technologies will optimize pre-flight path planning to account for energy-consumption using conventional path planning techniques. Second, it will optimize online path augmentation decisions, e.g., avoidance/formation maneuvers or alterations in mission objectives, using advanced Artificial Intelligence and Machine Learning (AI/ML) techniques that will provide energy-aware path augmentations in real-time based on the available information and emergent constraints. Finally, GREEN will optimize control action decision making processes for executing planned paths and path augmentation based on work pioneered in the automotive industry to increase the fuel-economy of existing and future vehicle fleets. The GREEN project will have three main Phase I technical objectives. The first is to investigate and identify tradeoffs for the use of energy-aware optimization methods for pre-flight path planning and in-flight path augmentation. The second is to investigate and identify tradeoffs for the use of energy-aware control policy optimization techniques. The final technical objective is to present the identified trade-offs to Department of the Air Force (DAF) stakeholders and work with them to identify feasible use cases related to increasing range and endurance for Category 5 UAV.