I-Corps: Flow-aided aerial vehicle navigation and control

Cornell University, Ithaca NY

Investigators

Abstract

The broader impact of this I-Corps project is the development of technology to extend battery life in unmanned aerial vehicles (UAVs). Small unmanned aerial vehicles have been utilized in a wide range of fields, including aerophotography, delivery, surveying, and surveillance in confined spaces. However, the utilization and duration of flight of small UAVs is often limited by the allowed on-board battery capacity, especially in extreme windy conditions when UAVs need to make extra effort to reject disturbances and remain robust. The proposed technology solves the UAV navigation and control problems in turbulence by traversing turbulent flows using minimal time and energy. The new technology may enable more UAVs to operate in conditions beyond their current capabilities and could make UAVs more commercially viable. In addition, the new product fits well with the current trend towards convenient, contact-free, autonomous drone delivery services. The development of efficient UAV navigation and control strategies in wind may benefit the drone delivery industry in the future. This I-Corps project is based on the development of energy-harvesting control algorithms to extend battery life in unmanned aerial vehicles (UAVs). Inspired by principles from particle transport theory in fluid dynamics, the proposed technology provides intelligent control algorithms that enable the aerial vehicle to leverage beneficial flow structures, such as turbulent eddies, rising thermals, and tailwinds, and navigate in highly turbulent environments with significantly less expenditure of time and energy. An implicit model following (IMF) controller was developed to make the aerial vehicle follow the dynamic behavior of settling inertial particles undergoing the fast-tracking effect and extract energy from turbulent flows. Given on-board flow measurements, the controlled aerial vehicle tends to travel under advantageous tailwinds more often, while avoiding adverse headwinds autonomously. Compared to existing control techniques, the innovation of this technology is that prior knowledge of the exact flow parametric model is not required, and controlled aerial vehicles may harvest energy from wind gusts instead of using battery power to compensate for external wind disturbances. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.