I-Corps: Autonomous Unmanned Aerial Vehicles for Remote Sensing

The broader impact/commercial potential of this I-Corps project is the development of technology to increase the capabilities of unmanned aerial vehicles (UAVs) for remote sensing in the Arctic. The proposed technology may be used to more easily collect vegetation data, which may provide valuable insights into Arctic warming and global climate change. The proposed technology will encompass a flight control method for autonomously flying unmanned aerial vehicles over a heterogeneous, vegetation-populated terrain in search of select plant species, and a control method that enables flight in the challenging wind conditions often found in the Arctic. The technology may benefit the study of the Arctic by increasing opportunities for unmanned aerial vehicle remote sensor campaigns and their efficient execution. Commercial impact may result from partnering with companies that offer integrated airborne systems for remote sensing. For example, unmanned aerial vehicles have been used for wildfire fighting where the proposed technology may enable flight in challenging wind conditions, and may enhance the capability to collect data while flying in wildfire generated turbulence. In addition, the technology may benefit the agricultural industry where unmanned aerial vehicle service is the second largest unmanned aerial vehicle service market globally. This I-Corps project is based on the development of technology to enhance unmanned aerial vehicle (UAV) capabilities by overcoming key obstacles that limit their use for remote sensing of the Arctic. Propellers used to control UAV flight are limited in the forces they can produce. If the vehicle’s flight control system requires forces that exceed such limits, undesirable flight performance that jeopardizes the mission may occur. Therefore, deployment of UAVs in the Arctic is currently restricted to infrequent periods when mild winds exist. Likewise, remote sensing by unmanned aerial vehicles is limited by finite battery life and the need for consistent illumination periods. The proposed technology is designed to increase periods for remote sensing by providing stable unmanned aerial vehicle flight during stronger wind conditions and enable autonomous and efficient unmanned aerial vehicle remote sensing. The proposed technology includes a flight control system that mitigates the effects of propeller saturation enabling unmanned aerial vehicle operation in challenging wind conditions, a reinforcement learning-based autonomous guidance method that searches for specific plant species located in heterogeneous vegetation terrains, and experimental validation of the flight control system with an unmanned aerial vehicle operating in an Arctic analogous environment. 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.