Chen Gao is currently working as a control system engineer in Honeywell Aerospace. She received her PhD in Aerospace Engineering from University of Toronto, Institute for Aerospace Studies in 2014. Her research interests focus on path planning, autonomous UAV systems, state estimation, and robotics.
Autonomous soaring surveillance in wind fields with an unmanned aerial vehicle
Small unmanned aerial vehicles (UAVs) play an active role in developing low-cost autonomous platforms. The success of the applications needs to address the challenge of the short endurance of UAVs. Inspired by nature where birds utilize various wind patterns to stay airborne without flapping their wings, designing an autonomous soaring UAV, which can utilize its surrounding wind patterns to wisely decide the most energy-efficient path during its mission, is an interesting topic and a practical concern in real world applications.
An integration of soaring and a large-scale surveillance mission is considered in this presentation. The static and dynamic soaring and associated surveillance strategies will be introduced for different application scenarios. The bird-mimicking soaring maneuver is designed for UAVs to not only improve flight endurance by extracting energy from surrounding wind environment, but also finish the designated surveillance task and provide the dynamic surrounding wind map to allow future soaring flight.
Keywords: UAV, autonomous soaring, surveillance, dynamic wind map, energy-efficient, path planning, nonlinear controller design.