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18 April 2023 Nature, smart structures, and morphing UAVs
Daniel J. Inman, Kevin P. T. Haughn, Christina Harvey
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Proceedings Volume 12486, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023; 1248602 (2023) https://doi.org/10.1117/12.2666179
Event: SPIE Smart Structures + Nondestructive Evaluation, 2023, Long Beach, California, United States
Abstract
Nature through careful observation and tests of gliding avian species have resulted in new thoughts on how to design morphing uninhabited air vehicles (UAV) and what morphing motions might make for better performance. An understanding of avian flight stability suggests a new approach to morphing aircraft design. Of interest is how to create these motions using smart materials to replicate avian abilities. Coupled with new learning algorithms, methods for designing smart autonomous morphing airfoils for use in small UAVs are presented. Hardware based reinforcement learning (RL) techniques are used to teach a smart morphing wing to respond to gusts, following the inspiration of gliding gulls who respond immediately and autonomously to unknown changes in flow to maintain stability and control in unpredictable environments. We strive to translate this knowledge to flight control of UAVs. Last, a way forward is suggested to create new class of structures: autonomous multifunctional structures. An outline of what is needed in terms of future research is presented.
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Daniel J. Inman, Kevin P. T. Haughn, and Christina Harvey "Nature, smart structures, and morphing UAVs", Proc. SPIE 12486, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2023, 1248602 (18 April 2023); https://doi.org/10.1117/12.2666179
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KEYWORDS
Unmanned aerial vehicles
Machine learning
Smart structures
Design and modelling
Smart materials
Aerodynamics
Aerospace engineering
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