Fabrication and Mechanical Analysis of Bioinspired Gliding-optimized Wing Prototypes for Micro Aerial Vehicles

Isakhani, Hamid, Yue, Shigang, Xiong, Caihua , Chen, Wenbin, Sun, Xuelong and liu, Tian (2020) Fabrication and Mechanical Analysis of Bioinspired Gliding-optimized Wing Prototypes for Micro Aerial Vehicles. In: 5th International Conference on Advanced Robotics and Mechatronics (ICARM), 18-21 Dec. 2020.

Full content URL: https://doi.org/10.1109/ICARM49381.2020.9195392

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


Gliding is the most efficient flight mode that is explicitly appreciated by natural fliers. This is achieved by high-performance structures developed over millions of years of evolution. One such prehistoric insect, locust (Schistocerca gregaria) is a perfect example of a natural glider capable of endured transatlantic flights, which could potentially inspire numerous solutions to the problems in aerospace engineering. However, biomimicry of such aerodynamic properties is hindered by the limitations of conventional as well as modern fabrication technologies in terms of precision and availability, respectively. Therefore, we explore and propose novel combinations of economical manufacturing methods to develop various locust-inspired tandem wing prototypes (i.e. fore and hindwings), for further wind tunnel based aerodynamic studies. Additionally, we determine the flexural stiffness and maximum deformation rate of our prototypes and compare it to their counterparts in nature and literature, recommending the most suitable artificial bioinspired wing for gliding micro aerial vehicle applications.

Keywords:Prototypes, Fabrication, Three-dimensional displays, Aerodynamics, Three-dimensional printing, Thermoforming
Subjects:H Engineering > H671 Robotics
H Engineering > H143 Structural Mechanics
H Engineering > H700 Production and Manufacturing Engineering
H Engineering > H130 Computer-Aided Engineering
H Engineering > H440 Aerodynamics
Divisions:College of Science > School of Computer Science
ID Code:43687
Deposited On:15 Feb 2021 12:53

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