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arXiv 2202.07177cs.RO

Tombo Propeller: Bio-Inspired Deformable Structure toward Collision-Accommodated Control for Drones

Soft Haptics Lab., School of Materials Science, Japan Advanced Institute of Science and Technology(日本先进科学技术学院材料科学学院软触觉实验室);Tandon School of Engineering, New York University(纽约大学坦登工程学院);Japan Science and Technology Agency, PRESTO(日本科学技术厅)

Son Tien Bui, Quan Khanh Luu, Dinh Quang Nguyen, Nhat Dinh Minh Le, Giuseppe Loianno, Van Anh Ho

英文摘要:

There is a growing need for vertical take-off and landing vehicles, including drones, which are safe to use and can adapt to collisions. The risks of damage by collision, to humans, obstacles in the environment, and drones themselves, are significant. This has prompted a search into nature for a highly resilient structure that can inform a design of propellers to reduce those risks and enhance safety. Inspired by the flexibility and resilience of dragonfly wings, we propose a novel design for a biomimetic drone propeller called Tombo propeller. Here, we report on the design and fabrication process of this biomimetic propeller that can accommodate collisions and recover quickly, while maintaining sufficient thrust force to hover and fly. We describe the development of an aerodynamic model and experiments conducted to investigate performance characteristics for various configurations of the propeller morphology, and related properties, such as generated thrust force, thrust force deviation, collision force, recovery time, lift-to-drag ratio, and noise. Finally, we design and showcase a control strategy for a drone equipped with Tombo propellers that collides in mid-air with an obstacle and recovers from collision continuing flying. The results show that the maximum collision force generated by the proposed Tombo propeller is less than two-thirds that of a traditional rigid propeller, which suggests the concrete possibility to employ deformable propellers for drones flying in a cluttered environment. This research can contribute to morphological design of flying vehicles for agile and resilient performance.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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