Bioinspired Artificial Hair Sensors for Flight-by-Feel of Unmanned Aerial Vehicles: A Review

Author:

Hollenbeck Alex C.1ORCID,Grandhi Ramana1,Hansen John H.1ORCID,Pankonien Alexander M.2

Affiliation:

1. Air Force Institute of Technology, Wright-Patterson Air Force Base, Ohio 45433

2. Air Force Research Laboratory, Wright–Patterson Air Force Base, Ohio 45433

Abstract

Flight-by-feel is an emerging approach to flight control that uses distributed arrays of pressure, strain, and flow sensors to guide aircraft. Among these, hair-type flow sensors have received the least attention yet hold some advantages over conventional sensors. This paper reviews hair-like flow microsensors developed since 2013, focusing on developments in design, construction, and application. Hair-like flow sensors can be found in artificial cochleae, submersible navigation, terrestrial robots, and, rarely but increasingly, on aircraft. In this survey, we categorize hair-like flow sensors into three types (long whisker-like hairs, ultrasensitive microscale hairs, and short trichoid-like hairs), and primarily cover sensors that may be suitable for use on aircraft. The recent progress in flow-based flight control using distributed sensing is also discussed, along with the optimization of sensor placement and the potential for flight-by-feel in sixth-generation military and civilian aircraft designs. This survey aims to provide a consolidated account of the history and state-of-the-art of artificial hair-cell flow sensors, motivate consideration of flight-by-feel as a viable flight control paradigm, and define avenues for future research. As engineering and biological science continue to converge, we hope that researchers in both fields find this survey an inspirational and useful resource.

Funder

Air Force Institute of Technology

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Aerospace Engineering

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3