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http://hdl.handle.net/10119/18320
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Title: | Enabling landings on irregular surfaces for unmanned aerial vehicles via a novel robotic landing gear |
Authors: | Huang, Tsung Hsuan Elibol, Armagan Chong, Nak Young |
Keywords: | Unmanned Aerial Vehicles Non-destructive inspection Landing gear Vacuum suction Passive controlled structural mechanism |
Issue Date: | 2022-05-16 |
Publisher: | Springer Nature |
Magazine name: | Intelligent Service Robotics |
Volume: | 15 |
Start page: | 231 |
End page: | 243 |
DOI: | 10.1007/s11370-022-00420-y |
Abstract: | Unmanned Aerial Vehicles (UAVs) have been attracting much attention and changing our daily lives. Recent technological advances in the development of UAVs have drastically increased both their general capabilities and areas of application. Among many others, one of the areas that benets immediately from using UAVs could be remote inspection, since they can provide an alternative means of access to structures and collect data from locations difficult to reach for human inspectors. Lately, wall-climbing UAVs outfitted with contact-type sensors have been proposed to collect data for the periodic inspection and maintenance of buildings. However, the major drawback is that they can be used only for at surfaces. In this paper, we present a lightweight robotic landing gear for enabling UAVs to land on irregular surfaces, without affecting the on-board flight control system that keeps the UAV in level flight during the entire mission. Our novel design uses a vacuum system for robotic landing gear to attach to the surface, and the movable counterweight composed of a vacuum motor and other control components to balance the flight. To lighten the total weight of UAV, the proposed robotic landing gear system has only one servo motor for gear operation and a passive mechanical structure that guides the vacuum suction cup at the frontal robotic legs to adapt to different shapes of surfaces. We present details of a prototype mechanism and landing experimental results under different scenarios generated within our laboratory environment. |
Rights: | This is the author's version of the work. Copyright (C) 2022, Tsung Hsuan Huang, Armagan Elibol, Nak Young Chong, under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature. The version published by Springer-Verlag is available at www.springerlink.com, https://link.springer.com/article/10.1007/s11370-022-00420-y |
URI: | http://hdl.handle.net/10119/18320 |
Material Type: | author |
Appears in Collections: | b10-1. 雑誌掲載論文 (Journal Articles)
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