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Vision Based Surface Slope Estimation for Unmanned Aerial Vehicle Perching

[+] Author Affiliations
Haijie Zhang, Jianguo Zhao

Colorado State University, Fort Collins, CO

Paper No. DSCC2018-9210, pp. V002T21A004; 10 pages
doi:10.1115/DSCC2018-9210
From:
  • ASME 2018 Dynamic Systems and Control Conference
  • Volume 2: Control and Optimization of Connected and Automated Ground Vehicles; Dynamic Systems and Control Education; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Energy Systems; Estimation and Identification; Intelligent Transportation and Vehicles; Manufacturing; Mechatronics; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Control of IC Engines and Powertrain Systems; Modeling and Management of Power Systems
  • Atlanta, Georgia, USA, September 30–October 3, 2018
  • Conference Sponsors: Dynamic Systems and Control Division
  • ISBN: 978-0-7918-5190-6
  • Copyright © 2018 by ASME

abstract

Unmanned aerial vehicles are applied to many different fields such as surveillance, search, and monitoring. However, a critical issue for unmanned aerial vehicles is that they suffer from short flight time. To address this, perching becomes a new necessary capability for unmanned aerial vehicles. However, before perching on the desired surface, usually the orientation of the UAV needs to be adjusted to make the perching mechanism to firmly attach to the surface. In this paper, a vision algorithm is introduced to estimate the surface slope of the perching object. Equipped with a distance sensor and a monocular camera, the surface slopes in both X and Y directions can be estimated simultaneously. A bunch of experiments with different slope combinations are carried out. Combined with a Kalman Filter, the experiment results show this algorithm is much better compared with the previous algorithms especially when the main movement of the unmanned aerial vehicle is along the camera optical axis.

Copyright © 2018 by ASME

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