As the development of computer vision and the popularity of unmanned aerial vehicle, using visual information to control the UAV motion becomes a hotspot. Time-to-contact is one of the concepts that is used to control robot motion such as braking, landing, perching, and obstacle avoidance based on visual information. In this paper, to explore the capability and potential of a direct featureless time-to-contact estimation algorithm for unmanned aerial vehicle motion control, we design an integrated unmanned aerial vehicle system and verify the accuracy of the featureless time-to-contact estimation algorithm. In addition, compressed sensing is combined with the featureless method in time-to-contact estimation to potentially improve the computational speed. The experiment results show that the featureless time-to-contact estimation algorithm, the developed UAV platform and compressed sensing can be readily applied for UAV vision based control.
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ASME 2017 Dynamic Systems and Control Conference
October 11–13, 2017
Tysons, Virginia, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-5829-5
PROCEEDINGS PAPER
An Integrated Unmanned Aerial Vehicle System for Vision Based Control Available to Purchase
Haijie Zhang,
Haijie Zhang
Colorado State University, Fort Collins, CO
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Jianguo Zhao
Jianguo Zhao
Colorado State University, Fort Collins, CO
Search for other works by this author on:
Haijie Zhang
Colorado State University, Fort Collins, CO
Jianguo Zhao
Colorado State University, Fort Collins, CO
Paper No:
DSCC2017-5405, V003T39A011; 8 pages
Published Online:
November 14, 2017
Citation
Zhang, H, & Zhao, J. "An Integrated Unmanned Aerial Vehicle System for Vision Based Control." Proceedings of the ASME 2017 Dynamic Systems and Control Conference. Volume 3: Vibration in Mechanical Systems; Modeling and Validation; Dynamic Systems and Control Education; Vibrations and Control of Systems; Modeling and Estimation for Vehicle Safety and Integrity; Modeling and Control of IC Engines and Aftertreatment Systems; Unmanned Aerial Vehicles (UAVs) and Their Applications; Dynamics and Control of Renewable Energy Systems; Energy Harvesting; Control of Smart Buildings and Microgrids; Energy Systems. Tysons, Virginia, USA. October 11–13, 2017. V003T39A011. ASME. https://doi.org/10.1115/DSCC2017-5405
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