Vision-based UAV flight control and obstacle avoidance

Zhihai He; Ram Venkataraman Iyer; Phillip R. Chandler

Vision-based UAV flight control and obstacle avoidance

Zhihai He, Ram Venkataraman Iyer, Phillip R. Chandler

Mathematics and Statistics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

39 Scopus citations

Abstract

In this work, we explore various ideas and approaches to deal with the inherent uncertainty and image noise in motion analysis, and develop a low-complexity, accurate and reliable scheme to estimate the motion fields from UAV navigation videos. The motion field information allows us to accurately estimate ego-motion parameters of the UAV and refine (or correct) the motion measurements from other sensors. Based on the motion field information, we also compute the range map for objects in the scene. Once we have accurate knowledge about the vehicle motion and its navigation environment (range map), control and guidance laws can be designed to navigate the UAV between way points and avoid obstacles.

Original language	English
Title of host publication	Proceedings of the 2006 American Control Conference
Pages	2166-2170
Number of pages	5
State	Published - 2006
Event	2006 American Control Conference - Minneapolis, MN, United States Duration: Jun 14 2006 → Jun 16 2006

Publication series

Name	Proceedings of the American Control Conference
Volume	2006
ISSN (Print)	0743-1619

Conference

Conference	2006 American Control Conference
Country	United States
City	Minneapolis, MN
Period	06/14/06 → 06/16/06

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Link to publication in Scopus

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Cite this

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abstract = "In this work, we explore various ideas and approaches to deal with the inherent uncertainty and image noise in motion analysis, and develop a low-complexity, accurate and reliable scheme to estimate the motion fields from UAV navigation videos. The motion field information allows us to accurately estimate ego-motion parameters of the UAV and refine (or correct) the motion measurements from other sensors. Based on the motion field information, we also compute the range map for objects in the scene. Once we have accurate knowledge about the vehicle motion and its navigation environment (range map), control and guidance laws can be designed to navigate the UAV between way points and avoid obstacles.",

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AB - In this work, we explore various ideas and approaches to deal with the inherent uncertainty and image noise in motion analysis, and develop a low-complexity, accurate and reliable scheme to estimate the motion fields from UAV navigation videos. The motion field information allows us to accurately estimate ego-motion parameters of the UAV and refine (or correct) the motion measurements from other sensors. Based on the motion field information, we also compute the range map for objects in the scene. Once we have accurate knowledge about the vehicle motion and its navigation environment (range map), control and guidance laws can be designed to navigate the UAV between way points and avoid obstacles.

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