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Proceedings Paper

UXO detection, characterization, and remediation using intelligent robotic systems
Author(s): Saed Amer; Amir Shirkhodaie; Haroun Rababaah
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Paper Abstract

An intelligent robotic system can be distinguished from other machines by its ability to sense, learn, and react to its environment despite various task uncertainties. One of the most powerful sensing modality for robotic system is vision as it enables the robot to see its environment, recognize objects around it and interact with objects to accomplish its task. This paper discusses vision enabling techniques that allows a robot to detect, characterize, classify, and discriminate UneXploded Ordnance (UXO) from clutters in unstructured environments. A soft-computing approach is proposed and validated via indoor and outdoor experiments to measure its performance efficiency and effectiveness in correctly detection and classifying UXO vs. XO and other clutter. The proposed technique has many potential applications for military, homeland security, law enforcement, and in particular, environment UXO remediation and clean-up operations.

Paper Details

Date Published: 29 April 2008
PDF: 12 pages
Proc. SPIE 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII, 69530P (29 April 2008); doi: 10.1117/12.777778
Show Author Affiliations
Saed Amer, Tennessee State Univ. (United States)
Amir Shirkhodaie, Tennessee State Univ. (United States)
Haroun Rababaah, Tennessee State Univ. (United States)


Published in SPIE Proceedings Vol. 6953:
Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII
Russell S. Harmon; John H. Holloway; J. Thomas Broach, Editor(s)

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