UXO detection, characterization, and remediation using intelligent robotic systems

Saed Amer; Amir Shirkhodaie; Haroun Rababaah

doi:10.1117/12.777778

29 April 2008 UXO detection, characterization, and remediation using intelligent robotic systems

Saed Amer, Amir Shirkhodaie, Haroun Rababaah

Proceedings Volume 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII; 69530P (2008) https://doi.org/10.1117/12.777778
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

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.

Citation Download Citation

Saed Amer, Amir Shirkhodaie, and Haroun Rababaah "UXO detection, characterization, and remediation using intelligent robotic systems", Proc. SPIE 6953, Detection and Sensing of Mines, Explosive Objects, and Obscured Targets XIII, 69530P (29 April 2008); https://doi.org/10.1117/12.777778

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available