SAFER vehicle inspection: a multimodal robotic sensing platform

David L. Page; Yohan Fougerolle; Andreas F. Koschan; Andrei Gribok; Mongi A. Abidi; David J. Gorsich; Grant R. Gerhart

doi:10.1117/12.542808

2 September 2004 SAFER vehicle inspection: a multimodal robotic sensing platform

David L. Page, Yohan Fougerolle, Andreas F. Koschan, Andrei Gribok, Mongi A. Abidi, David J. Gorsich, Grant R. Gerhart

Proceedings Volume 5422, Unmanned Ground Vehicle Technology VI; (2004) https://doi.org/10.1117/12.542808
Event: Defense and Security, 2004, Orlando, Florida, United States

Abstract

The current threats to U.S. security both military and civilian have led to an increased interest in the development of technologies to safeguard national facilities such as military bases, federal buildings, nuclear power plants, and national laboratories. As a result, the Imaging, Robotics, and Intelligent Systems (IRIS) Laboratory at The University of Tennessee (UT) has established a research consortium, known as SAFER (Security Automation and Future Electromotive Robotics), to develop, test, and deploy sensing and imaging systems for unmanned ground vehicles (UGV). The targeted missions for these UGV systems include -- but are not limited to --under vehicle threat assessment, stand-off check-point inspections, scout surveillance, intruder detection, obstacle-breach situations, and render-safe scenarios. This paper presents a general overview of the SAFER project. Beyond this general overview, we further focus on a specific problem where we collect 3D range scans of under vehicle carriages. These scans require appropriate segmentation and representation algorithms to facilitate the vehicle inspection process. We discuss the theory for these algorithms and present results from applying them to actual vehicle scans.

Citation Download Citation

David L. Page, Yohan Fougerolle, Andreas F. Koschan, Andrei Gribok, Mongi A. Abidi, David J. Gorsich, and Grant R. Gerhart "SAFER vehicle inspection: a multimodal robotic sensing platform", Proc. SPIE 5422, Unmanned Ground Vehicle Technology VI, (2 September 2004); https://doi.org/10.1117/12.542808

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