Treffer: SAFER vehicle inspection: A multimodal robotic sensing platform

Title:
SAFER vehicle inspection: A multimodal robotic sensing platform
Source:
Unmanned ground vehicle technology VI (Orlando FL, 13-15 April 2004)SPIE proceedings series. :549-560
Publisher Information:
Bellingham WA: SPIE, 2004.
Publication Year:
2004
Physical Description:
print, 26 ref
Original Material:
INIST-CNRS
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Imaging, Robotics, and Intelligent Systems Laboratory, The University of Tennessee, Knoxville, TN, 37996-2100, France
LE2i-CNRS Université de Bourgogne, 12 rue de la fonderie, 71200 Le Creusot, France
U. S. Army RDECOM Tank-Automotive Research, Development and Engineering Center, Warren, MI, 48397-5000, United States
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16367881
Database:
PASCAL Archive

Weitere Informationen

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.