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Proceedings Paper

Verification and reconciliation of virtual world model for radioactive waste cleanup
Author(s): Sharon X. Wang; Dean Haddox; Carl D. Crane III; James S. Tulenko
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Paper Abstract

The main task of sensing for robotics and automation is to provide 3D geometrical environment information to robot control and visualization systems, which is often referred as facility characterization or environment mapping. Particularly in radioactive waste cleanup operations, such as the Tank Waste Retrieval (TWR) task where the environment is hazardous, automated sensing techniques are necessary for accurate facility characterization that will be used by remote controlled robots for a safe and orderly cleanup process. This research proposes a facility characterization system which combines the strength of computer vision and computer graphics and which maximizes the use of a priori information. Using a novel image registration method, this system is able to detect the difference between the pre-modeled virtual world and sensed real world. Combined with 3D sensing data, the information can be used for verification and reconciliation of the virtual world database. In the proposed system, the environment is pre-modeled as the virtual world. This virtual world database provides the template for the virtual/real world registration. Once the virtual/real images are registered, the comparison can be accomplished by image subtraction. As the result of the comparison, any missing objects or unanticipated objects will be detected. Utilizing the 3D information, the surfaces of these objects can be reconstructed. This information in turn is used for geometric primitives detection and virtual world updating. The initial testing demonstrates that this system has potential to accomplish the TWR task.

Paper Details

Date Published: 3 October 1995
PDF: 11 pages
Proc. SPIE 2588, Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling, (3 October 1995); doi: 10.1117/12.222675
Show Author Affiliations
Sharon X. Wang, ID Vision, Inc. (United States)
Dean Haddox, Univ. of Florida (United States)
Carl D. Crane III, Univ. of Florida (United States)
James S. Tulenko, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 2588:
Intelligent Robots and Computer Vision XIV: Algorithms, Techniques, Active Vision, and Materials Handling
David P. Casasent, Editor(s)

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