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In this paper we present our progress in the research and development of an augmented reality (AR) system for the remote inspection of hazardous environments. It specifically addresses one particular application with which we are involved--that of improving the inspection of underground sewer pipes using robotic vehicles and 3D graphical overlays coupled with stereoscopic visual data. Traditional sewer inspection using a human operator and CCTV systems is a mature technology--though the task itself is difficult, subjective and prone to error. The work described here proposes not to replace the expert human inspector--but to enhance and increase the information that is available to him and to augment that information with other previously stored data. We describe our current system components which comprise a robotic stereo head device, a simulated sewer crawling vehicle and our AR system. We then go on to discuss the lengthy calibration procedures which are necessary in to align any graphical overlay information with live video data. Some experiments in determining alignment errors under head motion and some investigations into the use of a calibrated virtual cursor are then described.
Shaun W. Lawson andJohn R. G. Pretlove
"Augmented reality and stereo vision for remote scene characterization", Proc. SPIE 3840, Telemanipulator and Telepresence Technologies VI, (8 November 1999); https://doi.org/10.1117/12.369273
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Shaun W. Lawson, John R. G. Pretlove, "Augmented reality and stereo vision for remote scene characterization," Proc. SPIE 3840, Telemanipulator and Telepresence Technologies VI, (8 November 1999); https://doi.org/10.1117/12.369273