Warren Whittaker

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Unknown, unexplored and abandoned subterranean voids threaten mining operations, surface developments and the environment. Hazards within these spaces preclude human access to create and verify extensive maps or to characterize and analyze the environment. To that end, we have developed a mobile robot capable of autonomously exploring and mapping abandoned(More)
Inherent dangers in mining operations motivate the use of robotic technology for addressing hazardous situations that prevent human access. In the context of this case study, we examine the application of a robotic tool for map verification and void profiling in abandoned limestone mines for analysis of cavity extent. To achieve this end, our device enables(More)
A method is developed that improves the accuracy of super-resolution range maps over interpolation by fusing actively illuminated HDR camera imagery with LIDAR data in dark subterranean environments. The key approach is shape recovery from estimation of the illumination function and integration in a Markov Random Field (MRF) framework. A virtual(More)
In this paper we address the issue of Computer Vision in Antarctica for robot navigation by analysing images collected at Patriot Hills, Antarctica in the Fall of 1998. Conditions produced by polar weather and terrain are unique and challenging for perception equipment and computer vision algorithms. The later aspect will be studied here through the(More)
Geo met ric modeling fro m range scanners can be vastly improved by sampling the scene with a Nyquist criterion. This work presents a method to estimate frequency content a priori from intensity imagery using wavelet analysis and to utilize these estimates in efficient single-view sampling. The key idea is that under certain constrained and estimab le image(More)
In this paper we address the issue of Computer Vision in Antarctica for robot navigation by analysing images collected at Patriot Hills, Antarctica in the Fall of 1998. Conditions produced by polar weather and terrain are unique and challenging for perception equipment and computer vision algorithms. The later aspect will be studied here through the(More)
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