William L. Fehlman

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A physics-based adaptive Bayesian pattern classification model that uses a thermal infrared imaging system to automatically sense passive thermal objects in unstructured outdoor environments for mobile robots is described. The usefulness of thermal infrared imaging as a mobile robot sensing modality is explored, and a set of thermal-physical features used(More)
The goal of our research is to give mobile robots the ability to deal with real world instructions outdoors such as “Go down to the big tree and turn left.” Inherent in such a paradigm is the robot being able to recognize a “big tree” and do it in unstructured environments without too many pre-mapped fixed landmarks. Ultimately we envision mobile robots(More)
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