Robert E. Karlsen

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This paper introduces novel methods for terrain classification and characterization with a mobile robot. In the context of this paper, terrain classification aims at associating terrains with one of a few predefined, commonly known categories, such as gravel, sand, or asphalt. Terrain characterization, on the other hand, aims at determining key parameters(More)
This paper presents a method to forecast terrain trafficability from visual appearance. During training, the system identifies a set of image chips (or exemplars) that span the range of terrain appearance. Each chip is assigned a vector tag of vehicle-terrain interaction characteristics that are obtained from on-board sensors and simple performance models,(More)
This paper presents an algorithm for online image-based terrain classification that mimics a human supervisor’s segmentation and classification of training images into “Go” and “NoGo” regions. The algorithm identifies a set of image chips (or exemplars) in the training images that span the range of terrain appearance. It then uses the exemplars to segment(More)
Visual Search Distributions Robert E. Karlsen U.S. ArmyTank Automotive Research, Development and Engineering Center Warren, MI 48397-5000 In this paper, we explore the distribution of search times in narrow-field-of-view visual search tasks. In these types of experiments, it is typical to perform tests with multiple observers examining multiple scenes. The(More)
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