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2009
ACM

Visual detection of novel terrain via two-class classification

10 years 6 months ago
Visual detection of novel terrain via two-class classification
Remote sensing of terrain characteristics is an important component for autonomous operation of mobile robots in natural terrain. Often this involves classification of terrain into one of a set of a priori known terrain classes. Situations can frequently arise, however, where an autonomous robot encounters a terrain class that does not belong to one of these known classes. This paper proposes an approach for visual detection of novel terrain based on a two-class support vector machine (SVM) for situations when known terrain classes can be confidently associated with only a subset of the training data. Experimental results from a four-wheeled mobile robot in Mars analog terrain demonstrate the effectiveness of this approach. Categories and Subject Descriptors I.5.2 [Pattern Recognition]: Design Methodology – classifier design and analysis General Terms Algorithms, Experimentation, Theory Keywords Machine vision, robot sensing systems, terrain mapping, image classification.
Christopher A. Brooks, Karl Iagnemma
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where SAC
Authors Christopher A. Brooks, Karl Iagnemma
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