We present efficient multiscale approaches to the segmentation of natural clutter, specifically grass and forest, and to the enhancement of anomalies in synthetic aperture radar (SAR) imagery. The methods we propose exploit the coherent nature of SAR sensors. In particular, they take advantage of the characteristic statistical differences in imagery of different terrain types, as a function of ...

Terrain classification is a critical component of any autonomous mobile robot system operating in unknown realworld environments. Over the years, several proprioceptive terrain classification techniques have been introduced to increase robustness or act as a fallback for traditional vision based approaches. However, they lack widespread adaptation due to various factors that include inadequate ...

Sensory perception for unmanned ground vehicle navigation has received great attention from the robotics community. However, sensors mounted on the vehicle are regularly viewpoint impaired. A vehicle navigating at high speeds in offroad environments may be unable to react to negative obstacles such as large holes and cliffs. One approach to address this problem is to complement the sensing capa...

This paper describes a method for classifying the traversability of terrain by combining unsupervised learning of color models that predict scene geometry with supervised learning of the relationship between geometric features and traversability. A neural network is trained offline on hand-labeled geometric features computed from stereo data. An online process learns the association between col...

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In this paper we investigate the potential for enhancing the perception capabilities of smart wheelchair systems (SWS) in an urban environment through intensity-based terrain classification. A 3D camera system was employed that provided both range and intensity (remission) measurements to objects in the scene. Each sensor measurement was represented by a feature vector consisting of range ρ, be...

POL-SAR data acquired from the two 1994 ights of the SIR-C/X-SAR platform has illustrated the variability of measurements due to seasonal, spectral, and angular changes. Consequently, statistical techniques for terrain classi cation make robust, unsupervised classi cation problematic. We present an algorithm for classifying terrain that accounts for variability in terrain signatures by deriving...

The usability of mobile robots for surveillance, search and rescue missions can be significantly improved by intelligent functionalities decreasing the cognitive load on the operator or even allowing autonomous operations, e.g., when communication fails. Mobility in this regard is not only a mechatronic problem but also a perception, modeling and planning challenge. Here, the perception issue o...

Texture has long been regarded as spatial distributions of gray-level variation, and texture analysis has generally been connned to the 2-D image domain. Introducing the concept of \3-D world texture", this paper considers texture as a function of 3-D structures and proposes a set of \3-D textural features". The proposed 3-D features appear to have a great potential in terrain classiication. Ex...