Adam R. Bates

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Autonomous robots in unknown and unstructured environments must be able to distinguish safe and unsafe terrain in order to navigate effectively. Stereo depth data is effective in the near field, but agents should also be able to observe and learn perceptual models for identifying traversable surfaces and obstacles in the far field. As the robot passes(More)
— Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. At the core of this navigation task lies the concept of identifying safe, traversable paths which allow the robot to progress toward a goal. Stereo vision is frequently exploited for autonomous navigation, but has limitations in terms of its density(More)
Date______________ The final copy of this thesis has been examined by the signatories, and we Find that both the content and the form meet acceptable presentation standards of scholarly work in the above mentioned discipline. An approach to stereo based local path planning in unstructured environments is presented. The approach differs from previous stereo(More)
— Autonomous robot navigation in unstructured outdoor environments is a challenging area of active research. At the core of this navigation task lies the concept of identifying safe, traversable paths which allow the robot to progress toward a goal. Stereo vision is frequently exploited for autonomous navigation, but has limitations in terms of its density(More)
Many terrains in outdoor robot navigation problems have paths that are distinct and continuous compared to the non-traversable regions. In image space these paths correspond to continuous segments that can be thought of as clusters embedded in image feature space. These segments very often translate directly to traversable ground plane. In this paper we(More)
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