A survey on recent object detection techniques useful for monocular vision-based planetary terrain classification

Authors:
Yang Gao;Conrad Spiteri;Minh-Tri Pham;Said Al-Milli
Affiliations:
-;-;-;-
Venue:
Robotics and Autonomous Systems
Year:
2014

Citing 65
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Abstract

Direct terrain classification from monocular images for autonomous navigation of planetary rovers is a relatively new and challenging research area, not only because of the hardware limitation of a rover, but also because the rocks and obstacles to be detected exhibit diverse morphologies and have no uniform properties to distinguish them from background soil. We present a survey of recently developed object detection techniques that can be useful for terrain classification for planetary rovers. We start with summarizing current vision-based terrain classification methods. We then provide a comprehensive and structured overview of recent object detection techniques, focusing on those applicable to terrain classification.