Abstract
In this paper we present our approach to 3D surface reconstruction from large sparse range data sets. In space robotics constructing an accurate model of the environment is very important for a variety of reasons. In particular, the constructed model can be used for: safe tele-operation, path planning, planetary exploration and mapping of points of interest. Our approach is based on acquiring range scans from different view-points with overlapping regions, merge them together into a single data set, and fit a triangular mesh on the merged data points. We demonstrate the effectiveness of our approach in a path planning scenario and also by creating the accessibility map for a portion of the Mars Yard located in the Canadian Space Agency.
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