In robot applications requiring interaction with a partially/unknown environment, mapping is of paramount importance. This paper presents an effective surface growing algorithm for map building based on laser scan generated point clouds. The algorithm directly converts a point cloud into a surface and normals form which sees a significant reduction in data size and is in a desirable format for planning the interaction with surfaces. It can be used in applications such as robotic cleaning, painting and welding.
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