Feature-based mapping with grounded landmark and place labels
Trevor, Alexander J. B.
Rogers, John G.
Christensen, Henrik I.
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Service robots can benefit from maps that support their tasks and facilitate communication with humans. For efficient interaction, it is practical to be able to reference structures and objects in the environment, e.g. “fetch the mug from the kitchen table.” Towards this end, we present a feature-based SLAM and semantic mapping system which uses a variety of feature types as landmarks, including planar surfaces such as walls, tables, and shelves, as well as objects such as door signs. These landmarks can be optionally labeled by a human for later reference. Support for partitioning maps into labeled regions or places is also presented.