Abstract

Recently1 there has been a growing interest in human
augmented mapping[1, 2]. That is: a mobile robot builds
a low level spatial representation of the environment based
on its sensor readings while a human provides labels for
human concepts, such as rooms, which are then augmented
or anchored to this representation or map [3]. Given such an
augmented map the robot has the ability to communicate with
the human about spatial concepts using the labels that the
human understand. For instance, the robot could report it is
in the ”kitchen”, instead of a set Cartesian coordinates which
are probably meaningless to the human.