Robots providing services to human users in personal context are known
as personal service robots. Enriching and facilitating people's lives
are their general missions. Acquisition of spatial representations is
therefore crucial for such a robot to move around in a human-shared
environment, provide services and interact with the user about the
environment. With methods developed in the field of autonomous
exploration it is possible for a mobile robot to build a metric
representation from sensor data, while exploring an initially unknown
environment. However, due to the limited perceptual abilities of the
robot and dynamic changes in the environment over time, challenges still
pose for robots. Besides, in order to make the communication about the
environment reliable, a mapping between the spatial understanding of the
user and the robot has to be built in a service context. Human Robot
Joint Spatial Exploration is proposed in this book to build a framework
that allows people to help the robot complete the exploration of the
environment initially unknown to it and makes the robot interactively
learn from people to build a spatial representation.