  Virtual borders are employed to allow humans the interactive and flexible
restriction of their mobile robots' workspaces in human-centered environments,
e.g. to exclude privacy zones from the workspace or to indicate certain areas
for working. They have been successfully specified in interaction processes
using methods from human-robot interaction. However, these methods often lack
an expressive feedback system, are restricted to robot's on-board interaction
capabilities and require a direct line of sight between human and robot. This
negatively affects the user experience and interaction time. Therefore, we
investigate the effect of a smart environment on the teaching of virtual
borders with the objective to enhance the perceptual and interaction
capabilities of a robot. For this purpose, we propose a novel interaction
method based on a laser pointer, that leverages a smart home environment in the
interaction process. This interaction method comprises an architecture for a
smart home environment designed to support the interaction process, the
cooperation of human, robot and smart environment in the interaction process, a
cooperative perception including stationary and mobile cameras to perceive
laser spots and an algorithm to extract virtual borders from multiple camera
observations. The results of an experimental evaluation support our hypotheses
that our novel interaction method features a significantly shorter interaction
time and a better user experience compared to an approach without support of a
smart environment. Moreover, the interaction method does not negatively affect
other user requirements concerning completeness and accuracy.

Robotics