  With the rising prominence of WiFi in common spaces, efforts have been made
in the robotics community to take advantage of this fact by incorporating WiFi
signal measurements in indoor SLAM (Simultaneous Localization and Mapping)
systems. SLAM is essential in a wide range of applications, especially in the
control of autonomous robots. This paper describes recent work in the
development of WiFi-based localization and addresses the challenges currently
faced in achieving WiFi-based geometric mapping. Inspired by the field of
research into k-visibility, this paper presents the concept of inverse
k-visibility and proposes a novel algorithm that allows robots to build a map
of the free space of an unknown environment, essential for planning,
navigation, and avoiding obstacles. Experiments performed in simulated and
real-world environments demonstrate the effectiveness of the proposed
algorithm.
